[Federal Register Volume 86, Number 154 (Friday, August 13, 2021)]
[Rules and Regulations]
[Pages 44774-45615]
From the Federal Register Online via the Government Publishing Office [www.gpo.gov]
[FR Doc No: 2021-16519]



[[Page 44773]]

Vol. 86

Friday,

No. 154

August 13, 2021

Part II

Book 2 of 2 Books

Pages 44773-45620





Department of Health and Human Services





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Centers for Medicare & Medicaid Services



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42 CFR Parts 412, 413, 425, et al.



 Medicare Program; Hospital Inpatient Prospective Payment Systems for 
Acute Care Hospitals and the Long-Term Care Hospital Prospective 
Payment System and Policy Changes and Fiscal Year 2022 Rates; Quality 
Programs and Medicare Promoting Interoperability Program Requirements 
for Eligible Hospitals and Critical Access Hospitals; Changes to 
Medicaid Provider Enrollment; and Changes to the Medicare Shared 
Savings Program; Final Rule

  Federal Register / Vol. 86, No. 154 / Friday, August 13, 2021 / Rules 
and Regulations  

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DEPARTMENT OF HEALTH AND HUMAN SERVICES

Centers for Medicare & Medicaid Services

42 CFR Parts 412, 413, 425, 455, and 495

[CMS-1752-F and CMS-1762-F]
RINs 0938-AU44 and 0938-AU56


Medicare Program; Hospital Inpatient Prospective Payment Systems 
for Acute Care Hospitals and the Long-Term Care Hospital Prospective 
Payment System and Policy Changes and Fiscal Year 2022 Rates; Quality 
Programs and Medicare Promoting Interoperability Program Requirements 
for Eligible Hospitals and Critical Access Hospitals; Changes to 
Medicaid Provider Enrollment; and Changes to the Medicare Shared 
Savings Program

AGENCY: Centers for Medicare & Medicaid Services (CMS), HHS.

ACTION: Final rule.

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SUMMARY: This final rule revises the Medicare hospital inpatient 
prospective payment systems (IPPS) for operating and capital-related 
costs of acute care hospitals to implement changes arising from our 
continuing experience with these systems for FY 2022 and to implement 
certain recent legislation. The final rule also updates the payment 
policies and the annual payment rates for the Medicare prospective 
payment system (PPS) for inpatient hospital services provided by long-
term care hospitals (LTCHs) for FY 2022. It also finalizes a May 10, 
2021 interim final rule with comment period regarding rural 
reclassification through the Medicare Geographic Classification Review 
Board (MGCRB). The final rule also implements changes and updates for 
the Medicare Promoting Interoperability, Hospital Value-Based 
Purchasing, Hospital Readmissions Reduction, Hospital Inpatient Quality 
Reporting, Hospital-Acquired Condition Reduction, the PPS-Exempt Cancer 
Hospital Reporting, and the Long-Term Care Hospital Quality Reporting 
programs. It also finalizes provisions that alleviate a longstanding 
problem related to claiming Medicare bad debt and provide a 
participation opportunity for eligible accountable care organizations 
(ACOs).

DATES: This final rule is effective October 1, 2021.

FOR FURTHER INFORMATION CONTACT: 
    Donald Thompson, (410) 786-4487, and Michele Hudson, (410) 786-
4487, Operating Prospective Payment, MS-DRG Relative Weights, Wage 
Index, Hospital Geographic Reclassifications, Capital Prospective 
Payment, Excluded Hospitals, Medicare Disproportionate Share Hospital 
(DSH) Payment Adjustment, Sole Community Hospitals (SCHs), Medicare-
Dependent Small Rural Hospital (MDH) Program, Low-Volume Hospital 
Payment Adjustment, and Critical Access Hospital (CAH) Issues.
    Emily Lipkin, (410) 786-3633 and Jim Mildenberger, (410) 786-4551, 
Long-Term Care Hospital Prospective Payment System and MS-LTC-DRG 
Relative Weights Issues.
    Emily Forrest, (202) 205-1922, Market-Based Data Collection and 
Market-Based MS-DRG Relative Weight Methodology Issues.
    Allison Pompey, (410) 786-2348, New Technology Add On Payments and 
New COVID-19 Treatments Add-on Payments Issues.
    Mady Hue, (410) 786-4510, and Andrea Hazeley, (410) 786-3543, MS-
DRG Classifications Issues.
    Mollie Knight, (410) 786-7948, and Bridget Dickensheets, (410) 786-
8670, Rebasing and Revising the Hospital Market Baskets Issues.
    Siddhartha Mazumdar, (410) 786-6673, Rural Community Hospital 
Demonstration Program Issues.
    Jeris Smith, (410) 786-0110, Frontier Community Health Integration 
Project Demonstration Issues.
    Pamela Brown, [email protected], Hospital Readmissions 
Reduction Program--Administration Issues.
    Jim Poyer, [email protected], Hospital Readmissions Reduction 
Program--Readmissions--Measures Issues.
    Jennifer Tate, [email protected], Hospital-Acquired 
Condition Reduction Program--Administration Issues.
    Yuling Li, (410) 786-8421, Hospital-Acquired Condition Reduction 
Program--Measures Issues.
    Julia Venanzi, [email protected], Hospital Inpatient 
Quality Reporting and Hospital Value-Based Purchasing Programs--
Administration Issues
    Katrina Hoadley, [email protected], Hospital Inpatient 
Quality Reporting and Hospital Value-Based Purchasing Programs--
Measures Issues Except Hospital Consumer Assessment of Healthcare 
Providers and Systems Issues.
    Elizabeth Goldstein, (410) 786-6665, Hospital Inpatient Quality 
Reporting and Hospital Value-Based Purchasing--Hospital Consumer 
Assessment of Healthcare Providers and Systems Measures Issues.
    Annie Hollis, [email protected], PPS-Exempt Cancer Hospital 
Quality Reporting--Administration Issues.
    Katrina Hoadley, [email protected], PPS-Exempt Cancer 
Hospital Quality Reporting Program-Measure Issues
    Christy Hughes, (410) 786-5662, Long-Term Care Hospital Quality 
Reporting Program--Data Reporting Issues.
    Jessica Warren, [email protected] and Elizabeth Holland, 
[email protected], Promoting Interoperability Programs.
    Candace Anderson, (410) 786-1553, Medicaid Enrollment of Medicare 
Providers and Suppliers for Purposes of Processing Claims for Cost-
Sharing for Services Furnished to Dually Eligible Beneficiaries.
    Naseem Tarmohamed, (410) 786-0814, or 
[email protected], for issues related to the Shared 
Savings Program.

SUPPLEMENTARY INFORMATION: 

Tables Available Through the Internet on the CMS Website

    The IPPS tables for this FY 2022 final rule are available through 
the internet on the CMS website at: https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/AcuteInpatientPPS/index.html. Click on 
the link on the left side of the screen titled, ``FY 2022 IPPS Final 
rule Home Page'' or ``Acute Inpatient--Files for Download.'' The LTCH 
PPS tables for this FY 2022 final rule are available through the 
internet on the CMS website at: http://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/LongTermCareHospitalPPS/index.html under the 
list item for Regulation Number CMS-1752-F. For further details on the 
contents of the tables referenced in this final rule, we refer readers 
to section VI. of the Addendum to this FY 2022 IPPS/LTCH PPS final 
rule.
    Readers who experience any problems accessing any of the tables 
that are posted on the CMS websites, as previously identified, should 
contact Michael Treitel at (410) 786-4552.

Table of Contents

I. Executive Summary and Background
    A. Executive Summary
    B. Background Summary
    C. Summary of Provisions of Recent Legislation Implemented in 
This Final Rule
    D. Issuance of Proposed and Interim Final Rulemakings

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    E. Advancing Health Information Exchange
    F. Use of FY 2020 or FY 2019 Data in the FY 2022 IPPS and LTCH 
PPS Ratesetting
II. Changes to Medicare Severity Diagnosis-Related Group (MS-DRG) 
Classifications and Relative Weights
    A. Background
    B. Adoption of the MS-DRGs and MS-DRG Reclassifications
    C. FY 2022 MS-DRG Documentation and Coding Adjustment
    D. Changes to Specific MS-DRG Classifications
    E. Recalibration of the FY 2022 MS-DRG Relative Weights
    F. Add-On Payments for New Services and Technologies for FY 2022
III. Changes to the Hospital Wage Index for Acute Care Hospitals
    A. Background
    B. Worksheet S-3 Wage Data for the Proposed FY 2022 Wage Index
    C. Verification of Worksheet S-3 Wage Data
    D. Method for Computing the Proposed FY 2022 Unadjusted Wage 
Index
    E. Occupational Mix Adjustment to the FY 2022 Wage Index
    F. Analysis and Implementation of the Occupational Mix 
Adjustment and the Proposed FY 2022 Occupational Mix Adjusted Wage 
Index
    G. Application of the Rural Floor, Application of the State 
Frontier Floor, and Continuation of the Low Wage Index Hospital 
Policy, and Budget Neutrality Adjustment
    H. FY 2022 Wage Index Tables
    I. Revisions to the Wage Index Based on Hospital Redesignations 
and Reclassifications
    J. Out-Migration Adjustment Based on Commuting Patterns of 
Hospital Employees
    K. Reclassification From Urban to Rural Under Section 
1886(d)(8)(E) of the Act Implemented at 42 CFR 412.103
    L. Process for Requests for Wage Index Data Corrections
    M. Labor-Related Share for the FY 2022 Wage Index
IV. Rebasing and Revising of the Hospital Market Baskets for Acute 
Care Hospitals
    A. Background
    B. Rebasing and Revising the IPPS Market Basket
    C. Market Basket for Certain Hospitals Presently Excluded From 
the IPPS
    D. Rebasing and Revising the Capital Input Price Index (CIPI)
V. Other Decisions and Changes to the IPPS for Operating System
    A. Changes in the Inpatient Hospital Updates for FY 2021 (Sec.  
412.64(d))
    B. Rural Referral Centers (RRCs)--Annual Updates to Case-Mix 
Index and Discharge Criteria (Sec.  412.96)
    C. Payment Adjustment for Low-Volume Hospitals (Sec.  412.101)
    D. Indirect Medical Education (IME) Payment Adjustment Factor 
(Sec.  412.105)
    E. Payment Adjustment for Medicare Disproportionate Share 
Hospitals (DSHs) for FY 2022 (Sec.  412.106)
    F. Counting Days Associated With Section 1115 Demonstration 
Projects in the Medicaid Fraction
    G. Hospital Readmissions Reduction Program: Updates and Changes 
(Sec. Sec.  [thinsp]412.150 through 412.154)
    H. Hospital Value-Based Purchasing (VBP) Program: Updates and 
Changes (Sec. Sec.  [thinsp]412.160 through 412.167)
    I. Hospital-Acquired Conditions (HAC) Reduction Program: Updates 
and Changes (Sec.  412.170)
    J. Proposed Payments for Indirect and Direct Graduate Medical 
Education Costs (Sec. Sec.  412.105 and 413.75 through 413.83)
    K. Rural Community Hospital Demonstration Program
    L. Market-Based MS-DRG Relative Weight--Policy Changes (Sec.  
413.20)
    M. Payment Adjustment for CAR T-cell Clinical Trial and Expanded 
Use for Immunotherapy Cases (Sec. Sec.  412.85 and 412.312)
VI. Changes to the IPPS for Capital-Related Costs
    A. Overview
    B. Additional Provisions
    C. Annual Update for FY 2022
VII. Changes for Hospitals Excluded From the IPPS
    A. Rate-of-Increase in Payments to Excluded Hospitals for FY 
2022
    B. Critical Access Hospitals (CAHs)
VIII. Changes to the Long-Term Care Hospital Prospective Payment 
System (LTCH PPS) for FY 2022
    A. Background of the LTCH PPS
    B. Medicare Severity Long-Term Care Diagnosis-Related Group (MS-
LTC-DRG) Classifications and Relative Weights for FY 2021
    C. Changes to the LTCH PPS Payment Rates and Other Proposed 
Changes to the LTCH PPS for FY 2022
IX. Quality Data Reporting Requirements for Specific Providers and 
Suppliers
    A. Advancing to Digital Quality Measurement and the Use of Fast 
Healthcare Interoperability Resources (FHIR) in Hospital Quality 
Programs--Request for Information
    B. Closing the Health Equity Gap in CMS Hospital Quality 
Programs--Request For Information
    C. Hospital Inpatient Quality Reporting (IQR) Program
    D. Changes to the PPS-Exempt Cancer Hospital Quality Reporting 
(PCHQR) Program
    E. Long-Term Care Hospital Quality Reporting Program (LTCH QRP)
    F. Changes to the Medicare Promoting Interoperability Programs
X. Changes for Hospitals and Other Providers and Suppliers
    A. Medicaid Enrollment of Medicare Providers and Suppliers for 
Purposes of Processing Claims for Cost-Sharing for Services 
Furnished to Dually Eligible Beneficiaries--Policy Changes (Sec.  
455.410)
    B. Medicare Shared Savings Program--Policy Changes (Sec.  
425.600)
XI. MedPAC Recommendations
XII. Other Required Information
    A. Publicly Available Files
    B. Collection of Information Requirements
Regulation Text

Addendum--Schedule of Standardized Amounts, Update Factors, and Rate-
of-Increase Percentages Effective With Cost Reporting Periods Beginning 
on or After October 1, 2021 and Payment Rates for LTCHs Effective for 
Discharges Occurring on or After October 1, 2021

I. Summary and Background
II. Changes to Prospective Payment Rates for Hospital Inpatient 
Operating Costs for Acute Care Hospitals for FY 2022
    A. Calculation of the Proposed Adjusted Standardized Amount
    B. Adjustments for Area Wage Levels and Cost-of-Living
    C. Calculation of the Prospective Payment Rates
III. Changes to Payment Rates for Acute Care Hospital Inpatient 
Capital-Related Costs for FY 2022
    A. Determination of the Federal Hospital Inpatient Capital-
Related Prospective Payment Rate Update for FY 2022
    B. Calculation of the Inpatient Capital-Related Prospective 
Payments for FY 2022
    C. Capital Input Price Index
IV. Changes to Payment Rates for Excluded Hospitals: Rate-of-
Increase Percentages for FY 2022
V. Changes to the Payment Rates for the LTCH PPS for FY 2022
    A. LTCH PPS Standard Federal Payment Rate for FY 2022
    B. Adjustment for Area Wage Levels Under the LTCH PPS for FY 
2022
    C. Cost-of-Living Adjustment (COLA) for LTCHs Located in Alaska 
and Hawaii
    D. Adjustment for LTCH PPS High-Cost Outlier (HCO) Cases
    E. Update to the IPPS Comparable/Equivalent Amounts To Reflect 
the Statutory Changes to the IPPS DSH Payment Adjustment Methodology
    F. Computing the Adjusted LTCH PPS Federal Prospective Payments 
for FY 2022
VI. Tables Referenced in This Rule Generally Available Through the 
internet on the CMS website

Appendix A--Economic Analyses

I. Regulatory Impact Analysis
    A. Statement of Need
    B. Overall Impact
    C. Objectives of the IPPS and the LTCH PPS
    D. Limitations of Our Analysis
    E. Hospitals Included in and Excluded From the IPPS
    F. Effects on Hospitals and Hospital Units Excluded From the 
IPPS
    G. Quantitative Effects of the Policy Changes Under the IPPS for 
Operating Costs
    H. Effects of Other Policy Changes
    I. Effects of Changes in the Capital IPPS
    J. Effects of Payment Rate Changes and Policy Changes Under the 
LTCH PPS
    K. Effects of Requirements for Hospital Inpatient Quality 
Reporting (IQR) Program

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    L. Effects of Requirements for the PPS-Exempt Cancer Hospital 
Quality Reporting (PCHQR) Program
    M. Effects of Requirements for the Long-Term Care Hospital 
Quality Reporting Program (LTCH QRP)
    N. Effects of Requirements Regarding the Promoting 
Interoperability Program
    O. Alternatives Considered
    P. Overall Conclusion
    Q. Regulatory Review Costs
II. Accounting Statements and Tables
    A. Acute Care Hospitals
    B. LTCHs
III. Regulatory Flexibility Act (RFA) Analysis
IV. Impact on Small Rural Hospitals
V. Unfunded Mandate Reform Act (UMRA) Analysis
VI. Executive Order 13175
VII. Executive Order 12866

Appendix B: Recommendation of Update Factors for Operating Cost Rates 
of Payment for Inpatient Hospital Services

I. Background
II. Inpatient Hospital Update for FY 2022
    A. FY 2022 Inpatient Hospital Update
    B. Update for SCHs and MDHs for FY 2022
    C. FY 2022 Puerto Rico Hospital Update
    D. Update for Hospitals Excluded from the IPPS for FY 2022
    E. Update for LTCHs for FY 2022
III. Secretary's Recommendation
IV. MedPAC Recommendation for Assessing Payment Adequacy and 
Updating Payments in Traditional Medicare

I. Executive Summary and Background

A. Executive Summary

1. Purpose and Legal Authority
    This FY 2022 IPPS/LTCH PPS final rule makes payment and policy 
changes under the Medicare inpatient prospective payment systems (IPPS) 
for operating and capital-related costs of acute care hospitals as well 
as for certain hospitals and hospital units excluded from the IPPS. In 
addition, it makes payment and policy changes for inpatient hospital 
services provided by long-term care hospitals (LTCHs) under the long-
term care hospital prospective payment system (LTCH PPS). This final 
rule also makes policy changes to programs associated with Medicare 
IPPS hospitals, IPPS-excluded hospitals, and LTCHs. In this FY 2022 
final rule, we are continuing policies to address wage index 
disparities impacting low wage index hospitals. We are finalizing our 
implementation of Section 9831 of the American Rescue Plan Act of 2021, 
which permanently established the imputed floor wage index policy. In 
addition, we are finalizing the regulations implemented in CMS-1762-IFC 
(86 CFR 24735-24739), which allowed hospitals with a rural 
redesignation under the Act to reclassify through the MGCRB using the 
rural reclassified area as the geographic area in which the hospital is 
located. This final rule includes policies related to new technology 
add-on payments. We are also finalizing our proposal to repeal the 
collection of market-based rate information on the Medicare cost report 
and the market-based MS-DRG relative weight methodology.
    We are establishing new requirements and revising existing 
requirements for eligible hospitals and CAHs participating in the 
Medicare Promoting Interoperability Program.
    We are providing estimated and newly established performance 
standards for the Hospital Value-Based Purchasing (VBP) Program, and 
updated policies for the Hospital Readmissions Reduction Program, 
Hospital Inpatient Quality Reporting (IQR) Program, Hospital VBP 
Program, Hospital-Acquired Condition (HAC) Reduction Program, Long-Term 
Care Hospital Quality Reporting Program (LTCH QRP), and the PPS-Exempt 
Cancer Hospital Reporting (PCHQR) Program. Additionally, due to the 
impact of the COVID-19 PHE on measure data used in our value-based 
purchasing programs, we are finalizing our proposal to suppress several 
measures in the Hospital VBP, HAC Reduction, and Hospital Readmissions 
Reduction Programs. As a result of these measure suppressions for the 
Hospital VBP Program we are also implementing a special scoring 
methodology for FY 2022 that results in a value-based incentive payment 
amount that matches the 2-percent reduction to the base operating DRG 
payment amount.
    We note that the FY 2022 IPPS/LTCH PPS proposed rule included our 
proposals related to the implementation of the provisions of the 
Consolidated Appropriations Act (CAA) of 2021 related to payments to 
hospitals for direct graduate medical education (GME) and indirect 
medical education (IME) costs. Please refer to the proposed rule (86 FR 
25502 through 25524) for additional background information on these 
proposals. Due to the number and nature of the comments that we 
received on the implementation of sections 126, 127 and 131 of the CAA 
of 2021 relating to payments to hospitals for direct GME and IME costs, 
we will address public comments associated with these issues in future 
rulemaking.
    In addition, we note that the FY 2022 IPPS/LTCH PPS proposed rule 
included our proposals related to the organ acquisition payment policy 
for transplant hospitals, donor community hospitals and organ 
procurement organizations. Please refer to the proposed rule (86 FR 
25656 through 25676) for additional background information on these 
proposals. Due to the number and nature of the comments that we 
received on the organ acquisition payment policy proposals we will 
address public comments associated with these issues in future 
rulemaking.
    Under various statutory authorities, we either discuss continued 
program implementation or are making changes to the Medicare IPPS, to 
the LTCH PPS, other related payment methodologies and programs for FY 
2022 and subsequent fiscal years, and other policies and provisions 
included in this rule. These statutory authorities include, but are not 
limited to, the following:
     Section 1886(d) of the Social Security Act (the Act), 
which sets forth a system of payment for the operating costs of acute 
care hospital inpatient stays under Medicare Part A (Hospital 
Insurance) based on prospectively set rates. Section 1886(g) of the Act 
requires that, instead of paying for capital-related costs of inpatient 
hospital services on a reasonable cost basis, the Secretary use a 
prospective payment system (PPS).
     Section 1886(d)(1)(B) of the Act, which specifies that 
certain hospitals and hospital units are excluded from the IPPS. These 
hospitals and units are: Rehabilitation hospitals and units; LTCHs; 
psychiatric hospitals and units; children's hospitals; cancer 
hospitals; extended neoplastic disease care hospitals, and hospitals 
located outside the 50 States, the District of Columbia, and Puerto 
Rico (that is, hospitals located in the U.S. Virgin Islands, Guam, the 
Northern Mariana Islands, and American Samoa). Religious nonmedical 
health care institutions (RNHCIs) are also excluded from the IPPS.
     Sections 123(a) and (c) of the BBRA (Public Law (Pub. L.) 
106-113) and section 307(b)(1) of the BIPA (Pub. L. 106-554) (as 
codified under section 1886(m)(1) of the Act), which provide for the 
development and implementation of a prospective payment system for 
payment for inpatient hospital services of LTCHs described in section 
1886(d)(1)(B)(iv) of the Act.
     Sections 1814(l), 1820, and 1834(g) of the Act, which 
specify that payments are made to critical access hospitals (CAHs) 
(that is, rural hospitals or facilities that meet certain statutory 
requirements) for inpatient and outpatient services and that these 
payments are generally based on 101 percent of reasonable cost.
     Section 1886(a)(4) of the Act, which specifies that costs 
of approved

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educational activities are excluded from the operating costs of 
inpatient hospital services. Hospitals with approved graduate medical 
education (GME) programs are paid for the direct costs of GME in 
accordance with section 1886(h) of the Act.
     Section 1886(b)(3)(B)(viii) of the Act, which requires the 
Secretary to reduce the applicable percentage increase that would 
otherwise apply to the standardized amount applicable to a subsection 
(d) hospital for discharges occurring in a fiscal year if the hospital 
does not submit data on measures in a form and manner, and at a time, 
specified by the Secretary.
     Section 1866(k) of the Act, which provides for the 
establishment of a quality reporting program for hospitals described in 
section 1886(d)(1)(B)(v) of the Act, referred to as ``PPS-exempt cancer 
hospitals.''
     Section 1886(o) of the Act, which requires the Secretary 
to establish a Hospital Value-Based Purchasing (VBP) Program, under 
which value-based incentive payments are made in a fiscal year to 
hospitals meeting performance standards established for a performance 
period for such fiscal year.
     Section 1886(p) of the Act, which establishes a Hospital-
Acquired Condition (HAC) Reduction Program, under which payments to 
applicable hospitals are adjusted to provide an incentive to reduce 
hospital-acquired conditions.
     Section 1886(q) of the Act, as amended by section 15002 of 
the 21st Century Cures Act, which establishes the Hospital Readmissions 
Reduction Program. Under the program, payments for discharges from an 
applicable hospital as defined under section 1886(d) of the Act will be 
reduced to account for certain excess readmissions. Section 15002 of 
the 21st Century Cures Act directs the Secretary to compare hospitals 
with respect to the number of their Medicare-Medicaid dual-eligible 
beneficiaries (dual-eligibles) in determining the extent of excess 
readmissions.
     Section 1886(r) of the Act, as added by section 3133 of 
the Affordable Care Act, which provides for a reduction to 
disproportionate share hospital (DSH) payments under section 
1886(d)(5)(F) of the Act and for a new uncompensated care payment to 
eligible hospitals. Specifically, section 1886(r) of the Act requires 
that, for fiscal year 2014 and each subsequent fiscal year, subsection 
(d) hospitals that would otherwise receive a DSH payment made under 
section 1886(d)(5)(F) of the Act will receive two separate payments: 
(1) 25 percent of the amount they previously would have received under 
section 1886(d)(5)(F) of the Act for DSH (``the empirically justified 
amount''), and (2) an additional payment for the DSH hospital's 
proportion of uncompensated care, determined as the product of three 
factors. These three factors are: (1) 75 percent of the payments that 
would otherwise be made under section 1886(d)(5)(F) of the Act; (2) 1 
minus the percent change in the percent of individuals who are 
uninsured; and (3) a hospital's uncompensated care amount relative to 
the uncompensated care amount of all DSH hospitals expressed as a 
percentage.
     Section 1886(m)(5) of the Act, which requires the 
Secretary to reduce by two percentage points the annual update to the 
standard Federal rate for discharges for a long-term care hospital 
(LTCH) during the rate year for LTCHs that do not submit data in the 
form, manner, and at a time, specified by the Secretary.
     Section 1886(m)(6) of the Act, as added by section 
1206(a)(1) of the Pathway for Sustainable Growth Rate (SGR) Reform Act 
of 2013 (Pub. L. 113-67) and amended by section 51005(a) of the 
Bipartisan Budget Act of 2018 (Pub. L. 115-123), which provided for the 
establishment of site neutral payment rate criteria under the LTCH PPS, 
with implementation beginning in FY 2016. Section 51005(b) of the 
Bipartisan Budget Act of 2018 amended section 1886(m)(6)(B) by adding 
new clause (iv), which specifies that the IPPS comparable amount 
defined in clause (ii)(I) shall be reduced by 4.6 percent for FYs 2018 
through 2026.
     Section 1899B of the Act, as added by section 2(a) of the 
Improving Medicare Post-Acute Care Transformation Act of 2014 (IMPACT 
Act) (Pub. L. 113-185), which provides for the establishment of 
standardized data reporting for certain post-acute care providers, 
including LTCHs.
     Section 1899 of the Act which established the Medicare 
Shared Savings Program (Shared Savings Program) to facilitate 
coordination and cooperation among providers and suppliers to improve 
the quality of care for Medicare fee-for-service (FFS) beneficiaries 
and reduce the rate of growth in expenditures under Medicare Parts A 
and B.
     Section 1902(kk)(3) of the Act, as amended by section 
6401(b) of the Affordable Care Act, which mandates that states require 
providers and suppliers to comply with the same disclosure requirements 
established by the Secretary under section 1866(j)(5) of the Act.
     Section 2107(e)(1) of the Act, as amended by section 
6401(c) of the Affordable Care Act, which makes the requirements of 
section 1902(kk) of the Act, including the disclosure requirements, 
applicable to CHIP.
2. Summary of the Major Provisions
    The following is a summary of the major provisions in this final 
rule. In general, these major provisions are being finalized as part of 
the annual update to the payment policies and payment rates, consistent 
with the applicable statutory provisions. A general summary of the 
changes in this final rule is presented in section I.D. of the preamble 
of this final rule.
a. MS-DRG Documentation and Coding Adjustment
    Section 631 of the American Taxpayer Relief Act of 2012 (ATRA, Pub. 
L. 112- 240) amended section 7(b)(1)(B) of Public Law 110-90 to require 
the Secretary to make a recoupment adjustment to the standardized 
amount of Medicare payments to acute care hospitals to account for 
changes in MS-DRG documentation and coding that do not reflect real 
changes in case-mix, totaling $11 billion over a 4-year period of FYs 
2014, 2015, 2016, and 2017. The FY 2014 through FY 2017 adjustments 
represented the amount of the increase in aggregate payments as a 
result of not completing the prospective adjustment authorized under 
section 7(b)(1)(A) of Public Law 110-90 until FY 2013. Prior to the 
ATRA, this amount could not have been recovered under Public Law 110-
90. Section 414 of the Medicare Access and CHIP Reauthorization Act of 
2015 (MACRA) (Pub. L. 114-10) replaced the single positive adjustment 
we intended to make in FY 2018 with a 0.5 percent positive adjustment 
to the standardized amount of Medicare payments to acute care hospitals 
for FYs 2018 through 2023. (The FY 2018 adjustment was subsequently 
adjusted to 0.4588 percent by section 15005 of the 21st Century Cures 
Act.) Therefore, for FY 2022, we are making an adjustment of +0.5 
percent to the standardized amount.
b. Extension of the New COVID-19 Treatments Add-on Payment (NCTAP)
    In response to the COVID-19 PHE, we established the New COVID-19 
Treatments Add-on Payment (NCTAP) under the IPPS for COVID-19 cases 
that meet certain criteria (85 FR 71157 and 71158). We believe that as 
drugs and biological products become available and are authorized for 
emergency use or approved by Food and Drug Administration (FDA) for the 
treatment

[[Page 44778]]

of COVID-19 in the inpatient setting, it is appropriate to increase the 
current IPPS payment amounts to mitigate any potential financial 
disincentives for hospitals to provide new COVID-19 treatments during 
the PHE. Therefore, effective for discharges occurring on or after 
November 2, 2020 and until the end of the PHE for COVID-19, CMS 
established the NCTAP.
    We anticipate that there might be inpatient cases of COVID-19, 
beyond the end of the PHE, for which payment based on the assigned MS-
DRG may not adequately reflect the additional cost of new COVID-19 
treatments. In order to continue to mitigate potential financial 
disincentives for hospitals to provide these new treatments, and to 
minimize any potential payment disruption immediately following the end 
of the PHE, we believe that the NCTAP should remain available for cases 
involving eligible treatments for the remainder of the fiscal year in 
which the PHE ends (for example, until September 30, 2022). After 
review of public comments received, and for the reasons discussed in 
section II.F. of the preamble of this final rule, we are finalizing to 
extend the NCTAP through the end of the fiscal year in which the PHE 
ends for all eligible products, including those approved for new 
technology add-on payments for FY 2022, with any new technology add-on 
payment reducing the amount of the NCTAP.
c. Use of FY 2020 or FY 2019 Data in the FY 2022 IPPS and LTCH PPS 
Ratesetting
    For the IPPS and LTCH PPS ratesetting, our longstanding goal is 
always to use the best available data overall. In section I.F. of the 
preamble of this final rule, we discuss our analysis of the best 
available data for use in the development of this FY 2022 IPPS/LTCH PPS 
final rule given the potential impact of the public health emergency 
(PHE) for the Coronavirus Disease (COVID-19). As discussed in section 
I.F. of the preamble of this final rule, we are using the FY 2019 data, 
such as the FY 2019 MedPAR file, for the FY 2022 ratesetting for 
circumstances where the FY 2020 data is significantly impacted by the 
COVID-19 PHE, primarily in that the utilization of inpatient services 
reflect generally markedly different utilization for certain types of 
services in FY 2020 than would have been expected in the absence of the 
PHE.
d. Continuation of the Low Wage Index Hospital Policy
    To help mitigate wage index disparities between high wage and low 
hospitals, in the FY 2020 IPPS/LTCH PPS rule (84 FR 42326 through 
42332), we adopted a policy to increase the wage index values for 
certain hospitals with low wage index values (the low wage index 
hospital policy). This policy was adopted in a budget neutral manner 
through an adjustment applied to the standardized amounts for all 
hospitals. We also indicated that this policy will be effective for at 
least 4 years, beginning in FY 2020, in order to allow employee 
compensation increases implemented by these hospitals sufficient time 
to be reflected in the wage index calculation. Therefore, for FY 2022, 
we are continuing the low-wage index hospital policy, and are also 
applying this policy in a budget neutral manner by applying an 
adjustment to the standardized amounts.
e. Implementation of Section 9831 of the American Rescue Plan Act of 
2021 (Pub. L. 117-2) Imputed Floor Wage Index Policy for All-Urban 
States
    Section 9831 of the American Rescue Plan Act of 2021 (Pub. L. 117-
2) amended section 1886(d)(3)(E) of the Act (42 U.S.C. 1395ww(d)(3)(E)) 
to establish a minimum area wage index for hospitals in all-urban 
States. Specifically, section 1886(d)(3)(E)(iv) of the Act (as added by 
section 9831(a)(2) of Pub. L. 117-2) reinstates the imputed floor wage 
index policy for all-urban States effective for discharges on or after 
October 1, 2021 (FY 2022) with no expiration date using the methodology 
described in 42 CFR 412.64(h)(4)(vi) as in effect for FY 2018. 
Furthermore, section 1886(d)(3)(E)(iv)(III) of the Act provides that 
the imputed floor wage index shall not be applied in a budget neutral 
manner. We refer readers to section III.G.2. of this final rule for a 
summary of the provisions of section 9831 of Public Law 117-2 that we 
are implementing in this final rule.
f. DSH Payment Adjustment and Additional Payment for Uncompensated Care
    Section 3133 of the Affordable Care Act modified the Medicare 
disproportionate share hospital (DSH) payment methodology beginning in 
FY 2014. Under section 1886(r) of the Act, which was added by section 
3133 of the Affordable Care Act, starting in FY 2014, Medicare DSHs 
receive 25 percent of the amount they previously would have received 
under the statutory formula for Medicare DSH payments in section 
1886(d)(5)(F) of the Act. The remaining amount, equal to 75 percent of 
the amount that otherwise would have been paid as Medicare DSH 
payments, is paid as additional payments after the amount is reduced 
for changes in the percentage of individuals that are uninsured. Each 
Medicare DSH will receive an additional payment based on its share of 
the total amount of uncompensated care for all Medicare DSHs for a 
given time period.
    In this final rule, we are updating our estimates of the three 
factors used to determine uncompensated care payments for FY 2022. We 
are also continuing to use uninsured estimates produced by CMS' Office 
of the Actuary (OACT) as part of the development of the National Health 
Expenditure Accounts (NHEA) in the calculation of Factor 2. Consistent 
with the policy adopted in the FY 2021 IPPS/LTCH PPS final rule for FY 
2022 and subsequent fiscal years, we are using a single year of data on 
uncompensated care costs from Worksheet S-10 of the FY 2018 cost 
reports to calculate Factor 3 in the FY 2022 methodology for all 
eligible hospitals with the exception of Indian Health Service (IHS) 
and Tribal hospitals and Puerto Rico hospitals. For IHS and Tribal 
hospitals and Puerto Rico hospitals we are finalizing our proposal to 
continue to use the low-income insured days proxy to calculate Factor 3 
for these hospitals for FY 2022. We are also finalizing certain 
methodological changes for calculating Factor 3 for FY 2022.
g. Modification of Limitations on Redesignation by the Medicare 
Geographic Classification Review Board (MGCRB)
    In May 10, 2021 Federal Register (86 FR 24735), concurrent with the 
FY 2022 IPPS/LTCH PPS proposed rule, we published an interim final rule 
with comment period (IFC) (CMS-1762-IFC) that amended our current 
regulations to allow hospitals with a rural redesignation under the Act 
to reclassify through the Medicare MGCRB using the rural reclassified 
area as the geographic area in which the hospital is located. These 
regulatory changes align our policy with the decision in Bates County 
Memorial Hospital v. Azar, effective with reclassifications beginning 
with fiscal year (FY) 2023. We respond to the public comments on CMS-
1762-IFC in this final rule, and finalize the regulatory changes made 
therein.
h. Reduction of Hospital Payments for Excess Readmissions
    We are making changes to policies for the Hospital Readmissions 
Reduction Program, which was established under section 1886(q) of the 
Act, as amended by section 15002 of the 21st Century

[[Page 44779]]

Cures Act. The Hospital Readmissions Reduction Program requires a 
reduction to a hospital's base operating DRG payment to account for 
excess readmissions of selected applicable conditions. For FY 2017 and 
subsequent years, the reduction is based on a hospital's risk-adjusted 
readmission rate during a 3-year period for acute myocardial infarction 
(AMI), heart failure (HF), pneumonia, chronic obstructive pulmonary 
disease (COPD), elective primary total hip arthroplasty/total knee 
arthroplasty (THA/TKA), and coronary artery bypass graft (CABG) 
surgery. In this FY 2022 IPPS/LTCH PPS final rule, we are finalizing 
the following policies: (1) To adopt a cross-program measure 
suppression policy for the duration of the public health emergency for 
COVID-19; (2) to suppress the Hospital 30-Day, All-Cause, Risk-
Standardized Readmission Rate (RSRR) following Pneumonia 
Hospitalization measure (NQF #0506) for the FY 2023 program year; (3) 
to modify the remaining five condition-specific readmission measures to 
exclude COVID-19 diagnosed patients from the measure denominators, 
beginning with the FY 2023 program year; (4) to use the MedPAR data 
that aligns with the applicable period for FY 2022; (5) to 
automatically adopt the use of MedPAR data corresponding to the 
applicable period beginning with the FY 2023 program year and all 
subsequent program years, unless otherwise specified by the Secretary; 
and (6) to update the regulatory text to reflect that our Hospital 
Compare website has been renamed and is now referred to as Care 
Compare. We are clarifying our Extraordinary Circumstances Exceptions 
(ECE) policy, and we also requested public comment on opportunities to 
advance health equity through possible future stratification of results 
by race and ethnicity for condition/procedure-specific readmission 
measures and by expansion of standardized data collection to additional 
social factors, such as language preference and disability status. We 
also sought comment on mechanisms of incorporating other demographic 
characteristics into analyses that address and advance health equity, 
such as the potential to include administrative and self-reported data 
to measure co-occurring disability status.
i. Hospital Value-Based Purchasing (VBP) Program
    Section 1886(o) of the Act requires the Secretary to establish a 
Hospital VBP Program under which value-based incentive payments are 
made in a fiscal year to hospitals based on their performance on 
measures established for a performance period for such fiscal year. In 
this final rule, we are finalizing our proposals to: (1) Establish a 
measure suppression policy for the duration of the public health 
emergency for COVID-19; (2) suppress the Hospital Consumer Assessment 
of Healthcare Providers and Systems (HCAHPS), Medicare Spending Per 
Beneficiary (MSPB), and five Healthcare-Associated Infection (HAI) 
measures, for the FY 2022 program year; and (3) suppress the Hospital 
30-Day, All-Cause, Risk-Standardized Mortality Rate Following Pneumonia 
(PN) Hospitalization (MORT-30-PN) measure for the FY 2023 program year. 
We are also finalizing our proposal to revise the scoring and payment 
methodology for the FY 2022 program year such that hospitals will not 
receive Total Performance Scores. We believe that awarding a TPS to any 
hospital based off the remaining measures that are not suppressed would 
not result in a fair national comparison and, as a result, are not 
awarding a TPS to any hospital for the FY 2022 program year. Instead, 
we are finalizing our proposal to award each hospital a payment 
incentive multiplier that results in a value-based incentive payment 
that is equal to the amount withheld for the fiscal year (2 percent). 
We are finalizing our proposal to remove the CMS Patient Safety and 
Adverse Events Composite (CMS PSI 90) measure beginning with FY 2023 
because the costs associated with the measure outweigh the benefit of 
its use in the program. We are also finalizing our proposal to update 
the baseline periods for certain measures affected by the ECE granted 
in response to the COVID-19 PHE and making a technical update to our 
terminology used in the Hospital VBP Program regulations.
j. Hospital-Acquired Condition (HAC) Reduction Program
    Section 1886(p) of the Act establishes an incentive to hospitals to 
reduce the incidence of hospital-acquired conditions by requiring the 
Secretary to make an adjustment to payments to applicable hospitals, 
effective for discharges beginning on October 1, 2014. This 1-percent 
payment reduction applies to hospitals that rank in the worst-
performing quartile (25 percent) of all applicable hospitals, relative 
to the national average, of conditions acquired during the applicable 
period and on all of the hospital's discharges for the specified fiscal 
year. In this FY 2022 IPPS/LTCH PPS final rule, we are: (1) Clarifying 
our ECE policy; (2) finalizing our proposal to adopt a cross-program 
measure suppression policy for the duration of the public health 
emergency for COVID-19; (3) finalizing our proposal to apply that 
measure suppression policy to suppress certain program data from FY 
2022, FY 2023, and FY 2024 HAC Reduction Programs; and (4) finalizing 
our proposal to update the regulatory text to reflect that the Hospital 
Compare website has been renamed and is now referred to as Care 
Compare.
k. Hospital Inpatient Quality Reporting (IQR) Program
    Under section 1886(b)(3)(B)(viii) of the Act, subsection (d) 
hospitals are required to report data on measures selected by the 
Secretary for a fiscal year in order to receive the full annual 
percentage increase that would otherwise apply to the standardized 
amount applicable to discharges occurring in that fiscal year.
    In this FY 2022 IPPS/LTCH PPS final rule, we are making several 
changes. We are finalizing the adoption of five new measures: (1) A new 
structural measure--Maternal Morbidity Structural Measure--beginning 
with a shortened reporting period from October 1, 2021 through December 
31, 2021 affecting the CY 2021 reporting period/FY 2023 payment 
determination; (2) the Hybrid Hospital-Wide All-Cause Risk Standardized 
Mortality (Hybrid HWM) measure in a stepwise fashion, beginning with a 
voluntary reporting period from July 1, 2022 through June 30, 2023, and 
followed by mandatory reporting from July 1, 2023 through June 30, 
2024, affecting the FY 2026 payment determination and for subsequent 
years; (3) the COVID-19 Vaccination Coverage among Health Care 
Personnel (HCP) measure beginning with a shortened reporting period 
from October 1, 2021 through December 31, 2021, affecting the CY 2021 
reporting period/FY 2023 payment determination and with quarterly 
reporting beginning with the FY 2024 payment determination and for 
subsequent years; and two medication-related adverse event eCQMs 
beginning with the CY 2023 reporting period/FY 2025 payment 
determination; (4) Hospital Harm-Severe Hypoglycemia eCQM (NQF #3503e); 
and (5) Hospital Harm-Severe Hyperglycemia eCQM (NQF #3533e).
    We are also finalizing the removal of three measures: (1) Exclusive 
Breast Milk Feeding (PC-05) (NQF #0480) beginning with the FY 2026 
payment determination; (2) Admit Decision Time to ED Departure Time for 
Admitted Patients (ED-2) (NQF #0497) beginning with the FY 2026 payment 
determination; and (3) the Discharged on Statin Medication eCQM (STK-
06)

[[Page 44780]]

(NQF #0439), beginning with the FY 2026 payment determination. We are 
not finalizing our proposals to remove the following two measures: (1) 
Death Among Surgical Inpatients with Serious Treatable Complications 
(CMS PSI-04); and (2) Anticoagulation Therapy for Atrial Fibrillation/
Flutter eCQM (STK-03) (NQF #0436).
    In the FY 2022 IPPS/LTCH PPS proposed rule (86 FR 25070), we 
requested comment from stakeholders on the potential future development 
and inclusion of two measures: (1) A mortality measure for patients 
admitted with COVID-19; and (2) a patient-reported outcomes measure 
following elective total hip and/or total knee arthroplasty (THA/TKA). 
We also requested comment from stakeholders on ways we can leverage 
measures to address gaps in existing health equity generally as well as 
comment on: (1) Potential future confidential stratified reporting for 
the Hospital-Wide All-Cause Unplanned Readmission (HWR) measure using 
both dual eligibility and race/ethnicity; and (2) potential future 
reporting of a structural measure to assess the degree of hospital 
leadership engagement in health equity performance data. We also 
requested feedback across programs on potential actions and priority 
areas that would enable the continued transformation of our quality 
measurement toward greater digital capture of data and use of the FHIR 
standard.
    In addition, we are finalizing our proposal that beginning with the 
CY 2023 reporting period/FY 2025 payment determination, hospitals will 
be required to use certified technology that has been updated 
consistent with the 2015 Edition Cures Update and clarifying that 
certified technology must support the reporting requirements for all 
available eCQMs. We also are finalizing our provision that hybrid 
measures comply with the same certification requirements as eCQMs, 
specifically that EHR technology must be certified to the 2015 Edition 
Cures Update. We are revising 42 CFR 412.140(a)(2) and 42 CFR 
412.140(e)(2)(iii) to replace the terms ``Security Administrator'' and 
``System Administrator'' with the term ``security official'' in 
alignment with other CMS quality programs. Due to an updated URL for 
the QualityNet website from QualityNet.org to QualityNet.cms.gov, we 
are also revising Hospital IQR Program regulations at 42 CFR 
412.140(a)(1) and 42 CFR 412.140(c)(2)(i) to reflect updates to the 
QualityNet website. Lastly, we are finalizing our proposal to extend 
the effects of the educational review process for chart-abstracted 
measures beginning with validations affecting the FY 2024 payment 
determination.
l. PPS-Exempt Cancer Hospital Quality Reporting Program
    Section 1866(k)(1) of the Act requires, for purposes of FY 2014 and 
each subsequent fiscal year, that a hospital described in section 
1886(d)(1)(B)(v) of the Act (a PPS-exempt cancer hospital, or a PCH) 
submit data in accordance with section 1866(k)(2) of the Act with 
respect to such fiscal year. There is no financial impact to PCH 
Medicare payment if a PCH does not participate.
    In this final rule, we are removing the Oncology: Plan of Care for 
Pain--Medical Oncology and Radiation Oncology (NQF #0383) (PCH-15) 
measure beginning with the FY 2024 program year, adopting the COVID-19 
Vaccination Coverage among Healthcare Personnel measure beginning with 
the FY 2023 program year, making a technical update to the terminology 
we use in the program, and codifying existing PCHQR Program policies in 
our regulations.
m. Medicare Promoting Interoperability Program
    For purposes of reducing the burden on eligible hospitals and CAHs, 
we are making several changes to the Medicare Promoting 
Interoperability Program. Specifically, we are: (1) Continuing the EHR 
reporting period of a minimum of any continuous 90-day period for new 
and returning eligible hospitals and CAHs for CY 2023 and increasing 
the EHR reporting period to a minimum of any continuous 180-day period 
for new and returning eligible hospitals and CAHs for CY 2024; (2) 
maintaining the Electronic Prescribing Objective's Query of PDMP 
measure as optional while increasing its available bonus from 5 points 
to 10 points for the EHR reporting period in CY 2022; (3) adding a new 
Health Information Exchange (HIE) Bi-Directional Exchange measure as a 
yes/no attestation to the HIE objective as an optional alternative to 
the two existing measures beginning with the EHR reporting period in CY 
2022; (4) requiring reporting a ``yes'' on four of the existing Public 
Health and Clinical Data Exchange Objective measures (Syndromic 
Surveillance Reporting, Immunization Registry Reporting, Electronic 
Case Reporting, and Electronic Reportable Laboratory Result Reporting) 
or requesting the applicable exclusion(s); (5) adding a new measure to 
the Protect Patient Health Information objective that requires eligible 
hospitals and CAHs to attest to having completed an annual assessment 
of SAFER Guides beginning with the EHR reporting period in CY 2022; (6) 
removing attestation statements 2 and 3 from the Promoting 
Interoperability Program's prevention of information blocking 
requirement; (7) increasing the minimum required score for the 
objectives and measures from 50 points to 60 points (out of 100 points) 
in order to be considered a meaningful EHR user; and (8) adopting two 
new eCQMs to the Medicare Promoting Interoperability Program's eCQM 
measure set beginning with the reporting period in CY 2023, in addition 
to removing three eCQMs from the measure set beginning with the 
reporting period in CY 2024, which updates are in alignment with the 
eCQM updates being finalized for the Hospital IQR Program. We are 
amending our regulation texts as necessary to incorporate several of 
these changes. We are not finalizing our proposal to remove the 
Anticoagulation Therapy for Atrial Fibrillation/Flutter eCQM (STK-03) 
(NQF #0436) in alignment with the Hospital IQR Program. We are also not 
finalizing our proposal to modify the Provide Patients Electronic 
Access to Their Health Information measure by requiring eligible 
hospitals and CAHs to ensure that patient health information remains 
available to the patient (or patient-authorized representative). We 
will consider the feedback we received for future rulemaking.
n. Repeal of Market-Based Data Collection and Market-Based MS-DRG 
Relative Weight Methodology
    As discussed in section V.L. of the preamble of this final rule, we 
are finalizing our proposal, without modification, to repeal the 
requirement that a hospital report on the Medicare cost report the 
median payer-specific negotiated charge that the hospital has 
negotiated with all of its MA organization payers, by MS-DRG, for cost 
reporting periods ending on or after January 1, 2021. We are also 
finalizing our proposal, without modification, to repeal the market-
based MS-DRG relative weight methodology adopted for calculating the 
MS-DRG relative weights effective in FY 2024, and to continue using the 
existing cost-based methodology for calculating the MS-DRG relative 
weights for FY 2024 and subsequent fiscal years. Lastly, we solicited 
comment on alternative approaches or data sources that could be used in 
Medicare fee-for-service (FFS) ratesetting. We will continue to 
consider these comments as applicable.

[[Page 44781]]

o. Medicare Shared Savings Program
    We are making changes to policies for the Shared Savings Program, 
which was established under section 1899 of the Act, to allow eligible 
ACOs participating in the BASIC track's glide path the option to elect 
to forgo automatic advancement along the glide path's increasing levels 
of risk and potential reward for performance year (PY) 2022. Under the 
policy we are adopting in this final rule, prior to the automatic 
advancement for PY 2022, an eligible ACO may elect to remain in the 
same level of the BASIC track's glide path in which it participated 
during PY 2021. For PY 2023, an ACO that elects this advancement 
deferral option will be automatically advanced to the level of the 
BASIC track's glide path in which it would have participated during PY 
2023 if it had advanced automatically to the required level for PY 2022 
(unless the ACO elects to advance more quickly before the start of PY 
2023).
3. Summary of Costs and Benefits
    The following table provides a summary of the costs, savings, 
benefits associated with the major provisions described in section 
I.A.3. of the preamble of this final rule.
BILLING CODE 4120-01-P

[[Page 44782]]

[GRAPHIC] [TIFF OMITTED] TR13AU21.000


[[Page 44783]]


[GRAPHIC] [TIFF OMITTED] TR13AU21.001


[[Page 44784]]


[GRAPHIC] [TIFF OMITTED] TR13AU21.002

BILLING CODE 4120-01-C

[[Page 44785]]

B. Background Summary

1. Acute Care Hospital Inpatient Prospective Payment System (IPPS)
    Section 1886(d) of the Act sets forth a system of payment for the 
operating costs of acute care hospital inpatient stays under Medicare 
Part A (Hospital Insurance) based on prospectively set rates. Section 
1886(g) of the Act requires the Secretary to use a prospective payment 
system (PPS) to pay for the capital-related costs of inpatient hospital 
services for these ``subsection (d) hospitals.'' Under these PPSs, 
Medicare payment for hospital inpatient operating and capital-related 
costs is made at predetermined, specific rates for each hospital 
discharge. Discharges are classified according to a list of diagnosis-
related groups (DRGs).
    The base payment rate is comprised of a standardized amount that is 
divided into a labor-related share and a nonlabor-related share. The 
labor-related share is adjusted by the wage index applicable to the 
area where the hospital is located. If the hospital is located in 
Alaska or Hawaii, the nonlabor-related share is adjusted by a cost-of-
living adjustment factor. This base payment rate is multiplied by the 
DRG relative weight.
    If the hospital treats a high percentage of certain low-income 
patients, it receives a percentage add-on payment applied to the DRG-
adjusted base payment rate. This add-on payment, known as the 
disproportionate share hospital (DSH) adjustment, provides for a 
percentage increase in Medicare payments to hospitals that qualify 
under either of two statutory formulas designed to identify hospitals 
that serve a disproportionate share of low-income patients. For 
qualifying hospitals, the amount of this adjustment varies based on the 
outcome of the statutory calculations. The Affordable Care Act revised 
the Medicare DSH payment methodology and provides for a new additional 
Medicare payment beginning on October 1, 2013, that considers the 
amount of uncompensated care furnished by the hospital relative to all 
other qualifying hospitals.
    If the hospital is training residents in an approved residency 
program(s), it receives a percentage add-on payment for each case paid 
under the IPPS, known as the indirect medical education (IME) 
adjustment. This percentage varies, depending on the ratio of residents 
to beds.
    Additional payments may be made for cases that involve new 
technologies or medical services that have been approved for special 
add-on payments. In general, to qualify, a new technology or medical 
service must demonstrate that it is a substantial clinical improvement 
over technologies or services otherwise available, and that, absent an 
add-on payment, it would be inadequately paid under the regular DRG 
payment. In addition, certain transformative new devices and certain 
antimicrobial products may qualify under an alternative inpatient new 
technology add-on payment pathway by demonstrating that, absent an add-
on payment, they would be inadequately paid under the regular DRG 
payment.
    The costs incurred by the hospital for a case are evaluated to 
determine whether the hospital is eligible for an additional payment as 
an outlier case. This additional payment is designed to protect the 
hospital from large financial losses due to unusually expensive cases. 
Any eligible outlier payment is added to the DRG-adjusted base payment 
rate, plus any DSH, IME, and new technology or medical service add-on 
adjustments.
    Although payments to most hospitals under the IPPS are made on the 
basis of the standardized amounts, some categories of hospitals are 
paid in whole or in part based on their hospital-specific rate, which 
is determined from their costs in a base year. For example, sole 
community hospitals (SCHs) receive the higher of a hospital-specific 
rate based on their costs in a base year (the highest of FY 1982, FY 
1987, FY 1996, or FY 2006) or the IPPS Federal rate based on the 
standardized amount. SCHs are the sole source of care in their areas. 
Specifically, section 1886(d)(5)(D)(iii) of the Act defines an SCH as a 
hospital that is located more than 35 road miles from another hospital 
or that, by reason of factors such as an isolated location, weather 
conditions, travel conditions, or absence of other like hospitals (as 
determined by the Secretary), is the sole source of hospital inpatient 
services reasonably available to Medicare beneficiaries. In addition, 
certain rural hospitals previously designated by the Secretary as 
essential access community hospitals are considered SCHs.
    Under current law, the Medicare-dependent, small rural hospital 
(MDH) program is effective through FY 2022. For discharges occurring on 
or after October 1, 2007, but before October 1, 2022, an MDH receives 
the higher of the Federal rate or the Federal rate plus 75 percent of 
the amount by which the Federal rate is exceeded by the highest of its 
FY 1982, FY 1987, or FY 2002 hospital-specific rate. MDHs are a major 
source of care for Medicare beneficiaries in their areas. Section 
1886(d)(5)(G)(iv) of the Act defines an MDH as a hospital that is 
located in a rural area (or, as amended by the Bipartisan Budget Act of 
2018, a hospital located in a State with no rural area that meets 
certain statutory criteria), has not more than 100 beds, is not an SCH, 
and has a high percentage of Medicare discharges (not less than 60 
percent of its inpatient days or discharges in its cost reporting year 
beginning in FY 1987 or in two of its three most recently settled 
Medicare cost reporting years).
    Section 1886(g) of the Act requires the Secretary to pay for the 
capital-related costs of inpatient hospital services in accordance with 
a prospective payment system established by the Secretary. The basic 
methodology for determining capital prospective payments is set forth 
in our regulations at 42 CFR 412.308 and 412.312. Under the capital 
IPPS, payments are adjusted by the same DRG for the case as they are 
under the operating IPPS. Capital IPPS payments are also adjusted for 
IME and DSH, similar to the adjustments made under the operating IPPS. 
In addition, hospitals may receive outlier payments for those cases 
that have unusually high costs.
    The existing regulations governing payments to hospitals under the 
IPPS are located in 42 CFR part 412, subparts A through M.
2. Hospitals and Hospital Units Excluded From the IPPS
    Under section 1886(d)(1)(B) of the Act, as amended, certain 
hospitals and hospital units are excluded from the IPPS. These 
hospitals and units are: Inpatient rehabilitation facility (IRF) 
hospitals and units; long-term care hospitals (LTCHs); psychiatric 
hospitals and units; children's hospitals; cancer hospitals; extended 
neoplastic disease care hospitals, and hospitals located outside the 50 
States, the District of Columbia, and Puerto Rico (that is, hospitals 
located in the U.S. Virgin Islands, Guam, the Northern Mariana Islands, 
and American Samoa). Religious nonmedical health care institutions 
(RNHCIs) are also excluded from the IPPS. Various sections of the 
Balanced Budget Act of 1997 (BBA) (Pub. L. 105-33), the Medicare, 
Medicaid and SCHIP [State Children's Health Insurance Program] Balanced 
Budget Refinement Act of 1999 (BBRA, Pub. L. 106-113), and the 
Medicare, Medicaid, and SCHIP Benefits Improvement and Protection Act 
of 2000 (BIPA, Pub. L. 106-554) provide for the implementation of PPSs 
for IRF hospitals and units, LTCHs, and psychiatric hospitals and units 
(referred to as inpatient psychiatric facilities (IPFs)). (We note that 
the annual updates to the LTCH PPS are included

[[Page 44786]]

along with the IPPS annual update in this document. Updates to the IRF 
PPS and IPF PPS are issued as separate documents.) Children's 
hospitals, cancer hospitals, hospitals located outside the 50 States, 
the District of Columbia, and Puerto Rico (that is, hospitals located 
in the U.S. Virgin Islands, Guam, the Northern Mariana Islands, and 
American Samoa), and RNHCIs continue to be paid solely under a 
reasonable cost-based system, subject to a rate-of-increase ceiling on 
inpatient operating costs. Similarly, extended neoplastic disease care 
hospitals are paid on a reasonable cost basis, subject to a rate-of-
increase ceiling on inpatient operating costs.
    The existing regulations governing payments to excluded hospitals 
and hospital units are located in 42 CFR parts 412 and 413.
3. Long-Term Care Hospital Prospective Payment System (LTCH PPS)
    The Medicare prospective payment system (PPS) for LTCHs applies to 
hospitals described in section 1886(d)(1)(B)(iv) of the Act, effective 
for cost reporting periods beginning on or after October 1, 2002. The 
LTCH PPS was established under the authority of sections 123 of the 
BBRA and section 307(b) of the BIPA (as codified under section 
1886(m)(1) of the Act). Section 1206(a) of the Pathway for SGR Reform 
Act of 2013 (Pub. L. 113-67) established the site neutral payment rate 
under the LTCH PPS, which made the LTCH PPS a dual rate payment system 
beginning in FY 2016. Under this statute, effective for LTCH's cost 
reporting periods beginning in FY 2016 cost reporting period, LTCHs are 
generally paid for discharges at the site neutral payment rate unless 
the discharge meets the patient criteria for payment at the LTCH PPS 
standard Federal payment rate. The existing regulations governing 
payment under the LTCH PPS are located in 42 CFR part 412, subpart O. 
Beginning October 1, 2009, we issue the annual updates to the LTCH PPS 
in the same documents that update the IPPS.
4. Critical Access Hospitals (CAHs)
    Under sections 1814(l), 1820, and 1834(g) of the Act, payments made 
to critical access hospitals (CAHs) (that is, rural hospitals or 
facilities that meet certain statutory requirements) for inpatient and 
outpatient services are generally based on 101 percent of reasonable 
cost. Reasonable cost is determined under the provisions of section 
1861(v) of the Act and existing regulations under 42 CFR part 413.
5. Payments for Graduate Medical Education (GME)
    Under section 1886(a)(4) of the Act, costs of approved educational 
activities are excluded from the operating costs of inpatient hospital 
services. Hospitals with approved graduate medical education (GME) 
programs are paid for the direct costs of GME in accordance with 
section 1886(h) of the Act. The amount of payment for direct GME costs 
for a cost reporting period is based on the hospital's number of 
residents in that period and the hospital's costs per resident in a 
base year. The existing regulations governing payments to the various 
types of hospitals are located in 42 CFR part 413.

C. Summary of Provisions of Recent Legislation Implemented in This 
Final Rule

1. The Medicare Access and CHIP Reauthorization Act of 2015 (Pub. L. 
114-10)
    Section 414 of the Medicare Access and CHIP Reauthorization Act of 
2015 (MACRA, Pub. L. 114-10) specifies a 0.5 percent positive 
adjustment to the standardized amount of Medicare payments to acute 
care hospitals for FYs 2018 through 2023. These adjustments follow the 
recoupment adjustment to the standardized amounts under section 1886(d) 
of the Act based upon the Secretary's estimates for discharges 
occurring from FYs 2014 through 2017 to fully offset $11 billion, in 
accordance with section 631 of the ATRA. The FY 2018 adjustment was 
subsequently adjusted to 0.4588 percent by section 15005 of the 21st 
Century Cures Act.
2. The American Rescue Plan Act of 2021 (Pub. L. 117-2)
    Section 9831 of the American Rescue Plan Act of 2021 (Pub. L. 117-
2) amended section 1886(d)(3)(E) of the Act (42 U.S.C. 1395ww(d)(3)(E)) 
to establish a minimum area wage index for hospitals in all-urban 
States. Specifically, section 1886(d)(3)(E)(iv) of the Act (as added by 
section 9831(a)(2) of Pub. L. 117-2) reinstates the imputed floor wage 
index policy for all-urban states effective for discharges on or after 
October 1, 2021 (FY 2022) with no expiration date using the methodology 
described in 42 CFR 412.64(h)(4)(vi) as in effect for FY 2018.

D. Issuance of Proposed and Interim Final Rulemakings

1. FY 2022 IPPS/LTCH PPS Proposed Rule
    In the FY 2022 IPPS/LTCH PPS proposed rule appearing in the May 10, 
2021 Federal Register (86 FR 25070), we set forth proposed payment and 
policy changes to the Medicare IPPS for FY 2022 operating costs and 
capital-related costs of acute care hospitals and certain hospitals and 
hospital units that are excluded from IPPS. In addition, we set forth 
proposed changes to the payment rates, factors, and other payment and 
policy-related changes to programs associated with payment rate 
policies under the LTCH PPS for FY 2022.
    The following is a general summary of the changes that we proposed 
to make.
a. Proposed Changes to MS-DRG Classifications and Recalibrations of 
Relative Weights
    In section II. of the preamble of the proposed rule, we include--
     Proposed changes to MS-DRG classifications based on our 
yearly review for FY 2022.
     Proposed adjustment to the standardized amounts under 
section 1886(d) of the Act for FY 2022 in accordance with the 
amendments made to section 7(b)(1)(B) of Public Law 110-90 by section 
414 of the MACRA.
     Proposed recalibration of the MS-DRG relative weights.
     A discussion of the proposed FY 2022 status of new 
technologies approved for add-on payments for FY 2022, a presentation 
of our evaluation and analysis of the FY 2022 applicants for add-on 
payments for high-cost new medical services and technologies (including 
public input, as directed by Pub. L. 108-173, obtained in a town hall 
meeting) for applications not submitted under an alternative pathway, 
and a discussion of the proposed status of FY 2022 new technology 
applicants under the alternative pathways for certain medical devices 
and certain antimicrobial products.
     A proposal to extend the New COVID-19 Treatments Add-on 
Payment (NCTAP) through the end of the fiscal year in which the PHE 
ends for certain products and discontinue NCTAP for products approved 
for new technology add-on payments in FY 2022.
b. Proposed Changes to the Hospital Wage Index for Acute Care Hospitals
    In section III. of the preamble of the proposed rule, we proposed 
to revise to the wage index for acute care hospitals and the annual 
update of the wage data. Specific issues addressed include, but were 
not limited to, the following:
     The proposed FY 2022 wage index update using wage data 
from cost reporting periods beginning in FY 2018.
     Calculation, analysis, and implementation of the proposed 
occupational mix adjustment to the wage index for acute care hospitals 
for

[[Page 44787]]

FY 2022 based on the 2019 Occupational Mix Survey.
     Proposed application of the rural floor and the frontier 
State floor, and continuation of the low wage index hospital policy.
     Proposed implementation of the imputed floor wage index 
policy for all-urban States under section 9831 of the American Rescue 
Plan Act of 2021 (Pub. L. 117-2).
     Proposed revisions to the wage index for acute care 
hospitals, based on hospital redesignations and reclassifications under 
sections 1886(d)(8)(B), (d)(8)(E), and (d)(10) of the Act.
     Proposed revisions to the regulations at Sec.  412.278 
regarding the Administrator's Review of MGCRB decisions.
     Proposed changes to rural reclassification cancellation 
requirements at Sec.  412.103(g).
     Proposed adjustment to the wage index for acute care 
hospitals for FY 2022 based on commuting patterns of hospital employees 
who reside in a county and work in a different area with a higher wage 
index.
     Proposed labor-related share for the proposed FY 2022 wage 
index.
c. Proposed Rebasing and Revising of the Hospital Market Baskets
    In section IV. of the preamble of the proposed rule, we proposed to 
rebase and revise the hospital market baskets for acute care hospitals 
and update the labor-related share.
d. Other Decisions and Proposed Changes to the IPPS for Operating Costs
    In section V. of the preamble of the proposed rule, we discussed 
proposed changes or clarifications of a number of the provisions of the 
regulations in 42 CFR parts 412 and 413, including the following:
     Proposed inpatient hospital update for FY 2022.
     Proposed updated national and regional case-mix values and 
discharges for purposes of determining RRC status.
     The statutorily required IME adjustment factor for FY 
2022.
     Proposed changes to the methodologies for determining 
Medicare DSH payments and the additional payments for uncompensated 
care.
     Proposed requirements for payment adjustments under the 
Hospital Readmissions Reduction Program for FY 2022.
     The provision of estimated and newly established 
performance standards for the calculation of value-based incentive 
payments, as well as a proposal to suppress multiple measures and 
provide net-neutral payment adjustments under the Hospital Value-Based 
Purchasing Program.
     Proposed requirements for payment adjustments to hospitals 
under the HAC Reduction Program for FY 2022.
     Discussion of and proposed changes relating to the 
implementation of the Rural Community Hospital Demonstration Program in 
FY 2022.
     Proposed revisions to the regulations regarding the 
counting of days associated with section 1115 demonstration projects in 
the Medicaid fraction.
     Proposals to implement provisions of the Consolidated 
Appropriations Act relating to payments to hospitals for direct 
graduate medical education (GME) and indirect medical education (IME) 
costs.
     Proposed repeal of the market-based data collection 
requirement and market-based MS-DRG relative weight methodology
e. Proposed FY 2022 Policy Governing the IPPS for Capital-Related Costs
    In section VI. of the preamble to the proposed rule, we discussed 
the proposed payment policy requirements for capital-related costs and 
capital payments to hospitals for FY 2022.
f. Proposed Changes to the Payment Rates for Certain Excluded 
Hospitals: Rate-of-Increase Percentages
    In section VII. of the preamble of the proposed rule, we discussed 
the following:
     Proposed changes to payments to certain excluded hospitals 
for FY 2022.
     Proposed continued implementation of the Frontier 
Community Health Integration Project (FCHIP) Demonstration.
g. Proposed Changes to the LTCH PPS
    In section VIII. of the preamble of the proposed rule, we set forth 
proposed changes to the LTCH PPS Federal payment rates, factors, and 
other payment rate policies under the LTCH PPS for FY 2022.
h. Proposed Changes Relating to Quality Data Reporting for Specific 
Providers and Suppliers
    In section IX. of the preamble of the proposed rule, we addressed 
the following:
     We requested information on CMS's future plans to define 
digital quality measures (dQMs) in CMS Hospital Quality Programs and on 
CMS' continued efforts to close the health equity gap in CMS Hospital 
Quality Programs.
     Proposed requirements for the Hospital Inpatient Quality 
Reporting (IQR) Program.
     Proposed changes to the requirements for the quality 
reporting program for PPS-exempt cancer hospitals (PCHQR Program).
     Proposed changes to the requirements under the LTCH 
Quality Reporting Program (QRP). We also sought information on CMS's 
future plans to define digital quality measures (dQMs) for the LTCH QRP 
and on CMS' continued efforts to close the health equity gap.
     Proposed changes to requirements pertaining to eligible 
hospitals and CAHs participating in the Medicare Promoting 
Interoperability Program.
i. Other Proposals Included in the Proposed Rule
    Section X. of the preamble of the proposed rule included the 
following proposals:
     Proposed changes pertaining to Medicaid enrollment of 
Medicare-enrolled providers and suppliers to 42 CFR part 455.410 and 
request for comment on provider experiences where State Medicaid 
agencies apply the Medicaid payment and coverage rules to a claim for a 
Medicare service rather than adjudicating the claim for Medicare cost-
sharing liability.
     Proposed changes pertaining to Medicare's share of organ 
acquisition costs transplanted into Medicare beneficiaries and the 
charges for services provided to cadaveric organ donors by donor 
community hospitals and transplants hospitals.
     Proposed changes pertaining to the Shared Savings Program 
that would allow eligible ACOs participating in the BASIC track's glide 
path to maintain their current level of participation for PY 2022.
j. Other Provisions of the Proposed Rule
    Section XI. of the preamble to the proposed rule included our 
discussion of the MedPAC Recommendations.
    Section XII. of the preamble to the proposed rule includes the 
following:
     A descriptive listing of the public use files associated 
with the proposed rule.
     The collection of information requirements for entities 
based on our proposals.
     Information regarding our responses to public comments.
k. Determining Prospective Payment Operating and Capital Rates and 
Rate-of-Increase Limits for Acute Care Hospitals
    In sections II. and III. of the Addendum to the proposed rule, we 
set

[[Page 44788]]

forth proposed changes to the amounts and factors for determining the 
proposed FY 2022 prospective payment rates for operating costs and 
capital-related costs for acute care hospitals. We proposed to 
establish the threshold amounts for outlier cases. In addition, in 
section IV. of the Addendum to the proposed rule, we addressed the 
proposed update factors for determining the rate-of-increase limits for 
cost reporting periods beginning in FY 2022 for certain hospitals 
excluded from the IPPS.
l. Determining Prospective Payment Rates for LTCHs
    In section V. of the Addendum to the proposed rule, we set forth 
proposed changes to the amounts and factors for determining the 
proposed FY 2022 LTCH PPS standard Federal payment rate and other 
factors used to determine LTCH PPS payments under both the LTCH PPS 
standard Federal payment rate and the site neutral payment rate in FY 
2022. We are proposing to establish the adjustments for the wage index, 
labor-related share, the cost-of-living adjustment, and high-cost 
outliers, including the applicable fixed-loss amounts and the LTCH 
cost-to-charge ratios (CCRs) for both payment rates.
m. Impact Analysis
    In Appendix A of the proposed rule, we set forth an analysis of the 
impact the proposed changes would have on affected acute care 
hospitals, CAHs, LTCHs, PCHs and other entities.
n. Recommendation of Update Factors for Operating Cost Rates of Payment 
for Hospital Inpatient Services
    In Appendix B of the proposed rule, as required by sections 
1886(e)(4) and (e)(5) of the Act, we provide our recommendations of the 
appropriate percentage changes for FY 2022 for the following:
     A single average standardized amount for all areas for 
hospital inpatient services paid under the IPPS for operating costs of 
acute care hospitals (and hospital-specific rates applicable to SCHs 
and MDHs).
     Target rate-of-increase limits to the allowable operating 
costs of hospital inpatient services furnished by certain hospitals 
excluded from the IPPS.
     The LTCH PPS standard Federal payment rate and the site 
neutral payment rate for hospital inpatient services provided for LTCH 
PPS discharges.
o. Discussion of Medicare Payment Advisory Commission Recommendations
    Under section 1805(b) of the Act, MedPAC is required to submit a 
report to Congress, no later than March 15 of each year, in which 
MedPAC reviews and makes recommendations on Medicare payment policies. 
MedPAC's March 2021 recommendations concerning hospital inpatient 
payment policies address the update factor for hospital inpatient 
operating costs and capital-related costs for hospitals under the IPPS. 
We addressed these recommendations in Appendix B of the proposed rule. 
For further information relating specifically to the MedPAC March 2021 
report or to obtain a copy of the report, contact MedPAC at (202) 220-
3700 or visit MedPAC's website at: http://www.medpac.gov.
2. Medicare Geographic Classification Review Board (MGCRB) Interim 
Final Rule With Comment Period
    In the interim final rule with comment period appearing in the May 
10, 2021 Federal Register (86 FR 25735) (hereinafter referred to as 
CMS-1762-IFC), we implemented regulations which allowed hospitals with 
a rural redesignation under the section XXXX of the Act to reclassify 
through the Medicare Geographic Classification Review Board (MGCRB) 
using the rural reclassified area as the geographic area in which the 
hospital is located.

E. Advancing Health Information Exchange

    The Department of Health and Human Services (HHS) has a number of 
initiatives designed to encourage and support the adoption of 
interoperable health information technology and to promote nationwide 
health information exchange to improve health care and patient access 
to their health information.
    To further interoperability in post-acute care settings, CMS and 
the Office of the National Coordinator for Health Information 
Technology (ONC) participate in the Post-Acute Care Interoperability 
Workgroup (PACIO http://pacioproject.org/) to facilitate collaboration 
with industry stakeholders to develop FHIR standards. These standards 
could support the exchange and reuse of patient assessment data derived 
from the Minimum Data Set (MDS), Inpatient Rehabilitation Facility-
Patient Assessment Instrument (IRF-PAI), LTCH Continuity Assessment 
Record and Evaluation (CARE Data Set (LCDS), Outcome and Assessment 
Information Set (OASIS), and other sources. The PACIO Project has 
focused on FHIR implementation guides for functional status, cognitive 
status and new use cases on advance directives and speech language 
pathology. We encourage post-acute care (PAC) provider and health 
information technology (IT) vendor participation as the efforts 
advance.
    The CMS Data Element Library (DEL) continues to be updated and 
serves as the authoritative resource for PAC assessment data elements 
and their associated mappings to health IT standards, such as Logical 
Observation Identifiers Names and Codes (LOINC) and Systematized 
Nomenclature of Medicine Clinical Terms (SNOMED). The DEL furthers CMS' 
goal of data standardization and interoperability. These interoperable 
data elements can reduce provider burden by allowing the use and 
exchange of healthcare data; supporting provider exchange of electronic 
health information for care coordination, person-centered care; and 
supporting real-time, data driven, clinical decision-making. Standards 
in the Data Element Library (https://del.cms.gov/DELWeb/pubHome) can be 
referenced on the CMS website and in the ONC Interoperability Standards 
Advisory (ISA). The 2021 ISA is available at https://www.healthit.gov/isa.
    The 21st Century Cures Act (Cures Act) (Pub. L. 114-255, enacted 
December 13, 2016) requires HHS to take new steps to enable the 
electronic sharing of health information ensuring interoperability for 
providers and settings across the care continuum. The Cures Act 
includes a trusted exchange framework and common agreement (TEFCA) 
provision \1\ that will enable the nationwide exchange of electronic 
health information across health information networks and provide an 
important way to enable bi-directional health information exchange in 
the future. For more information on current developments related to 
TEFCA, we refer readers to https://www.healthit.gov/topic/interoperability/trusted-exchange-framework-and-common-agreement and 
https://rce.sequoiaproject.org/.
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    \1\ ONC, Draft 2 Trusted Exchange Framework and Common 
Agreement, https://www.healthit.gov/sites/default/files/page/2019-04/FINALTEFCAQTF41719508version.pdf.
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    The ONC final rule entitled ``21st Century Cures Act: 
Interoperability, Information Blocking, and the ONC Health IT 
Certification Program'' (85 FR 25642) published in the May 1, 2020 
Federal Register, (hereinafter referred to as ``ONC Cures Act Final 
Rule'')

[[Page 44789]]

implemented policies related to information blocking as authorized 
under section 4004 of the 21st Century Cures Act. Information blocking 
is generally defined as a practice by a health IT developer of 
certified health IT, health information network, health information 
exchange, or health care provider that, except as required by law or 
specified by the HHS Secretary as a reasonable and necessary activity, 
is likely to interfere with access, exchange, or use of electronic 
health information. For a health care provider (as defined in 45 CFR 
171.102), the definition of information blocking (see 45 CFR 171.103) 
specifies that the provider knows that the practice is unreasonable, as 
well as likely to interfere with access, exchange, or use of electronic 
health information.\2\ To deter information blocking, health IT 
developers of certified health IT, health information networks and 
health information exchanges whom the HHS Inspector General determines, 
following an investigation, have committed information blocking, are 
subject to civil monetary penalties of up to $1 million per violation. 
Appropriate disincentives for health care providers need to be 
established by the Secretary through rulemaking. Stakeholders can learn 
more about information blocking at https://www.healthit.gov/curesrule/final-rule-policy/information-blocking. ONC has posted information 
resources including fact sheets (https://www.healthit.gov/curesrule/resources/fact-sheets), frequently asked questions (https://www.healthit.gov/curesrule/resources/information-blocking-faqs), and 
recorded webinars (https://www.healthit.gov/curesrule/resources/webinars).
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    \2\ For other types of actors (health IT developers of certified 
health IT and health information network or health information 
exchange, as defined in 45 CFR 171.102), the definition of 
``information blocking'' (see 45 CFR 171.103) specifies that the 
actor ``knows, or should know, that such practice is likely to 
interfere with access, exchange, or use of electronic health 
information.''
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    We invite providers to learn more about these important 
developments and how they are likely to affect LTCHs.

F. Use of FY 2020 or FY 2019 Data in the FY 2022 IPPS and LTCH PPS 
Ratesetting

    We primarily use two data sources in the IPPS and LTCH PPS 
ratesetting: Claims data and cost report data. The claims data source 
is the MedPAR file, which includes fully coded diagnostic and procedure 
data for all Medicare inpatient hospital claims for discharges in a 
fiscal year. Our goal is always to use the best available data overall 
for ratesetting. Ordinarily, the best available MedPAR data would be 
the most recent MedPAR file that contains claims from discharges for 
the fiscal year that is 2 years prior to the fiscal year that is the 
subject of the rulemaking. For FY 2022 ratesetting, under ordinary 
circumstances, the best available data would be the FY 2020 MedPAR 
file. The cost report data source is the Medicare hospital cost report 
data files from the most recent quarterly HCRIS release. For example, 
ordinarily, the best available cost report data used in relative weight 
calculations would be based on the cost reports beginning 3 fiscal 
years prior to the fiscal year that is the subject of the rulemaking. 
For the FY 2022 ratesetting, under ordinary circumstances, that would 
be the FY 2019 cost report data from HCRIS, which would contain many 
cost reports ending in FY 2020 based on each hospital's cost reporting 
period.
    In the FY 2022 IPPS/LTCH PPS proposed rule (86 FR 25086 through 
25090), we discussed that the FY 2020 MedPAR claims file and the FY 
2019 HCRIS dataset both contain data significantly impacted by the 
COVID-19 PHE, primarily in that the utilization of inpatient services 
was generally markedly different for certain types of services in FY 
2020 than would have been expected in the absence of the PHE. 
Accordingly, we questioned whether these data sources are the best 
available data to use for the FY 2022 ratesetting. In the proposed 
rule, we identified two factors for assessing whether these data 
sources represent the best available data. The first factor is to what 
extent the FY 2019 data from before the COVID-19 PHE is a better 
overall approximation of FY 2022 inpatient experience (for example, 
whether the share of total inpatient utilization for elective surgeries 
will be more similar to FY 2019 than to FY 2020), or alternatively, to 
what extent the FY 2020 data which include the COVID-19 PHE time period 
is a better overall approximation of FY 2022 inpatient experience (for 
example, whether the share of total inpatient utilization for 
respiratory infections will be more similar to FY 2020 than to FY 
2019). The second factor is to what extent the decision to use the FY 
2019 or FY 2020 data differentially impacts the FY 2022 IPPS 
ratesetting.
    In the proposed rule, in order to help assess likely inpatient 
utilization in FY 2022, we examined the trend in the number of COVID-19 
vaccinations in the United States as reported to the Centers for 
Disease Control (CDC) (see https://www.cdc.gov/coronavirus/2019-ncov/covid-data/covidview/index.html, accessed April 16, 2021).
    The U.S. COVID-19 Vaccination Program began December 14, 2020. As 
of April 15, 2021, 198.3 million vaccine doses had been administered. 
Overall, about 125.8 million people, or 37.9 percent of the U.S. 
population, had received at least one dose of vaccine as of this date. 
About 78.5 million people, or 23.6 percent of the U.S. population had 
been fully vaccinated.\3\ As of April 15, the 7-day average number of 
administered vaccine doses reported to CDC per day was 3.3 million, a 
10.3 percent increase from the previous week. As of April 15, 80 
percent of people 65 or older had received at least one dose of 
vaccine; 63.7 percent were fully vaccinated. Nearly one-half (48.3 
percent) of people 18 or older had received at least one dose of 
vaccine; 30.3 percent were fully vaccinated. Nationally, COVID-19-
related emergency department visits as well as both hospital admissions 
and current hospitalizations had risen among patients ages 18 to 64 
years in recent weeks, but emergency department visits and 
hospitalizations among people ages 65 years and older had decreased, 
likely demonstrating the important role vaccination plays in protecting 
against COVID-19.
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    \3\ People who are fully vaccinated (formerly receiving 2 doses) 
represents the number of people who have received the second dose in 
a two-dose COVID-19 vaccine series or one dose of the single-dose 
J&J/Janssen COVID-19 vaccine.
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    As indicated by the CDC, COVID-19 vaccines are effective at 
preventing COVID-19.\4\ For example, a CDC report on the effectiveness 
of the Pfizer-BioNTech and Moderna COVID-19 vaccines when administered 
in real-world conditions found that after being fully vaccinated with 
either of these vaccines a person's risk of infection is reduced by up 
to 90 percent. With respect to inpatient utilization in FY 2020, in the 
proposed rule we stated our belief that COVID-19 and the risk of 
disease were drivers of the different utilization patterns observed. 
Therefore, the continuing rapid increase in vaccinations coupled with 
the overall effectiveness of the vaccines led us to conclude based on 
the information

[[Page 44790]]

available at the time of the proposed rule that there will be 
significantly lower risk of COVID-19 in FY 2022 and fewer 
hospitalizations for COVID-19 for Medicare beneficiaries in FY 2022 
than there were in FY 2020. This called into question the applicability 
of inpatient data from FY 2020 to the FY 2022 time period for hospitals 
paid under the IPPS and LTCH PPS.
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    \4\ Interim Estimates of Vaccine Effectiveness of BNT162b2 and 
mRNA-1273 COVID-19 Vaccines in Preventing SARS-CoV-2 Infection Among 
Health Care Personnel, First Responders, and Other Essential and 
Frontline Workers--Eight U.S. Locations, December 2020-March 2021, 
available at https://www.cdc.gov/mmwr/volumes/70/wr/mm7013e3.htm?s_cid=mm7013e3_e&ACSTrackingID=USCDC_921-DM53321&ACSTrackingLabel=MMWR%20Early%20Release%20-%20Vol.%2070%2C%20March%2029%2C%202021&deliveryName=USCDC_921-DM53321, accessed April 2, 2021).
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    In the proposed rule, we also reviewed CDC guidance to healthcare 
facilities during the COVID-19 PHE (see https://www.cdc.gov/coronavirus/2019-ncov/hcp/guidance-hcf.html). In its most recent 
guidance available at the time of the proposed rule, the CDC described 
how the COVID-19 pandemic has changed how health care is delivered in 
the United States and has affected the operations of healthcare 
facilities. Effects cited by the CDC include increases in patients 
seeking care for respiratory illnesses, patients deferring and delaying 
non-COVID-19 care, disruptions in supply chains, fluctuations in 
facilities' occupancy, absenteeism among staff because of illness or 
caregiving responsibilities, and increases in mental health concerns.
    In the proposed rule, in order to investigate the effects cited by 
the CDC, we examined the claims data from the FY 2020 MedPAR compared 
to the FY 2019 MedPAR. Overall, in FY 2020, inpatient admissions under 
the IPPS dropped by approximately 14 percent compared to FY 2019. 
Elective surgeries declined significantly, and the share of admissions 
for MS-DRGs associated with the treatment of COVID-19 increased. For 
example, the number of inpatient admissions for MS-DRG 470 (Major Hip 
and Knee Joint Replacement or Reattachment of Lower Extremity without 
MCC) dropped by 40 percent in FY 2020. Its share of inpatient 
admissions dropped from 4.0 percent in FY 2019 to 2.8 percent in FY 
2020. The number of inpatient admissions for MS-DRG 177 (Respiratory 
Infections and Inflammations with MCC) increased by +133 percent. Its 
share of inpatient admissions increased from 0.8 percent in FY 2019 to 
2.2 percent in FY 2020. This data analysis from the proposed rule was 
consistent with the observations in the CDC's guidance that COVID-19 
increased the number of patients seeking care for respiratory 
illnesses, and caused patients to defer and delay non-COVID-19 care. In 
the proposed rule, we noted that these observed changes in the claims 
data also extend to the cost reports submitted by hospitals that 
include the COVID-19 PHE time period, since those cost reports that 
extend into the COVID-19 PHE are based in part on the discharges that 
occurred during that time.
    In the proposed rule, we concluded that the effects noted by the 
CDC are specific to the pandemic and to the extent that the effects on 
healthcare facilities noted by the CDC are not expected to continue 
into FY 2022, it would suggest that the inpatient data from FY 2020 
impacted by the COVID-19 PHE may be less suitable for use in the FY 
2022 ratesetting.
    In the proposed rule, we also considered the analysis of 2020 IPPS 
real case-mix included in the notice titled ``CY 2021 Inpatient 
Hospital Deductible and Hospital and Extended Care Services Coinsurance 
Amounts'' that appeared in the Federal Register on November 12, 2020 
(85 FR 71916). Section 1813(b) of the Act prescribes the method for 
computing the amount of the inpatient hospital deductible. The 
inpatient hospital deductible is an amount equal to the inpatient 
hospital deductible for the preceding CY, adjusted by the best estimate 
of the payment-weighted average of the applicable percentage increases 
used for updating the payment rates to hospitals, and adjusted to 
reflect changes in real case-mix.
    To develop the adjustment to reflect changes in real case-mix, we 
first calculated an average case-mix for each hospital that reflected 
the relative costliness of that hospital's mix of cases compared to 
those of other hospitals. We then computed the change in average case-
mix for hospitals paid under the IPPS in FY 2020 compared to FY 2019, 
using Medicare claims from IPPS hospitals received as of July 2020. 
Those claims represented a total of about 6.1 million Medicare 
discharges for FY 2020 and provided the most recent case-mix data 
available at the time of that analysis. Based on these claims, the 
change in average case-mix in FY 2020 was 2.8 percent. Based on these 
claims and past experience, we expected the overall case-mix change to 
be 3.8 percent as the year progressed and more FY 2020 data became 
available.
    Real case-mix is that portion of case-mix that is due to changes in 
the mix of cases in the hospital and not due to coding optimization. As 
stated in the November 2020 notice, COVID-19 has complicated the 
determination of real case-mix increase. COVID-19 cases typically group 
to higher-weighted MS-DRGs, and hospitals have experienced a concurrent 
reduction in cases that group to lower weighted MS-DRGs. Both of these 
factors cause a real increase in case-mix. We compared the average 
case-mix for February 2020 through July 2020 (COVID-19 period) with 
average case-mix for October 2019 through January 2020 (pre-COVID-19 
period). Since this increase applies for only a portion of CY 2020, we 
allocated this increase by the estimated discharges over the 2 
periods--a 2.5 percent increase for FY 2020. The 1.3-percent residual 
case-mix increase is a mixture of real case-mix and coding 
optimization. Over the past several years, we have observed total case-
mix increases of about 0.5 percent per year and have assumed that they 
are real. Thus, based on the information available, we expect that 0.5 
percent of the residual 1.3 percent change in average case-mix for FY 
2020 will be real. The combination of the 2.5 percent COVID-19 effect 
and the remaining residual 0.5-percent real case-mix increase results 
in an estimated 3.0 percent increase in real case-mix for FY 2020.
    Because this analysis was based on Medicare claims from IPPS 
hospitals received as of July 2020, in the proposed rule, we calculated 
case-mix values for FY 2019 and FY 2020 based on the full year FY 2019 
and FY 2020 MedPAR files to help assess the change in case-mix based on 
more complete data. For FY 2019 we calculated a case-mix value of 1.813 
and for FY 2020 we calculated a case-mix value of 1.883, an increase in 
total case-mix of 3.9 percent. These were calculated using the MS-DRG 
relative weights in effect for those time periods.\5\ This was 
consistent with the estimate in the Notice of the CY 2021 Inpatient 
Hospital Deductible and Hospital and Extended Care Services Coinsurance 
Amounts that the change in total case-mix for FY 2020 would be 3.8 
percent when more complete data was available.
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    \5\ Section 3710 of the Coronavirus Aid, Relief, and Economic 
Security (CARES) Act directs the Secretary of HHS to increase the 
weighting factor of the assigned DRG by 20 percent for an individual 
diagnosed with COVID-19 discharged during the COVID-19 PHE period. 
In order to make the case-mix values more comparable, the 20 percent 
increase is not included.
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    The increases in patients seeking care for respiratory illnesses 
and patients deferring and delaying non-COVID-19 care during FY 2020, 
the increasing number of vaccinations for COVID-19, and the high 
estimate of FY 2020 real case-mix growth all led us to believe that FY 
2020 is not the best overall approximation of inpatient experience in 
FY 2022 and that FY 2019 as the most recent complete FY prior to the 
COVID-19 PHE is a better approximation of FY 2022 inpatient experience.
    As we indicated in the proposed rule, whether the data is a better 
overall

[[Page 44791]]

approximation of FY 2022 inpatient experience is one factor in 
assessing which data source represents the best available data for the 
FY 2022 rulemaking. Another factor is to what extent the decision to 
use the FY 2019 or FY 2020 data differentially impacts the FY 2022 
ratesetting. One way to assess this factor is to model the change in 
the total case-mix, which is a driver of spending, if our assumption 
regarding the FY 2022 inpatient experience used in calculating the MS-
DRG relative weights turns out to be less accurate based on actual FY 
2022 experience. In the proposed rule, we estimated the difference in 
the total case-mix if we calculated the MS-DRG relative weights based 
on the FY 2019 claims data and the actual utilization is ultimately 
more similar to the FY 2020 data, as compared to if we calculated the 
MS-DRG relative weights based on the FY 2020 data and the actual 
utilization is ultimately more similar to the FY 2019 data.
    We first calculated a set of MS-DRG relative weights using an 
assumption that the FY 2022 inpatient experience would be similar to 
the FY 2019 data. Specifically, we used the proposed version 39 GROUPER 
(which would be applicable to discharges occurring in FY 2022) and the 
FY 2019 MedPAR data to calculate MS-DRG relative weights. We refer to 
these MS-DRG relative weights as the FY 2019-based weights.
    We next calculated a set of MS-DRG relative weights using an 
assumption that the FY 2022 inpatient experience would be more similar 
to the FY 2020 data. Specifically, we used the proposed version 39 
GROUPER and the FY 2020 MedPAR data to calculate MS-DRG relative 
weights. This is how we would ordinarily calculate the proposed FY 2022 
MS-DRG relative weights. We refer to these MS-DRG relative weights as 
the FY 2020-based weights.
    We then estimated the difference in case-mix under the FY 2019-
based weights and the FY 2020-based weights if the FY 2022 inpatient 
experience ended up being the reverse of the assumption made when 
calculating that set of relative weights. In other words, we compared 
estimated case-mix calculated under four different scenarios. For the 
FY 2019-based weights, we calculated the case-mix using claims from the 
FY 2019 MedPAR as an approximation of the actual FY 2022 experience 
(Scenario A), and using claims from the FY 2020 MedPAR as an 
approximation of the actual FY 2022 experience (Scenario B). For the FY 
2020-based weights, we calculated the case-mix using claims from the FY 
2020 MedPAR as an approximation of the actual FY 2022 experience 
(Scenario C), and using claims from the FY 2019 MedPAR as an 
approximation of the actual FY 2022 experience (Scenario D).
    The results are shown in the following table.
    [GRAPHIC] [TIFF OMITTED] TR13AU21.003
    
    In Scenario A and Scenario C, there is by definition no 
differential impact on total case-mix due to a less accurate assumption 
made when the MS-DRG relative weights were calculated: The FY 2022 
inpatient experience matches the assumption used when the MS-DRG 
relative weights were calculated. In Scenario B and Scenario D, it is 
the reverse of the assumption used when the MS-DRG relative weights 
were calculated.
    In the proposed rule, we explained that in Scenario B, when the FY 
2019-based weights were used, but the FY 2022 inpatient experience 
turns out to be more similar to FY 2020 data, the less accurate 
assumption does not differentially impact the modelled case-mix. This 
can be seen by comparing the modelled case-mix under Scenario B (1.885) 
with the modelled case-mix under Scenario C (also 1.885). In other 
words, if the FY 2019-based weights and inpatient experience turn out 
to be more similar to the FY 2020 data, then the modelled case-mix is 
approximately the same as if we had used the FY 2020-based weights. The 
results show that use of the FY 2019-based weights did not impact the 
modelled case-mix compared to using the FY 2020-based weights.
    In the proposed rule, we explained that the same conclusion is not 
true of Scenario D where the FY 2020-based weights were used, but the 
FY 2022 inpatient experience turns out to be more similar to FY 2019 
data. Here the less accurate assumption does differentially impact the 
modelled case-mix, by -0.2 percent. This can be seen by comparing the 
modelled case-mix under Scenario D (1.816) with the modelled case-mix 
under Scenario A (1.820). In other words, if we use the FY 2020-based 
weights, and FY 2022 inpatient experience turns out to be more similar 
to FY 2019 data, the modelled case-mix is -0.2 percent lower than if we 
had used the FY 2019-based weights. This shows that use of the FY 2020-
based weights does impact the modelled case-mix compared to a result 
from using the FY 2019-based weights.
    Putting aside that we believe FY 2019 is a more likely 
approximation of the FY 2022 inpatient experience for the reasons 
discussed earlier, the previous analysis from the proposed rule 
indicates that the differential effect of the FY 2022 MS-DRG relative 
weights is more limited if the FY 2019-based weights are used than it 
is if the FY 2020-based weights are used, should the FY 2022 inpatient 
experience not match the assumption used to calculate the MS-DRG 
relative weights.

[[Page 44792]]

    Another payment factor that is impacted by the use of the FY 2019 
or FY 2020 data in the FY 2022 ratesetting is the outlier fixed-loss 
threshold. As discussed in section II.A.4.j. of the proposed rule, 
section 1886(d)(5)(A) of the Act provides for payments in addition to 
the basic prospective payments for ``outlier'' cases involving 
extraordinarily high costs. To qualify for outlier payments, a case 
must have costs greater than the sum of certain payments and the 
``outlier threshold'' or ``fixed-loss'' amount (a dollar amount by 
which the costs of a case must exceed payments in order to qualify for 
an outlier payment). In accordance with section 1886(d)(5)(A)(iv) of 
the Act, outlier payments for any year are projected to be not less 
than 5 percent nor more than 6 percent of total operating DRG payments 
plus outlier payments. We target 5.1 percent within this range. Section 
1886(d)(3)(B) of the Act requires the Secretary to reduce the average 
standardized amount by a factor to account for the estimated proportion 
of total DRG payments made to outlier cases. In other words, outlier 
payments are prospectively estimated to be budget neutral overall under 
the IPPS.\6\
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    \6\ More information on outlier payments may be found on the CMS 
website at: http://www.cms.gov/Medicare/Medicare-Fee-forService-Payment/AcuteInpatientPPS/outlier.html.
---------------------------------------------------------------------------

    In the proposed rule, under an assumption that the FY 2022 
inpatient experience will be more similar to FY 2019 data, we estimated 
an outlier fixed-loss amount of $30,967. Under an assumption that FY 
2022 inpatient experience will be more similar to FY 2020 data, we 
estimated an outlier fixed-loss amount of $36,843, a difference of 
$5,876 or approximately 20 percent higher. Again, putting aside that we 
believe FY 2019 is a better approximation of the FY 2022 inpatient 
experience for the reasons discussed earlier, we concluded in the 
proposed rule that the difference between the two estimated outlier 
fixed-loss amounts means there is a consequence to making a decision as 
to the best available data for estimating the FY 2022 outlier fixed-
loss amount in the form of potentially exceeding or falling short of 
the targeted 5.1 percent of total operating DRG payments plus outlier 
payments.
    In summary, in the proposed rule, we highlighted two factors in the 
decision regarding the best available data to use in the FY 2022 
ratesetting. The first factor was to what extent the FY 2019 data from 
before the COVID-19 PHE is a better overall approximation of FY 2022 
inpatient experience, or alternatively, to what extent the FY 2020 data 
including the COVID-19 PHE time period is a better overall 
approximation of FY 2022 inpatient experience. After analyzing this 
issue and for the reasons discussed, in the proposed rule we stated our 
belief that FY 2019 is generally a better overall approximation of FY 
2022. The second factor was to what extent the decision to use the FY 
2019 or FY 2020 data differentially impacts the FY 2022 IPPS 
ratesetting. After analyzing this issue, in the proposed rule we 
determined that the decision does differentially impact the overall FY 
2022 IPPS ratesetting in two primary ways. First, a decision to base 
the MS-DRG relative weights on the FY 2020 data has an impact of -0.2 
percent if the FY 2022 inpatient experience is more like FY 2019 data. 
Second, the decision to use the FY 2019 or FY 2020 data results in an 
approximately 20 percent difference in the estimate of the outlier 
fixed-loss amount.
    Taking these factors into account, in the FY 2022 IPPS/LTCH PPS 
proposed rule (86 FR 25089) we proposed to use the FY 2019 data for the 
FY 2022 ratesetting for circumstances where the FY 2020 data is 
significantly impacted by the COVID-19 PHE, primarily in that the data 
reflect generally markedly different utilization for certain types of 
services in FY 2020 than would have been expected in the absence of the 
PHE, as discussed previously. For example, we proposed to use the FY 
2019 MedPAR claims data for purposes where we ordinarily would have 
used the FY 2020 MedPAR claims data, such as in our analysis of changes 
to MS-DRG classifications (as discussed in greater detail in section 
II.D. of the preamble of the proposed rule). Similarly, we proposed to 
use cost report data from the FY 2018 HCRIS file for purposes where we 
ordinarily would have used the FY 2019 HCRIS file, such as in 
determining the FY 2022 IPPS MS-DRG relative weights (as discussed in 
greater detail in section II.E. of the preamble of the proposed rule). 
(As noted previously, the FY 2019 HCRIS data would contain many cost 
reports ending in FY 2020 based on each hospital's cost reporting 
period.)
    In section I.O. of Appendix A of the proposed rule, we stated that 
we were considering, as an alternative to this proposal, the use of the 
same FY 2020 data that we would ordinarily use for purposes of FY 2022 
ratesetting, and which we may consider finalizing based on 
consideration of comments received. To facilitate comment on this 
alternative for FY 2022, we made data and other supplemental files 
available. We refer the reader to section I.O. of Appendix A of the FY 
2022 IPPS/LTCH PPS proposed rule (86 FR 25784) for more information on 
these supplemental files and where they may be found.
    Comment: The vast majority of commenters were fully supportive of 
our proposal to use the FY 2019 data for the FY 2022 ratesetting for 
circumstances where the FY 2020 data is significantly impacted by the 
COVID-19 PHE. A commenter was supportive of our proposal but noted that 
transplant volume was higher in 2020 than 2019. However, the commenter 
stated that it recognized that due to the nature of hospital admissions 
during 2020 and the number and types of procedures provided in the 
hospital during the PHE, use of 2019 data is necessary.
    A commenter who stated they did not disagree with our proposal, 
expressed a concern that surges in COVID-19 cases could still occur in 
the future, making it impossible to predict what FY 2022 will look 
like. The commenter mentioned the slowing COVID-19 vaccination rate in 
many areas and the emergence of new COVID-19 variants that the COVID-19 
vaccines were not tested against as reasons to support this concern.
    Some commenters were supportive of our proposal, but urged CMS to 
make or consider certain technical adjustments when calculating the FY 
2022 relative weights. We refer readers to section II.E. of the 
preamble to this final rule for a complete discussion of these 
comments. A few commenters objected to CMS not using FY 2020 data to 
calculate the payment adjustment for CAR T-cell clinical trial and 
expanded access use immunotherapy cases. We refer readers to section 
V.M. of the preamble to this final rule for a complete discussion of 
these comments. A commenter expressed concern about not using FY 2020 
data in FY 2022 ratesetting for the LTCH PPS, in particular with 
respect to how the additional costs LTCHs incurred in 2020 will be 
reflected in future years' rates. We believe this commenter may have 
misunderstood the role of the market basket update and refer readers to 
section VIII.A.4. of the preamble to this final rule for a complete 
discussion of this comment.
    Response: We appreciate the commenters' support of our proposal to 
use the FY 2019 data for the FY 2022 ratesetting for circumstances 
where the FY 2020 data is significantly impacted by the COVID-19 PHE. 
In response to the commenter who expressed concerns about the 
possibility of future surges in COVID-19 making it impossible to 
predict what FY 2022 will look like, we appreciate the feedback. 
However, we believe the most recent vaccination and

[[Page 44793]]

hospitalization data reported by the CDC, discussed later in this 
section, support our assumption that there will be significantly lower 
risk of COVID-19 in FY 2022 and fewer hospitalizations for COVID-19 for 
Medicare beneficiaries in FY 2022 than there were in FY 2020. To 
address to the extent possible the commenter's concerns about the 
efficacy of the COVID-19 vaccines against new variants, we refer the 
reader to the June 25th weekly summary report from the CDC that states 
``recent studies have shown that the vaccines available in the United 
States are effective against variants currently circulating, including 
B.1.617.2.'' \7\
---------------------------------------------------------------------------

    \7\ Keep Variants at Bay. Get Vaccinated Today., available at 
https://www.cdc.gov/coronavirus/2019-ncov/covid-data/covidview/past-reports/06252021.html accessed July 6, 2021).
---------------------------------------------------------------------------

    Since the publication of the proposed rule, we have continued to 
monitor the vaccination and hospitalization data reported by the CDC 
(see https://www.cdc.gov/coronavirus/2019-ncov/covid-data/covidview/past-reports/07022021.html, accessed July 6, 2021). As of July 1, 2021, 
328.2 million vaccine doses have been administered. Overall, about 
181.3 million people, or 54.6 percent of the U.S. population, have 
received at least one dose of vaccine as of this date. About 155.9 
million people, or 47.0 percent of the U.S. population have been fully 
vaccinated. As of July 1, the 7-day average number of administered 
vaccine doses reported to CDC per day was 334,816, a 45.3 percent 
decrease from the previous week. As of July 1, 2021, 88.2 percent of 
people 65 or older have received at least one dose of vaccine; 78.3 
percent are fully vaccinated. Two-thirds (66.7 percent) of people 18 or 
older have received at least one dose of vaccine; 57.7 percent are 
fully vaccinated. Nationally, the COVID-19-related 7-day moving average 
for new hospital admissions has been generally decreasing since 
publication of the proposed rule, demonstrating the important role 
vaccination is playing in protecting against COVID-19. As of July 3, 
2021 (the most recent date with data available at the time of writing), 
the 7-day moving average for new hospital admissions was 1,821, down 
significantly from the 7-day moving average peak of 16,492 recorded on 
January 9th, 2021 and the 7-day moving average of 5,075 recorded on 
April 27, 2021, the date the proposed rule was issued.\8\
---------------------------------------------------------------------------

    \8\ New Admissions of Patients with Confirmed COVID-19., 
available at https://covid.cdc.gov/covid-data-tracker/#new-hospital-admissions accessed July 3, 2021).
---------------------------------------------------------------------------

    In the proposed rule, we analyzed the significant growth in real-
case mix observed in the FY 2020 MedPAR claims data. This analysis was 
consistent with the observations in the CDC's guidance that COVID-19 
increased the number of patients seeking care for respiratory 
illnesses, and caused patients to defer and delay non-COVID-19 care. 
While we acknowledge that the rate of vaccination for the U.S. 
population has slowed considerably since we released the proposed rule, 
the total number of vaccines administered, especially for people 65 or 
older, along with the latest hospitalization trends, lead us to 
continue to believe that there will be a significantly lower risk of 
COVID-19 in FY 2022 and fewer hospitalizations for COVID-19 for 
Medicare beneficiaries in FY 2022 than there were in FY 2020. For these 
reasons, we continue to believe that FY 2020 is not the best overall 
approximation of inpatient experience in FY 2022 and that FY 2019 as 
the most recent complete FY prior to the COVID-19 PHE is a better 
approximation of FY 2022 inpatient experience.
    Therefore, after considering the comments received and evaluating 
the most recent vaccination and hospitalization data from the CDC, we 
are finalizing our proposal to use the FY 2019 data for the FY 2022 
ratesetting for circumstances where the FY 2020 data is significantly 
impacted by the COVID-19 PHE, primarily in that the data reflect 
generally markedly different utilization for certain types of services 
in FY 2020 than would have been expected in the absence of the PHE, as 
discussed previously. For example, in this final rule we used the FY 
2019 MedPAR claims data for purposes where we ordinarily would have 
used the FY 2020 MedPAR claims data, such as in our analysis of changes 
to MS-DRG classifications (as discussed in greater detail in section 
II.D. of the preamble of this final rule). Similarly, we used cost 
report data from the FY 2018 HCRIS file for purposes where we 
ordinarily would have used the FY 2019 HCRIS file, such as in 
determining the FY 2022 IPPS MS-DRG relative weights (as discussed in 
greater detail in section II.E. of the preamble of this final rule). 
(As noted previously, the FY 2019 HCRIS data would contain many cost 
reports ending in FY 2020 based on each hospital's cost reporting 
period.)
    We note that MedPAR claims data and cost report data from the HCRIS 
file are examples of the data sources for which we discuss the use of 
the FY 2019 data for the FY 2022 ratesetting in this final rule. We 
have clearly identified throughout this final rule where and how we are 
using alternative data than what ordinarily would be used for the FY 
2022 IPPS and LTCH PPS ratesetting, including certain provider specific 
information.

II. Changes to Medicare Severity Diagnosis-Related Group (MS-DRG) 
Classifications and Relative Weights

A. Background

    Section 1886(d) of the Act specifies that the Secretary shall 
establish a classification system (referred to as diagnosis-related 
groups (DRGs) for inpatient discharges and adjust payments under the 
IPPS based on appropriate weighting factors assigned to each DRG. 
Therefore, under the IPPS, Medicare pays for inpatient hospital 
services on a rate per discharge basis that varies according to the DRG 
to which a beneficiary's stay is assigned. The formula used to 
calculate payment for a specific case multiplies an individual 
hospital's payment rate per case by the weight of the DRG to which the 
case is assigned. Each DRG weight represents the average resources 
required to care for cases in that particular DRG, relative to the 
average resources used to treat cases in all DRGs.
    Section 1886(d)(4)(C) of the Act requires that the Secretary adjust 
the DRG classifications and relative weights at least annually to 
account for changes in resource consumption. These adjustments are made 
to reflect changes in treatment patterns, technology, and any other 
factors that may change the relative use of hospital resources.

B. Adoption of the MS-DRGs and MS-DRG Reclassifications

    For information on the adoption of the MS-DRGs in FY 2008, we refer 
readers to the FY 2008 IPPS final rule with comment period (72 FR 47140 
through 47189).
    For general information about the MS-DRG system, including yearly 
reviews and changes to the MS-DRGs, we refer readers to the previous 
discussions in the FY 2010 IPPS/RY 2010 LTCH PPS final rule (74 FR 
43764 through 43766) and the FYs 2011 through 2021 IPPS/LTCH PPS final 
rules (75 FR 50053 through 50055; 76 FR 51485 through 51487; 77 FR 
53273; 78 FR 50512; 79 FR 49871; 80 FR 49342; 81 FR 56787 through 
56872; 82 FR 38010 through 38085, 83 FR 41158 through 41258, 84 FR 
42058 through 42165, and 85 FR 58445 through 58596 respectively).

[[Page 44794]]

C. FY 2022 MS-DRG Documentation and Coding Adjustment

1. Background on the Prospective MS-DRG Documentation and Coding 
Adjustments for FY 2008 and FY 2009 Authorized by Public Law 110-90 and 
the Recoupment or Repayment Adjustment Authorized by Section 631 of the 
American Taxpayer Relief Act of 2012 (ATRA).
    In the FY 2008 IPPS final rule with comment period (72 FR 47140 
through 47189), we adopted the MS-DRG patient classification system for 
the IPPS, effective October 1, 2007, to better recognize severity of 
illness in Medicare payment rates for acute care hospitals. The 
adoption of the MS-DRG system resulted in the expansion of the number 
of DRGs from 538 in FY 2007 to 745 in FY 2008. By increasing the number 
of MS-DRGs and more fully taking into account patient severity of 
illness in Medicare payment rates for acute care hospitals, MS-DRGs 
encourage hospitals to improve their documentation and coding of 
patient diagnoses.
    In the FY 2008 IPPS final rule with comment period (72 FR 47175 
through 47186), we indicated that the adoption of the MS-DRGs had the 
potential to lead to increases in aggregate payments without a 
corresponding increase in actual patient severity of illness due to the 
incentives for additional documentation and coding. In that final rule 
with comment period, we exercised our authority under section 
1886(d)(3)(A)(vi) of the Act, which authorizes us to maintain budget 
neutrality by adjusting the national standardized amount, to eliminate 
the estimated effect of changes in coding or classification that do not 
reflect real changes in case mix. Our actuaries estimated that 
maintaining budget neutrality required an adjustment of -4.8 percentage 
points to the national standardized amount. We provided for phasing in 
this -4.8 percentage point adjustment over 3 years. Specifically, we 
established prospective documentation and coding adjustments of -1.2 
percentage points for FY 2008, -1.8 percentage points for FY 2009, and 
-1.8 percentage points for FY 2010.
    On September 29, 2007, Congress enacted the TMA [Transitional 
Medical Assistance], Abstinence Education, and QI [Qualifying 
Individuals] Programs Extension Act of 2007 (Pub. L. 110-90). Section 
7(a) of Public Law 110-90 reduced the documentation and coding 
adjustment made as a result of the MS- DRG system that we adopted in 
the FY 2008 IPPS final rule with comment period to -0.6 percentage 
point for FY 2008 and -0.9 percentage point for FY 2009.
    As discussed in prior year rulemakings, and most recently in the FY 
2017 IPPS/LTCH PPS final rule (81 FR 56780 through 56782), we 
implemented a series of adjustments required under sections 7(b)(1)(A) 
and 7(b)(1)(B) of Public Law 110-90, based on a retrospective review of 
FY 2008 and FY 2009 claims data. We completed these adjustments in FY 
2013 but indicated in the FY 2013 IPPS/LTCH PPS final rule (77 FR 53274 
through 53275) that delaying full implementation of the adjustment 
required under section 7(b)(1)(A) of Public Law 110-90 until FY 2013 
resulted in payments in FY 2010 through FY 2012 being overstated, and 
that these overpayments could not be recovered under Public Law 110-90. 
In addition, as discussed in prior rulemakings and most recently in the 
FY 2018 IPPS/LTCH PPS final rule (82 FR 38008 through 38009), section 
631 of the American Taxpayer Relief Act of 2012 (ATRA) amended section 
7(b)(1)(B) of Public Law 110-90 to require the Secretary to make a 
recoupment adjustment or adjustments totaling $11 billion by FY 2017. 
This adjustment represented the amount of the increase in aggregate 
payments as a result of not completing the prospective adjustment 
authorized under section 7(b)(1)(A) of Public Law 110-90 until FY 2013.
2. Adjustments Made for FYs 2018, 2019, 2020, and 2021 as Required 
Under Section 414 of Public Law 114-10 (MACRA) and Section 15005 of 
Public Law 114-255
    As stated in the FY 2017 IPPS/LTCH PPS final rule (81 FR 56785), 
once the recoupment required under section 631 of the ATRA was 
complete, we had anticipated making a single positive adjustment in FY 
2018 to offset the reductions required to recoup the $11 billion under 
section 631 of the ATRA. However, section 414 of the MACRA (which was 
enacted on April 16, 2015) replaced the single positive adjustment we 
intended to make in FY 2018 with a 0.5 percentage point positive 
adjustment for each of FYs 2018 through 2023. In the FY 2017 
rulemaking, we indicated that we would address the adjustments for FY 
2018 and later fiscal years in future rulemaking. Section 15005 of the 
21st Century Cures Act (Pub. L. 114-255), which was enacted on December 
13, 2016, amended section 7(b)(1)(B) of the TMA, as amended by section 
631 of the ATRA and section 414 of the MACRA, to reduce the adjustment 
for FY 2018 from a 0.5 percentage point positive adjustment to a 0.4588 
percentage point positive adjustment. As we discussed in the FY 2018 
rulemaking, we believe the directive under section 15005 of Public Law 
114-255 is clear. Therefore, in the FY 2018 IPPS/LTCH PPS final rule 
(82 FR 38009) for FY 2018, we implemented the required +0.4588 
percentage point adjustment to the standardized amount. In the FY 2019 
IPPS/LTCH PPS final rule (83 FR 41157), the FY 2020 IPPS/LTCH PPS final 
rule (84 FR 42057), and the FY 2021 IPPS/LTCH PPS final rule (85 FR 
58444 and 58445), consistent with the requirements of section 414 of 
the MACRA, we implemented 0.5 percentage point positive adjustments to 
the standardized amount for FY 2019, FY 2020, and FY 2021, 
respectively. We indicated the FY 2018, FY 2019, FY 2020, and FY 2021 
adjustments were permanent adjustments to payment rates. We also stated 
that we plan to propose future adjustments required under section 414 
of the MACRA for FYs 2022 and 2023 in future rulemaking.
3. Adjustment for FY 2022
    Consistent with the requirements of section 414 of the MACRA, we 
proposed to implement a 0.5 percentage point positive adjustment to the 
standardized amount for FY 2022. We stated that this proposed 
adjustment would constitute a permanent adjustment to payment rates. We 
also stated that we plan to propose the final adjustment required under 
section 414 of the MACRA for FY 2023 in future rulemaking.
    Comment: A commenter reiterated their position from prior year 
comments that CMS misinterpreted the relevant statutory authority, 
which they believe explicitly assumes that the ATRA recoupment would 
result in negative adjustments totaling -3.2 percentage points 
completed through FY 2017, rather than the cumulative -3.9 percentage 
point adjustment made by CMS. The commenter stated that CMS should have 
made an additional 0.7 percent positive adjustment to the standardized 
amount in FY 2018. The commenter stated that the failure to make this 
adjustment resulted in an incorrect reduction in the standardized 
amount for all subsequent years. We also received multiple comments 
recommending that CMS commit to use its authority (a commenter 
specifically citing CMS's authority under Sec.  1886(d)(5)(I) of the 
Act) to restore the full amount of the cumulative -3.9 percentage point 
adjustment made to achieve the $11 billion targeted by the ATRA. A 
commenter requested CMS

[[Page 44795]]

specify the method for full repayment of this reduction to all 
providers by FY 2023 in the final rule, instead of waiting until future 
rulemaking to propose the final adjustment for FY 2023.
    Response: As we discussed in response to a similar comment in the 
FY 2021 IPPS/LTCH PPS final rule (85 FR 58444 through 58445) and in 
prior rules, we believe section 414 of the MACRA and section 15005 of 
the 21st Century Cures Act set forth the levels of positive adjustments 
for FYs 2018 through 2023. We are not convinced that the adjustments 
prescribed by MACRA were predicated on a specific adjustment level 
estimated or implemented by CMS in previous rulemaking. We see no 
evidence that Congress enacted these adjustments with the intent that 
CMS would make an additional +0.7 percentage point adjustment in FY 
2018 to compensate for the higher than expected final ATRA adjustment 
made in FY 2017, nor are we persuaded that it would be appropriate to 
use the Secretary's exceptions and adjustments authority under section 
1886(d)(5)(I) of the Act to adjust payments in FY 2022 to restore any 
additional amount of the original 3.9 percentage point reduction, given 
Congress' prescriptive adjustment levels under section 414 of the MACRA 
and section 15005 of the 21st Century Cures Act. CMS did not propose 
the specific level of adjustment to be made in FY 2023, and therefore 
we will proceed as planned to discuss the future (and final) adjustment 
under section 414 of the MACRA in FY 2023 rulemaking.
    After consideration of the public comments we received, we are 
finalizing our proposal to implement a 0.5 percentage point adjustment 
to the standardized amount for FY 2022.

D. Changes to Specific MS-DRG Classifications

1. Discussion of Changes to Coding System and Basis for FY 2022 MS-DRG 
Updates
a. Conversion of MS-DRGs to the International Classification of 
Diseases, 10th Revision (ICD-10)
    As of October 1, 2015, providers use the International 
Classification of Diseases, 10th Revision (ICD-10) coding system to 
report diagnoses and procedures for Medicare hospital inpatient 
services under the MS-DRG system instead of the ICD-9-CM coding system, 
which was used through September 30, 2015. The ICD-10 coding system 
includes the International Classification of Diseases, 10th Revision, 
Clinical Modification (ICD-10-CM) for diagnosis coding and the 
International Classification of Diseases, 10th Revision, Procedure 
Coding System (ICD-10-PCS) for inpatient hospital procedure coding, as 
well as the ICD-10-CM and ICD-10-PCS Official Guidelines for Coding and 
Reporting. For a detailed discussion of the conversion of the MS-DRGs 
to ICD-10, we refer readers to the FY 2017 IPPS/LTCH PPS final rule (81 
FR 56787 through 56789).
b. Basis for FY 2022 MS-DRG Updates
    Given the need for more time to carefully evaluate requests and 
propose updates, as discussed in the FY 2018 IPPS/LTCH PPS final rule 
(82 FR 38010), we changed the deadline to request updates to the MS-
DRGs to November 1 of each year, which provided an additional five 
weeks for the data analysis and review process. In the FY 2021 IPPS/
LTCH PPS proposed rule (85 FR 32472), we stated that with the continued 
increase in the number and complexity of the requested changes to the 
MS-DRG classifications since the adoption of ICD-10 MS-DRGs, and in 
order to consider as many requests as possible, more time is needed to 
carefully evaluate the requested changes, analyze claims data, and 
consider any proposed updates. We further stated we were changing the 
deadline to request changes to the MS-DRGs to October 20 of each year 
to allow for additional time for the review and consideration of any 
proposed updates. However, in the FY 2021 IPPS/LTCH PPS final rule (85 
FR 58445), due to the unique circumstances for the FY 2021 IPPS/LTCH 
PPS final rule for which we waived the delayed effective date, we 
maintained the deadline of November 1, 2020 for FY 2022 MS-DRG 
classification change requests. We also noted that we expected to 
reconsider a change in the deadline beginning with comments and 
suggestions submitted for FY 2023. We stated in the proposed rule that 
while we continue to believe that a change in the deadline from 
November 1 to October 20 will provide hospitals sufficient time to 
assess potential impacts and inform future MS-DRG recommendations, we 
are maintaining the deadline of November 1 for FY 2023 MS-DRG 
classification change requests.
    Comment: Commenters expressed support for a future change to the 
deadline for requesting updates to the MS-DRG classifications from 
November 1 to October 20. The commenters also recommended that CMS 
consider implementing an additional submission deadline, such as 
earlier in the calendar year. According to the commenters, while the 
current process to submit requests for changes to the MS-DRG 
classifications may be submitted at any time prior to the fall 
deadline, a second target submission date may encourage interested 
parties to submit requests earlier in the year and enable additional 
time for CMS to carefully evaluate requested changes, analyze claims 
data and consider proposed changes.
    Response: We appreciate the commenters feedback and support for our 
discussion regarding a future change to the deadline for requesting 
updates to the MS-DRG classifications from November 1 to October 20. We 
also thank the commenters for the suggestion to add a second submission 
date, and may consider any changes to the deadline and/or the frequency 
for submissions of requests for MS-DRG classification changes for 
future fiscal years.
    Interested parties had to submit MS-DRG classification change 
requests for FY 2022 by November 1, 2020, and the comments that were 
submitted in a timely manner for FY 2022 are discussed in this section 
of the preamble of this final rule. As we discuss in the sections that 
follow, we may not be able to fully consider all of the requests that 
we receive for the upcoming fiscal year. We have found that, with the 
implementation of ICD-10, some types of requested changes to the MS-DRG 
classifications require more extensive research to identify and analyze 
all of the data that are relevant to evaluating the potential change. 
We note in the discussion that follows those topics for which further 
research and analysis are required, and which we will continue to 
consider in connection with future rulemaking. Interested parties 
should continue to submit any comments and suggestions for FY 2023 by 
November 1, 2021 via the CMS MS-DRG Classification Change Request 
Mailbox located at: [email protected].
    We provided a test version of the ICD-10 MS-DRG GROUPER Software, 
Version 39, in connection with the FY 2022 IPPS/LTCH PPS proposed rule 
so that the public could better analyze and understand the impact of 
the proposals included in the proposed rule. We noted that this test 
software reflected the proposed GROUPER logic for FY 2022. Therefore, 
it included the new diagnosis and procedure codes that are effective 
for FY 2022 as reflected in Table 6A.--New Diagnosis Codes--FY 2022 and 
Table 6B.--New Procedure Codes--FY 2022 that were associated with the 
proposed rule and did not include the diagnosis codes that are invalid 
beginning in FY 2022 as reflected in Table 6C.--Invalid Diagnosis 
Codes--

[[Page 44796]]

FY 2022 and Table 6D.--Invalid Procedure Codes--FY 2022 that was 
associated with the proposed rule. Those tables were not published in 
the Addendum to the proposed rule, but are available via the internet 
on the CMS website at: https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/AcuteInpatientPPS/index.html as described in section 
VI. of the Addendum to the proposed rule. Because the diagnosis and 
procedure codes no longer valid for FY 2022 are not reflected in the 
test software, we made available a supplemental file in Table 6P.1a 
that included the mapped Version 39 FY 2022 ICD-10-CM codes and the 
deleted Version 38 FY 2021 ICD-10-CM codes that should be used for 
testing purposes with users' available claims data. In addition, we 
made available a supplemental file in Table 6P.1b that included the 
mapped Version 39 FY 2022 ICD-10-PCS codes and the deleted Version 38 
FY 2021 ICD-10-PCS codes that should be used for testing purposes with 
users' available claims data. Therefore, users had access to the test 
software allowing them to build case examples that reflect the 
proposals that were included in the proposed rule. In addition, users 
were able to view the draft version of the ICD-10 MS-DRG Definitions 
Manual, Version 39.
    The test version of the ICD-10 MS-DRG GROUPER Software, Version 39, 
the draft version of the ICD-10 MS-DRG Definitions Manual, Version 39, 
and the supplemental mapping files in Table 6P.1a and Table 6P.1b of 
the FY 2021 and FY 2022 ICD-10-CM diagnosis and ICD-10-PCS procedure 
codes are available at https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/AcuteInpatientPPS/MS-DRG-Classifications-and-Software.
    Following are the changes that we proposed to the MS-DRGs for FY 
2022. We invited public comments on each of the MS-DRG classification 
proposed changes, as well as our proposals to maintain certain existing 
MS-DRG classifications discussed in the proposed rule. In some cases, 
we proposed changes to the MS-DRG classifications based on our analysis 
of claims data and consultation with our clinical advisors. In other 
cases, we proposed to maintain the existing MS-DRG classifications 
based on our analysis of claims data and consultation with our clinical 
advisors. As discussed in section I.F of the preamble of the proposed 
rule, we proposed to use claims data from the March 2020 update of the 
FY 2019 MedPAR file in our analysis of proposed MS-DRG classification 
changes for FY 2022, consistent with our goal of using the best 
available data overall for ratesetting. Alternatively, we also provided 
the results of our analysis of proposed MS-DRG classification changes 
using claims data from the September 2020 update of the FY 2020 MedPAR 
file. As a result, for the FY 2022 IPPS/LTCH PPS proposed rule, our MS-
DRG analysis was based on ICD-10 claims data from the March 2020 update 
of the FY 2019 MedPAR file, which contains hospital claims received 
from October 1, 2018 through March 31, 2020, for discharges occurring 
through September 30, 2019. In addition, we also analyzed ICD-10 claims 
data from the September 2020 update of the FY 2020 MedPAR file, which 
contains hospital claims received from October 1, 2019 through 
September 30, 2020, for discharges occurring through September 30, 
2020. In our discussion of the proposed MS-DRG reclassification 
changes, we referred to these claims data as the ``March 2020 update of 
the FY 2019 MedPAR file'' and ``the September 2020 update of the FY 
2020 MedPAR file.''
    In this FY 2022 IPPS/LTCH PPS final rule, we summarize the public 
comments we received on our proposals, present our responses, and state 
our final policies. For this FY 2022 final rule, we generally did not 
perform any further MS-DRG analysis of claims data. Therefore, the MS-
DRG analysis is based on ICD-10 claims data from both the March 2020 
update of the FY 2019 MedPAR file and the September 2020 update of the 
FY 2020 MedPAR file, as set forth in the proposed rule, except as 
otherwise noted. As explained in previous rulemaking (76 FR 51487), in 
deciding whether to propose to make further modifications to the MS-
DRGs for particular circumstances brought to our attention, we consider 
whether the resource consumption and clinical characteristics of the 
patients with a given set of conditions are significantly different 
than the remaining patients represented in the MS-DRG. We evaluate 
patient care costs using average costs and lengths of stay and rely on 
the judgment of our clinical advisors to determine whether patients are 
clinically distinct or similar to other patients represented in the MS-
DRG. In evaluating resource costs, we consider both the absolute and 
percentage differences in average costs between the cases we select for 
review and the remainder of cases in the MS-DRG. We also consider 
variation in costs within these groups; that is, whether observed 
average differences are consistent across patients or attributable to 
cases that are extreme in terms of costs or length of stay, or both. 
Further, we consider the number of patients who will have a given set 
of characteristics and generally prefer not to create a new MS-DRG 
unless it would include a substantial number of cases.
    In the FY 2021 IPPS/LTCH PPS final rule (85 FR 58448), we finalized 
our proposal to expand our existing criteria to create a new 
complication or comorbidity (CC) or major complication or comorbidity 
(MCC) subgroup within a base MS-DRG. Specifically, we finalized the 
expansion of the criteria to include the NonCC subgroup for a three-way 
severity level split. We stated we believed that applying these 
criteria to the NonCC subgroup would better reflect resource 
stratification as well as promote stability in the relative weights by 
avoiding low volume counts for the NonCC level MS-DRGs. We noted that 
in our analysis of MS-DRG classification requests for FY 2021 that were 
received by November 1, 2019, as well as any additional analyses that 
were conducted in connection with those requests, we applied these 
criteria to each of the MCC, CC, and NonCC subgroups. We also noted 
that the application of the NonCC subgroup criteria going forward may 
result in modifications to certain MS-DRGs that are currently split 
into three severity levels and result in MS-DRGs that are split into 
two severity levels. We stated that any proposed modifications to the 
MS-DRGs would be addressed in future rulemaking consistent with our 
annual process and reflected in Table 5--Proposed List of Medicare 
Severity Diagnosis Related Groups (MS-DRGs), Relative Weighting 
Factors, and Geometric and Arithmetic Mean Length of Stay for the 
applicable fiscal year.
    In our analysis of the MS-DRG classification requests for FY 2022 
that we received by November 1, 2020, as well as any additional 
analyses that were conducted in connection with those requests, we 
applied these criteria to each of the MCC, CC, and NonCC subgroups, as 
described in the following table.

[[Page 44797]]

[GRAPHIC] [TIFF OMITTED] TR13AU21.004

    In general, once the decision has been made to propose to make 
further modifications to the MS-DRGs as described previously, such as 
creating a new base MS-DRG, or in our evaluation of a specific MS-DRG 
classification request to split (or subdivide) an existing base MS-DRG 
into severity levels, all five criteria must be met for the base MS-DRG 
to be split (or subdivided) by a CC subgroup. We note that in our 
analysis of requests to create a new MS-DRG, we typically evaluate the 
most recent year of MedPAR claims data available. For example, in the 
FY 2022 IPPS/LTCH PPS proposed rule we stated our MS-DRG analysis was 
based on ICD-10 claims data from both the March 2020 update of the FY 
2019 MedPAR file and the September 2020 update of the FY 2020 MedPAR 
file. However, in our evaluation of requests to split an existing base 
MS-DRG into severity levels, as noted in prior rulemaking (80 FR 
49368), we typically analyze the most recent two years of data. This 
analysis includes 2 years of MedPAR claims data to compare the data 
results from 1 year to the next to avoid making determinations about 
whether additional severity levels are warranted based on an isolated 
year's data fluctuation and also, to validate that the established 
severity levels within a base MS-DRG are supported. The first step in 
our process of evaluating if the creation of a new CC subgroup within a 
base MS-DRG is warranted is to determine if all the criteria is 
satisfied for a three way split. If the criteria fail, the next step is 
to determine if the criteria are satisfied for a two way split. If the 
criteria for both of the two way splits fail, then a split (or CC 
subgroup) would generally not be warranted for that base MS-DRG. If the 
three way split fails on any one of the five criteria and all five 
criteria for both two way splits (1_23 and 12_3) are met, we would 
apply the two way split with the highest R2 value. We note that if the 
request to split (or subdivide) an existing base MS-DRG into severity 
levels specifies the request is for either one of the two way splits 
(1_23 or 12_3), in response to the specific request, we will evaluate 
the criteria for both of the two way splits, however we do not also 
evaluate the criteria for a three way split.
    In the FY 2022 IPPS/LTCH PPS proposed rule, we stated that using 
the March 2020 update of the FY 2019 MedPAR file and the September 2020 
update of the FY 2020 MedPAR file, we analyzed how applying the NonCC 
subgroup criteria to all MS-DRGs currently split into three severity 
levels would affect the MS-DRG structure beginning in FY 2022. We noted 
that findings from our analysis indicated that approximately 32 MS-DRGs 
would be subject to change based on the three-way severity level split 
criterion finalized in FY 2021. Specifically, we found that applying 
the NonCC subgroup criteria to all MS-DRGs currently split into three 
severity levels would result in the deletion of 96 MS-DRGs (32 MS-DRGs 
x 3 severity levels = 96) and the creation of 58 new MS-DRGs. We 
further noted that these updates would also involve a redistribution of 
cases, which would impact the relative weights, and, thus, the payment 
rates proposed for particular types of cases. We referred the reader to 
Table 6P.1c associated with the proposed rule for the list of the 96 
MS-DRGs that would be subject to deletion and the list of the 58 new 
MS-DRGs that would be proposed for creation for FY 2022 under this 
policy if the NonCC subgroup criteria were applied.
    We stated in the proposed rule that in light of the public health 
emergency (PHE), we had concerns about the impact of implementing this 
volume of MS-DRG changes at this time, and our belief that it may be 
appropriate to delay application of the NonCC subgroup criteria to 
existing MS-DRGs in order to maintain more stability in the current MS-
DRG structure. Therefore, we proposed to delay the application of the 
NonCC subgroup criteria to existing MS-DRGs with a three-way severity 
level split until FY 2023, and proposed for FY 2022 to maintain the 
current structure of the 32 MS-DRGs that currently have a three-way 
severity level split (total of 96 MS-DRGs) that would otherwise be 
subject to these criteria.
    Comment: Several commenters expressed support for our proposal to 
delay the application of the expanded three-way severity level split 
criteria to the NonCC subgroup until fiscal year 2023 in light of the 
PHE, and to maintain the current structure of the MS-DRGs. Many 
commenters also recommended that a complete analysis of the MS-DRG 
changes to be proposed for fiscal year 2023 in connection with the 
expanded three-way severity split criteria be conducted and made 
available to enable the public an opportunity to review and consider 
the redistribution of cases, the impact to the relative weights (for 
example, Table 5--Proposed List of Medicare Severity

[[Page 44798]]

Diagnosis Related Groups (MS-DRGs), Relative Weighting Factors, and 
Geometric and Arithmetic Mean Length of Stay), payment rates and 
hospital case mix to allow meaningful comment prior to implementation. 
A few commenters suggested delaying the application of the expanded 
three-way severity split NonCC subgroup criteria until fiscal year 2024 
to allow analysis of claims data from FY 2022 that may better reflect 
post pandemic utilization. Another commenter recommended delaying any 
changes until FY 2025.
    A commenter expressed concern that changes to the underlying MS-DRG 
structure may inadvertently exacerbate payment differentials between 
different types of hospitals (e.g., urban versus rural) based on the 
types of services they provide, which may negatively impact Medicare 
beneficiary access to some services. Another commenter stated it 
reviewed its hospital specific data and had concerns that the ``with 
cc'' level will be reduced on several MS-DRGs. This commenter stated 
that if its case mix remains the same it would continue to treat many 
patients with comorbid conditions and receive payment consistent with a 
MS-DRG at the ``without CC'' level. The commenter identified the 
following four MS-DRGs that appeared to be impacted the most with 
respect to lost revenue, MS-DRG 617 (Amputation of Lower Limb for 
Endocrine, Nutritional and Metabolic Disorder with CC); MS-DRG 847 
(Chemotherapy without Acute Leukemia as Secondary Diagnosis with CC); 
MS-DRG 854 (Infectious and Parasitic Diseases with O.R. Procedure with 
CC) and MS-DRG 958 (Other O.R. Procedures for Multiple Significant 
Trauma with CC). Lastly, the commenter recommended that CMS also 
further assess other proposed groupings, such as the maternity MS-DRGs, 
due to historically low volumes in these MS-DRGs and to determine if it 
would be appropriate to combine any of them.
    Another commenter requested that CMS provide data transparency to 
illustrate volumes by MS-DRG that support the proposal for changes to 
the 96 MS-DRGs discussed in the FY 2022 IPPS/LTCH PPS proposed rule and 
to also consider patient mix for the obstetric MS-DRGs. This commenter 
also suggested that CMS examine the impact for surgical versus medical 
MS-DRGs with respect to redistribution and associated impacts to the 
relative weights. According to the commenter, the impact appears to be 
greater for surgical MS-DRGs.
    Finally, a commenter who expressed support for CMS' proposal to 
delay implementation of the expanded three-way severity split criteria 
to the NonCC subgroup recommended that any proposed changes to the 
structure of the MS-DRGs should consist of the impact of the proposed 
CC/MCC redesign and not the current CC/MCC structure that is scheduled 
to be changed.
    Response: We appreciate the commenters' support. In response to the 
recommendation that a complete analysis of the MS-DRG changes to be 
proposed for FY 2023 in connection with the application of the expanded 
three-way severity split criteria to the NonCC subgroup be conducted 
and made publicly available, we plan to perform and make publicly 
available a more detailed analysis in connection with any future 
proposed changes, consistent with our annual claims analysis for MS-DRG 
classification change proposals. With respect to the commenters who 
suggested delaying the application of the expanded three-way severity 
split NonCC subgroup criteria until fiscal year 2024 or later, 
including to allow the use of FY 2022 claims data, we appreciate the 
feedback and will take these suggestions under consideration.
    In response to the commenters who expressed concern that changes to 
the underlying MS-DRG structure may inadvertently exacerbate payment 
differentials between different types of hospitals based on the types 
of services they provide, or would have the greatest impacts with 
respect to particular MS-DRGs, we note that generally, changes to the 
MS-DRG classifications and related policies under the IPPS that are 
implemented on an annual basis may affect payment for different types 
of hospitals depending on the services they provide, and, note that we 
intend to conduct and make publicly available analysis of the 
application of the NonCC subgroup criteria in connection with any 
future proposed changes, consistent with our annual MS-DRG analysis, 
including with respect to particular MS-DRGs.
    We appreciate the commenters' feedback suggesting further review of 
the maternity (obstetric) MS-DRGs and agree that these groupings 
warrant special consideration. As discussed in prior rulemaking (83 FR 
41210), we cannot adopt the same approach to refine the maternity and 
newborn MS-DRGs because of the extremely low volume of Medicare 
patients there are in these DRGs.
    In response to the commenter who requested that CMS provide data 
transparency to illustrate volumes by MS-DRG that support the proposal 
for changes to the 96 MS-DRGs discussed in the FY 2022 IPPS/LTCH PPS 
proposed rule, we refer the reader to Table 6P.1l associated with this 
final rule and available via the internet at https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/AcuteInpatientPPS. This table 
displays the volume (case counts) by each MS-DRG based on claims data 
from the March 2020 update of the FY 2019 MedPAR file and the September 
2020 update of the FY 2020 MedPAR file.
    We also thank the commenter for its suggestion to examine the 
impact for surgical versus medical MS-DRGs and agree that type of 
information can be useful for stakeholders.
    With respect to the commenter who recommended that any proposed 
changes to the structure of the MS-DRGs should consist of the impact of 
the proposed CC/MCC redesign and not the current CC/MCC structure that 
is scheduled to be changed, it is not clear to us from the limited 
comment if the commenter is referring to the potential changes in 
connection with the comprehensive CC/MCC analysis that is currently in 
progress. We note that any proposed modifications to the MS-DRGs would 
be addressed in future rulemaking, including any proposed changes to 
the severity level designation of diagnosis codes, and would be 
considered and taken into account with application of the NonCC 
subgroup criteria.
    After consideration of the public comments we received, we are 
finalizing our proposal to delay the application of the NonCC subgroup 
criteria to existing MS-DRGs with a three-way severity level split 
until FY 2023 or later, and are finalizing for FY 2022 to maintain the 
current structure of the 32 MS-DRGs that currently have a three-way 
severity level split.
    We are making the FY 2022 ICD-10 MS-DRG GROUPER and Medicare Code 
Editor (MCE) Software Version 39, the ICD-10 MS-DRG Definitions Manual 
files Version 39 and the Definitions of Medicare Code Edits Manual 
Version 39 available to the public on our CMS website at: https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/AcuteInpatientPPS/MS-DRG-Classifications-and-Software.
2. Pre-MDC: MS-DRG 018 Chimeric Antigen Receptor (CAR) T-Cell Therapy
    In the FY 2021 IPPS/LTCH PPS final rule (85 FR 58451 through 
58453), we finalized our proposal to create Pre-MDC MS-DRG 018 
(Chimeric Antigen Receptor (CAR) T-cell Immunotherapy) and to reassign 
cases reporting ICD-10-PCS procedure codes XW033C3 (Introduction of 
engineered autologous chimeric antigen receptor t-cell

[[Page 44799]]

immunotherapy into peripheral vein, percutaneous approach, new 
technology group 3) or XW043C3 (Introduction of engineered autologous 
chimeric antigen receptor t-cell immunotherapy into central vein, 
percutaneous approach, new technology group 3) from Pre-MDC MS-DRG 016 
(Autologous Bone Marrow Transplant with CC/MCC or T-cell 
Immunotherapy), to new Pre-MDC MS-DRG 018 effective with discharges on 
and after October 1, 2020. We also finalized our proposal to revise the 
title for MS-DRG 016 from ``Autologous Bone Marrow Transplant with CC/
MCC or T-cell Immunotherapy'' to ``Autologous Bone Marrow Transplant 
with CC/MCC'' to reflect these changes.
    Additionally, in the FY 2021 IPPS/LTCH PPS final rule in response 
to public comments expressing concern that Pre-MDC MS-DRG 018 is 
specific to one mechanistic approach to cellular therapy, and in 
response to commenters who sought clarification on how future CAR T-
cell and non-CAR T-cell therapy products would be assigned, we stated 
that if additional cellular therapies should become available, we would 
use our established process to determine the MS-DRG assignment. The 
commenters requested that CMS provide flexibility for future cellular 
therapies, as they are made available and not restrict Pre-MDC MS-DRG 
018 to CAR T-cell therapies alone. In this section of this rule, we 
discuss the assignment of these therapies in more detail.
    As discussed in the FY 2022 IPPS/LTCH PPS proposed rule (86 FR 
25094), during the September 8-9, 2020 ICD-10 Coordination and 
Maintenance Committee meeting, several topics involving requests for 
new procedure codes related to CAR T-cell therapies, non-CAR T-cell 
therapies and other immunotherapies were discussed. We referred the 
reader to the CMS website at: https://www.cms.gov/Medicare/Coding/ICD10/C-and-M-Meeting-Materials for additional detailed information 
regarding these requests for new procedure codes.
    As noted in prior rulemaking (85 FR 32543), for new procedure codes 
that have been finalized through the ICD-10 Coordination and 
Maintenance Committee meeting process and are proposed to be classified 
as O.R. procedures or non-O.R. procedures affecting the MS-DRG, our 
clinical advisors recommend the MS-DRG assignment which is then made 
available in association with the proposed rule (Table 6B.--New 
Procedure Codes) and subject to public comment. These proposed 
assignments are generally based on the assignment of predecessor codes 
or the assignment of similar codes. As discussed in section II.D.13 of 
the preamble of the proposed rule and this final rule, Table 6B.--New 
Procedure Codes, lists the new procedure codes that have been approved 
to date that will be effective with discharges on and after October 1, 
2021. Included in Table 6B are the following new procedure codes that 
describe the administration of CAR T-cell and non-CAR T-cell therapies 
and other immunotherapies. As stated in the proposed rule, consistent 
with our established process, we examined the MS-DRG assignment for the 
predecessor codes to determine the most appropriate MS-DRG assignment 
and, consistent with the assignment of those predecessor codes, we 
proposed to classify the following new procedure codes as non-O.R. 
procedures affecting Pre-MDC MS-DRG 018, as shown in Table 6B.--New 
Procedure Codes associated with the proposed rule and available via the 
internet on the CMS website at https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/AcuteInpatientPPS/index/.
BILLING CODE 4120-01-P

[[Page 44800]]

[GRAPHIC] [TIFF OMITTED] TR13AU21.005

BILLING CODE 4120-01-C
    In connection with our proposed assignment of the listed procedure 
codes to Pre-MDC MS-DRG 018, we also proposed to revise the title for 
Pre-MDC MS-DRG 018 ``Chimeric Antigen Receptor (CAR) T-cell 
Immunotherapy'' to ``Chimeric Antigen Receptor (CAR) T-cell and Other 
Immunotherapies'' to better reflect the cases reporting the 
administration of non-CAR T-cell therapies and other immunotherapies 
that would also be assigned to this MS-DRG (for example, Introduction 
of lifileucel immunotherapy into peripheral vein, percutaneous 
approach, new technology group 7), in addition to CAR T-cell therapies.
    Comment: Several commenters agreed with the proposal to assign the 
listed ICD-10-PCS procedure codes to Pre-MDC MS-DRG 018 and to revise 
the title to include ``Other Immunotherapies.'' A commenter who 
expressed support for the change to Pre-MDC MS-DRG 018 stated its view 
that the domain of cellular therapeutics will become increasingly 
important in the care of Medicare beneficiaries with cancer in the 
future and that creating sufficient plasticity in the diagnostic coding 
system to permit the continued integration of new and innovative 
therapeutics into the evidence-based care of Medicare beneficiaries is 
essential. Another commenter stated they appreciated the recognition of 
the differentiated nature of cancer care, as well as the importance of 
innovation in

[[Page 44801]]

the domain of immune-oncology, which it stated was a necessary part of 
effective, equitable cancer care delivery to CMS beneficiaries who 
receive their care at both PPS and PPS-Exempt centers to ensure 
equitable access. A commenter stated the proposed change to Pre-MDC MS-
DRG 018 furthers the goal of securing expedited access for Medicare 
beneficiaries to innovative therapies. Another commenter stated the 
proposal responds to stakeholder concerns that currently, Pre-MDC MS-
DRG 018 is specific to one mechanistic approach to cellular therapy. 
This same commenter and other commenters stated the proposal is also 
responsive to stakeholder requests that CMS provide flexibility for 
future cellular therapies as they are made available, and not restrict 
Pre-MDC MS-DRG 018 to CAR T-cell therapies alone.
    However, some commenters who expressed appreciation of CMS' 
recognition of non-CAR T-cell immunotherapy and a need to revise the 
description for Pre-MDC MS-DRG 018 requested further clarification from 
CMS on what the ``Other Immunotherapies'' terminology is intended to 
include. The commenters stated the term ``Other Immunotherapies'' is 
very general and may lead to confusion since ``immunotherapy'' is a 
broad term that is applied across several therapeutic areas (for 
example Diabetes, Rheumatoid Arthritis, Cancer, etc.) to describe 
treatments that stimulate an immune response within patients. A 
commenter stated that the National Cancer Institute differentiates 
immunotherapy for cancer patients into several types (for example, 
Immune checkpoint inhibitors, T-cell transfer therapy, Monoclonal 
antibodies, etc.). This commenter stated their belief that CMS is not 
intending to refer to a broad array of immunotherapy and suggested that 
more precise language in the descriptor of Pre-MDC MS-DRG 018 may be 
beneficial. Some commenters recommended that CMS consider using 
terminology such as ``Immune Effector Cells'' in place of ``Other 
Immunotherapies'' with respect to the description of the MS-DRG. Other 
commenters suggested that CMS consider revising the title for Pre-MDC 
MS-DRG 018 to ``Autologous T-cell Immunotherapies''. Another commenter 
stated they recognized the intent of the proposed change and commended 
the effort by CMS to ensure that future cellular and CAR T-cell 
therapies are rapidly assigned to a MS-DRG to allow for proper payment, 
however, similar to other commenters, this commenter requested 
clarification as to whether the proposed revision to the title of Pre-
MDC MS-DRG 18 is intended to incorporate solely cellular and CAR T-cell 
therapies, or whether the goal is to include all cancer 
immunotherapeutic agents since the term ``immunotherapy'' is broad and 
future novel cancer immunotherapeutic agents may have different 
resource utilization.
    A commenter acknowledged that CMS is faced with a challenging 
landscape in incorporating the administration of new gene and cell 
therapies into the IPPS and recognized that CMS' proposed assignment of 
procedure codes describing the administration of tumor-infiltrating 
lymphocyte (TIL) therapies to MS-DRG 018 is to the most similar MS-DRG 
that covers similar clinical characteristics and comorbidities. 
However, whether for TIL therapies or other products in the pipeline, 
the commenter recommended that CMS consider the following factors when 
determining a permanent payment mechanism:

 Patient diagnosis and product indication (solid vs. blood 
cancers)
 Cell collection methodologies (tissue biopsy, pheresis, etc.)
 Product administration methodologies
 Patient clinical care regimes and durations
 Product safety and toxicity profiles that impact inpatient 
care and follow-up

    According to the commenter, society experts state there are 
distinct and important differences in these factors between TIL 
therapies and CAR T-cell therapies that may support reconsideration of 
the MS-DRG assignment after a product is approved by the FDA and is 
used to treat Medicare beneficiaries. The commenter recommended further 
consideration of the appropriateness and patient access implications, 
based on these factors, before grouping the two types of therapies 
together on a long-term basis. This commenter also suggested that if 
CMS finalized a change to the title of MS-DRG 018 to include TIL 
therapies upon their initial approval, as proposed, that the title of 
the MS-DRG more clearly reflect the specialized products assigned to 
it.
    A few commenters urged CMS to finalize the proposal while 
continuing to work with stakeholders on ways to improve the 
predictability and stability of hospital payment for these complex, 
novel cell therapies that provide options for patients who so 
desperately need them. Other commenters stated that if the proposed 
revision to the title for Pre-MDC MS-DRG 018 is finalized, that CMS 
should continue to monitor and assess the appropriateness of therapies 
assigned to MS-DRG 018, if they continue to be aligned on resource use, 
and whether additional refinements or MS-DRGs may be warranted in the 
future. The commenters also suggested that CMS consider and detail a 
process for creating new Pre-MDC MS-DRGs that reflect utilization and 
clinical similarity consistent with the current overall IPPS 
infrastructure while maintaining important resource and clinical 
differences to maintain relative weight stability.
    Other commenters opposed or expressed strong concerns with the 
proposal to assign the procedure codes describing non-CAR T-cell and 
other immunotherapies to Pre-MDC MS-DRG 018 and to revise the title of 
the MS-DRG. These commenters stated that assigning therapies that are 
clinically distinct from CAR T-cell therapies and may vary in resource 
use has the potential to distort future rate setting and will disrupt 
the Agency's measured multi-year approach in establishing a MS-DRG 
dedicated to CAR T-cell therapy. According to the commenters, expanding 
the MS-DRG to other immunotherapies one year after it has been 
implemented holds the risk of creating additional payment uncertainty 
around CAR T-cell therapies. The commenters urged CMS to maintain Pre-
MDC MS-DRG 018 specifically for autologous CAR T-cell therapies only, 
as a long-term solution for reliable and predictable payments that will 
enable hospitals to provide access to CAR T-cell therapies for Medicare 
beneficiaries.
    Some commenters recommended that CMS publicly propose MS-DRG 
mappings in advance of making a final assignment decision and provide 
an opportunity for stakeholders to submit comments with respect to 
proposed mappings. Other commenters stated the new technology add-on 
payment process should be independent of the process for obtaining a 
MS-DRG assignment for a new code.
    A few commenters provided specific information relating to the 
process that is involved for patients undergoing treatment with CAR T-
cell therapy. The commenters outlined the stage of leukapheresis where 
T-cells are separated and removed from the blood and the remaining 
blood is returned to the body, followed by the T-cells being sent to a 
manufacturing facility where they are genetically engineered and grown 
in a laboratory until millions of T-cells are produced. These 
commenters did not agree with the assignment of procedure codes 
describing non-CAR T-cell therapies and other

[[Page 44802]]

immunotherapies to Pre-MDC MS-DRG 018 stating the treatment processes 
are distinctly different and that some products have yet to be approved 
by the FDA.
    A commenter who specifically opposed the modification of Pre-MDC 
MS-DRG 018 for FY 2022 stated that there are not any non-CAR T-cell 
therapy FDA approved products that are anticipated in the near term. 
This commenter further stated that CMS' proposal to include ``other 
immunotherapies'' in the description for Pre-MDC MS-DRG 018 is overly 
broad and risks inclusion of therapeutics which are not well aligned 
with CAR T-cell cases being mapped to this MS-DRG. According to the 
commenter, CMS has not provided sufficient detail about the rationale 
and supporting evidence for assignment of non-CAR T-cell products to 
MS-DRG 018. The commenter also stated that the term ``immunotherapy'' 
could describe products that treat a range of conditions, and those 
products may have different experience with potential complications and 
expected length of stay than CAR T-cell products as well as different 
costs for the product itself. This same commenter recommended that CMS 
provide evidence of clinical consistency and resource use alignment in 
future rulemaking when proposing therapies that may map to Pre-MDC MS-
DRG-018 and allow for public comments. Another commenter expressed 
concern that the proposed change to encompass ``other immunotherapies'' 
in Pre-MDC MS-DRG 018 could set a precedent for creating ``generic'' 
MS-DRGs for gene therapies, which, according to the commenter, could 
hamper timely beneficiary access to needed treatment. This commenter 
urged CMS to limit Pre-MDC MS-DRG 018 to all types of CAR T-cell 
therapies and to consider creating new MS-DRGs for therapies, such as 
gene therapies, outside the CAR T-cell space.
    Response: We thank the commenters for their support of our proposal 
to assign the listed procedure codes describing CAR T-cell, non-CAR T-
cell and other immunotherapies to Pre-MDC MS-DRG 018 and to modify the 
title for Pre-MDC MS-DRG 018 to reflect this assignment. As previously 
noted, we used our established process to examine the MS-DRG assignment 
for the predecessor codes to determine the most appropriate MS-DRG 
assignment. Specifically, we reviewed the predecessor code and MS-DRG 
assignment most closely associated with the new procedure code, and in 
the absence of claims data, we considered other factors that may be 
relevant to the MS-DRG assignment, including the severity of illness, 
treatment difficulty, complexity of service and the resources utilized 
in the diagnosis and/or treatment of the condition. We have noted in 
prior rulemaking that this process does not automatically result in the 
new procedure code being assigned to the same MS-DRG or to have the 
same designation (O.R. versus Non-O.R.) as the predecessor code. As 
stated in the preamble of the proposed rule and discussed in this final 
rule, we proposed to classify the new procedure codes as Non-O.R. 
procedures affecting Pre-MDC MS-DRG 018, as shown in Table 6B.--New 
Procedure Codes that was associated with the proposed rule and 
available via the internet on the CMS website at https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/AcuteInpatientPPS/index/, 
providing the opportunity for public comment on the MDC, MS-DRG 
assignment and designation.
    The predecessor code and associated MS-DRG assignment (if 
applicable) for the listed codes are as follows:
BILLING CODE 4120-01-P

[[Page 44803]]

[GRAPHIC] [TIFF OMITTED] TR13AU21.006


[[Page 44804]]


[GRAPHIC] [TIFF OMITTED] TR13AU21.007

BILLING CODE 4120-01-C
    As shown in the table, all the procedure codes have a predecessor 
code that was previously assigned to Pre-MDC MS-DRG 018 with the

[[Page 44805]]

exception of four procedure codes (XW033G7, XW033L7, XW043G7, and 
XW043L7) that have a predecessor code that was designated Non-O.R. and 
did not impact any MS-DRG assignment. Two of the four codes describe 
the introduction (administration) of an allogeneic CAR T-cell therapy 
and are intended to capture any allogeneic CAR T-cell products that may 
become available and do not yet have a unique procedure code. The other 
two codes specifically describe the product lifileucel. We believe that 
at this time, as the field of cellular and gene immunotherapies is 
continuing to evolve very rapidly, that it is appropriate to initially 
classify the procedure codes describing allogeneic CAR T-cell therapy 
and lifileucel to Pre-MDC MS-DRG 018 because there are clinical 
similarities with respect to the administration of these products, the 
complexity of the conditions in which they are treating, and resource 
utilization that are consistent with other CAR T-cell products 
currently assigned to the MS-DRG. As a commenter specifically noted in 
its support to assign the procedure codes describing the introduction 
of lifileucel (XW033L7 and XW043L7) to Pre-MDC MS-DRG 018, both 
lifileucel (a tumor-infiltrating lymphocyte or TIL therapy) and CAR T-
cell therapies require collection of a patient's lymphocyte cells which 
are a key component of a complicated manufacturing process to produce a 
patient-specific therapeutic dose, both are primarily administered in 
the inpatient setting due to risk of significant but treatable adverse 
events and the resources are anticipated to be comparable with respect 
to the intensity of patient care that includes the treatment phase, 
monitoring, management of any adverse events, and length of stay. While 
for TIL therapy the source of the lymphocyte is the patient's tumor and 
is obtained through surgical resection, and for CAR T-cell therapy the 
source of the lymphocyte is the patient's blood, obtained through 
apheresis, both therapies require a patient's lymphocytes. We also 
appreciate another commenter's recognition of the challenges involved 
with incorporating the administration of new gene and cellular 
therapies into the IPPS and the view that assignment of procedure codes 
describing the administration of tumor-infiltrating lymphocyte (TIL) 
therapies to Pre-MDC MS-DRG 018 is to the most similar MS-DRG that 
reflects similar clinical characteristics and comorbidities. With 
respect to allogeneic CAR T-cell therapies, it is understood that these 
therapies are not derived from a patient's own cells and therefore are 
not ``autologous'', however, the resources and complexity in the care 
and clinical management of these patients may be considered comparable 
when taking into account diagnosis, prognosis, and treatment difficulty 
(for example, frequent adjustments in dosing regimens in efforts to 
prevent rejection of the new cells and susceptibility to infection). We 
note that the definition of a MS-DRG will not be so specific that every 
patient is identical, rather, the level of variation is known and 
predictable. Thus, while the precise resource intensity of a patient 
cannot be predicted, the average pattern of resource intensity of a 
group of patients in a MS-DRG can be accurately predicted.
    We also appreciate the commenter's feedback on factors to consider 
for products that are in the pipeline with respect to MS-DRG assignment 
as a permanent payment mechanism. We agree that there may be 
distinctions to account for as we continue to gain more experience in 
the utilization of these therapies and have additional claims data to 
analyze.
    We acknowledge the commenters' concerns that the term ``Other 
Immunotherapies'' that was proposed for the title of Pre-MDC MS-DRG 018 
may be considered broad. While, as several commenters stated in their 
comments, cellular therapies and gene therapies are an evolving field, 
the term ``Other Immunotherapies'' is intended to encompass the group 
of therapies that are currently available and being utilized today (for 
which codes have been created for reporting in response to industry 
requests or are being considered for implementation), and to enable 
appropriate MS-DRG assignment for any future therapies that may also 
fit into this category and are not specifically identified as a CAR T-
cell product, that may become available (for example receive marketing 
authorization or a newly established procedure code in the ICD-10-PCS 
classification) during FY 2022. We appreciate the suggestions to 
consider alternative terminology for the title (description) of Pre-MDC 
MS-DRG 018 and look forward to continuing to work with stakeholders on 
this issue in the future. At this time, for FY 2022, we believe it is 
premature to finalize any of the suggested title revisions by 
commenters to Pre-MDC MS-DRG 018 that may not fully reflect the various 
types of therapies and products described by the different procedure 
codes that are currently assigned or may be considered for assignment 
there in FY 2022. We also note that any proposed changes to modify the 
logic for case assignment and/or the title to Pre-MDC MS-DRG 018 would 
be considered in future rulemaking. We further note that the process of 
code creation and proposed assignment to the most appropriate MS-DRG 
exists independently, regardless of whether there is an associated 
application for a new technology add-on payment for a product or 
technology submitted for consideration in a given fiscal year. 
Specifically, requests for a new code(s) or updates to existing codes 
are addressed through the ICD-10 Coordination and Maintenance Committee 
meetings where code proposals are presented and the public is provided 
the opportunity to comment. All codes finalized after the September 
meeting must be reviewed and are subsequently proposed for assignment 
under the ICD-10 MS-DRGs through notice and comment rulemaking. Codes 
that are finalized after the March meeting are also reviewed and 
subject to our established process of initially reviewing the 
predecessor codes MS-DRG assignment and designation, while considering 
other relevant factors as previously described. The codes that are 
finalized after the March meeting are specifically identified with a 
footnote in Tables 6A.--New Diagnosis Codes and Table 6B.--New 
Procedure Codes that are made publicly available in association with 
the final rule via the internet on the CMS website at https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/AcuteInpatientPPS. The public may provide feedback on these finalized 
assignments which are then taken into consideration for the following 
fiscal year. We refer the reader to section II.D.16 of the preamble of 
this final rule for additional information regarding the ICD-10 
Coordination and Maintenance Committee meeting process. Lastly, we note 
that while some of the commenters opposed the revision to the title and 
assignment of the new ICD-10-PCS procedure codes to Pre-MDC MS-DRG 018, 
these commenters did not provide any alternative MS-DRGs for CMS to 
consider.
    In response to concerns involving payment uncertainty, we disagree 
that modifying Pre-MDC MS-DRG 018 to include other immunotherapies one 
year after it has been implemented carries a risk of creating 
additional payment uncertainty around CAR T-cell therapies and 
volatility in the relative weight for Pre-MDC MS-DRG 018. As stated in 
section II.E.2.b. of the preamble of the proposed rule and this

[[Page 44806]]

final rule, we proposed and are finalizing to maintain the methodology 
for the relative weight calculation for Pre-MDC MS-DRG 018. We refer 
the reader to section II.E.2.b. of the preamble of this final rule for 
the detailed discussion. Since the new procedure codes describing CAR 
T-cell, non-CAR T-cell or other immunotherapies are effective with 
discharges on and after October 1, 2021 and based on our understanding 
that the administration of these therapies continues to be in clinical 
trials, any claims reporting these new procedure codes containing 
diagnosis code Z00.6 or having standardized drug charges of less than 
$373,000 would be excluded from the calculation of the relative weight 
for Pre-MDC MS-DRG 018. During this timeframe, as additional claims 
data is made available, we will be better positioned to further 
evaluate if changes to the current methodology or other modifications 
to the procedure code assignments and MS-DRG are warranted.
    We appreciate the unique process that is involved with the 
development and production of CAR T-cell therapies, however, under the 
IPPS, when evaluating appropriate MS-DRG assignment for technologies 
(for example devices) that are utilized in the performance of a 
procedure we do not take into consideration how a specific device is 
manufactured compared to how other similar devices are manufactured. 
Rather, we analyze and consider the procedure(s) for which the 
technology is utilized for or in, and the resources involved in the 
performance of the procedure. As discussed, based on the information to 
date, we believe that the initial assignment of the listed procedure 
codes is appropriate. Based on the nature of some comments, it appears 
commenters were suggesting that CMS apply the criteria that is utilized 
for the new technology add-on application process when suggesting what 
factors CMS should consider for MS-DRG assignment of CAR T-cell, non-
CAR T-cell, and other immunotherapies. We note that the new technology 
add-on application criteria is separate and distinct from the code 
request process and subsequent MS-DRG assignment process.
    In response to the commenter who stated there are not any non-CAR 
T-cell therapy FDA approved products that are anticipated in the near 
term, we wish to clarify that the proposed and final assignment of a 
procedure code to a MS-DRG is not dependent upon a products FDA 
approval. Similarly, the creation of a code to describe a technology 
that is utilized in the performance of a procedure or service does not 
require FDA approval of the technology.
    With respect to the commenters' recommendation for CMS to continue 
to assess the appropriateness of the therapies being proposed or 
finalized to group to Pre-MDC MS-DRG 018, we note that, as discussed in 
the preamble of the proposed rule and this final rule we use our 
established process to examine the MS-DRG assignment for the 
predecessor codes to determine the most appropriate MS-DRG assignment 
and, consistent with the assignment of those predecessor codes, we 
propose to classify new procedure codes as shown Table 6B.--New 
Procedure Codes in association with the proposed rule each year. The 
procedure codes describing CAR T-cell, non-CAR T-cell or other 
immunotherapies are effective with discharges on and after October 1, 
2021 as shown in Table 6B.--New Procedure Codes associated with this 
final rule and available via the internet on the CMS website at: 
https://www.cms.gov/medicare/medicare-fee-for-service-payment/
acuteinpatientpps. In connection with the creation of new procedure 
codes (and diagnosis codes), the MS-DRGs are reviewed and recalibrated 
on an annual basis to specifically identify changes in utilization and 
resources, and to allow the opportunity for public comment on proposed 
changes under the IPPS.
    In response to the comment that the term ``immunotherapy'' could 
describe products that treat a range of conditions, we note that for FY 
2022 we are addressing an immediate need to account for any upcoming 
therapies that may be made available that are not specifically 
classified as a CAR T-cell therapy to enable appropriate payment and 
predictability. We note that the ICD-10-CM diagnosis codes identify 
specific conditions and are available for tracking indications and 
other purposes. We also note that because MS-DRG 018 is a Pre-MDC, the 
logic for case assignment is dependent on the procedure codes that are 
specifically assigned to the logic of the MS-DRG. Therefore, if a 
particular type of immunotherapy is not specifically described by one 
of the procedure codes that are listed in the definition (logic) for 
Pre-MDC MS-DRG 018, then the logic for case assignment to this MS-DRG 
would not be satisfied and another MS-DRG would be appropriately 
assigned based on the GROUPER logic (the definition of the MS-DRG).
    After consideration of the public comments received, for FY 2022, 
we are finalizing our proposal to assign the listed procedure codes 
describing CAR T-cell, non-CAR T-cell and other immunotherapies to Pre-
MDC MS-DRG 018 and to modify the title to ``Chimeric Antigen Receptor 
(CAR) T-cell and Other Immunotherapies'' to better reflect the cases 
reporting the administration of non-CAR T-cell therapies and other 
immunotherapies.
    When additional claims data becomes available for the CAR T-cell, 
non-CAR T-cell therapies and other immunotherapies for which new 
procedure codes have been created and are effective October 1, 2021 or 
that may be created and become effective during FY 2022, we can 
evaluate that data to determine if further modifications to Pre-MDC MS-
DRG 018 are warranted. We plan to continue engaging with stakeholders 
on additional options for consideration in this field of cellular and 
gene therapies, such as the creation of new and distinct MS-DRGs and to 
determine if the creation of a new MDC (Major Diagnostic Category) may 
be warranted to which unique MS-DRGs could be established and the 
appropriate corresponding procedure codes could be proposed for 
assignment.
3. MDC 03 (Diseases and Disorders of Ear, Nose, Mouth and Throat)
    In the FY 2021 IPPS/LTCH PPS final rule (85 FR 58462 through 
58471), we finalized our proposal to create two new base MS-DRGs, 140 
and 143, with a three-way severity level split for new MS-DRGs 140, 
141, and 142 (Major Head and Neck Procedures with MCC, with CC, and 
without CC/MCC, respectively) and new MS-DRGs 143, 144, and 145 (Other 
Ear, Nose, Mouth and Throat O.R. Procedures with MCC, with CC, and 
without CC/MCC, respectively). We provided the list of procedure codes 
that were finalized to define the logic for the new MS-DRGs in Tables 
6P.2a, 6P.2b, and 6P.2c associated with the final rule and available 
via the internet on the CMS website at https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/AcuteInpatientPPS/index/. As discussed 
in the FY 2022 IPPS/LTCH PPS proposed rule (86 FR 25095 through 25098), 
we received two separate but related requests to review and reconsider 
the MS-DRG assignments for a subset of the procedure codes listed in 
Table 6P.2a (procedure codes assigned to MS-DRGs 140, 141, and 142) and 
Table 6P.2b (procedure codes assigned to MS-DRGs 143, 144, and 145). In 
this section of this rule, we discuss each of these separate, but 
related requests.

[[Page 44807]]

a. Major Head and Neck Procedures
    The requestor provided the following procedure codes from Table 
6P.2a associated with the FY 2021 IPPS/LTCH PPS final rule for CMS to 
examine.
BILLING CODE 4120-01-P
[GRAPHIC] [TIFF OMITTED] TR13AU21.008

BILLING CODE 4120-01-C
    The requestor stated that the listed procedure codes do not appear 
appropriately assigned to MS-DRGs 140, 141, and 142. According to the 
requestor, if any one of the five procedure codes describing a 
procedure performed on the cranial cavity (0W9100Z, 0W910ZZ, 0WC10ZZ, 
0WC13ZZ, or 0WX14ZZ) is assigned in conjunction with a principal 
diagnosis from MDC 03 (Diseases and Disorders of Ear, Nose, Mouth, and 
Throat), it appears more appropriate that cases reporting the diagnosis 
and procedure combination would group to MS-DRGs 25, 26, and 27 
(Craniotomy and Endovascular Intracranial Procedures with MCC, with CC, 
and without CC/MCC, respectively) (for example, ``craniotomy'' MS-DRGs) 
in MDC 01 (Diseases and Disorders of the Central Nervous System) or to 
MS-DRGs 981, 982, and 983 (Extensive O.R. Procedures Unrelated to 
Principal Diagnosis with MCC, with CC, and without CC/MCC, 
respectively). The requestor stated that drainage and extirpation from 
the cranial cavity always involves drilling or cutting through the 
skull regardless of the approach, therefore the five procedure codes 
identified warrant assignment to the ``craniotomy'' MS-DRGs. For the 
three procedure codes describing excision of subcutaneous tissue of 
chest, back, or abdomen (0JB60ZZ, 0JB70ZZ, and 0JB80ZZ), the requestor 
stated those codes should group to MS-DRGs 987, 988, and 989 (Non-
extensive O.R. Procedures Unrelated to Principal Diagnosis with MCC, 
with CC, and without CC/MCC, respectively) because they are not 
pertinent to the ear, nose, mouth, or throat.
    In the FY 2022 IPPS/LTCH PPS proposed rule (86 FR 25096 through 
25097), we stated that we reviewed this request and noted that the five 
procedure codes describing procedures performed on the cranial cavity 
are already assigned to MDC 01 and group to the ``craniotomy'' MS-DRGs 
(25, 26, and 27) when reported with a principal diagnosis from MDC 01, 
and are also currently classified as Extensive O.R. procedures, 
resulting in assignment to MS-DRGs 981, 982, and 983 when any one of 
the five procedure codes is reported on the claim and is unrelated to 
the MDC to which the case was assigned based on the principal 
diagnosis. We also noted that in addition to MS-DRGs 25, 26, and 27, 
MS-DRG 23 (Craniotomy with Major Device Implant or Acute Complex CNS 
Principal Diagnosis with MCC or Chemotherapy Implant or Epilepsy with 
Neurostimulator) and MS-DRG 24 (Craniotomy with Major Device Implant or 
Acute Complex CNS Principal Diagnosis without MCC) include procedures 
performed on structures located within the cranial cavity, are included 
in the range of MS-DRGs known as the ``craniotomy'' MS-DRGs in MDC 01, 
and the five procedure codes submitted by the requestor describing 
procedures performed on the cranial cavity are also assigned to these 
MS-DRGs. We referred the requestor to Appendix E of the ICD-10 MS-DRG 
Definitions Manual for further discussion of how each procedure code 
may be assigned to multiple MDCs and MS-DRGs under the IPPS. The ICD-10 
MS-DRG Definitions Manual is located on the CMS website at https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/AcuteInpatientPPS/MS-DRG-Classifications-and-Software. We also noted 
that these five procedure codes were previously assigned to MS-DRGs 131 
and 132 (Cranial and Facial Procedures with and without CC/MCC, 
respectively) in MDC 03 under version 37 of the ICD-10 MS-DRGs prior to 
the restructuring that was finalized effective FY 2021 for MS-DRG 129 
(Major Head and Neck Procedures with CC/MCC or Major Device) and MS-DRG 
130 (Major Head and Neck Procedures without CC/MCC), MS-DRGs 131 and 
132, and MS-DRGs 133 and 134 (Other Ear, Nose, Mouth and Throat O.R. 
Procedures with and without CC/MCC, respectively).
    With regard to the three procedure codes describing excision of 
subcutaneous tissue of chest, back, or abdomen (0JB60ZZ, 0JB70ZZ, and 
0JB80ZZ), the requestor suggested that the codes should group to MS-
DRGs 987, 988, and 989 (Non-extensive O.R. Procedures Unrelated to 
Principal Diagnosis with MCC, with CC, and without CC/MCC, 
respectively) specifically because they are not pertinent to the ear, 
nose, mouth, or throat, however, we noted it is unclear if the 
requestor was concerned more broadly that the three procedure codes 
should not group to any MS-DRGs in MDC 03 (Diseases and Disorders of 
Ear, Nose, Mouth and Throat), given the stated rationale for the 
request.
    We stated in the proposed rule that, upon our review, we believed 
that the three procedure codes describing excision of subcutaneous 
tissue of chest, back, and abdomen (0JB60ZZ, 0JB70ZZ, and 0JB80ZZ), 
which do not describe major head and neck procedures, were 
inadvertently included in Table 6P.2a for assignment to MS-DRGs 140, 
141, and 142. However, we also stated we believe that the codes are 
appropriate for assignment in MDC 03 and noted that the three procedure 
codes were previously assigned to MS-DRGs 133 and 134 (Other Ear, Nose, 
Mouth and

[[Page 44808]]

Throat O.R. Procedures with and without CC/MCC, respectively) in MDC 03 
prior to the restructuring that was finalized effective FY 2021 for MS-
DRGs 129, 130, 131, 132, 133, and 134. We also provided the following 
clarification in the FY 2021 IPPS/LTCH PPS final rule (85 FR 58470), as 
stated in the ICD-10 MS-DRG Definitions Manual, ``In each MDC there is 
usually a medical and a surgical class referred to as ``other medical 
diseases'' and ``other surgical procedures,'' respectively. The 
``other'' medical and surgical classes are not as precisely defined 
from a clinical perspective. The other classes would include diagnoses 
or procedures, which were infrequently encountered or not well defined 
clinically. For example, the ``other'' medical class for the 
Respiratory System MDC would contain the diagnoses ``other somatoform 
disorders'' and ``congenital malformation of the respiratory system,'' 
while the ``other'' surgical class for the female reproductive MDC 
would contain the surgical procedures ``excision of liver'' (liver 
biopsy in ICD-9-CM) and ``inspection of peritoneal cavity'' 
(exploratory laparotomy in ICD-9-CM). The ``other'' surgical category 
contains surgical procedures which, while infrequent, could still 
reasonably be expected to be performed for a patient in the particular 
MDC.''
    In the proposed rule, we noted that during our review of procedure 
codes 0JB60ZZ, 0JB70ZZ, and 0JB80ZZ (describing excision of 
subcutaneous tissue of chest, back, and abdomen, respectively) we also 
confirmed that these procedures are currently designated as Extensive 
O.R. procedures. Consistent with other procedure codes on the Non-
extensive procedure code list, we stated we do not believe the 
procedures described by these procedure codes necessarily utilize the 
resources or have the level of technical complexity as the procedures 
on the Extensive O.R. procedures list. Therefore, we agreed that the 
procedure codes describing these procedures would be more appropriately 
designated as Non-extensive procedures and group to MS-DRGs 987, 988, 
and 989 (Non-extensive O.R. Procedures Unrelated to Principal Diagnosis 
with MCC, with CC, and without CC/MCC, respectively) when any one of 
the three procedure codes is reported on a claim and is unrelated to 
the MDC to which the case was assigned based on the principal 
diagnosis. We referred the reader to section II.D.10. of the preamble 
of the proposed rule for further discussion regarding our proposal to 
reassign these procedure codes from MS-DRGs 981, 982, and 983 
(Extensive O.R. Procedures Unrelated to Principal Diagnosis with MCC, 
with CC, and without CC/MCC, respectively) to MS-DRGs 987, 988, and 989 
(Non-extensive O.R. Procedures Unrelated to Principal Diagnosis with 
MCC, with CC, and without CC/MCC, respectively) for FY 2022.
    Therefore, we proposed to reassign the three procedure codes 
describing excision of subcutaneous tissue of chest, back, or abdomen 
(0JB60ZZ, 0JB70ZZ, and 0JB80ZZ) from MS-DRGs 140, 141, and 142 (Major 
Head and Neck Procedures with MCC, with CC, and without CC/MCC, 
respectively) to MS-DRGs 143, 144, and 145 (Other Ear, Nose, Mouth and 
Throat O.R. Procedures with MCC, with CC, and without CC/MCC, 
respectively) in MDC 03 for FY 2022. We refer the reader to section 
II.D.10. of the preamble of this final rule for further discussion 
regarding the designation of these codes as Extensive O.R. procedures 
versus Non-extensive O.R. procedures and our finalized reassignment of 
these codes from MS-DRGs 981, 982, and 983 to MS-DRGs 987, 988, and 989 
for FY 2022.
    Comment: Commenters supported the proposed reassignment of the 
three procedure codes describing excision of subcutaneous tissue of 
chest, back, or abdomen from MS-DRGs 140, 141, and 142 to MS-DRGs 143, 
144, and 145.
    Response: We appreciate the commenters' support.
    After consideration of the public comments we received, we are 
finalizing our proposal to reassign procedure codes 0JB60ZZ, 0JB70ZZ, 
and 0JB80ZZ describing excision of subcutaneous tissue of chest, back, 
or abdomen from MS-DRGs 140, 141, and 142 to MS-DRGs 143, 144, and 145 
for FY 2022.
b. Other Ear, Nose, Mouth and Throat O.R. Procedures
    As discussed in the FY 2022 IPPS/LTCH PPS proposed rule (86 FR 
25097 through 25098) and noted earlier, we received two separate but 
related requests to review and reconsider the MS-DRG assignments for a 
subset of the procedure codes listed in Table 6P.2a and Table 6P.2b 
associated with the FY 2021 IPPS/LTCH PPS final rule. In this section 
of this rule, we discuss the second request related to procedure codes 
listed in Table 6P.2b associated with the FY 2021 IPPS/LTCH PPS final 
rule and currently assigned to MS-DRGs 143, 144 and 145.
    The requestor provided a list of 82 procedure codes from Table 
6P.2b associated with the FY 2021 IPPS/LTCH PPS final rule for CMS to 
examine. We refer the reader to Table 6P.1d associated with the FY 2022 
IPPS/LTCH PPS proposed rule and this final rule and available via the 
internet at: https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/AcuteInpatientPPS/index/ for the list of procedure codes that 
were provided by the requestor. According to the requestor, if any one 
of the 82 procedure codes is assigned in conjunction with a principal 
diagnosis code from MDC 03, it appears more appropriate that cases 
reporting the diagnosis and procedure code combination would group to 
MS-DRGs 981, 982, and 983 (Extensive O.R. Procedures Unrelated to 
Principal Diagnosis with MCC, with CC, and without CC/MCC, 
respectively) or to MS-DRGs 987, 988, and 989 (Non-extensive O.R. 
Procedures Unrelated to Principal Diagnosis with MCC, with CC, and 
without CC/MCC, respectively) versus MS-DRGs 143, 144, and 145 (Other 
Ear, Nose, Mouth And Throat O.R. Procedures with MCC, with CC, and 
without CC/MCC, respectively). However, the requestor also stated that 
of the 82 procedure codes, the following three procedure codes 
describing control of bleeding in the cranial cavity warrant grouping 
to MS-DRGs 25, 26, and 27 (for example, ``craniotomy'' MS-DRGs) in MDC 
01, for the same reasons previously described in the prior section 
pertaining to the five other procedures performed on the cranial 
cavity.
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[[Page 44809]]

[GRAPHIC] [TIFF OMITTED] TR13AU21.009

BILLING CODE 4120-01-C
    We reviewed this request and similar to the discussion in the prior 
section for the separate but related request, we noted that the 
``other'' surgical category contains surgical procedures which, while 
infrequent, could still reasonably be expected to be performed for a 
patient in the particular MDC. We stated we continue to believe that 
the 82 procedure codes provided by the requestor are appropriately 
assigned to MS-DRGs 143, 144, and 145 in MDC 03. With regard to the 
requestor's assertion that cases reporting any one of the 82 procedure 
codes would more appropriately group to the MS-DRGs for Extensive O.R. 
procedures or Non-extensive O.R. procedures when reported in 
conjunction with a principal diagnosis from MDC 03, we noted that, as 
shown in Table 6P.2b associated with the FY 2021 IPPS/LTCH PPS final 
rule, the procedure codes that were finalized for assignment to MS-DRGs 
143, 144, and 145 were previously assigned to MS-DRGs 129 and 130, 131 
and 132, or 133 and 134 in MDC 03. We also noted that, as discussed in 
prior rulemaking, cases that contain O.R. procedures will map to MS-DRG 
981, 982, or 983 (Extensive O.R. Procedure Unrelated to Principal 
Diagnosis with MCC, with CC, and without CC/MCC, respectively) or MS-
DRG 987, 988, or 989 (Non-Extensive O.R. Procedure Unrelated to 
Principal Diagnosis with MCC, with CC, and without CC/MCC, 
respectively) when they do not contain a principal diagnosis that 
corresponds to one of the MDCs to which that procedure is assigned. For 
these reasons, we proposed to maintain the current structure for MS-
DRGs 143, 144, and 145 for FY 2022.
    Comment: A few commenters recommended that CMS reconsider the list 
of 82 procedure codes assigned to MS-DRGs 143, 144, and 145 (Other Ear, 
Nose, Mouth and Throat O.R. Procedures with MCC, with CC and without 
CC/MCC, respectively) that were displayed in Table 6P.1d associated 
with the proposed rule when reported with a principal diagnosis from 
MDC 03.
    The commenters acknowledged that the ``other'' surgical category 
contains surgical procedures which, while infrequent, could still 
reasonably be expected to be performed for a patient in the particular 
MDC, however, the commenters stated it is unclear what clinical 
scenarios would result in certain procedure codes listed being assigned 
with a diagnosis in MDC 03. The commenters provided the following list 
of 38 procedure codes as examples of procedures that would not be 
expected to be performed with a diagnosis from MDC 03.
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[[Page 44810]]

[GRAPHIC] [TIFF OMITTED] TR13AU21.010

BILLING CODE 4120-01-C
    Another commenter requested transparency for the logic and data for 
the exclusion of the 82 procedure codes and suggested that CMS may not 
have any data for these procedures within MS-DRGs 143, 144, and 145 
that were created in FY 2021.
    Response: We appreciate the commenters' feedback and acknowledge 
that the listed procedure codes would not appear to be clinically 
indicated specifically for diagnoses in MDC 03. The commenter is 
correct that it is too soon to have data available for the listed 
procedure codes under MS-DRGs 143, 144, and 145 that were created 
effective FY 2021. However, in our analysis of the FY 2018 MedPAR data 
that was studied in our initial review of MDC 03 in consideration of 
potential restructuring, for MS-DRG 133 (currently MS-DRG 144), we 
identified one case reporting procedure code 0DJ04ZZ (Inspection of 
upper intestinal tract, percutaneous endoscopic approach) with an 
average length of stay of 14 days and average costs of $5,728 and one 
case reporting procedure code 0FB00ZX (Excision of liver, open 
approach, diagnostic) with an average length of stay of 17 days and 
average costs of $32,642. We continued to believe that these 
procedures, in addition and/or including the 38 procedure codes listed 
that are now the subject of commenters' concerns, appropriate to 
maintain in the logic for case assignment to the ``other'' surgical MS-
DRGs in MDC 03. However, as a result of the ongoing concerns expressed 
by commenters specifically regarding the assignment of the 38 listed 
procedure codes and the suggestion that CMS should reconsider the 
current MS-DRG assignment, we determined it may be helpful to provide 
the comparable translations under ICD-9-CM for commenters to better 
understand how these 38 procedures were initially grouped to the ICD-10 
MS-DRGs as a result of replication during the conversion from ICD-9 to 
ICD-10 based MS-DRGs. We refer the reader to Table

[[Page 44811]]

6P.1m for findings from our analysis of the 38 listed procedure codes, 
which indicates how these procedures were classified under ICD-10-PCS 
based on the comparable translations under ICD-9-CM resulting in the 
current MS-DRG assignment. We note that we were unable to fully 
evaluate the 82 procedure codes and believe it may be advantageous to 
evaluate further when claims data becomes available under the 
restructured MS-DRGs (143, 144, and 145) that were effective with 
discharges beginning FY 2021.
    In response to the commenter who requested transparency for the 
logic, we note that the GROUPER logic for all the MS-DRGs is made 
publicly available in the ICD-10 MS-DRG Definitions Manual via the 
internet on the CMS website at: https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/AcuteInpatientPPS/MS-DRG-Classifications-and-Software.
    After consideration of the public comments we received, we are 
finalizing to maintain the assignment of the listed 82 procedure codes 
to MS-DRGs 143, 144, and 145 for FY 2022. We will continue to review 
the appropriateness of procedure code assignment to these MS-DRGs in 
connection with our broader comprehensive procedure code analysis.
    As noted in the proposed rule, with regard to the three procedure 
codes describing control of bleeding in the cranial cavity (0W310ZZ, 
0W313ZZ, and 0W314ZZ), and the requestor's suggestion that the codes 
should group to MS-DRGs 25, 26, and 27 in MDC 01, we consulted with our 
clinical advisors who stated these procedures are consistent with the 
existing procedure codes included in the logic for case assignment to 
MS-DRGs 25, 26, and 27. We refer the reader to section II.D.10. of the 
preamble of the proposed rule and this final rule for further 
discussion of this request, as well as the finalized assignment of 
these codes to MS-DRGs 23, 24, 25, 26, and 27 for FY 2022.
4. MDC 04 (Diseases and Disorders of the Respiratory System)
a. Bronchiectasis
    In the FY 2022 IPPS/LTCH PPS proposed rule (86 FR 25098), we 
discussed a request we received to reassign cases reporting diagnosis 
codes describing bronchiectasis from MS-DRGs 190, 191, and 192 (Chronic 
Obstructive Pulmonary Disease with MCC, with CC, and without CC/MCC, 
respectively) to MS-DRGs 177, 178, and 179 (Respiratory Infections and 
Inflammation with MCC, with CC, and without CC/MCC, respectively). 
Bronchiectasis is described by the following diagnosis codes:
BILLING CODE 4120-01-P
[GRAPHIC] [TIFF OMITTED] TR13AU21.011

BILLING CODE 4120-01-C
    According to the requestor, the underlying pathophysiology of 
bronchiectasis is more similar to cystic fibrosis than it is to chronic 
obstructive pulmonary disease (COPD). The requestor stated that in 
bronchiectasis, there is an inciting event that creates scarring in the 
lung which prevents the lung from clearing out mucous like it normally 
would. The accumulation of abnormal mucous results in an environment 
conducive to bacterial growth and commonly found bacteria in this 
setting is very similar to those of cystic fibrosis with staphylococcus 
aureus, pseudomonas aeruginosa, and non-tuberculous mycobacterium. The 
requestor reported that when patients develop an exacerbation of 
bronchiectasis, this is because of a buildup of mucous compounded by 
overwhelming growth of the previously discussed bacteria. The requestor 
also stated that patients admitted to the hospital for bronchiectasis 
exacerbation are treated aggressively with intravenous (IV) antibiotics 
to suppress the bacterial infection in combination with airway 
clearance therapies. The requestor further stated that, unlike in an 
acute COPD exacerbation, these patients do not always require steroids 
as there is not necessarily airway reactivity.
    The requestor maintained that the underlying reason for admission 
to the hospital for these patients is the bacterial infection component 
of the exacerbation, with the standard course of treatment for these 
pulmonary bacterial infections averaging a minimum of 10-14 days due to 
the slow growing nature of the bacteria commonly encountered in these 
patients.
    We stated in the FY 2022 IPPS/LTCH PPS proposed rule that we 
reviewed this request and believed that bronchiectasis is appropriately 
assigned to MS-DRGs 190, 191, and 192 (Chronic Obstructive Pulmonary 
Disease with MCC, with CC, and without CC/MCC, respectively) because 
bronchiectasis, like COPD, is a chronic condition. We noted that with 
respect to the requestor's comments, cystic fibrosis, a genetic disease 
that affects mucous producing cells resulting in recurring lung 
infections, can lead to bronchiectasis. However, our clinical advisors 
indicated that the cause of bronchiectasis can be multifactorial or 
even remain undefined. Regardless of the cause, when present, 
bronchiectasis is an irreversible chronic pulmonary condition due to 
abnormal change to or destruction of normal pulmonary anatomy (the 
major bronchi and bronchiole walls), resulting in impaired air movement 
in and out of the lungs. COPD, regardless of the cause (smoking, 
pollution, other exposures), is a chronic pulmonary condition due to 
change/destruction of normal pulmonary anatomy, resulting in impaired 
air movement in and out of the lungs. Both bronchiectasis and COPD 
patients have abnormal pulmonary function tests and abnormal anatomic 
findings on chest x-ray and/or chest CT. Therefore, for these reasons, 
we proposed to maintain the structure of MS-DRGs 190, 191, and 192 for 
FY 2022.
    Comment: Commenters agreed with our proposal to maintain the 
structure of MS-DRGs 190, 191, and 192.
    Response: We thank the commenters for their support.
    After consideration of the public comments we received, we are 
finalizing our proposal to maintain the structure of MS-DRGs 190, 191, 
and 192 for FY 2022.

[[Page 44812]]

b. Major Chest Procedures
    In the FY 2020 IPPS/LTCH PPS proposed (84 FR 19234) and final rules 
(84 FR 42148), we stated that in review of the procedures that are 
currently assigned to MS-DRGs 163, 164, and 165 (Major Chest Procedures 
with MCC, with CC and without CC/MCC, respectively) and 166, 167, and 
168 (Other Respiratory System O.R. Procedures with MCC, with CC, and 
without CC/MCC, respectively), that further refinement of these MS-DRGs 
may be warranted. In this section of this rule, we discuss our review 
of the procedures and restructuring these MS-DRGs for FY 2022.
    We began our review of MS-DRGs 163, 164, 165, 166, 167, and 168 by 
first examining all the procedures currently assigned to these MS-DRGs. 
We referred the reader to the ICD-10 MS-DRG Definitions Manual Version 
38.1, which is available via the internet on the CMS website at: 
https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/AcuteInpatientPPS for complete documentation of the GROUPER logic for 
MS-DRGs 163, 164, 165, 166, 167, and 168.
    We stated in the proposed rule that in our review of the procedures 
currently assigned to MS-DRGs 163, 164, 165, 166, 167, and 168, we 
found 17 procedure codes in MS-DRGs 163, 164, and 165 describing laser 
interstitial thermal therapy (LITT) of body parts that do not describe 
areas within the respiratory system, which would not be clinically 
appropriate to maintain in the logic. These procedure codes are listed 
in the following table.
BILLING CODE 4120-01-P
[GRAPHIC] [TIFF OMITTED] TR13AU21.012

BILLING CODE 4120-01-C
    During our review of these 17 procedure codes, we identified 
additional MDCs and MS-DRG assignments that are also not clinically 
appropriate to maintain in the logic because the body parts described 
by the codes are not consistent with the organ system, etiology or 
clinical specialty of the MDC to which the procedure code is currently 
assigned. For example, 16 of the 17 procedure codes (all except 
procedure code DVY0KZZ) are included in the logic for case assignment 
to MDC 12 (Diseases and Disorders of the Male Reproductive System) in 
MS-DRGs 715 and 716 (Other Male Reproductive System O.R. Procedures for 
Malignancy with and without CC/MCC, respectively) and MS-DRGs 717 and 
718 (Other Male Reproductive System O.R. Procedures Except Malignancy 
with and without CC/MCC, respectively) which is not clinically 
appropriate. Therefore, we proposed to reassign these 17 procedure 
codes from their current MS-DRG assignments in MDC 04, and from the 
additional MDCs and MS-DRGs identified during our review that were 
found to be clinically inappropriate, to their clinically appropriate 
MDC and MS-DRGs as shown in Table 6P.2b associated with the proposed 
rule and this final rule (which is available via the internet on the 
CMS website at: https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/AcuteInpatientPPS).
    Comment: Commenters agreed with the proposed reassignment of the 
listed procedure codes as shown in Table 6P.2b associated with the 
proposed rule describing LITT of various body parts to the proposed 
more clinically appropriate MDCs and MS-DRGs. However, a commenter 
suggested that CMS consider reassignment of code D0Y6KZZ to MS-DRGs 28, 
29, and 30 (Spinal Procedures with MCC, with CC or Spinal 
Neurostimulators and without CC/CC, respectively) rather than MS-DRGs 
40, 41, and 42 (Peripheral, Cranial Nerve and Other Nervous System 
Procedures with MCC, with CC and without CC/MCC, respectively) as being 
more clinically and anatomically homogenous.
    Response: We thank the commenters for their support. In response to 
the commenter who suggested that CMS consider reassignment of code 
D0Y6KZZ to MS-DRGs 28, 29, and 30 rather than MS-DRGs 40, 41, and 42 we 
note that our clinical advisors continue to believe this is an 
appropriate

[[Page 44813]]

assignment to MS-DRGs 40, 41, and 42 because the resources involved in 
the performance of a LITT procedure of the spinal cord (code D0Y6KZZ) 
clinically align more appropriately with the resources involved in the 
performance of stereotactic radiosurgery of spinal cord procedures 
currently assigned to MS-DRGs 40, 41, and 42 (procedure codes D026DZZ, 
D026HZZ, and D026JZZ).
    We also note that, as discussed in section II.D.10. of the preamble 
of the proposed rule and this final rule, we identified additional 
procedure codes describing LITT of various body parts, in addition to 
the 17 procedure codes listed earlier in this section. The 14 
additional procedure codes are:
BILLING CODE 4120-01-P
[GRAPHIC] [TIFF OMITTED] TR13AU21.013

BILLING CODE 4120-01-C
    As these codes also describe laser interstitial thermal therapy 
(LITT) of various body parts, we conducted further review of the MDC 
and MS-DRG assignments of these 14 procedure codes consistent with our 
initial review of the 17 procedure codes, and determined that 
clinically inappropriate assignments also exist or that the current MS-
DRG assignment is not in alignment with the resources that are utilized 
in the performance of the LITT procedure. For example, we examined 
procedure codes D0Y0KZZ and D0Y1KZZ describing LITT of brain and brain 
stem, respectively, that are currently assigned to the ``craniotomy'' 
MS-DRGs 23, 24, 25 26, and 27 in MDC 01 (Diseases and Disorders of the 
Central Nervous System). The technique to perform the LITT procedure on 
these structures is considered minimally invasive and does not involve 
a craniotomy, therefore, continued assignment to the craniotomy MS-DRGs 
is not clinically appropriate. While we agree that these procedures are 
appropriately assigned to MDC 01, similar to our review for procedure 
code D0Y6KZZ describing LITT of spinal cord, we believe it is more 
appropriate for the procedures described by codes D0Y0KZZ and D0Y1KZZ 
to be reassigned to MS-DRGs 40, 41, and 42. We then examined procedure 
codes DBY0KZZ, DBY1KZZ, DBY2KZZ, DBY5KZZ, DBY6KZZ, DBY7KZZ, and DBY8KZZ 
describing LITT of respiratory structures including the trachea, 
bronchus, lung, pleura, mediastinum, chest wall, and diaphragm, 
respectively, that are currently assigned to the ``major chest 
procedures'' MS-DRGs 163, 164, and 165. While we agree that these 
procedures are appropriately assigned to MDC 04, we do not believe LITT 
of these respiratory structures utilize the same resources or require 
the same level of complexity as the other procedures currently defined 
in the GROUPER logic as ``major chest procedures'' since, as noted 
previously, LITT is considered a minimally invasive procedure and there 
are no large incisions with extensive muscle dissection. For these 
reasons, we believe it is more appropriate for the procedure codes 
describing LITT of respiratory structures to be reassigned to MS-DRGs 
166, 167, and 168 (Other Respiratory System O.R. Procedures with MCC, 
with CC, and without CC/MCC, respectively).
    After consideration of the public comments we received and based on 
the analysis described previously, we are finalizing our proposal, with 
modification, to reassign the 31 listed procedure codes as shown in 
Table 6P.2b associated with this final rule describing LITT of various 
body parts to the more clinically appropriate MDCs and MS-DRGs for FY 
2022.
    During our review of the procedure codes describing LITT of various 
body parts we also confirmed that these procedures are currently 
designated as Extensive O.R. procedures. We do not believe the 
procedures described by these procedure codes necessarily utilize the 
resources or have the level of technical complexity as the other 
procedures on the Extensive O.R. procedures list. We stated in the 
proposed rule that we believe that the procedure codes describing these 
procedures would be more appropriately designated as Non-extensive 
procedures and group to MS-DRGs 987, 988, and 989 (Non-extensive O.R. 
Procedures Unrelated to Principal Diagnosis with MCC, with CC, and 
without CC/MCC, respectively) when any one of the procedure codes is 
reported on a claim and is unrelated to the MDC to which the case was 
assigned based on the principal diagnosis. We refer the reader to 
section II.D.10. of the preamble of the proposed rule and this final 
rule for further discussion regarding reassignment of these procedure 
codes from MS-DRGs 981, 982, and 983 (Extensive O.R. Procedures 
Unrelated to Principal Diagnosis with

[[Page 44814]]

MCC, with CC, and without CC/MCC, respectively) to MS-DRGs 987, 988, 
and 989 (Non-extensive O.R. Procedures Unrelated to Principal Diagnosis 
with MCC, with CC, and without CC/MCC, respectively) for FY 2022.
    We also identified five procedure codes describing repair of the 
esophagus procedures currently assigned to MS-DRGs 163, 164, and 165 
that would not be clinically appropriate to maintain in the logic. The 
procedure codes are 0DQ50ZZ (Repair esophagus, open approach), 0DQ53ZZ 
(Repair esophagus, percutaneous approach), 0DQ54ZZ (Repair esophagus, 
percutaneous endoscopic approach), 0DQ57ZZ (Repair esophagus, via 
natural or artificial opening), and 0DQ58ZZ (Repair esophagus, via 
natural or artificial opening endoscopic), and are currently assigned 
to the following MDCs and MS-DRGs.
BILLING CODE 4120-01-P
[GRAPHIC] [TIFF OMITTED] TR13AU21.014


[[Page 44815]]


[GRAPHIC] [TIFF OMITTED] TR13AU21.015

BILLING CODE 4120-01-C
    We stated that the five procedure codes describing repair of 
esophagus procedures are not clinically coherent with the other 
procedures in MS-DRGs 163, 164, and 165 that describe procedures 
performed on major chest structures. Therefore, we proposed to remove 
procedure codes 0DQ50ZZ, 0DQ53ZZ, 0DQ54ZZ, 0DQ57ZZ, and 0DQ58ZZ from 
the logic in MDC 04 for FY 2022.
    Comment: Commenters agreed with the proposal to remove procedure 
codes 0DQ50ZZ, 0DQ53ZZ, 0DQ54ZZ, 0DQ57ZZ, and 0DQ58ZZ from the logic in 
MDC 04.
    Response: We appreciate the commenters' support.
    After consideration of the public comments we received, we are 
finalizing our proposal to remove procedure codes 0DQ50ZZ, 0DQ53ZZ, 
0DQ54ZZ, 0DQ57ZZ, and 0DQ58ZZ describing repair of the esophagus from 
the logic in MDC 04 for FY 2022.
    As discussed in the FY 2022 IPPS/LTCH PPS proposed rule (86 FR 
25102), during our review of procedure codes 0DQ50ZZ, 0DQ53ZZ, 0DQ54ZZ, 
0DQ57ZZ, and 0DQ58ZZ (describing repair of esophagus procedures) we 
also confirmed that these procedures are currently designated as 
Extensive O.R. procedures. We stated we do not believe the procedures 
described by procedure codes 0DQ53ZZ, 0DQ57ZZ, and 0DQ58ZZ necessarily 
utilize the resources or have the level of technical complexity as the 
other procedures on the Extensive O.R. procedures list. We further 
stated we believe that the procedure codes describing these procedures 
would be more appropriately designated as Non-extensive procedures and 
group to MS-DRGs 987, 988, and 989 (Non-extensive O.R. Procedures 
Unrelated to Principal Diagnosis with MCC, with CC, and without CC/MCC, 
respectively) when any one of the three procedure codes is reported on 
a claim and is unrelated to the MDC to which the case was assigned 
based on the principal diagnosis. We refer the reader to section 
II.D.10. of the preamble of the proposed rule and this final rule for 
further discussion regarding reassignment of these procedure codes from 
MS-DRGs 981, 982, and 983 (Extensive O.R. Procedures Unrelated to 
Principal Diagnosis with MCC, with CC, and without CC/MCC, 
respectively) to MS-DRGs 987, 988, and 989 (Non-extensive O.R. 
Procedures Unrelated to Principal Diagnosis with MCC, with CC, and 
without CC/MCC, respectively) for FY 2022.
    Next, we examined claims data from the March 2020 update of the FY 
2019 MedPAR file and the September 2020 update of the FY 2020 MedPAR 
file for all cases in MS-DRGs 163, 164, 165, 166, 167, and 168. Our 
findings are shown in the following tables.
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[[Page 44816]]

[GRAPHIC] [TIFF OMITTED] TR13AU21.016

[GRAPHIC] [TIFF OMITTED] TR13AU21.017

BILLING CODE 4210-01-C
    As shown in the tables, there were a higher number of cases 
reported in MS-DRGs 163, 164, 165, 166, 167, and 168 from the March 
2020 update of the FY 2019 MedPAR file in comparison to the September 
2020 update of the FY 2020 MedPAR file and overall, the cases reported 
have comparable average lengths of stay and comparable average costs 
for both fiscal years.
    We then examined claims data from both the March 2020 update of the 
FY 2019 MedPAR file and the September 2020 update of the FY 2020 MedPAR 
file for MS-DRGs 163, 164, 165, 166, 167, and 168 to compare costs, 
complexity of service and clinical coherence for each procedure code 
currently assigned to these MS-DRGs to assess any potential 
reassignment of the procedures. We refer the reader to Table 6P.1e and 
Table 6P.1f associated with the proposed rule and this final rule 
(which is available via the internet on the CMS website at: https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/AcuteInpatientPPS) for the detailed claims data analysis. Table 6P.1e 
contains the data analysis findings of procedure codes currently 
assigned to MS-DRGs 163, 164, 165, 166, 167, and 168 from the March 
2020 update of the FY 2019 MedPAR file and Table 6P.1f contains the 
data analysis findings of procedure codes currently assigned to MS-DRGs 
163, 164, 165, 166, 167, and 168 from the September 2020 update of the 
FY 2020 MedPAR file. We note that if a procedure code that is currently 
assigned to MS-DRGs 163, 164, 165, 166, 167, or 168 is not displayed, 
it is because there were no cases found reporting that code in the 
assigned MS-DRG.
    As shown in Table 6P.1e and Table 6P.1f associated with the 
proposed rule and this final rule, in our examination of the claims 
data from both the March 2020 update of the FY 2019 MedPAR file and 
September 2020 update of the FY 2020 MedPAR file, we found there is 
wide variation in the volume, length of stay, and average costs for the 
procedures currently assigned to MS-DRGs 163, 164, 165, 166, 167, and 
168. There were several instances in which only one occurrence of a 
procedure was reported with a procedure code from MS-DRGs 163, 164, 
165, 166, 167, or 168, and the average length of stay for these 
specific cases ranged from 1 day to 97 days. For example, in the 
analysis of claims data from the March 2020 update of the FY 2019 
MedPAR file, during our review of MS-DRG 163, we found 153 procedures 
for which only one occurrence of the procedure was reported with the 
average length of stay ranging from 2 days to 65 days and the average 
costs ranging from $3,760 to $195,447 for these cases. For MS-DRG 164, 
we found 145 procedures for which only one occurrence of the procedure 
was reported with the average length of stay ranging from 1 day to 28 
days and the average costs ranging from $1,886 to $137,810 for these 
cases. For MS-DRG 165, we found 111 procedures for which only one 
occurrence of the procedure was reported with the average length of 
stay ranging from 1 day to 23 days and the average costs ranging from 
$2,656 to $73,092 for these cases. For MS-DRG 166, we found 150 
procedures for which only one occurrence of the procedure was reported 
with the average length of stay ranging from 1 day to 61 days and the 
average costs ranging from $3,230 to $246,679 for these cases. For MS-
DRG 167, we found 110 procedures for which only one occurrence of the 
procedure was reported with the average length of stay ranging from 1 
day to 23 days and the average costs ranging from $2,058 to $149,220 
for these cases. For MS-DRG 168, we found 68 procedures for which only 
one occurrence of the procedure was reported with the average length of 
stay ranging from 1 day to 18 days and the average costs ranging from 
$2,033 to $35,576 for these cases.
    Our analysis of the claims data from the September 2020 update of 
the FY 2020 MedPAR file resulted in similar findings to those from the 
March 2020 update of the FY 2019 MedPAR file; there were several 
instances in which only one occurrence of a procedure was reported with 
a procedure code from MS-DRGs 163, 164, 165, 166, 167, or 168. During 
our review of MS-DRG 163, we found 139 procedures for which only one 
occurrence of the procedure

[[Page 44817]]

was reported with the average length of stay ranging from 2 days to 97 
days and the average costs ranging from $5,697 to $205,696 for these 
cases. For MS-DRG 164, we found 122 procedures for which only one 
occurrence of the procedure was reported with the average length of 
stay ranging from 1 day to 35 days and the average costs ranging from 
$3,204 to $120,128 for these cases. For MS-DRG 165, we found 92 
procedures for which only one occurrence of the procedure was reported 
with the average length of stay ranging from 1 day to 16 days and the 
average costs ranging from $2,682 to $164,014 for these cases. For MS-
DRG 166, we found 141 procedures for which only one occurrence of the 
procedure was reported with the average length of stay ranging from 1 
day to 45 days and the average costs ranging from $3,230 to $246,679 
for these cases. For MS-DRG 167, we found 105 procedures for which only 
one occurrence of the procedure was reported with the average length of 
stay ranging from 1 day to 22 days and the average costs ranging from 
$2,150 to $112,465 for these cases. For MS-DRG 168, we found 72 
procedures for which only one occurrence of the procedure was reported 
with the average length of stay ranging from 1 day to 9 days and the 
average costs ranging from $1,563 to $76,061 for these cases.
    Our clinical advisors reviewed the procedures currently assigned to 
MS-DRGs 163, 164, 165, 166, 167, and 168 to identify the patient 
attributes that currently define each of these procedures and to group 
them with respect to complexity of service and resource intensity. This 
process included separating the procedures according to the surgical 
approach (open, percutaneous, percutaneous endoscopic, via natural or 
artificial opening, via natural or artificial opening endoscopic, and 
external).
    We also considered the claims data from the March 2020 update of 
the FY 2019 MedPAR file and the September 2020 update of the FY 2020 
MedPAR file for MS-DRGs 163, 164, 165, 166, 167, and 168 to further 
analyze the average length of stay and average costs for the cases 
reporting procedures assigned to any one of these MS-DRGs as well as 
clinical coherence for these cases. For example, procedures that we 
believe represent greater treatment difficulty and reflect a class of 
patients who are similar clinically with regard to consumption of 
hospital resources were grouped separately from procedures that we 
believe to be less complex but still reflect patients who are similar 
clinically with regard to consumption of hospital resources. This 
approach differentiated the more complex procedures, such as procedures 
performed on the sternum and ribs (for example, major chest) from the 
less complex procedures such as bypass procedures performed on 
peripheral vessels or diagnostic biopsies.
    We stated in the FY 2022 IPPS/LTCH PPS proposed rule that as an 
initial step in our proposed restructuring of these MS-DRGs, we 
identified the following 26 procedure codes that are currently assigned 
to MS-DRGs 166, 167, and 168 that we believe represent procedures 
performed on structures that align more appropriately with the 
procedures assigned to MS-DRGs 163, 164, and 165 that describe major 
chest procedures.
BILLING CODE 4120-01-P
[GRAPHIC] [TIFF OMITTED] TR13AU21.018

BILLING CODE 4120-01-C
    We analyzed claims data from the March 2020 update of the FY 2019 
MedPAR file for the listed procedure codes in MS-DRGs 166, 167, and 
168. We noted that if a listed procedure code is not displayed, it is 
because there were no cases found reporting that code among MS-DRGs 
166, 167, and 168. Our findings are shown in the following table.
BILLING CODE 4120-01-P

[[Page 44818]]

[GRAPHIC] [TIFF OMITTED] TR13AU21.019

BILLING CODE 4120-01-C
    We then analyzed claims data from the September 2020 update of the 
FY 2020 MedPAR file for the listed procedure codes in MS-DRGs 166, 167, 
and 168. We noted that if a listed procedure code is not displayed, it 
is because there were no cases found reporting that code among MS-DRGs 
166, 167, and 168. Our findings are shown in the following table.
BILLING CODE 4120-01-P

[[Page 44819]]

[GRAPHIC] [TIFF OMITTED] TR13AU21.020

BILLING CODE 4120-01-C
    We referred the reader to Tables 6P.1e and 6P.1f for detailed 
claims data for the previously listed procedures in MS-DRGs 163, 164, 
165, 166, 167, and 168 from the March 2020 update of the FY 2019 MedPAR 
file and the September 2020 update of the FY 2020 MedPAR file, 
respectively, and noted in the proposed rule that while some of the 26 
listed procedure codes identified in MS-DRGs 166, 167, and 168 may not 
have been reported in either year's MedPAR claims data or only had one 
occurrence in which the procedure was reported, we believe these 
procedures described by the listed 26 procedure codes are clinically 
coherent with the other procedures that are currently assigned to MS-
DRGs 163, 164, and 165. For example, in our analysis of the March 2020 
update of the FY 2019 MedPAR file, as shown in the table, we found 
procedure code 02QW0ZZ reported with one occurrence with an average 
length of stay of 15 days and average costs of $46,829. Despite finding 
only one case, we stated that we believe procedures described by this 
procedure code, as well as related procedure codes describing 
procedures performed on the great vessels, are more clinically coherent 
with the procedures assigned to MS-DRGs 163, 164, and 165 and align 
more appropriately with the average length of stay and average costs of 
those MS-DRGs. Similarly, in our analysis of the September 2020 update 
of the FY 2020 MedPAR file, as shown in the table, we found procedure 
code 0PS204Z reported with 344 occurrences with an average length of 
stay of 9.6 days and average costs of $48,340. We stated that we 
believe procedures described by this procedure code, as well as related 
procedure codes describing procedures performed to repair or resect the 
ribs, are more clinically coherent with the procedures

[[Page 44820]]

assigned to MS-DRGs 163, 164, and 165 and also align more appropriately 
with the average length of stay and average costs of those MS-DRGs.
    As a result of our preliminary review of MS-DRGs 163, 164, 165, 
166, 167, and 168, for FY 2022, we proposed the reassignment of the 
listed 26 procedure codes (9 procedure codes describing repair of 
pulmonary or thoracic structures, and 17 procedure codes describing 
procedures performed on the sternum or ribs) from MS-DRGs 166, 167, and 
168 to MS-DRGs 163, 164, and 165 in MDC 04. We stated that our data 
analysis shows that for the cases reporting any one of the 26 procedure 
codes, generally, they have an average length of stay and average costs 
that appear more consistent with the average length of stay and average 
costs of cases in MS-DRGs 163, 164, and 165. Our clinical advisors also 
agreed that these procedures clinically align with the other procedures 
that are currently assigned to MS-DRGs 163, 164, and 165. We referred 
the reader to Table 6P.2c associated with the proposed rule for the 
list of procedure codes we proposed for reassignment from MS-DRGs 166, 
167, and 168 to MS-DRGs 163, 164, and 165 in MDC 04.
    Comment: Commenters supported the proposed reassignment of the 
listed 26 procedure codes from MS-DRGs 166, 167, and 168 to MS-DRGs 
163, 164, and 165 in MDC 04.
    Response: We appreciate the commenters' support.
    After consideration of the public comments received, we are 
finalizing our proposal to reassign the listed 26 procedure codes (9 
procedure codes describing repair of pulmonary or thoracic structures, 
and 17 procedure codes describing procedures performed on the sternum 
or ribs), as listed in Table 6P.2c associated with this final rule, 
from MS-DRGs 166, 167, and 168 to MS-DRGs 163, 164, and 165 in MDC 04 
for FY 2022.
    As discussed in the proposed rule, after this initial review of all 
the procedures currently assigned to MS-DRGs 163, 164, 165, 166, 167, 
and 168, in combination with the results of the data analysis as 
reflected in Tables 6P.1e and 6P.1f, our clinical advisors support a 
phased restructuring of these MS-DRGs. We believe further analysis of 
the procedures assigned to these MS-DRGs is warranted based on the 
creation of new procedure codes that have been assigned to these MS-
DRGs in recent years for which claims data are not yet available and 
the need for additional time to examine the procedures currently 
assigned to those MS-DRGs by clinical intensity, complexity of service 
and resource utilization. We will continue to evaluate the procedures 
assigned to these MS-DRGs as additional claims data become available.
5. MDC 05 (Diseases and Disorders of the Circulatory System)
a. Short-Term External Heart Assist Device
    As discussed in the FY 2022 IPPS/LTCH PPS proposed rule (86 FR 
25106 through 25115), Impella[supreg] Ventricular Support Systems are 
temporary heart assist devices intended to support blood pressure and 
provide increased blood flow to critical organs in patients with 
cardiogenic shock, by drawing blood out of the heart and pumping it 
into the aorta, partially or fully bypassing the left ventricle to 
provide adequate circulation of blood (replace or supplement left 
ventricle pumping) while also allowing damaged heart muscle the 
opportunity to rest and recover in patients who need short-term support 
for up to 6 days. The ICD-10-PCS codes that describe the insertion of 
Impella[supreg] heart assist devices are currently assigned to MS-DRG 
215 (Other Heart Assist System Implant). We referred the reader to the 
ICD-10 MS-DRG Definitions Manual Version 38.1, which is available via 
the internet on the CMS website at: https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/AcuteInpatientPPS/MS-DRG-Classifications-and-Software for complete documentation of the GROUPER 
logic for MS-DRG 215.
    In the FY 2019 IPPS/LTCH PPS final rule (83 FR 41159 through 
41170), we discussed public comments that recommended that CMS continue 
to monitor the data in MS-DRG 215 for future consideration of 
distinctions (for example, different approaches and evolving 
technologies) that may impact the clinical and resource use of 
procedures utilizing heart assist devices. Our data analysis showed a 
wide range in the average length of stay and the average costs for 
cases reporting procedures that involve a biventricular short-term 
external heart assist system versus a short-term external heart assist 
system. We noted we were aware that the AHA published Coding Clinic 
advice that clarified coding and reporting for certain external heart 
assist devices due to the technology being approved for new indications 
but the claims data current at that time did not yet reflect that 
updated guidance. We also noted that there had been recent updates to 
the descriptions of the codes for heart assist devices. The qualifier 
``intraoperative'' was added effective October 1, 2017 (FY 2018) to the 
procedure codes describing the insertion of short-term external heart 
assist system procedures to distinguish between procedures where the 
device was only used intraoperatively and was removed at the conclusion 
of the procedure versus procedures where the device was not removed at 
the conclusion of the procedure and for which that qualifier would not 
be reported. We agreed with the commenters that continued monitoring of 
the data and further analysis was necessary prior to proposing any 
modifications to MS-DRG 215 and finalized our proposal to maintain the 
current structure of MS-DRG 215 for FY 2019.
    In the FY 2020 IPPS/LTCH PPS final rule (84 FR 42167) we discussed 
public comments on our proposals related to recalibration of the FY 
2020 relative weights and the changes in relative weights from FY 2019. 
Several commenters expressed concern about significant reductions to 
the relative weight for MS-DRG 215. Commenters stated that the 
reduction in the proposed relative weight was 29 percent, the largest 
decrease of any MS-DRG; commenters also noted that the cumulative 
decrease to the relative weight for MS-DRG 215 would be 43 percent 
since FY 2017. Commenters stated that the proposed relative weights 
would result in significant underpayments to facilities, which would in 
turn limit access to heart assist devices. After reviewing the comments 
received and the data used in our ratesetting calculations, we 
acknowledged an outlier circumstance where the weight for a MS-DRG was 
seeing a significant reduction for each of the 3 years since CMS began 
using the ICD-10 data in calculating the relative weights. Therefore, 
for the reasons discussed in the FY 2020 final rule, we adopted a 
temporary one-time measure for FY 2020 where the FY 2020 relative 
weight was set equal to the FY 2019 relative weight, which in turn had 
been set equal to the FY 2018 relative weight.
    In the FY 2021 IPPS/LTCH PPS final rule (85 FR 58598) we again 
acknowledged an outlier circumstance where the weight for MS-DRG 215 
was seeing a significant reduction for each of the 4 years since CMS 
began using the ICD-10 data in calculating the relative weights. We 
stated while we would ordinarily consider this weight change to be 
appropriately driven by the underlying data, given the comments 
received, and in an abundance of caution because this may be the MS-DRG 
assigned when a hospital provides temporary right ventricular support 
for

[[Page 44821]]

up to 14 days in critical care patients for the treatment of acute 
right heart failure or decompensation caused by complications related 
to COVID-19, including pulmonary embolism, we adopted a temporary one-
time measure for FY 2021 for MS-DRG 215. Specifically, we set the 2021 
relative weight for MS-DRG 215 equal to the average of the FY 2020 
relative weight and the otherwise applicable FY 2021 weight.
    For the FY 2022 IPPS/LTCH PPS proposed rule, we received a request 
to reassign certain cases reporting procedure codes describing the 
insertion of a percutaneous short-term external heart assist device 
from MS-DRG 215 to MS-DRGs 216, 217, and 218 (Cardiac Valve and Other 
Major Cardiothoracic Procedures with Cardiac Catheterization with MCC, 
with CC, and without CC/MCC, respectively). According to the requestor, 
there are two distinct clinical populations within MS-DRG 215: High-
risk Percutaneous Coronary Intervention (PCI) patients receiving short 
term ``intraoperative'' external heart assist systems where the device 
is only used intraoperatively and is removed at the conclusion of the 
procedure, and those patients in or at risk of cardiogenic shock 
requiring longer heart pump support and ICU stays. The requestor stated 
that cases in which short-term external heart assist systems are placed 
intraoperatively require fewer resources. The requestor suggested that 
moving the less resource intensive cases that report a procedure code 
that describes the intraoperative insertion of short-term external 
heart assist systems from MS-DRG 215 into MS-DRG 216, 217, and 218, 
will clinically align the two distinctly different patient populations, 
and consequently will address the potential decrease in the relative 
weight of MS-DRG 215.
    The requestor stated it performed its own analysis of claims in MS-
DRG 215 that involve the intraoperative insertion of a short-term 
external heart assist device (as identified by the presence of ICD-10-
PCS codes 02HA3RJ (Insertion of short-term external heart assist system 
into heart, intraoperative, percutaneous approach) and 5A0221D 
(Assistance with cardiac output using impeller pump, continuous). The 
requestor stated that its analysis found that if procedures involving 
intraoperative placement of a short-term external heart assist device 
were moved into MS-DRGs 216, 217 and 218, it would result in an 
increase in the average costs and average lengths of stay for the cases 
that would remain to be assigned to MS-DRG 215.
    As discussed in the proposed rule, during our review of this issue, 
we noted that when a patient is admitted and has an Impella[supreg] 
external heart assist device inserted two ICD-10-PCS codes are 
assigned: A code that describes the insertion of the device and code 
5A0221D that describes assistance with an impeller pump. Therefore, our 
analysis included procedure code 02HA3RJ as identified by the requestor 
as well as similar procedure codes 02HA0RJ (Insertion of short-term 
external heart assist system into heart, intraoperative, open approach) 
and 02HA4RJ (Insertion of short-term external heart assist system into 
heart, intraoperative, percutaneous endoscopic approach) that also 
describe the intraoperative insertion of a short-term heart assist 
device, differing only in approach. Because the assistance with an 
Impella[supreg] is coded with ICD-10-PCS code 5A0221D whether the 
device is used only intraoperatively or in instances where the device 
is left in place at the conclusion of the procedure, we did not include 
this code in our analysis. We also noted that the requestor suggested 
that the cases reporting a procedure code describing the intraoperative 
insertion of a short-term external heart assist device be moved to MS-
DRGs 216, 217 and 218 but these MS-DRGs are defined by the performance 
of cardiac catheterization. Therefore, we expanded our analysis to also 
include MS-DRGs 219, 220 and 221 (Cardiac Valve and Other Major 
Cardiothoracic Procedures without Cardiac Catheterization with MCC, 
with CC, and without CC/MCC, respectively).
    We stated in the FY 2022 IPPS/LTCH PPS proposed rule that first, we 
examined claims data from the March 2020 update of the FY 2019 MedPAR 
file for MS-DRG 215 to identify cases reporting ICD-10-PCS codes 
02HA0RJ, 02HA3RJ or 02HA4RJ and a procedure code describing the 
performance of a cardiac catheterization. Our findings are shown in the 
following table:
[GRAPHIC] [TIFF OMITTED] TR13AU21.021

    As shown in the table, we identified a total of 7,741 cases within 
MS-DRG 215 with an average length of stay of 7.8 days and average costs 
of $68,234. Of these 7,741 cases, there are 2,943 cases that include 
both a procedure code describing the intraoperative insertion of a 
short-term external heart assist device and a procedure code describing 
the performance of a cardiac catheterization with an average length of 
stay of 7.1 days and average costs of $60,449. Of these 2,943 cases, 
there are 23 cases reporting a procedure code describing the open 
intraoperative

[[Page 44822]]

insertion of a short-term external heart assist device with a procedure 
code describing the performance of a cardiac catheterization with an 
average length of stay of 8.9 days and average costs of $85,806. There 
are 2,904 cases reporting a procedure code describing a percutaneous 
intraoperative insertion of a short-term external heart assist device 
with a procedure code describing the performance of a cardiac 
catheterization with an average length of stay of 7.1 days and average 
costs of $60,227. There are 16 cases reporting a procedure code 
describing a percutaneous endoscopic intraoperative insertion of a 
short-term external heart assist device with a procedure code 
describing the performance of a cardiac catheterization approach with 
an average length of stay of 6.4 days and average costs of $64,217. The 
data analysis shows that for the cases in MS-DRG 215 reporting ICD-10-
PCS codes 02HA0RJ, 02HA3RJ or 02HA4RJ with a procedure code describing 
the performance of a cardiac catheterization, generally, the average 
length of stay is shorter and the average costs are lower than the 
average length of stay and average costs (with the exception of the 
average costs and length of stay for the 23 cases reporting a procedure 
code describing the open intraoperative insertion of a short-term 
external heart assist device with a procedure code describing the 
performance of a cardiac catheterization which are higher) compared to 
all cases in that MS-DRG.
    In the proposed rule, we indicated that we also examined claims 
data from the March 2020 update of the FY 2019 MedPAR file for MS-DRGs 
216, 217 and 218. Our findings are shown in the following table.
[GRAPHIC] [TIFF OMITTED] TR13AU21.022

    Because MS-DRG 215 is a base DRG and there is a three-way split 
within MS-DRGs 216, 217, and 218, we indicated that we also analyzed 
the cases reporting a procedure code describing the intraoperative 
insertion of a short-term external heart assist device with a procedure 
code describing the performance of a cardiac catheterization for the 
presence or absence of a secondary diagnosis designated as a 
complication or comorbidity (CC) or a major complication or comorbidity 
(MCC).
[GRAPHIC] [TIFF OMITTED] TR13AU21.023

    This data analysis shows the cases in MS-DRG 215 reporting ICD-10-
PCS codes 02HA0RJ, 02HA3RJ or 02HA4RJ with a procedure code describing 
the performance of a cardiac catheterization when distributed based on 
the presence or absence of a secondary diagnosis designated as a 
complication or comorbidity (CC) or a major complication or comorbidity 
(MCC) have average costs generally more similar to the average costs in 
the FY 2019 MedPAR file for MS-DRGs 216, 217 and 218 respectively, 
while the average lengths of stay are shorter. While the cases from MS-
DRG 215 reporting a procedure code describing the intraoperative 
insertion of a short-term external heart assist device with a procedure 
code describing the performance of a cardiac catheterization ``with 
CC'' and ``without CC/MCC'' have higher average costs than the average 
costs of MS-DRGs 217 and 218, these costs are closer to the average 
costs of those MS-DRGs than they are to the average costs of MS-DRG 
215. The average costs of the cases from MS-DRG 215 reporting a 
procedure code describing the intraoperative insertion of a short-term 
external heart assist device with a procedure code describing the 
performance of a cardiac catheterization ``with MCC'' are lower than 
the average costs of both MS-DRGs 215 and 216.
    Next, we examined claims data from the March 2020 update of the FY 
2019 MedPAR file for MS-DRG 215 to identify cases reporting ICD-10-PCS 
codes 02HA0RJ, 02HA3RJ or 02HA4RJ without a procedure code describing 
the performance of a cardiac catheterization. Our findings are shown in 
the following table:

[[Page 44823]]

[GRAPHIC] [TIFF OMITTED] TR13AU21.024

    As shown in the table, of the 7,741 cases within MS-DRG 215, there 
are 432 cases that include a procedure code describing the 
intraoperative insertion of a short-term external heart assist device 
without a procedure code describing the performance of a cardiac 
catheterization with an average length of stay of 4.8 days and average 
costs of $53,607. Of these 432 cases, there are eight cases reporting a 
procedure code describing the open intraoperative insertion of a short-
term external heart assist device without a procedure code describing 
the performance of a cardiac catheterization with an average length of 
stay of 8.8 days and average costs of $141,242. There are 423 cases 
reporting a procedure code describing a percutaneous intraoperative 
insertion of a short-term external heart assist device without a 
procedure code describing the performance of a cardiac catheterization 
with an average length of stay of 4.7 days and average costs of 
$51,964. There is one case reporting a procedure code describing a 
percutaneous endoscopic intraoperative insertion of a short-term 
external heart assist device without a procedure code describing the 
performance of a cardiac catheterization approach with a length of stay 
of 2 days and costs of $47,289. We noted that the data analysis shows 
that for the cases in MS-DRG 215 reporting ICD-10-PCS codes 02HA0RJ, 
02HA3RJ or 02HA4RJ without a procedure code describing the performance 
of a cardiac catheterization, generally, the average length of stay is 
shorter and the average costs are lower than the average length of stay 
and average costs (with the exception of the average costs and length 
of stay for the eight cases describing the open intraoperative 
insertion of a short-term external heart assist device without a 
procedure code describing the performance of a cardiac catheterization 
which are higher) compared to all cases in that MS-DRG.
    We also examined claims data from the March 2020 update of the FY 
2019 MedPAR file for MS-DRGs 219, 220 and 221. Our findings are shown 
in the following table.
[GRAPHIC] [TIFF OMITTED] TR13AU21.025

    Similarly, because MS-DRG 215 is a base DRG and there is a three-
way split within MS-DRGs 219, 220 and 221, we stated that we also 
analyzed the cases reporting a procedure code describing the 
intraoperative insertion of a short-term external heart assist device 
without a procedure code describing the performance of a cardiac 
catheterization for the presence or absence of a secondary diagnosis 
designated as a complication or comorbidity (CC) or a major 
complication or comorbidity (MCC).

[[Page 44824]]

[GRAPHIC] [TIFF OMITTED] TR13AU21.026

    We indicated in the proposed rule that this data analysis shows the 
cases in MS-DRG 215 reporting ICD-10-PCS codes 02HA0RJ, 02HA3RJ or 
02HA4RJ without a procedure code describing the performance of a 
cardiac catheterization when distributed based on the presence or 
absence of a secondary diagnosis designated as a complication or 
comorbidity (CC) or a major complication or comorbidity (MCC) have 
average costs generally more similar to the average costs in the FY 
2019 MedPAR file for MS-DRGs 219, 220 and 221 respectively, while the 
average lengths of stay are shorter. While the cases from MS-DRG 215 
reporting a procedure code describing the intraoperative insertion of a 
short-term external heart assist device, without a procedure code 
describing the performance of a cardiac catheterization ``with MCC'', 
``with CC'' and ``without CC/MCC'' have higher average costs than the 
average costs MS-DRGs 219, 220 and 221, respectively, these costs are 
closer to the average costs of those MS-DRGs than they are to the 
average costs of MS-DRG 215.
    We also examined claims data from the September 2020 update of the 
FY 2020 MedPAR file for MS-DRG 215 to identify cases reporting ICD-10-
PCS codes 02HA0RJ, 02HA3RJ or 02HA4RJ with a procedure code describing 
the performance of a cardiac catheterization. Our findings are shown in 
the following table:
[GRAPHIC] [TIFF OMITTED] TR13AU21.027

    As shown in the table, we identified a total of 6,275 cases within 
MS-DRG 215 with an average length of stay of 7.9 days and average costs 
of $72,144. Of these 6,275 cases, there are 2,395 cases that include 
both a procedure code describing the intraoperative insertion of a 
short-term external heart assist device and a procedure code describing 
the performance of a cardiac catheterization with an average length of 
stay of 6.8 days and average costs of $62,260. Of these 2,395 cases, 
there were 25 cases reporting a procedure code describing the open 
intraoperative insertion of a short-term external heart assist device 
with a procedure code describing the performance of a cardiac 
catheterization with an average length of stay of 8.2 days and average 
costs of $85,954. There are 2,360 cases reporting a procedure code 
describing a percutaneous intraoperative insertion of a short-term 
external heart assist device with a procedure code describing the 
performance of a cardiac catheterization with an average length of stay 
of 6.8 days and average costs of $61,965. There are 10 cases reporting 
a procedure code describing a percutaneous endoscopic intraoperative 
insertion of a short-term external heart assist device with a procedure 
code describing the performance of a cardiac catheterization approach 
with an average length of stay of 6.9 days and average costs of 
$72,564. The data analysis shows that for the cases in MS-DRG 215 
reporting ICD-10-PCS codes 02HA0RJ, 02HA3RJ or

[[Page 44825]]

02HA4RJ with a procedure code describing the performance of a cardiac 
catheterization, when examined collectively, the average length of stay 
is shorter (6.8 days versus 7.9 days) and the average costs are lower 
($62,260 versus $72,144) than the average length of stay and average 
costs (of all cases in that MS-DRG). We noted there were some 
differences noted in cases reporting a procedure code describing the 
intraoperative insertion of a short-term external heart assist device 
with a procedure code describing the performance of a cardiac 
catheterization when examined by operative approach. For the 25 cases 
reporting a procedure code describing the open intraoperative insertion 
of a short-term external heart assist device with a procedure code 
describing the performance of a cardiac catheterization, the average 
costs were higher ($85,954 versus $72,144) and average length of stay 
was slightly longer (8.2 days versus 7.9 days) when compared to all 
cases in that MS-DRG. For the 10 cases reporting a procedure code 
describing the percutaneous endoscopic intraoperative insertion of a 
short-term external heart assist device with a procedure code 
describing the performance of a cardiac catheterization, the average 
costs were nearly equal ($72,564 versus $72,144) and average length of 
stay was shorter (6.9 days versus 7.9 days) when compared to all cases 
in that MS-DRG.
    We also examined claims data from the September 2020 update of the 
FY 2020 MedPAR file for MS-DRGs 216, 217 and 218. Our findings are 
shown in the following table.
[GRAPHIC] [TIFF OMITTED] TR13AU21.028

    Because MS-DRG 215 is a base DRG and there is a three-way split 
within MS-DRGs 216, 217, and 218, we also analyzed the cases reporting 
a procedure code describing the intraoperative insertion of a short-
term external heart assist device with a procedure code describing the 
performance of a cardiac catheterization for the presence or absence of 
a secondary diagnosis designated as a complication or comorbidity (CC) 
or a major complication or comorbidity (MCC).
[GRAPHIC] [TIFF OMITTED] TR13AU21.029

    This data analysis shows the cases in MS-DRG 215 reporting ICD-10-
PCS codes 02HA0RJ, 02HA3RJ or 02HA4RJ with a procedure code describing 
the performance of a cardiac catheterization when distributed based on 
the presence or absence of a secondary diagnosis designated as a 
complication or comorbidity (CC) or a major complication or comorbidity 
(MCC) have average costs generally more similar to the average costs in 
the FY 2020 MedPAR file for MS-DRGs 216, 217 and 218 respectively, 
while the average lengths of stay are shorter. While the cases from MS-
DRG 215 reporting a procedure code describing the intraoperative 
insertion of a short-term external heart assist device with a procedure 
code describing the performance of a cardiac catheterization ``with 
CC'' and ``without CC/MCC'' have higher average costs than the average 
costs of MS-DRGs 217 and 218, these costs are closer to the average 
costs of those MS-DRGs than they are to the average costs of MS-DRG 
215. The average costs of the cases from MS-DRG 215 reporting a 
procedure code describing the intraoperative insertion of a short-term 
external heart assist device with a procedure code describing the 
performance of a cardiac catheterization ``with MCC'' are lower than 
the average costs of both MS-DRGs 215 and 216.
    Next, we examined claims data from the September 2020 update of the 
FY 2020 MedPAR file for MS-DRG 215 to identify cases reporting ICD-10-
PCS codes 02HA0RJ, 02HA3RJ or 02HA4RJ without a procedure code 
describing the performance of a cardiac catheterization. Our findings 
are shown in the following table:

[[Page 44826]]

[GRAPHIC] [TIFF OMITTED] TR13AU21.030

    As shown in the table, of the 6,275 cases within MS-DRG 215, there 
are 331 cases that include a procedure code describing the 
intraoperative insertion of a short-term external heart assist device 
without a procedure code describing the performance of a cardiac 
catheterization with an average length of stay of 4.5 days and average 
costs of $52,181. Of these 331 cases, there are eight cases reporting a 
procedure code describing the open intraoperative insertion of a short-
term external heart assist device without a procedure code describing 
the performance of a cardiac catheterization with an average length of 
stay of 8.9 days and average costs of $80,314. There are 332 cases 
reporting a procedure code describing a percutaneous intraoperative 
insertion of a short-term external heart assist device without a 
procedure code describing the performance of a cardiac catheterization 
with an average length of stay of 4.4 days and average costs of 
$51,569. There is one case reporting a procedure code describing a 
percutaneous endoscopic intraoperative insertion of a short-term 
external heart assist device without a procedure code describing the 
performance of a cardiac catheterization approach with a length of stay 
of 2 days and costs of $24,379. The data analysis shows that for the 
cases in MS-DRG 215 reporting ICD-10-PCS codes 02HA0RJ, 02HA3RJ or 
02HA4RJ without a procedure code describing the performance of a 
cardiac catheterization, generally, the average length of stay is 
shorter and the average costs are lower than the average length of stay 
and average costs (with the exception of the average costs and length 
of stay for the eight cases reporting a procedure code describing the 
open intraoperative insertion of a short-term external heart assist 
device without a procedure code describing the performance of a cardiac 
catheterization which are higher) compared to all cases in that MS-DRG.
    We also examined claims data from the September 2020 update of the 
FY 2020 MedPAR file for MS-DRGs 219, 220 and 221. Our findings are 
shown in the following table.
[GRAPHIC] [TIFF OMITTED] TR13AU21.031

    Similarly, because MS-DRG 215 is a base DRG and there is a three-
way split within MS-DRGs 219, 220 and 221, we also analyzed the 331 
cases reporting a procedure code describing the intraoperative 
insertion of a short-term external heart assist device without a 
procedure code describing the performance of a cardiac catheterization 
for the presence or absence of a secondary diagnosis designated as a 
complication or comorbidity (CC) or a major complication or comorbidity 
(MCC).

[[Page 44827]]

[GRAPHIC] [TIFF OMITTED] TR13AU21.032

    This data analysis shows the cases in MS-DRG 215 reporting ICD-10-
PCS codes 02HA0RJ, 02HA3RJ or 02HA4RJ without a procedure code 
describing the performance of a cardiac catheterization when 
distributed based on the presence or absence of a secondary diagnosis 
designated as a complication or comorbidity (CC) or a major 
complication or comorbidity (MCC) have average costs generally more 
similar to the average costs in the FY 2020 MedPAR file for MS-DRGs 
219, 220 and 221 respectively, while the average lengths of stay are 
shorter. While the cases from MS-DRG 215 reporting a procedure code 
describing the intraoperative insertion of a short-term external heart 
assist device without a procedure code describing the performance of a 
cardiac catheterization ``with CC'' and ``without CC/MCC'' have higher 
average costs than the average costs of MS-DRGs 220 and 221, these 
costs are closer to the average costs of those MS-DRGs than they are to 
the average costs of MS-DRG 215. The average costs of the cases from 
MS-DRG 215 reporting a procedure code describing the intraoperative 
insertion of a short-term external heart assist device without a 
procedure code describing the performance of a cardiac catheterization 
``with MCC'' are lower than the average costs of both MS-DRGs 215 and 
219.
    We indicated in the proposed rule that our clinical advisors 
reviewed the clinical issues and the claims data and agreed that cases 
reporting a procedure code that describes the intraoperative insertion 
of a short-term external heart assist device are generally less 
resource intensive and are clinically distinct from other cases 
reporting procedure codes describing the insertion of other types of 
heart assist devices currently assigned to MS-DRG 215. Our clinical 
advisors stated that critically ill patients who are experiencing or at 
risk for cardiogenic shock from an emergent event such as heart attack 
or virus that impacts the functioning of the heart and requires longer 
heart pump support are different from those patients who require 
intraoperative support only. Patients receiving a short-term external 
heart assist device intraoperatively during coronary interventions 
often have an underlying disease pathology such as heart failure 
related to occluded coronary vessels that is broadly similar in kind to 
other patients also receiving these interventions without the need for 
an insertion of a short-term external heart assist device. In the post-
operative period, these patients can recover and can be sufficiently 
rehabilitated prior to discharge. For these reasons, we indicated our 
clinical advisors supported reassigning ICD-10-PCS codes 02HA0RJ, 
02HA3RJ, and 02HA4RJ that describe the intraoperative insertion of a 
short-term external heart assist device to MS-DRGs 216, 217, 218, 219, 
220 and 221 in MDC 05. They stated this reassignment would improve 
clinical coherence in these MS-DRGs.
    To compare and analyze the impact of our suggested modifications, 
we ran a simulation using the Version 38.1 ICD-10 MS-DRG GROUPER and 
the claims data from the March 2020 update of the FY 2019 MedPAR file. 
The following table reflects our simulation for ICD-10-PCS procedure 
codes 02HA0RJ, 02HA3RJ or 02HA4RJ that describe the intraoperative 
insertion of a short-term external heart assist device if they were 
moved to MS-DRGS 216, 217, 218, 219, 220 and 221.

[[Page 44828]]

[GRAPHIC] [TIFF OMITTED] TR13AU21.033

    We stated in the proposed rule that we believe the resulting 
proposed MS-DRG assignments would be more clinically homogeneous, 
coherent and better reflect hospital resource use while at the same 
time addressing concerns related to the relative weight of MS-DRG 215. 
A review of this simulation shows that this distribution of ICD-10-PCS 
codes 02HA0RJ, 02HA3RJ or 02HA4RJ that describe the intraoperative 
insertion of a short-term external heart assist device if moved to MS-
DRGs 216, 217, 218, 219, 220 and 221, increases the average costs of 
the cases remaining in MS-DRG 215 by over $4,500, while generally 
having a more limited effect on the average costs of MS-DRGs 216, 217, 
218, 219, 220 and 221.
    We also ran a simulation using the Version 38.1 ICD-10 MS-DRG 
GROUPER and the claims data from the September 2020 update of the FY 
2020 MedPAR file. The following table reflects our simulation for ICD-
10-PCS procedure codes 02HA0RJ, 02HA3RJ or 02HA4RJ that describe the 
intraoperative insertion of a short-term external heart assist device 
if they were moved to MS-DRGS 216, 217, 218, 219, 220 and 221.

[[Page 44829]]

[GRAPHIC] [TIFF OMITTED] TR13AU21.034

    As with our simulation based on the March 2020 update of the FY 
2019 MedPAR file, we indicated we believe that this simulation supports 
that the resulting proposed MS-DRG assignments would be more clinically 
homogeneous, coherent and better reflect hospital resource use while at 
the same time addressing concerns related to the relative weight of MS-
DRG 215. We noted that a review of this simulation shows that this 
distribution of ICD-10-PCS codes 02HA0RJ, 02HA3RJ or 02HA4RJ that 
describe the intraoperative insertion of a short-term external heart 
assist device if moved to MS-DRGs 216, 217, 218, 219, 220 and 221, 
increases the average costs of the cases remaining in MS-DRG 215 by 
over $6,000, while generally having a more limited effect on the 
average costs of MS-DRGS 216, 217, 218, 219, 220 and 221.
    Therefore, for FY 2022, we proposed to reassign ICD-10-PCS codes 
02HA0RJ, 02HA3RJ, and 02HA4RJ from MDC 05 in MS-DRG 215 to MS-DRGs 216, 
217, 218, 219, 220 and 221 in MDC 05.
    Comment: Commenters supported the proposal to reassign ICD-10-PCS 
codes 02HA0RJ, 02HA3RJ, and 02HA4RJ from MDC 05 in MS-DRG 215. These 
commenters stated they appreciated CMS' attention, careful review and 
efforts to create more long-term stability for heart assist devices, a 
life-saving technology. Some commenters stated CMS' actions will create 
a more clinically balanced structure for hospital payments for patients 
needing short-term external heart assist device support. Commenters 
stated that this reassignment will better reflect hospital resource 
utilization creating a more clinically homogenous coherent structure 
for acute patients that require intraoperative support of a short-term 
external heart assist device. A commenter stated this reassignment 
would also result in a relative weight for MS-DRG 215 that more 
accurately reflects the resource utilization of the procedures within 
that MS-DRG, as well as stabilizing the relative weight for MS-DRG 215, 
which has fluctuated over the last few years. Another commenter 
acknowledged intraoperative cases require fewer hospital resources 
during their admission than all other cases in MS-DRG 215 and stated 
removing ICD-10-PCS codes 02HA0RJ, 02HA3RJ, and 02HA4RJ describing 
intraoperative use from MS-DRG 215 maintains appropriate payment for 
longer term circulatory support, such as cardiogenic shock patients, 
who require more intensive resource use.
    Response: We thank the commenters for their support.
    Comment: Other commenters opposed CMS' proposal to reassign the 
short-term heart assist device ICD-10-PCS codes 02HA0RJ, 02HA3RJ, and 
02HA4RJ from MDC 05 in MS-DRG 215 to MS-DRGs 216, 217, 218, 219, 220 
and 221 in MDC 05. Some commenters urged CMS to reconsider the proposal 
regarding short-term external heart assist devices and leave procedure 
codes 02HA0RJ, 02HA3RJ, and 02HA4RJ in MS-DRG 215 where they are 
currently assigned. These commenters noted patients requiring 
intraoperative short-term external heart assist devices tend to be more 
severely ill and stated the proposal does not fully consider the 
complexity of care required for these patients and the associated 
resource utilization, in terms of the need for additional length of 
stay and monitoring. A commenter stated short-term external heart 
assist systems, require high resources consumption evidenced by 
critical care management, expensive drugs and tests; and specialized 
clinical staff such as: Physicians, nursing, perfusionists, etc. 
Another commenter stated they believe there may be hospital-specific 
differences with some facilities performing the diagnostic cardiac 
catheterizations as outpatient services prior to the inpatient 
admission for the other cardiothoracic procedures. A commenter 
expressed concern about the impact this change would have related to 
the increased use of the external heart assist devices and resources 
required to insert the device, including the cost of the device. This 
commenter stated an estimated 50% of the cases at their facility 
involving a short-term heart assist device would fall into a CC or 
NonCC category under the proposed MS-DRG change in spite of the fact 
the patients who require this device are at higher risk, which would 
mean that approximately 50% of their Medicare payment would be 
allocated to the cost

[[Page 44830]]

of the device itself. This commenter stated that an even greater 
negative financial impact may be recognized as there has been an 
increase in the use of Impella[supreg] devices due to higher incidence 
of advanced ischemic cardiomyopathy because of the COVID-19 pandemic 
and delays in treatment.
    Another commenter requested that CMS consider re-evaluation once 
the MedPAR data are normalized from the pandemic to consider structure 
revisions for these MS-DRGs. This commenter noted that there is a 
proposed relative weight reduction from 11.1579 to 10.5614 for MS- DRG 
215 even though CMS proposed to move the intraoperative short-term 
heart assist devices from this MS-DRG. This commenter stated this 
reduction does not seem appropriate especially if the proposed MS-DRG 
changes are finalized.
    Response: We thank the commenters for their feedback. Our clinical 
advisors have reviewed these concerns regarding the proposed 
reassignment and continue to state the resulting MS-DRG assignments, as 
proposed, would be more clinically homogeneous, coherent and better 
reflect hospital resource use because cases reporting a procedure code 
that describes the intraoperative insertion of a short-term external 
heart assist device are generally less resource intensive and are 
clinically distinct from other cases reporting procedure codes 
describing the insertion of other types of heart assist devices 
currently assigned to MS-DRG 215. Our clinical advisors acknowledge 
that while the need to have a short term heart assist device inserted 
can reflect on the severity of illness of the patient being treated, 
critically ill patients who are experiencing or at risk for cardiogenic 
shock from an emergent event such as heart attack or virus that impacts 
the functioning of the heart and require longer heart pump support and 
ICU stays are different from those patients who require intraoperative 
support only where the device is removed at the conclusion of the 
procedure. As additional claims data become available, we will continue 
to analyze the clinical nature of each of the procedures describing the 
insertion of short-term heart assist devices and their MS-DRG 
assignments to further improve the overall accuracy of the IPPS 
payments in future rulemaking.
    Comment: While indicating their support of CMS' proposal, some 
commenters urged CMS to refrain from moving cases reporting a procedure 
code describing the intraoperative insertion of a short-term external 
heart assist device into MS-DRG 219, 220, and 221. These commenters 
stated the cases should be assigned to MS-DRGs 216, 217 and 218 only, 
based on the presence or absence of a secondary diagnosis designated as 
a complication or comorbidity (CC) or a major complication or 
comorbidity (MCC). A few commenters stated that CMS should refrain from 
moving cases into MS-DRG 219, 220, or 221 because the claim volume of 
cases reporting a procedure code describing the intraoperative 
insertion of a short-term external heart assist device without a 
procedure code describing a cardiac catherization is under five hundred 
and intracardiac heart assist devices, such as Impella[supreg] devices 
require the use of diagnostic catheters, fluoroscopy, and hemodynamic 
monitoring during use, all resulting in higher costs. Considering the 
types of procedures that utilize short term circulatory support and the 
techniques used by these circulatory support devices, these commenters 
stated cases reporting a procedure code describing the intraoperative 
insertion of a short-term external heart assist device are comparable 
to those mapping to MS-DRG 216, 217 and 218, even when a cardiac 
catherization procedure is not performed. Other commenters asserted 
there are known coding and documentation issues seen with this complex 
therapy, without providing examples of these issues, and stated that 
reassigning ICD-10-PCS codes 02HA0RJ, 02HA3RJ, and 02HA4RJ to MS-DRGs 
219, 220, and 221, described as ``without cardiac catheterization'' may 
lead to coding errors since the vast majority of these procedures 
necessitate a cardiac catheterization.
    Response: We note that the requestor originally suggested that the 
cases reporting a procedure code describing the intraoperative 
insertion of a short-term external heart assist device be moved to MS-
DRGs 216, 217 and 218 but because these MS-DRGs are defined by the 
performance of cardiac catheterization, we specifically expanded our 
analysis to also include MS-DRGs 219, 220 and 221 (Cardiac Valve and 
Other Major Cardiothoracic Procedures without Cardiac Catheterization 
with MCC, with CC, and without CC/MCC, respectively). We do not believe 
it would be appropriate to assign all cases to the ``with cardiac 
catheterization'' MS-DRGs because the claims data would not reflect the 
additional resources associated with the performance of a cardiac 
catheterization in cases reporting a procedure code describing the 
intraoperative insertion of a short-term external heart assist device.
    As presented in the proposed rule and in this final rule, the data 
analysis performed show in both in the FY 2019 MedPAR file and the FY 
2020 MedPAR file, the average length of stay is shorter and the average 
costs are lower in cases reporting a procedure code describing the 
intraoperative insertion of a short-term external heart assist device 
without the performance of a cardiac catheterization when compared to 
cases reporting a procedure code describing the intraoperative 
insertion of a short-term external heart assist device with the 
performance of a cardiac catheterization when analyzed for the presence 
or absence of a secondary diagnosis designated as a complication or 
comorbidity (CC) or a major complication or comorbidity (MCC).
    Our clinical advisors believe that continued monitoring of the data 
and further analysis is needed prior to proposing any additional 
modifications to the MS-DRG assignment of cases reporting ICD-10-PCS 
codes 02HA0RJ, 02HA3RJ or 02HA4RJ without a procedure code describing 
the performance of a cardiac catheterization. Our clinical advisors 
believe maintaining the distinction between the performance of or lack 
of a cardiac catherization procedure is important in these subsets of 
cases as we continue to examine the volume and length of stay as well 
as considering a variety of factors pertaining to resource consumption 
and clinical characteristics that might account for differences in 
resource use before determining if additional modifications to the 
assignment of these procedure codes are warranted.
    In response to the suggestion that we refrain from moving cases 
into MS-DRG 219, 220, or 221 because claim volume of cases reporting a 
procedure code describing the intraoperative insertion of a short-term 
external heart assist device without a procedure code describing a 
cardiac catherization is low, we do not believe moving this subset of 
cases into an incoherent grouping simply because the case volume is low 
is in keeping with our goal to maintain clinically coherent groups that 
also more accurately stratify Medicare patients with varying levels of 
severity.
    Similarly, in response to the comments asserting that there are 
known coding and documentation issues seen with this complex therapy 
and that reassigning ICD-10-PCS codes 02HA0RJ, 02HA3RJ, and 02HA4RJ to 
MS-DRGs 219, 220, and 221, described as ``without cardiac 
catheterization'' may lead to coding errors since the vast majority of 
these procedures necessitate

[[Page 44831]]

a cardiac catheterization, we again do not believe moving cases into an 
MS-DRG because of the need for improved provider documentation or any 
additional coder instruction is in keeping with our goal to maintain 
clinically coherent groups that also more accurately stratify Medicare 
patients with varying levels of severity. We acknowledge that accurate 
coding of external heart assist devices has been the subject of 
confusion in the past, and we will continue to monitor the claims data 
for these procedures. As one of the four Cooperating Parties, we also 
will continue to collaborate with the American Hospital Association to 
provide guidance for coding external heart assist devices through the 
Coding Clinic for ICD-10-CM/PCS publication and to review the ICD-10-
PCS guidelines to determine where further clarifications may be made.
    Therefore, after consideration of the public comments we received, 
and for reasons stated previously, we are finalizing our proposal to 
reassign ICD-10-PCS codes 02HA0RJ, 02HA3RJ, and 02HA4RJ from MDC 05 in 
MS-DRG 215 to MS-DRGs 216, 217, 218, 219, 220 and 221 in MDC 05, 
without modification, effective October 1, 2021.
b. Type II Myocardial Infarction
    In the FY 2022 IPPS/LTCH PPS proposed rule (86 FR 25115 through 
25116), we discussed a request we received to review the MS-DRG 
assignment of ICD-10-CM diagnosis code I21.A1 (Myocardial infarction 
type 2). The requestor stated that when a type 2 myocardial infarction 
is documented, per coding guidelines, it is to be coded as a secondary 
diagnosis since it is due to an underlying cause. This requestor also 
noted that when a type 2 myocardial infarction is coded with a 
principal diagnosis in MDC 05 (Diseases and Disorders of the 
Circulatory System), the GROUPER logic assigns MS-DRGs 280 through 282 
(Acute Myocardial Infarction, Discharged Alive with MCC, with CC, and 
without CC/MCC, respectively). The requestor questioned if this GROUPER 
logic was correct or if the logic should be changed so that a type 2 
myocardial infarction, coded as a secondary diagnosis, does not result 
in the assignment of a MS-DRG that describes an acute myocardial 
infarction.
    As discussed in the proposed rule, to begin our analysis, we 
reviewed the GROUPER logic. We noted that the requestor is correct that 
when diagnosis code I21.A1 is reported as a secondary diagnosis in 
combination with a principal diagnosis in MDC 05, the case currently 
groups to medical MS-DRGs 280 through 282 in the absence of a surgical 
procedure, when the patient is discharged alive. We also noted that if 
the patient expires, GROUPER logic instead will assign MS-DRGs 283 
through 285 (Acute Myocardial Infarction, Expired with MCC, with CC, 
and without CC/MCC, respectively) when diagnosis code I21.A1 is 
reported as a secondary diagnosis in combination with a principal 
diagnosis in MDC 05.
    According to the Universal Definition of Myocardial Infarction 
(MI), developed by a global task force that included the European 
Society of Cardiology, the American College of Cardiology, the American 
Heart Association and the World Heart Federation (WHF), the diagnosis 
of MI requires the rise and/or fall of cardiac biomarkers with clinical 
evidence of ischemia in which there is evidence of myocardial injury or 
necrosis, defined by symptoms, electrocardiographic (ECG) changes, or 
new regional wall motion abnormalities. Since 2007, this definition 
further classifies myocardial infarctions into five distinct subtypes. 
While a type 1 MI is defined as a MI due to an acute coronary syndrome, 
type 2 MI is defined as a mismatch in myocardial oxygen supply and 
demand due to other causes such as coronary dissection, vasospasm, 
emboli, or hypotension that is not attributed to unstable coronary 
artery disease (CAD).
    We indicated in the proposed rule that our clinical advisors 
reviewed this issue and did not recommend changing the current MS-DRG 
assignment of ICD-10-CM diagnosis code I21.A1. As noted by the 
requestor, the ICD-10-CM Official Guidelines for Coding and Reporting 
state ``Type 2 myocardial infarction, (myocardial infarction due to 
demand ischemia or secondary to ischemic imbalance) is assigned to code 
I21.A1, Myocardial infarction type 2 with a code for the underlying 
cause coded first.'' We indicated our clinical advisors believed that 
cases reporting diagnosis code I21.A1 as a secondary diagnosis are 
associated with a severity of illness on par with cases reporting a 
principal diagnosis of another type myocardial infarction. They stated 
the diagnosis of myocardial infarction describes myocardial cell death 
due to inadequate oxygen supply to the myocardium for a prolonged 
period, regardless of the subtype. Our clinical advisors further 
stated, for clinical consistency, it is more appropriate to maintain 
the current assignment of ICD-10-CM diagnosis code I21.A1 with the 
other codes that describe myocardial infarction. Therefore, we did not 
propose to reassign diagnosis code I21.A1 from MS-DRGs 280 through 285.
    As discussed in the proposed rule, during our review of this issue 
we also noted that code I21.A1 (Myocardial infarction type 2) is 
currently one of the listed principal diagnoses in the GROUPER logic 
for MS-DRGs 222 and 223 (Cardiac Defibrillator Implant with Cardiac 
Catheterization with AMI, HF or Shock with and without MCC, 
respectively). However, code I21.A1 is not currently recognized in 
these same MS-DRGs when coded as a secondary diagnosis. As a result, 
when coded as a secondary diagnosis in combination with a principal 
diagnosis in MDC 05, MS-DRGs 224 and 225 (Cardiac Defibrillator Implant 
with Cardiac Catheterization without AMI, HF, or Shock with and without 
MCC, respectively) are instead assigned when reported with a listed 
procedure code. We referred the reader to the ICD-10 MS-DRG Definitions 
Manual Version 38.1, which is available via the internet on the CMS 
website at: https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/AcuteInpatientPPS/MS-DRG-Classifications-and-Software for 
complete documentation of the GROUPER logic for MS-DRGs 222, 223, 224, 
and 225.
    Acknowledging that coding guidelines instruct to code I21.A1 after 
the diagnosis code that describes the underlying cause, we indicated 
our clinical advisors recommended adding special logic in MS-DRGs 222 
and 223 to have code I21.A1 also qualify when coded as a secondary 
diagnosis in combination with a principal diagnosis in MDC 05 since 
these diagnosis code combinations also describe acute myocardial 
infarctions.
    As a result, we proposed modifications to the GROUPER logic to 
allow cases reporting diagnosis code I21.A1 (Myocardial infarction type 
2) as a secondary diagnosis to group to MS-DRGs 222 and 223 when 
reported with a listed procedure code for clinical consistency with the 
other MS-DRGs describing acute myocardial infarction.
    A diagnosis code may define the logic for a specific MS-DRG 
assignment in three different ways. The diagnosis code may be listed as 
principal or as any one of the secondary diagnoses, as a secondary 
diagnosis, or only as a secondary diagnosis as noted in more detail in 
the proposed rule and this final rule.
     Principal or secondary diagnoses. Indicates that a 
specific set of diagnoses are used in the definition of the MS-DRG. The 
diagnoses may be listed as principal or as any one of the secondary 
diagnoses. A special case of this condition is MS-DRG 008 in which two

[[Page 44832]]

diagnoses (for example, renal and diabetic) must both be present 
somewhere in the list of diagnoses in order to be assigned to MS-DRG 
008.
     Secondary diagnoses. Indicates that a specific set of 
secondary diagnoses are used in the definition of the MS-DRG. For 
example, a secondary diagnosis of acute leukemia with chemotherapy is 
used to define MS-DRG 839.
     Only secondary diagnoses. Indicates that in order to be 
assigned to the specified MS-DRG no secondary diagnoses other than 
those in the specified list may appear on the patient's record. For 
example, in order to be assigned to MS-DRG 795, only secondary 
diagnoses from the specified list may appear on the patient's record.
    We noted in the proposed rule that whenever there is a secondary 
diagnosis component to the MS-DRG logic, the diagnosis code can either 
be used in the logic for assignment to the MS-DRG or to act as a CC/
MCC. For this specific scenario, we proposed that code I21.A1, as a 
secondary diagnosis, be used in the definition of the logic for 
assignment to MS-DRGs 222 and 223, similar to the example described 
previously, where a secondary diagnosis of acute leukemia with 
chemotherapy is used to define MS-DRG 839, and therefore will not act 
as an MCC in these MS-DRGs.
    In summary, for FY 2022, we proposed to maintain the current 
structure of MS-DRGs 280 through 285. We proposed to modify the GROUPER 
logic to allow cases reporting diagnosis code I21.A1 (Myocardial 
infarction type 2) as a secondary diagnosis to group to MS-DRGs 222 and 
223 when reported with qualifying procedures.
    Comment: A commenter agreed with CMS' proposed modifications to the 
GROUPER logic to allow cases reporting diagnosis code I21.A1 
(Myocardial infarction type 2) as a secondary diagnosis to group to MS-
DRGs 222 and 223 (Cardiac Defibrillator Implant with Cardiac 
Catheterization with AMI, HF or Shock with and without MCC, 
respectively) when reported with qualifying procedures. This commenter 
stated they agreed that coding rules stipulate that diagnosis code 
I21.A1 must be reported as a secondary diagnosis.
    Response: We appreciate the commenters' support.
    Comment: Other commenters expressed concern with CMS' proposal. A 
commenter stated that they believed it is inappropriate to include 
cases with diagnosis code I21.A1 in the MS-DRGs that describe an acute 
myocardial infarction (MS-DRGs 280 through 285). The commenter 
expressed concern that if cases reporting diagnosis code I21.A1 are 
assigned to the MS-DRGs that describe an acute myocardial infarction, 
this would disrupt the resource accuracy of these MS-DRGs. They stated 
from a clinical perspective, the pattern of care for patients with type 
2 MI may vary considerably compared to the treatment of patients with 
other types of myocardial infarctions, namely Type 1 STEMI and Type 1 
NSTEMI. This commenter however, agreed with the proposal to modify the 
GROUPER logic to allow cases reporting diagnosis code I21.A1 as a 
secondary diagnosis to group to MS-DRGs 222 and 223 when reported with 
qualifying procedures and stated this portion of the proposal aligns 
with the intended use of type 2 MI and creates clinical consistency in 
MS-DRGs. The commenter also stated while it is inappropriate for 
diagnosis code I21.A1 to be classified as the diagnosis driving MS-DRG 
assignment, type 2 MI should be classified as a major complication or 
comorbidity (MCC) because patients with type 2 MI face an increased 
mortality risk. Another commenter stated the proposed rule did not 
provide rationale as to why code I21.A1 would not act as an MCC under 
the proposal to revise the GROUPER logic to allow cases reporting 
diagnosis code I21.A1 as a secondary diagnosis to group to MS-DRGs 222 
and 223 when reported with qualifying procedures. This commenter 
requested that data analysis be provided on the instances when this 
code would not act as an MCC.
    Response: We appreciate the commenters' feedback. We note to that 
the GROUPER logic assignment for each diagnosis code as a principal 
diagnosis is for grouping purposes only. As discussed in the FY 2019 
IPPS/LTCH PPS final rule (83 FR 41217) and the FY 2021 IPPS/LTCH PPS 
final rule (85 FR 58519), because the diagnoses are codes listed under 
the heading of ``Principal Diagnosis'' in the ICD-10 MS-DRG Definitions 
Manual, it may appear to indicate that these codes are to be reported 
as a principal diagnosis for assignment to these MS-DRGs. However, the 
Definitions Manual display of the GROUPER logic assignment for each 
diagnosis code does not correspond to coding guidelines for reporting 
the principal diagnosis. The MS-DRG logic must specifically require a 
condition to group based on whether it is reported as a principal 
diagnosis or a secondary diagnosis, and consider any procedures that 
are reported, in addition to consideration of the patient's age, sex 
and discharge status in order to affect the MS-DRG assignment. In other 
words, cases will group according to the GROUPER logic, regardless of 
any coding guidelines or coverage policies. It is the Medicare Code 
Editor (MCE) and other payer-specific edits that identify 
inconsistencies in the coding guidelines or coverage policies. These 
data integrity edits address issues such as data validity, coding 
rules, and coverage policies. Since the inception of the IPPS, the data 
editing function has been a separate and independent step in the 
process of determining a DRG assignment. The separation of the MS-DRG 
grouping and data editing functions allows the MS-DRG GROUPER to remain 
stable even though coding rules and coverage policies may change during 
the fiscal year.
    In response to the commenter that stated that if type 2 MI cases 
are assigned to the MS-DRGs that describe an acute myocardial 
infarction, this would disrupt the resource accuracy of these MS-DRGs, 
while at the same time agreeing with the proposal to allow cases 
reporting diagnosis code I21.A1 (Myocardial infarction type 2) as a 
secondary diagnosis to group to MS-DRGs 222 and 223 when reported with 
qualifying procedures, we are unclear of the commenters' rationale for 
these conflicting statements. Specifically, because MS-DRGs 222 and 223 
also describe an acute myocardial infarction, it is unclear why the 
commenter indicates a type 2 MI should only be considered an MI in this 
instance.
    In response to the commenter that stated that CMS did not provide 
rationale as to why code I21.A1 would not act as an MCC under the 
proposal to revise the GROUPER logic in MS-DRGs 222 and 223 and in 
response to their request that data analysis be provided on the 
instances when this code would not act as an MCC, as we indicated in 
the proposed rule, whenever there is a secondary diagnosis component to 
the MS-DRG logic, the diagnosis code can either be used in the logic 
for assignment to the MS-DRG or to act as a CC/MCC. It is not a 
question of data analysis. Although I21.A1 is designated as an MCC when 
reported as a secondary diagnosis, if code I21.A1, as a secondary 
diagnosis, is being used in the definition of the logic for assignment 
to MS-DRGs 222 and 223, it cannot act as an MCC in these MS-DRGs. 
Therefore, outside of MS-DRGs 222, 223, 280, 281, 282, 283, 284 and 
285, diagnosis code I21.A1 will continue to act as an MCC when reported 
as a secondary diagnosis in Version 39.
    After consideration of the public comments we received, we are 
finalizing our proposal to maintain the current structure of MS-DRGs 
280 through 285, without modification, for

[[Page 44833]]

FY 2022. We are also finalizing our proposal, without modification, to 
modify the GROUPER logic to allow cases reporting diagnosis code I21.A1 
(Myocardial infarction type 2) as a secondary diagnosis to group to MS-
DRGs 222 and 223 when reported with qualifying procedures, effective 
October 1, 2021.
c. Viral Cardiomyopathy
    In the FY 2022 IPPS/LTCH PPS proposed rule (86 FR 25116 through 
25117), we discussed three separate but related requests that we 
received to add ICD-10-CM diagnosis code B33.24 (Viral cardiomyopathy) 
to the list of principal diagnoses for MS-DRGs 314, 315, and 316 (Other 
Circulatory System Diagnoses with MCC, with CC, and without CC/MCC, 
respectively) in MDC 05. The requestors noted that a discontinuity 
exists in the current MDC assignment of diagnosis codes in ICD-10-CM 
subcategory B33.2. The list of the five ICD-10-CM diagnosis codes in 
subcategory B33.2, as well as their current MDC assignments, is found 
in the following table.
[GRAPHIC] [TIFF OMITTED] TR13AU21.035

    A requestor noted ICD-10-CM codes B33.20, B33.21, B33.22, and 
B33.23 are assigned to MDC 05 (Diseases and Disorders of the 
Circulatory System), while code B33.24 is assigned to MDC 18 
(Infectious and Parasitic Diseases, Systemic or Unspecified Sites). The 
requestor stated that the placement of ICD-10-CM diagnosis code B33.24 
within subcategory B33.2 is clinically appropriate, as all the 
diagnoses within this subcategory share a common etiology, involve the 
heart and supporting structures, and require the same intensity of 
hospital care. However, the assignment of code B33.24 to a different 
MDC is clinically incongruous with the placement of the other codes in 
the subcategory. According to the requestor, all of the conditions 
share similar etiology, anatomic location, and needs for care, 
therefore the five codes should all be assigned to MDC 05. This 
requestor also stated that reassigning code B33.24 to MDC 05 would 
ensure both clinical continuity and coding consistency within the B33.2 
subcategory. Another requestor stated MDC 05 surgical MS-DRGs should be 
assigned when procedures such as cardiac catheterization or coronary 
angioplasty are performed for a principal diagnosis of viral 
cardiomyopathy.
    In the proposed rule, we indicated that to begin our analysis, we 
reviewed the GROUPER logic. We noted that currently, cases reporting 
ICD-10-CM diagnosis code B33.24 as a principal diagnosis group to 
medical MS-DRGs 865 and 866 (Viral Illness with and without MCC, 
respectively) in MDC 18 in the absence of a surgical procedure. We 
indicated our clinical advisors reviewed this issue and noted viral 
cardiac infections may present as endocarditis (inflammation of the 
heart's inner lining), myocarditis (inflammation of the middle layer of 
the heart), pericarditis (inflammation of the pericardium), or 
cardiomyopathy (disease of the heart muscle). The infection usually 
begins somewhere other than the heart, often in the nose, lungs, or 
stomach. As the infection progresses, and the microbe multiplies and 
gets into the bloodstream, it can infiltrate the heart muscle. The 
growth and replication of viruses inside the heart can endanger the 
heart by destroying heart cells. The management of viral cardiomyopathy 
is similar to the management of other viral cardiac infections and can 
include bed rest, control of pain with non-steroidal anti-inflammatory 
agents and anti-microbial therapy to avoid permanent myocardial damage, 
cardiomegaly, and/or congestive cardiac failure.
    We indicated our clinical advisors agreed that the diagnosis of 
viral cardiomyopathy is clinically related to the other diagnoses in 
ICD-10-CM subcategory B33.2. We stated that they believed it is 
clinically appropriate for all five diagnoses in subcategory B33.2 to 
group to MDC 05 (Diseases and Disorders of the Circulatory System) as 
these conditions describe circulatory system conditions and 
complications and that this modification will improve clinical 
coherence. Therefore, we proposed to reassign ICD-10-CM diagnosis code 
B33.24 from MDC 18 in MS DRGs 865 and 866 (Viral Illness with and 
without MCC, respectively) to MDC 05 in MS DRGs 314, 315, and 316 
(Other Circulatory System Diagnoses with MCC, with CC, and without CC/
MCC, respectively). We stated in the proposed rule that, under this 
proposal, cases reporting procedure codes from MDC 05 in conjunction 
with principal diagnosis B33.24, would group to MS-DRGs in MDC 05.
    Comment: Commenters agreed with CMS' proposal to reassign ICD-10-CM 
diagnosis code B33.24 (Viral cardiomyopathy) from MDC 18 in MS DRGs 865 
and 866 (Viral Illness with and without MCC, respectively) to MDC 05 in 
MS-DRGs 314, 315, and 316 (Other Circulatory System Diagnoses with MCC, 
with CC, and without CC/MCC, respectively). Commenters stated this 
change will improve clinical coherence since viral cardiomyopathy is 
closely related to the other viral heart diseases in subcategory B33.2 
that are already assigned to MDC 05.
    Response: We appreciate the commenters' support.
    After consideration of the public comments we received, we are 
finalizing our proposal to reassign ICD-10-CM diagnosis code B33.24 
from MDC 18 in MS DRGs 865 and 866 (Viral Illness with and without MCC, 
respectively) to MDC 05 in MS DRGs 314, 315, and 316 (Other Circulatory 
System Diagnoses with MCC, with CC, and without CC/MCC, respectively), 
without modification, effective October 1, 2021.
d. Left Atrial Appendage Closure (LAAC)
    In the FY 2021 IPPS/LTCH PPS final rule (85 FR 58471 through 
58477), we identified nine ICD-10-PCS procedure codes that describe 
Left Atrial Appendage Closure (LAAC) procedures and noted their 
corresponding MS-DRG assignments in the ICD-10 MS-DRGs Version 37 as 
listed in the following table.

[[Page 44834]]

[GRAPHIC] [TIFF OMITTED] TR13AU21.036

    As discussed in the FY 2021 IPPS/LTCH PPS final rule, we examined 
claims data from the September 2019 update of the FY 2019 MedPAR file 
for cases reporting LAAC procedures with an open approach in MS-DRGs 
250 and 251 (Percutaneous Cardiovascular Procedures without Coronary 
Artery Stent with and without MCC, respectively). Our analysis showed 
that the cases reporting a LAAC procedure with an open approach in MS-
DRGs 250 and 251 had higher average costs and longer average length of 
stay compared to all cases in MS-DRGs 250 and 251. We also stated our 
clinical advisors believed that ICD-10-PCS codes 02L70CK, 02L70DK, and 
02L70ZK that describe a LAAC procedure with an open approach were more 
suitably grouped to MS-DRGs 273 and 274 (Percutaneous Intracardiac 
Procedures with and without MCC, respectfully). Therefore, we finalized 
our proposal to reassign ICD-10-PCS procedure codes 02L70CK, 02L70DK, 
and 02L70ZK from MS-DRGs 250 and 251 to MS-DRGs 273 and 274. We also 
finalized a revision to the titles for MS-DRG 273 and 274 to 
Percutaneous and Other Intracardiac Procedures with and without MCC, 
respectively to reflect this reassignment for FY 2021.
    In the FY 2022 IPPS/LTCH PPS proposed rule (86 FR 25117 through 
25118), we discussed a request we received to again review the MS-DRG 
assignment of cases involving LAAC procedures with an open approach in 
response to this final policy. The requestor disagreed with CMS' FY 
2021 IPPS/LTCH PPS final rule decision to move the three procedure 
codes describing the open occlusion of left atrial appendage to MS-DRGs 
273 and 274 (Percutaneous and Other Intracardiac Procedures with and 
without MCC, respectively). The requestor stated they believe that MS-
DRGs 228 and 229 (Other Cardiothoracic Procedures with and without MCC, 
respectively), would more appropriately correspond with the open 
procedural resources and longer length of stay expected with open heart 
procedures.
    We indicated in the proposed rule that our clinical advisors 
reviewed this request and continued to support the reassignment of ICD-
10-PCS procedure codes 02L70CK, 02L70DK, and 02L70ZK from MS-DRGs 250 
and 251 to MS-DRGs 273 and 274 because it allows all LAAC procedures to 
be grouped together under the same MS-DRGs and improves clinical 
coherence. Our clinical advisors stated open LAAC procedures are 
primarily performed in the absence of another O.R. procedure and 
generally are not performed with a more intensive open chest procedure. 
When performed as standalone procedures, open LAAC procedures share 
similar factors such as complexity and resource utilization with all 
other LAAC procedures. We noted that our clinical advisors continued to 
state our FY 2021 final policy results in MS-DRG assignments that are 
more clinically homogeneous and better reflect hospital resource use. 
Therefore, we proposed to maintain the assignment of codes 02L70CK, 
02L70DK, and 02L70ZK that describe the open occlusion of the left 
atrial appendage in MS-DRGs 273 and 274.
    Comment: A commenter expressed concern and requested that CMS 
reconsider its proposal to continue the assignment of the open LAAC 
procedure codes to MS-DRGs 273 and 274 (Percutaneous and Other 
Intracardiac Procedures with and without MCC, respectively) and instead 
assign these procedures to MS-DRGs 228 and 229 (Other Cardiothoracic 
Procedures with and without MCC, respectively). This commenter 
acknowledged in response to the FY 2021 proposed rule, they supported 
CMS' proposal to reassign the open approach left atrial appendage 
procedure codes from MS-DRGs 250 and 251 to MS-DRGS 273 and 274 at that 
time. However, the commenter stated that because CMS did not provide a 
detailed analysis of the claims data for the average length of stay and 
average costs related to the cases reporting procedure codes describing 
the open occlusion of left atrial appendage in the FY 2022 proposed 
rule, it reviewed the data analysis as presented in the FY 2021 IPPS/
LTCH PPS rule and compared it to the data analysis in Section II.D.5.d 
of the FY 2022 IPPS/LTCH PPS proposed rule (86 FR 25118 through 25121) 
which was presented as part of the discussion of a two-part request to 
review the MS-DRG assignments for cases involving surgical ablation 
procedures for atrial fibrillation. The commenter stated based on their 
own analysis, it appeared the average length of stay and average costs 
of open occlusion of left atrial appendage procedures would be more 
clinically aligned with MS-DRGs 228 and 229.
    Response: We appreciate the commenter's feedback. We note that the 
analysis discussed in FY 2021 rulemaking was based on the examination 
of claims data from the September 2019 update of the FY 2019 MedPAR 
file, while discussions in Section II. D. of the FY 2022 proposed rule 
are based on the examination of claims data from the March 2020 update 
of the FY 2019 MedPAR file, as well as the September 2020 update of the 
FY 2020 MedPAR file.
    We display in the following tables claims analysis using claims 
data from the March 2020 update of the FY 2019 MedPAR file, as well as 
the September 2020 update of the FY 2020 MedPAR file. We examined 
claims data from the March 2020 update of the FY 2019 MedPAR file for 
all cases in MS-DRGs 273 and 274 and compared the results to cases with 
a procedure code describing an open LAAC procedure.
BILLING CODE 4120-01-P

[[Page 44835]]

[GRAPHIC] [TIFF OMITTED] TR13AU21.037

    In MS-DRG 273, we found a total of 7,557 cases with an average 
length of stay of 6.1 days and average costs of $28,356. Of those 7,557 
cases, there were 29 cases reporting a LAAC procedure with an open 
approach, with an average length of stay of 7.6 days and average costs 
of $52,365. In MS-DRG 274, we found a total of 26,595 cases with an 
average length of stay of 2 days and average costs of $24,295. Of those 
26,595 cases, there were 89 cases reporting a LAAC procedure with an 
open approach, with an average length of stay of 3.5 days and average 
costs of $25,185. The analysis shows that the cases reporting a LAAC 
procedure with an open approach in MS-DRGs 273 and 274 have higher 
average costs compared to all cases in MS-DRGs 273 and 274 ($52,365 
versus $28,356 and $25,185 versus $24,295, respectively).
    We also examined claims data from the September 2020 update of the 
FY 2020 MedPAR file for all cases in MS-DRGs 273 and 274 and compared 
the results to cases with a procedure code describing an open LAAC 
procedure.
[GRAPHIC] [TIFF OMITTED] TR13AU21.038

BILLING CODE 4120-01-C
    In MS-DRG 273, we found a total of 6,542 cases with an average 
length of stay of 6.1 days and average costs of $30,671. Of those 6,542 
cases, there were 19 cases reporting a LAAC procedure with an open 
approach, with an average length of stay of 8.3 days and average costs 
of $47,421. In MS-DRG 274, we found a total of 23,125 cases with an 
average length of stay of 1.9 days and average costs of $25,880. Of 
those 23,125 cases, there were 55 cases reporting a LAAC procedure with 
an open approach, with an average length of stay of 3.1 days and 
average costs of $20,995. The analysis shows that the cases reporting a 
LAAC procedure with an open approach in MS-DRG 273 have higher average 
costs compared to all cases in MS-DRG 273 ($47,421 versus $30,671) 
while the cases reporting a LAAC procedure with an open approach in MS-
DRG 274 have lower average costs compared to all cases in MS-DRG 274 
($20,995 versus $25,880).
    While we recognize the average costs of the small number of cases 
reporting LAAC procedures with an open approach generally have average 
costs greater than the average costs of the cases in MS-DRGs 273 and 
274 overall, our clinical advisors continue to support the reassignment 
of the open occlusion of left atrial appendage procedures, which was 
finalized in FY 2021 rulemaking. The MS-DRG system is a system of 
averages, and it is expected that across the diagnostic related groups 
that within certain groups, some cases may demonstrate higher than 
average costs, while other cases may demonstrate lower than average 
costs.
    Our clinical advisors reviewed this issue and stated they do not 
believe that assigning procedure codes describing an open LAAC 
procedure to MS-DRGs 228 and 229 (Other Cardiothoracic Procedures with 
and without MCC, respectively) will improve clinical coherence, as this 
surgical class is not as precisely defined from a clinical perspective. 
MS-DRGs 228 and 229 are an example of the surgical MS-DRGs that are 
found within each MDC that include `other' procedures intended to 
encompass procedures that, while not directly related to the MDC, can 
and do occur with principal diagnoses in that MDC with sufficient 
frequency.
    Our clinical advisors note that, as stated in the ICD-10 MS-DRG 
Definitions Manual, ``In each MDC there is usually a medical and a 
surgical class referred to as ``other medical diseases'' and ``other 
surgical procedures,'' respectively. The ``other'' medical and surgical 
classes are not as precisely

[[Page 44836]]

defined from a clinical perspective. The other classes would include 
diagnoses or procedures which were infrequently encountered or not well 
defined clinically''. The ICD-10 MS-DRG Definitions Manual also states 
``The ``other'' surgical category contains surgical procedures which, 
while infrequent, could still reasonably be expected to be performed 
for a patient in the particular MDC.''
    Our clinical advisors continue to state that when performed as 
standalone procedures, open LAAC procedures share similar factors such 
as complexity and resource utilization with all other LAAC procedures. 
Moreover, our clinical advisors continue to support the FY 2021 
reassignment of the open occlusion of left atrial appendage procedures 
because it allows all LAAC procedures to be grouped together under the 
same MS-DRGs and improves clinical coherence. After consideration of 
the public comments we received, and for the reasons stated previously, 
we are finalizing our proposal to maintain the assignment of codes 
02L70CK, 02L70DK, and 02L70ZK that describe the open occlusion of the 
left atrial appendage in MS-DRGs 273 and 274, without modification, for 
FY 2022.
e. Surgical Ablation
    In the FY 2022 IPPS/LTCH PPS proposed rule (86 FR 25118 through 
25121), we discussed a two-part request we received to review the MS-
DRG assignments for cases involving the surgical ablation procedure for 
atrial fibrillation. Atrial fibrillation (AF) is an irregular and often 
rapid heart rate that occurs when the two upper chambers of the heart 
experience chaotic electrical signals. AF presents as either paroxysmal 
(lasting <7 days), persistent (lasting >7 day, but less than 1 year), 
or long standing persistent (chronic) (lasting >1 year) based on time 
duration and can increase the risk for stroke, heart failure, and 
mortality. Management of AF has two primary goals: Optimizing cardiac 
output through rhythm or rate control, and decreasing the risk of 
cerebral and systemic thromboembolism. Patients that worsen in 
symptomology or fail to respond to pharmacological treatment or other 
interventions may be referred for surgical ablation to treat their AF. 
Surgical ablation is a procedure that works by burning or freezing 
tissue on the inside of the heart to disrupt faulty electrical signals 
causing the arrhythmia, which can help the heart maintain a normal 
heart rhythm.
    As discussed in the proposed rule, the first part of this request 
was to create a new classification of surgical ablation MS-DRGs to 
better accommodate the costs of open concomitant surgical ablations. 
According to the requestor, patients undergoing surgical ablation are 
treated under two potential scenarios: (1) Open concomitant 
(combination) surgical ablation, meaning open surgical ablation 
performed during another open-heart surgical procedure such as mitral 
valve repair or replacement (MVR), aortic valve repair or replacement 
(AVR), or coronary artery bypass grafting (CABG) and (2) minimally 
invasive, percutaneous endoscopic, standalone surgical ablation as the 
sole therapeutic procedure performed. According to the requestor, open 
concomitant surgical ablation is an efficient procedure, as it allows 
treatment of AF and another clinical pathology in one procedure thereby 
decreasing the risk of future readmits, need for future repeat catheter 
ablation procedures, and patient mortality.
    The requestor identified the following potential procedure 
combinations that would comprise an ``open concomitant surgical 
ablation'' procedure.

 Open CABG + open surgical ablation
 Open MVR + open surgical ablation
 Open AVR + open surgical ablation
 Open MVR + open AVR + open surgical ablation
 Open MVR + open CABG + open surgical ablation
 Open MVR + open AVR + open CABG + open surgical ablation
 Open AVR + open CABG + open surgical ablation

    The requestor performed their own analysis of these procedure code 
combinations and stated that it found the average costs for open 
concomitant surgical ablation procedures were consistently higher 
compared to the average costs within their respective MS-DRGs, which 
could limit beneficiary access to these procedures.
    The requestor suggested that the following four MS-DRGs be created 
to address the differences in average costs and average lengths of stay 
it found in its data analysis:
     Suggested New MS-DRG XXX--Open Surgical Ablation with or 
without Other Cardiothoracic Procedure with Cardiac Catheterization 
with MCC;
     Suggested New MS-DRG XXX--Open Surgical Ablation with or 
without Other Cardiothoracic Procedure with Cardiac Catheterization 
without MCC;
     Suggested New MS-DRG XXX--Open Surgical Ablation with or 
without Other Cardiothoracic Procedure without Cardiac Catheterization 
with MCC; and
     Suggested New MS-DRG XXX--Open Surgical Ablation with or 
without Other Cardiothoracic Procedure without Cardiac Catheterization 
without MCC.
    In response to this request, we identified nine ICD-10-PCS codes 
that describe open surgical ablation. These codes and their 
corresponding MDC and MS-DRG assignments are listed in the following 
table.
BILLING CODE 4120-01-P
[GRAPHIC] [TIFF OMITTED] TR13AU21.039


[[Page 44837]]


    We stated in the proposed rule that the ICD-10 MS-DRGs Definitions 
Manual Version 38.1, for open concomitant surgical ablation procedures, 
the GROUPER logic assigns MS-DRGs 228 and 229 (Other Cardiothoracic 
Procedures with and without MCC, respectively) in most instances 
because MS-DRGs 228 and 229 are high in the surgical hierarchy GROUPER 
logic of MDC 05 (Diseases and Disorders of the Circulatory System). We 
would like to correct the statement in the proposed rule that, in ICD-
10 MS-DRGs Definitions Manual Version 38.1, for open concomitant 
surgical ablation procedures, the GROUPER logic assigns MS-DRGs 228 and 
229 (Other Cardiothoracic Procedures with and without MCC, 
respectively) in most instances. We list in the following table the 
open concomitant surgical ablation procedure code combinations and 
their corresponding MS-DRG assignments in the ICD-10 MS-DRGs 
Definitions Manual Version 38.1.
[GRAPHIC] [TIFF OMITTED] TR13AU21.040

BILLING CODE 4120-01-C
    Since patients can have multiple procedures reported with a 
principal diagnosis during a particular hospital stay, and a patient 
can be assigned to only one MS-DRG, the surgical hierarchy GROUPER 
logic provides a hierarchical order of surgical classes from the most 
resource-intensive to the least resource-intensive. Patients with 
multiple procedures are generally assigned to the MS-DRG that 
correlates to the most resource-intensive surgical class.
    As noted in the proposed rule, our clinical advisors reviewed this 
grouping issue and noted in open concomitant surgical ablation 
procedures, the CABG, MVR, and/or AVR components of the procedure are 
more technically complex than the open surgical ablation procedure. We 
noted that our clinical advisors stated that in open concomitant 
surgical ablation procedures, the MS-DRG assigned should be based on 
the most resource-intensive procedure performed. Therefore, we 
indicated we believed this request would be better addressed by 
proposing to revise the surgical hierarchy in MDC 05 rather than 
creating four new MS-DRGs. For FY 2022, we proposed to revise the 
surgical hierarchy for the MS-DRGs in MDC 05 to sequence MS-DRGs 231-
236 (Coronary Bypass) above MS-DRGs 228 and 229 to enable more 
appropriate MS-DRG assignment for these types of cases. We indicated in 
the proposed rule, that, under this proposal, if a procedure code 
describing a CABG and a procedure code describing an open surgical 
ablation are present, the GROUPER logic would assign the CABG surgical 
class because a CABG would be sequenced higher in the hierarchy than an 
open surgical ablation.
    Comment: Many commenters agreed with our proposal to revise the 
surgical hierarchy for the MS-DRGs in MDC 05 to sequence MS-DRGs 231-
236 (Coronary Bypass) above MS-DRGs 228 and 229. Some commenters stated 
the re-sequencing of the CABG MS-DRGs is long overdue. A commenter 
specifically stated they agreed with CMS' reasoning to revise the 
surgical hierarchy rather than to create new DRGs and stated from a 
clinical and payment standpoint, moving CABG MS-DRGs 231-236 above 
Other Cardiothoracic Procedure MS-DRGs 228-229 aligns the procedures 
better with their technical complexity and their costs.
    Response: We thank the commenters for their support.
    Comment: While supporting our proposal, other commenters stated 
that this proposal does not address the issue of the increased 
resources required to treat patients with AF that are also a candidate 
for an open surgical ablation procedure at the same time of their CABG 
procedure. Some commenters stated that CMS' proposal to revise the 
surgical hierarchy for CABG procedures does not advance patient access 
nor allow patients the opportunity to receive these procedures during 
the

[[Page 44838]]

CABG surgical procedure. Another commenter stated that the proposed 
revision to the surgical hierarchy fails to address the increased costs 
of cases associated with open concomitant surgical ablation for AF 
performed during open mitral valve procedures, which are assigned to 
MS-DRGs 216 through 221. Another commenter stated while they agree that 
surgical ablation procedures are not as resource intensive as CABG 
procedures, CMS' proposal does not give consideration to the increased 
costs the surgical ablation procedure adds to the CABG procedure.
    A commenter stated that CMS did not describe its methodology in 
detail regarding its analysis of the costs associated with performance 
of open surgical ablation for AF performed concomitantly during open-
heart procedures, preventing meaningful public comments. This commenter 
stated that concomitant surgical ablation does not represent an 
``incidental cost'' to a hospital that can be remedied just through 
changes in the existing surgical hierarchy.
    Commenters expressed concern that given the added costs of 
performing as many as three procedures at the same time, hospitals may 
more likely schedule the patient for separate procedures even though 
guidelines of the Society for Thoracic Surgeons and the Heart Rhythm 
Society recommend performing surgical ablation for AF at the time of 
open-heart procedures. A commenter stated that facilities receive only 
one MS-DRG payment when procedures are performed concomitantly and are 
therefore burdened with absorbing the additional expenses of other 
services provided, further stating that data have shown that mortality 
is significantly reduced in the first year following concomitant 
treatment.
    Many commenters urged CMS to either (1) create new MS-DRGs for 
these open concomitant procedures as originally requested, or (2) 
assign these procedures to MS-DRGs that consider the added procedure 
and device costs required. Another commenter requested that CMS create 
a supplemental payment mechanism that could be modeled based on the 
respective costs of the individual procedures determined by claims data 
and then adjusted for efficiencies of a single operative session to 
facilitate incremental payment when two major procedures are performed 
during the same hospital admission.
    Response: We appreciate the commenters' feedback.
    As discussed in section II.D.15. of the preamble of the proposed 
rule and this final rule, in our proposal to revise the surgical 
hierarchy for the MS-DRGs in MDC 05, MS-DRGs 216-221 (Cardiac Valve and 
Other Major Cardiothoracic Procedures) will continue to be sequenced 
above MS-DRGs 231-236 (Coronary Bypass) and MS-DRGs 228 and 229. Of 
note, in the absence of other procedure codes on the claim, we agree 
with the commenter that the only procedure code combination describing 
open concomitant surgical ablations affected by our proposal to revise 
the surgical hierarchy for the MS-DRGs in MDC 05 is ``Open CABG + Open 
Ablation''. Under this proposal, the six other combinations describing 
open concomitant surgical ablations will continue to be assigned to MS-
DRGs 216 through 221.
    In response to the comment that CMS did not describe its 
methodology in detail regarding its analysis of the costs associated 
with performance of open surgical ablation, as we discussed insection 
II.D.15. of the preamble of the proposed rule, we reviewed the surgical 
hierarchy within MDC 05 consistent with our annual process; 
specifically, we weigh the average costs of each MS-DRG in the class by 
frequency (that is, by the number of cases in the MS-DRG) to determine 
average resource consumption for the surgical class.
    With regard to the comments stating that the proposed revision to 
the surgical hierarchy fails to address the increased costs of cases 
associated with open concomitant surgical ablation, we examined the 
data analysis of cases reporting procedure code combinations describing 
open concomitant surgical ablations in the March 2020 update of the FY 
2019 MedPAR file and the September 2020 update of the FY 2020 MedPAR 
file for cases reporting procedure code combinations describing open 
concomitant surgical ablations. First, we refer the reader to Table 
6P.1n associated with this final rule (which is available via the 
internet on the CMS website at: https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/AcuteInpatientPPS) for the list of ICD-10-PCS 
procedure codes reflecting mitral valve repair or replacement (MVR), 
aortic valve repair or replacement (AVR), and coronary artery bypass 
grafting (CABG) procedures that we examined in our analysis of this 
issue. We also refer the reader to Table 6P.1o associated with this 
final rule (which is available via the internet on the CMS website at: 
https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/AcuteInpatientPPS) for data analysis findings of cases reporting 
procedure code combinations describing open concomitant surgical 
ablations currently assigned to MS-DRGs 216, 217, 218, 219, 220 and 221 
from the March 2020 update of the FY 2019 MedPAR file and from the 
September 2020 update of the FY 2020 MedPAR file. We note that if a 
procedure code combination that is currently assigned to MS-DRGs 216, 
217, 218, 219, 220 and 221 is not displayed, it is because there were 
no cases found reporting that combination in the assigned MS-DRG.
    As shown in Table 6P.1o associated with this final rule, in our 
examination of the claims data from both the March 2020 update of the 
FY 2019 MedPAR file and September 2020 update of the FY 2020 MedPAR 
file, while the average lengths of stay and average costs of cases 
reporting procedure code combinations describing open concomitant 
surgical ablations are higher than all cases in their respective MS-
DRG, we found there is variation in the volume, length of stay, and 
average costs of the cases. In the analysis of claims data from the 
March 2020 update of the FY 2019 MedPAR file, during our review of MS-
DRG 216, we found 1,145 cases reporting procedure code combinations 
describing open concomitant surgical ablations with the average length 
of stay ranging from 17.6 days to 24.3 days and average costs ranging 
from $77,868 to $125,120 for these cases. For MS-DRG 217, we found 295 
cases reporting procedure code combinations describing open concomitant 
surgical ablations with the average length of stay ranging from 10 days 
to 13 days and average costs ranging from $45,526 to $52,859 for these 
cases. For MS-DRG 218, we found 7 cases reporting procedure code 
combinations describing open concomitant surgical ablations with the 
average length of stay ranging from 7 days to 11 days and average costs 
ranging from $28,614 to $68,725 for these cases. For MS-DRG 219, we 
found 2,673 cases reporting procedure code combinations describing open 
concomitant surgical ablations with the average length of stay ranging 
from 11.6 days to 13.3 days and average costs ranging from $65,846 to 
$83,281 for these cases. For MS-DRG 220, we found 1,890 cases reporting 
procedure code combinations describing open concomitant surgical 
ablations with the average length of stay ranging from 7.3 days to 10.2 
days and average costs ranging from $44,568 to $64,726 for these cases. 
For MS-DRG 221, we found 110 cases reporting procedure code 
combinations describing open concomitant surgical ablations with the 
average length of stay ranging from 5.6 days to 6.8 days and average 
costs

[[Page 44839]]

ranging from $44,826 to $73,629 for these cases.
    Our analysis of the claims data from the September 2020 update of 
the FY 2020 MedPAR file resulted in similar findings to those from the 
March 2020 update of the FY 2019 MedPAR file; while the average lengths 
of stay and average costs of cases reporting procedure code 
combinations describing open concomitant surgical ablations are higher 
than all the cases in their respective MS-DRG, we found there is 
variation in the volume, length of stay, and average costs of the 
cases. In the analysis of claims data from the September 2020 update of 
the FY 2020 MedPAR file, during our review of MS-DRG 216, we found 931 
cases reporting procedure code combinations describing open concomitant 
surgical ablations with the average length of stay ranging from 16.1 
days to 20.5 days and average costs ranging from $79,732 to $108,552 
for these cases. For MS-DRG 217, we found 207 cases reporting procedure 
code combinations describing open concomitant surgical ablations with 
the average length of stay ranging from 9.2 days to 12 days and average 
costs ranging from $46,588 to $70,840 for these cases. For MS-DRG 218, 
we found 1 case reporting procedure code combinations describing open 
concomitant surgical ablations with a length of stay of 8 days and 
costs of $17,611. For MS-DRG 219, we found 1,998 cases reporting 
procedure code combinations describing open concomitant surgical 
ablations with the average length of stay ranging from 11.6 days to 
14.6 days and average costs ranging from $68,175 to $104,560 for these 
cases. For MS-DRG 220, we found 1,318 cases reporting procedure code 
combinations describing open concomitant surgical ablations with the 
average length of stay ranging from 7.5 days to 8.0 days and average 
costs ranging from $48,200 to $61,444 for these cases. For MS-DRG 221, 
we found 60 cases reporting procedure code combinations describing open 
concomitant surgical ablations with the average length of stay ranging 
from 5.1 days to 8.6 days and average costs ranging from $49,910 to 
$65,501 for these cases.
    In response to comments that urged CMS to create new MS-DRGs for 
these open concomitant procedures as originally requested, based on 
these data, our clinical advisors believe additional time is needed 
given the complexity of these code combinations and corresponding data 
before exploring a proposal to create new MS-DRGs for this subset of 
patients. For example, cases reporting a CABG and a procedure code 
describing an open surgical ablation without procedure codes describing 
an AVR or an MVR were found in MS-DRGs 216 through 221 meaning another 
cardiac valve or other major cardiothoracic procedure was reported, 
which could be contributing to the increased costs of these cases. 
Secondly, MS-DRGs 216, 217 and 218 are defined by the performance of 
cardiac catheterization, meaning a cardiac catherization procedure was 
reported, which could be also contributing to the increased costs of 
these cases. Lastly, the cases reporting an open concomitant surgical 
ablation code combination are predominately found in the higher (CC or 
MCC) severity level MS-DRGs of their current base MS-DRG assignment. 
Therefore, our clinical advisors believe that additional time is needed 
to allow for further analysis of the claims data to determine to what 
extent the patient's co-morbid conditions are also contributing to 
higher costs and to identify other contributing factors that might 
exist with respect to the increased length of stay and costs of these 
cases in these MS-DRGs. Our clinical advisors also believe that future 
data findings may demonstrate additional variance in resource 
utilization for this patient population.
    We also note, as discussed in Section D.1.b of the proposed rule 
and this final rule, using the March 2020 update of the FY 2019 MedPAR 
file and the September 2020 update of the FY 2020 MedPAR file, we 
analyzed how applying the NonCC subgroup criteria to all MS-DRGs 
currently split into three severity levels would affect the MS-DRG 
structure beginning in FY 2022. Findings from our analysis indicated 
that MS-DRGs 216, 217, 218 as well as approximately 31 other MS-DRGs 
would be subject to change based on the three-way severity level split 
criterion finalized in FY 2021. We refer the reader to Table 6P.1c 
associated with the proposed rule and this final rule (which is 
available via the internet on the CMS website at: https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/AcuteInpatientPPS) for the 
list of the 96 MS-DRGs that would be subject to deletion and the list 
of the 58 new MS-DRGs that would have been proposed for creation under 
this policy if the NonCC subgroup criteria were applied.
    As discussed previously, we are finalizing the delay of the 
application of the NonCC subgroup criteria to existing MS-DRGs with a 
three-way severity level split until FY 2023 or later, and are 
finalizing our proposal to maintain the current structure of the 32 MS-
DRGs that currently have a three-way severity level split (total of 96 
MS-DRGs) that would otherwise be subject to these criteria for FY 2022. 
Noting that currently the total number of cases in MS-DRG 218 is below 
500, and that we may consider consolidating these MS-DRGs into two 
severity levels based on the application of the NonCC subgroup criteria 
in future rule-making, as well as for the reasons stated previously, we 
believe additional time is needed to review the clinical nature of 
cases reporting an open concomitant surgical ablation code combination 
before creating new MS-DRGs for the subset of cases with procedure 
codes that describe open concomitant surgical ablation procedures that 
are currently assigned to MS-DRGs 216 through 221 at this time.
    In response to comment that the proposed hierarchy change will not 
address the increased resources required to treat patients with AF that 
are a candidate for an open surgical ablation procedure at the same 
time of their CABG procedure, we analyzed the March 2020 update of the 
FY 2019 MedPAR file for cases reporting the procedure code combination 
``Open CABG + Open Ablation'' of the seven potential procedure 
combinations that would comprise an ``open concomitant surgical 
ablation'' procedure, as this is the only concomitant procedure code 
combination potentially affected by the proposed hierarchy change (in 
the absence of other procedure codes that could affect MS-DRG 
assignment on the claim).
BILLING CODE 4120-01-P

[[Page 44840]]

[GRAPHIC] [TIFF OMITTED] TR13AU21.041

    As shown in the table, the data analysis performed indicates that 
the 1,010 cases in MS-DRG 228 reporting a procedure code that describes 
a CABG procedure as well as a procedure code describing an open 
ablation have an average length of stay that is longer than the average 
length of stay for all the cases in MS-DRG 228 (12.8 days versus 10.7 
days) and higher average costs when compared to all the cases in MS-DRG 
228 ($56,331 versus $45,772). The 1,041 cases in MS-DRG 229 reporting a 
procedure code that describes a CABG procedure as well as a procedure 
code describing an open ablation also have an average length of stay 
that is longer than the average length of stay for all the cases in MS-
DRG 229 (8.2 days versus 5.3 days) and higher average costs when 
compared to all the cases in MS-DRG 229 ($38,643 versus $29,454). As 
expected, there were zero cases found with procedure codes describing 
one of the other six ``open concomitant surgical ablation'' procedure 
code combinations as described by the requestor since GROUPER logic 
would assign MS-DRGs 216 through 221 for the other combinations.
    We then examined the redistribution of cases that is anticipated to 
occur as a result of the proposal to move MS-DRGs 231 through 236 
(Coronary Bypass) above MS-DRGs 228 and 229 in the surgical hierarchy 
of MDC 05 for Version 39 of the ICD-10 MS-DRGs, by processing the 
claims data from the March 2020 update of the FY 2019 MedPAR file 
through the ICD-10 MS-DRG GROUPER Version 38 and then processing the 
same claims data through the ICD-10 MS-DRG GROUPER Version 39 for 
comparison. The number of cases from this comparison that result in 
different MS-DRG assignments is the number of the cases that are 
anticipated to potentially shift or be redistributed. Our findings are 
shown in the following table.

[[Page 44841]]

[GRAPHIC] [TIFF OMITTED] TR13AU21.042

    We found a number of cases that are anticipated to potentially 
shift or be redistributed into MS-DRGs 231 through 236. The largest 
number of cases moving out of MS-DRG 228 are moving into MS-DRG 235, 
which means these cases reported a procedure code for CABG and a 
cardiothoracic procedure, such as a surgical ablation, without 
procedure codes reporting a PTCA or cardiac catherization. The largest 
number of cases moving out of MS-DRG 229 are moving into MS-DRG 236, 
which again means these cases reported a procedure code for CABG and a 
cardiothoracic procedure, such as a surgical ablation, without 
procedure codes reporting a PTCA or cardiac catherization.
    We then examined the claims data from the March 2020 update of the 
FY 2019 MedPAR file to identify the average length of stay and average 
costs for all cases in MS-DRGs 231, 232, 233, 234, 235 and 236. Our 
findings are shown in the following table.
[GRAPHIC] [TIFF OMITTED] TR13AU21.043

    In reviewing the data analysis performed, the 1,010 cases in MS-DRG 
228 reporting a procedure code that describes a CABG procedure as well 
as a procedure code describing an open ablation have an average length 
of stay that is longer than the average length of stay for all the 
cases in MS-DRG 235 (12.8 days versus 9.8 days) and higher average 
costs when compared to all the cases in MS-DRG 235 ($56,331 versus 
$42,133). The 1,041 cases in MS-DRG 229 reporting a procedure code that 
describes a CABG procedure as well as a procedure code describing an 
open ablation also have an average length of stay that is longer than 
the average length of stay for all the cases in MS-DRG 236 (8.2 days 
versus 6.4 days) and higher average costs when compared to all the 
cases in MS-DRG 236 ($38,643 versus $29,565). The average length of 
stay and average costs of cases reporting a procedure code that 
describes a CABG procedure as well as a procedure code describing an 
open ablation in MS-DRG 228 as well as a secondary diagnosis of MCC are 
closer aligned to costs of cases in MS-DRGs 233 (Coronary Bypass with 
Cardiac Catheterization with MCC) (12.8 days versus 12.7 days and 
$56,331 versus $54,170 respectively). The average length of stay and 
average costs of cases reporting a procedure code that describes a CABG 
procedure as well as a procedure code describing an open ablation in 
MS-DRG 229 without secondary diagnosis of MCC are closer aligned to 
costs of cases in MS-DRGs

[[Page 44842]]

234 (Coronary Bypass with Cardiac Catheterization without MCC) (8.2 
days versus 8.7 days and $38,643 versus $38,058 respectively).
    Next, we analyzed the September 2020 update of the FY 2020 MedPAR 
file for cases reporting a procedure code describing a CABG procedure 
with a procedure code describing an open ablation.
[GRAPHIC] [TIFF OMITTED] TR13AU21.044

    As shown in the table, the data analysis performed indicates that 
the 836 cases in MS-DRG 228 reporting a procedure code that describes a 
CABG procedure as well as a procedure code describing an open ablation 
have an average length of stay that is longer than the average length 
of stay for all the cases in MS-DRG 228 (12.8 days versus 10.2 days) 
and higher average costs when compared to all the cases in MS-DRG 228 
($60,327 versus $46,508). The 824 cases in MS-DRG 229 reporting a 
procedure code that describes a CABG procedure as well as a procedure 
code describing an open ablation also have an average length of stay 
that is longer than the average length of stay for all the cases in MS-
DRG 229 (7.9 days versus 4.9 days) and higher average costs when 
compared to all the cases in MS-DRG 229 ($39,392 versus $29,885). As 
expected, there were zero cases found with procedure codes describing 
one of the other six ``open concomitant ablation'' procedure code 
combinations as described by the requestor since GROUPER logic would 
assign MS-DRGs 216 through 221 for the other combinations.
    As we did with the March 2020 update of the FY 2019 MedPAR file, we 
then examined the redistribution of cases that is anticipated to occur 
by processing the claims data, this time from the September 2020 update 
of the FY 2020 MedPAR file through the ICD-10 MS-DRG GROUPER Version 38 
and then processed the same claims data through the ICD-10 MS-DRG 
GROUPER Version 39 for comparison. Our findings are shown in the table.

[[Page 44843]]

[GRAPHIC] [TIFF OMITTED] TR13AU21.045

    Similarly, we found a number of cases that are anticipated to 
potentially shift or be redistributed into MS-DRGs 231 through 236. The 
largest number of cases moving out of MS-DRG 228 are moving into MS-DRG 
235, which means these cases reported a procedure code for CABG and a 
cardiothoracic procedure, such as a surgical ablation, without 
procedure codes reporting a PTCA or cardiac catherization. The largest 
number of cases moving out of MS-DRG 229 are moving into MS-DRG 236, 
which again means these cases reported a procedure code for CABG and a 
cardiothoracic procedure, such as a surgical ablation, without 
procedure codes reporting a PTCA or cardiac catherization.
    We also examined the claims data from the September 2020 update of 
the FY 2020 MedPAR file to identify the average length of stay and 
average costs for all cases in MS-DRGs 231, 232, 233, 234, 235 and 236. 
Our findings are shown in the following table.
[GRAPHIC] [TIFF OMITTED] TR13AU21.046

    In reviewing the data analysis performed, the 836 cases in MS-DRG 
228 reporting a procedure code that describes a CABG procedure as well 
as a procedure code describing an open ablation have an average length 
of stay that is longer than the average length of stay for all the 
cases in MS-DRG 235 (12.8 days versus 9.7 days) and higher average 
costs when compared to all the cases in MS-DRG 235 ($60,327 versus 
$44,106). The 824 cases in MS-DRG 229 reporting a procedure code that 
describes a CABG procedure as well as a procedure code describing an 
open ablation also have an average length of stay that is longer than 
the average length of stay for all the cases in MS-DRG 236 (7.9 days 
versus 6.4 days) and higher average costs when compared to all the 
cases in MS-DRG 236 ($39,392

[[Page 44844]]

versus $31,170). The average length of stay and average costs of cases 
reporting a procedure code that describes a CABG procedure as well as a 
procedure code describing an open ablation in MS-DRG 228 as well as a 
secondary diagnosis of MCC are closer aligned to costs of cases in MS-
DRGs 233 (Coronary Bypass with Cardiac Catheterization with MCC) (12.8 
days versus 12.5 days and $60,327 versus $56,388 respectively). The 
average length of stay and average costs of cases reporting a procedure 
code that describes a CABG procedure as well as a procedure code 
describing an open ablation in MS-DRG 229 without secondary diagnosis 
of MCC are closer aligned to costs of cases in MS-DRGs 234 (Coronary 
Bypass with Cardiac Catheterization without MCC) (7.9 days versus 8.5 
days and $39,392 versus $39,406 respectively).
    In response to comments that urged CMS to assign these procedures 
to MS-DRGs that consider the added procedure and device costs required, 
our clinical advisors reviewed these data and continue to state that in 
open concomitant surgical ablation procedures, the CABG, MVR, and/or 
AVR components of the procedure are more technically complex than the 
open surgical ablation procedure. They also state that the proposed 
revision to the surgical hierarchy leads to a grouping that is more 
coherent and better accounts for the resources expended to address the 
more complex procedures from other cases redistributed during the 
hierarchy change. However, in cases where an open ablation is performed 
in combination with a coronary bypass procedure but without a PTCA or 
cardiac catherization procedure also being performed, to better address 
the concerns expressed in the public comments, our clinical advisors 
support the assignment of these cases to MS-DRGs 233 and 234 as an 
enhancement to better reflect the clinical severity and resource use 
involved in these cases. Our clinical advisors also support changing 
the titles of MS-DRGs 233 and 234 to ``Coronary Bypass with Cardiac 
Catheterization or Open Ablation with and without MCC, respectively'' 
to better reflect the assigned procedures.
    Therefore, after consideration of the public comments we received, 
and for the reasons discussed, we are finalizing our proposal to revise 
the surgical hierarchy for the MS-DRGs in MDC 05 to sequence MS-DRGs 
231-236 (Coronary Bypass) above MS-DRGs 228 and 229, effective October 
1, 2021. We refer the reader to section II.D.15. of the preamble of 
this final rule for the discussion of the surgical hierarchy and the 
complete list of our proposed modifications to the surgical hierarchy 
in MDC 05 as well as our finalization of that proposal. In addition, 
after consideration of the public comments we received and for the 
reasons discussed, we are also finalizing the assignment of cases with 
a procedure code describing coronary bypass and a procedure code 
describing open ablation to MS-DRGs 233 and 234 and changing the titles 
of these MS-DRGs to ``Coronary Bypass with Cardiac Catheterization or 
Open Ablation with and without MCC, respectively''.
    As discussed earlier in the proposed rule and in this section, this 
request involved two parts. The second part of the request was to 
reassign cases describing standalone percutaneous endoscopic surgical 
ablation. According to the requestor, standalone, percutaneous 
endoscopic surgical ablation is a rapidly growing therapy, indicated 
for highly symptomatic patients that have already failed medical 
management and/or percutaneous catheter ablation procedures. The 
requestor identified nine ICD-10-PCS codes that they stated describe 
percutaneous endoscopic surgical ablation. These codes and their 
corresponding MDC and MS-DRG assignments are listed in the following 
table.
[GRAPHIC] [TIFF OMITTED] TR13AU21.047

    The requestor performed their own analysis and stated that they 
found the most common MS-DRG assignment for cases describing standalone 
percutaneous endoscopic surgical ablation was MS-DRGs 228 and 229 
(Other Cardiothoracic Procedures with and without MCC, respectively) 
and that in those MS-DRGs, the standalone surgical ablation procedures 
cost more than all the procedures in their currently assigned MS-DRGs 
228 and

[[Page 44845]]

229. Therefore, the requestor recommended CMS reassign these procedures 
to higher weighted MS-DRGs 219 and 220 (Cardiac Valve and Other Major 
Cardiothoracic Procedures without Cardiac Catheterization with MCC and 
with CC, respectively).
    In response to this request, we examined claims data from the March 
2020 update of the FY 2019 MedPAR file for all cases in MS-DRGs 228 and 
229 and compared the results to cases with a procedure code describing 
a standalone percutaneous endoscopic surgical ablation procedure. Our 
findings are shown in the following table.
[GRAPHIC] [TIFF OMITTED] TR13AU21.048

    As shown in the table, the data analysis performed indicates that 
the 99 cases in MS-DRG 228 reporting a procedure code that describes 
percutaneous endoscopic surgical ablation have an average length of 
stay that is shorter than the average length of stay for all the cases 
in MS-DRG 228 (7.1 days versus 10.7 days) and higher average costs when 
compared to all the cases in MS-DRG 228 ($48,281 versus $45,772). The 
497 cases in MS-DRG 229 reporting a procedure code that describes 
percutaneous endoscopic surgical ablation have an average length of 
stay that is shorter than the average length of stay for all the cases 
in MS-DRG 229 (3.7 days versus 5.3 days) and higher average costs when 
compared to all the cases in MS-DRG 229 ($35,516 versus $29,454).
    We then examined the claims data from the March 2020 update of the 
FY 2019 MedPAR file to identify the average length of stay and average 
costs for all cases in MS-DRGs 219 and 220. Our findings are shown in 
the following table.
[GRAPHIC] [TIFF OMITTED] TR13AU21.049

    As shown in the table, for MS-DRG 219, there were a total of 15,597 
cases with an average length of stay of 10.9 days and average costs of 
$57,845. For MS-DRG 220, there were a total of 15,074 cases with an 
average length of stay of 6.5 days and average costs of $39,565.
    We also examined claims data from the September 2020 update of the 
FY 2020 MedPAR file for all cases in MS-DRGs 228 and 229 and compared 
the results to cases with a procedure code describing a standalone 
percutaneous endoscopic surgical ablation procedure. Our findings are 
shown in the following table.

[[Page 44846]]

[GRAPHIC] [TIFF OMITTED] TR13AU21.050

    As shown in the table, the data analysis performed indicates that 
the 84 cases in MS-DRG 228 reporting a procedure code that describes 
percutaneous endoscopic surgical ablation have an average length of 
stay that is shorter than the average length of stay for all the cases 
in MS-DRG 228 (6.9 days versus 10.2 days) and lower average costs when 
compared to all the cases in MS-DRG 228 ($44,710 versus $46,508). The 
393 cases in MS-DRG 229 reporting a procedure code that describes 
percutaneous endoscopic surgical ablation have an average length of 
stay that is shorter than the average length of stay for all the cases 
in MS-DRG 229 (3.4 days versus 4.9 days) and higher average costs when 
compared to all the cases in MS-DRG 229 ($34,237 versus $29,885).
    We then examined the claims data from the September 2020 update of 
the FY 2020 MedPAR file to identify the average length of stay and 
average costs for all cases in MS-DRGs 219 and 220. Our findings are 
shown in the following table.
[GRAPHIC] [TIFF OMITTED] TR13AU21.051

    As shown in the table, for MS-DRG 219, there were a total of 11,863 
cases with an average length of stay of 10.9 days and average costs of 
$61,934. For MS-DRG 220, there were a total of 10,072 cases with an 
average length of stay of 6.5 days and average costs of $41,800.
    As noted in the proposed rule, our analysis indicates that MS-DRGs 
219 and 220 generally have much higher average costs and longer average 
lengths of stay than the cases with a procedure code describing a 
standalone percutaneous endoscopic surgical ablation procedure 
currently assigned to MS-DRGs 228 and 229. Instead, the average costs 
and average length of stay for cases reporting a standalone 
percutaneous endoscopic surgical ablation appear to be generally more 
aligned with the average costs and average length of stay for all cases 
in MS-DRGs 228 and 229, where they are currently assigned. We indicated 
that our clinical advisors reviewed this issue and did not recommend 
changing the assignment of procedure codes describing percutaneous 
endoscopic surgical ablation. Therefore, for the reasons indicated, we 
proposed to maintain the current structure of MS-DRGs 219 and 220.
    Comment: Commenters disagreed with our proposal to maintain the 
current structure of MS-DRGs 219 and 220 and noted that payment for MS-
DRGs 228 and 229 has been trending downward over the last 5 years. Some 
commenters stated that CMS did not provide transparency to the details 
of its analysis to support why standalone hybrid surgical ablation 
procedures should not be moved from MS-DRGs 228 and 229. Another 
commenter stated CMS' proposed decline in payment rates makes it 
impossible for their facility to continue to provide these needed 
procedures to patients suffering from atrial fibrillation. Another 
commenter stated the proposed relative weight does not accurately 
reflect the costs of these device intensive procedures and that there 
has been no transparency into the cause for these significant declines. 
Other commenters asserted that hospitals will be forced to postpone or 
``trim back'' on providing patients access to more complex, resource 
intensive procedures such as these, to better align their costs with 
what they asserted were Medicare's inadequate payment levels. Other 
commenters requested that CMS use its statutory authority to not reduce 
the relative weight and payment for MS-DRGs 228 and 229, which contain 
stand-alone surgical ablation procedures for AF.
    Response: We appreciate the commenters' feedback. We note that we 
did not propose a change to the GROUPER logic of MS-DRGs 228 and 229. 
Our clinical advisors did not recommend changing the assignment of 
procedure codes describing percutaneous endoscopic surgical ablation, 
currently assigned to MS-DRGs 228 and 229, to MS-DRGs 219 and 220. 
Therefore, we proposed to maintain the current structure of MS-DRGs 219 
and 220. This proposal by extension also maintains the current 
structure of MS-DRGs 228 and 229. With regard to the comments about the 
implications for payment in MS-DRGs 228 and 229, we note that the goals 
of assigning or re-assigning procedure codes to MS-DRGs are to better 
clinically represent the resources involved in caring for these 
patients and enhance the overall accuracy of the system. In response to 
the comment that CMS did not provide transparency to

[[Page 44847]]

the details of its analysis in the proposed rule, we provided our 
claims analysis for the cases with a procedure code describing a 
standalone percutaneous endoscopic surgical ablation procedure as well 
as a discussion of that analysis and the basis for our proposal. It is 
unclear from the comments what additional details the commenters are 
referencing.
    In response to the comment that hospitals will be forced to 
postpone or ``trim back'' on providing patients access to these 
procedures in order to better align their costs with Medicare payment 
levels, as we have stated in prior rulemaking, it is not appropriate 
for facilities to deny treatment to beneficiaries needing a specific 
type of therapy or treatment that potentially involves increased costs.
    As we have indicated in the FY 2018 IPPS/LTCH PPS final rule (82 FR 
38103), the FY 2019 IPPS/LTCH PPS final rule (83 FR 41273), the FY 2020 
IPPS/LTCH PPS final rule (84 FR 42167) and the FY 2021 IPPS/LTCH final 
rule (85 FR 58598), we do not believe it is normally appropriate to 
address relative weight fluctuations that appear to be driven by 
changes in the underlying data even if we have addressed relative 
weight fluctuations in specific circumstances such as when a relative 
weight would have declined by more than 20 percent in one year, or in 
instances where we did not have sufficient MedPAR data to set accurate 
and stable cost relative weights for low volume MS-DRGs. We do however 
acknowledge the trending reduction in relative weights for MS-DRGs 228 
and 229 in our ratesetting as reflected in the following chart.
[GRAPHIC] [TIFF OMITTED] TR13AU21.052

BILLING CODE 4120-01-C
    We believe this weight change over time to be appropriately driven 
by the underlying data in the 5 years since CMS began using the ICD-10 
data in calculating the relative weights. We note that there are 809 
ICD-10-PCS codes assigned to the GROUPER logic of MS-DRGs 228 and 229 
in the ICD-10 MS-DRGs Definitions Manual Version 38.1, of which the 
procedure codes describing standalone ablation represent a small 
percentage.
    As stated in the ICD-10 MS-DRG Definitions Manual, ``In each MDC 
there is usually a medical and a surgical class referred to as ``other 
medical diseases'' and ``other surgical procedures,'' respectively. The 
``other'' medical and surgical classes are not as precisely defined 
from a clinical perspective. The other classes would include diagnoses 
or procedures which were infrequently encountered or not well defined 
clinically''. The ICD-10 MS-DRG Definitions Manual also states ``The 
``other'' surgical category contains surgical procedures which, while 
infrequent, could still reasonably be expected to be performed for a 
patient in the particular MDC.'' MS-DRGs 228 and 229 are an example of 
the surgical MS-DRGs that are found within each MDC that include 
``other'' procedures intended to encompass procedures that, while not 
directly related to the MDC, can and do occur with principal diagnoses 
in that MDC with sufficient frequency.
    As displayed in the proposed rule, when we examined claims data 
from the March 2020 update of the FY 2019 MedPAR file for all cases in 
MS-DRGs 228 and 229 and compared the results to cases with a procedure 
code describing a standalone percutaneous endoscopic surgical ablation 
procedure, the 99 cases in MS-DRG 228 reporting a procedure code that 
describes percutaneous endoscopic surgical ablation represent only 2% 
of the 4,436 total cases in MS-DRG 228. The 497 cases in MS-DRG 229 
reporting a procedure code that describes percutaneous endoscopic 
surgical ablation represent only 9% of the 5,250 total cases in MS-DRG 
229.
    Similarly, when we examined claims data from the September 2020 
update of the FY 2020 MedPAR file for all cases in MS-DRGs 228 and 229 
and compared the results to cases with a procedure code describing a 
standalone percutaneous endoscopic surgical ablation procedure, the 84 
cases in MS-DRG 228 reporting a procedure code that describes 
percutaneous endoscopic surgical ablation represent only 2% of the 
4,419 total cases in MS-DRG 228. The 393 cases in MS-DRG 229 reporting 
a procedure code that describes percutaneous endoscopic surgical 
ablation represent only 8% of the 4,732 total cases in MS-DRG 229.
    We also note that each year, we calculate the relative weights by 
dividing the average cost for cases within each MS-DRG by the average 
cost for cases across all MS-DRGs. It is to be expected that when MS-
DRGs are restructured, such as when procedure codes are reassigned or 
the hierarchy within an MDC is revised, resulting in

[[Page 44848]]

a different case-mix within the MS-DRGs, the relative weights of the 
MS-DRGs will change as a result. Over the past five years, there have 
been changes to the structure of MS-DRGS 228 and 229. Specifically, in 
the FY 2017 IPPS/LTCH PPS final rule (81 FR 56809 through 56813), we 
finalized our proposal to collapse MS-DRGs 228, 229, and 230 from three 
severity levels to two severity levels by deleting MS-DRG 230 and 
revised the structure of MS- DRG 229. We also finalized our proposal to 
reassign ICD-9-CM procedure code 35.97 and the cases reporting ICD-10-
PCS procedure code 02UG3JZ (Supplement mitral valve with synthetic 
substitute, percutaneous approach) from MS-DRGs 273 and 274 to MS-DRG 
228 and revised the titles of MS-DRG 228 and 229. In the FY 2020 IPPS/
LTCH PPS final rule (84 FR 42080 through 56813) we finalized our 
proposal to modify the structure of MS-DRGs 266 and 267 by reassigning 
ICD-10-PCS procedure code 02UG3JZ describing a transcatheter mitral 
valve repair with implant procedure from MS-DRGs 228 and 229 to MS-DRGs 
266 and 267 and revised the titles of MS- DRG 266 and 267. Finally, as 
discussed in the FY 2022 IPPS/LTCHPPS proposed rule, and earlier in 
this section, we proposed to revise the surgical hierarchy for the MS-
DRGs in MDC 05 to sequence MS-DRGs 231-236 (Coronary Bypass) above MS-
DRGs 228 and 229 for FY 2022. Therefore, the data appear to reflect 
that the difference in the relative weights reflected in Table 5 -List 
of Medicare Severity Diagnosis Related Groups (MS-DRGs), Relative 
Weighting Factors, and Geometric and Arithmetic Mean Length of Stay 
associated with final rule for the applicable fiscal year can be 
attributed to the fact that the finalization of these proposals 
resulted in a different case-mix within the MS-DRGs which is then being 
reflected in the relative weights. We refer the reader to section II.E. 
of the preamble of this FY 2022 IPPS/LTCH PPS final rule for a complete 
discussion of the relative weight calculations.
    Comment: A few commenters noted that hybrid standalone percutaneous 
endoscopic surgical ablation includes both a minimally invasive 
surgical ablation performed by a surgeon and catheter ablation 
performed by an electrophysiologist in the same hospital visit, and 
stated that the downward payment trend for the MS-DRGs 228 and 229 has 
resulted in hospitals being undercompensated for the costs of 
furnishing standalone hybrid percutaneous endoscopic surgical ablation 
procedures for AF. These commenters proposed two possible remedies to 
this underpayment, that CMS either (1) maintain the relative weights of 
MS-DRGs 228 and 229 for a year and then reassess the data, or (2) 
assign cases reporting procedure codes describing standalone 
percutaneous endoscopic surgical ablation from MS-DRGs 228 and 229 to 
the higher (MCC) severity level MS-DRG of its current base MS-DRG 
assignment, which is MS-DRG 228 (Other Cardiothoracic Procedures with 
MCC), to prevent underpayment for these procedures.
    Response: We appreciate the commenter's suggestions. In response to 
the request that CMS maintain the relative weights of MS-DRGs 228 and 
229 for a year, as stated in response to similar comments expressed by 
other commenters, we believe the weight change in these MS-DRGs over 
time to be appropriately driven by the underlying data. In response to 
the request that CMS assign cases reporting procedure codes describing 
standalone percutaneous endoscopic surgical ablation from MS-DRGs 228 
and 229 to the higher (MCC) severity level MS-DRG of its current base 
MS-DRG assignment, we examined the claims analysis as presented in the 
proposed rule and earlier in this section. Using the March 2020 update 
of the FY 2019 MedPAR file, the 497 cases in MS-DRG 229 reporting a 
procedure code that describes percutaneous endoscopic surgical ablation 
without a secondary diagnosis designated as an MCC have an average 
length of stay that is shorter than the average length of stay for all 
the cases in MS-DRG 228 (3.7 days versus 10.7 days) and lower average 
costs when compared to all the cases in MS-DRG 228 ($35,516 versus 
$45,772). Similarly, using the September 2020 update of the FY 2020 
MedPAR file, the 393 cases in MS-DRG 229 reporting a procedure code 
that describes percutaneous endoscopic surgical ablation without a 
secondary diagnosis designated as an MCC have an average length of stay 
that is shorter than the average length of stay for all the cases in 
MS-DRG 228 (3.4 days versus 10.2 days) and lower average costs when 
compared to all the cases in MS-DRG 228 ($34,237 versus $46,508). Our 
clinical advisors reviewed this analysis and do not support 
reassignment of cases reporting a procedure code that describes 
percutaneous endoscopic surgical ablation without a secondary diagnosis 
designated as an MCC from MS-DRG 229 to MS-DRG 228 based on this claims 
data analysis. Our advisors stated it would not be appropriate to 
reassign these cases into the higher severity level MS-DRG in the 
absence of an MCC and noted that the cases would not be clinically 
coherent with regard to resource utilization as reflected in the 
differences in average costs and average lengths of stay. As additional 
claims data becomes available, we will continue to analyze the clinical 
nature of procedure codes that describe percutaneous endoscopic 
surgical ablation and their MS-DRG assignments to further improve the 
overall accuracy of the IPPS payments in future rulemaking.
    Therefore, after consideration of the public comments we received, 
and for the reasons stated earlier, we are finalizing our proposal to 
maintain the current structure of MS-DRGs 219 and 220 for FY 2022.
f. Drug-Eluting Stents
    In the FY 2022 IPPS/LTCH PPS proposed rule (86 FR 25121 through 
25122), we discussed a request we received to review the MS-DRG 
assignments of claims involving the insertion of coronary stents in 
percutaneous coronary interventions. The requestor suggested that CMS 
eliminate the distinction between drug-eluting and bare-metal coronary 
stents in the MS-DRG classification. According to the requestor, coated 
stents have a clinical performance comparable to drug-eluting stents 
however they are grouped with bare-metal stents because they do not 
contain a drug. The requestor asserted that this comingling muddies the 
clinical coherence of the MS-DRG structure, as one cannot infer 
distinctions in clinical performance or benefits among the groups and 
potentially creates a barrier (based on hospital decision-making) to 
patient access to modern coated stents.
    The requestor listed the following MS-DRGs in its request.
     MS-DRG 246 (Percutaneous Cardiovascular Procedures with 
Drug-Eluting Stent with MCC or 4+ Arteries or Stents);
     MS-DRG 247 (Percutaneous Cardiovascular Procedures with 
Drug-Eluting Stent without MCC);
     MS-DRG 248 (Percutaneous Cardiovascular Procedures with 
Non-Drug-Eluting Stent with MCC or 4+ Arteries or Stents); and
     MS-DRG 249 (Percutaneous Cardiovascular Procedures with 
Non-Drug-Eluting Stent without MCC).
    According to the requestor, the non-drug-eluting stent MS-DRGs have 
outlived their usefulness in the stent market. The requestor performed 
its own analysis of MedPAR data from FY 2015 through FY 2019 and stated 
that it found the volume of cases describing non-drug-eluting coronary 
stents has

[[Page 44849]]

declined since 2015, culminating in FY 2019, with drug-eluting stents 
accounting for 96.1% of all stent cases within the Medicare program, 
while non-drug-eluting stents accounted for only 3.9% that year. The 
requestor asserted that the assignment of coated stents to the non-
drug-eluting stent category creates a market distortion as this newer 
technology is being comingled with very old technology at a payment 
disadvantage large enough to influence hospitals' willingness to 
prescribe, while at the same time acknowledging that the separation in 
average charges and costs between the non-drug-eluting stent category 
and the drug-eluting stent category is minimal in their analysis of the 
claims data.
    In the proposed rule, based on a review of the procedure codes that 
are currently assigned to MS-DRGs 246, 247, 248 and 249, we indicated 
that our clinical advisors agreed that further refinement of these MS-
DRGs may be warranted. However, we noted that in ICD-10-PCS, a stent is 
considered an intraluminal device. The distinction between drug-eluting 
and non-drug eluting intraluminal devices is found elsewhere in the 
ICD-10-PCS procedure code classification and evaluating this request 
requires a more extensive analysis to assess potential impacts across 
the MS-DRGs. For these reasons, at this time, we indicated that our 
clinical advisors recommended that rather than evaluating the procedure 
codes assigned to MS-DRGs 246, 247, 248 and 249 in isolation, 
additional analysis should be performed for this subset of procedure 
codes across the MS-DRGs, as part of the comprehensive procedure code 
review described in section II.D.11. of the preamble of the proposed 
rule and this final rule. Therefore, we indicated we believed it would 
be more appropriate to consider this request further during our 
comprehensive procedure code review in future rulemaking.
    Comment: We received a comment expressing concern that the 
existence of a payment differential between drug-eluting and bare-metal 
stents continues to prevent access for patients who are not able to 
obtain the clinical benefits of modern coated stents due to hospital 
margin concerns. The commenter stated that multiple clinical studies 
have consistently proven that the clinical safety and effectiveness of 
their cardiovascular coated stent is more similar to drug-eluting 
coronary stents when compared to bare-metal-stents. This commenter 
urged CMS to take timely action in refining the MS-DRGs to remedy the 
patient access issue, respectfully requested that CMS complete its 
analysis in time for the FY 2023 IPPS proposed rule, and also requested 
that CMS confirm the timing in this FY 2022 IPPS final rule.
    Response: We appreciate the commenter's comments. We note that the 
distinction between drug eluting and non-drug-eluting stents has long 
existed in the classification. In the FY 2003 IPPS/LTCH PPS final rule 
(67 FR 50003 through 50005), we created two new temporary CMS DRGs to 
reflect cases involving the insertion of a drug-eluting coronary artery 
stent as signified by the presence of code ICD-9-CM procedure code 
36.07 (Insertion of drug-eluting coronary artery stent): CMS DRG 526 
(Percutaneous Cardiovascular Procedure With Drug- Eluting Stent With 
AMI); and CMS DRG 527 (Percutaneous Cardiovascular Procedure With Drug-
Eluting Stent Without AMI) to parallel existing CMS DRGs 516 
(Percutaneous Cardiovascular Procedure with Acute Myocardial Infarction 
(AMI)) and 517(Percutaneous Cardiovascular Procedure with Coronary 
Artery Stent without AMI). Although the FDA had not yet approved the 
technology for use, at the time public presentation of the results from 
clinical trials found virtually no in-stent restenosis in patients 
treated with the drug-eluting stent. Therefore, we stated temporary CMS 
DRGs 526 and 527 CMS DRGs were created effective for discharges 
occurring on or after April 1, 2003 in recognition of the potentially 
significant impact this technology may conceivably have on the 
treatment of coronary artery blockages, the predictions of its rapid, 
widespread use, and that the higher costs of this technology could 
create undue financial hardships for hospitals due to the high volume 
of stent cases. The FDA ultimately approved drug-eluting stents for use 
in April 2003.
    In the FY 2006 IPPS/LTCH PPS (70 FR 47292 through 47295), we 
deleted CMS DRGs 516, 517, 526, and 527 and created four new CMS DRGs 
in their places. We stated that rather than divide the CMS DRG pairs 
based on whether the patient had an acute myocardial (AMI), we split 
each pair of CMS DRGs based on the presence or absence of a major 
cardiovascular condition to identify subgroups of significantly more 
severe patients who use greater hospital resources more accurately than 
was possible under the previous CMS DRGs. The new CMS DRG titles were: 
CMS DRG 555 (Percutaneous Cardiovascular Procedure with Major 
Cardiovascular Diagnosis); CMS DRG 556 (Percutaneous Cardiovascular 
Procedure with Non- Drug-Eluting Stent without Major Cardiovascular 
Diagnosis); CMS DRG 557 (Percutaneous Cardiovascular Procedure with 
Drug-Eluting Stent with Major Cardiovascular Diagnosis) (formerly CMS 
DRG 526); and CMS DRG 558 (Percutaneous Cardiovascular Procedure with 
Drug- Eluting Stent without Major Cardiovascular Diagnosis). In the FY 
2008 IPPS/LTCH PPS final rule we adopted the MS-DRGs and in that rule 
(72 FR 47259 through 47260) we stated we found that PTCAs with four or 
more vessels or four or more stents were more comparable in average 
charges to the higher weighted DRG in the group and made changes to the 
GROUPER logic. Claims containing ICD-9-CM procedure code 00.66 for 
PTCA, and code 36.07 (Insertion of drug-eluting coronary artery 
stent(s)), and code 00.43 (Procedure on four or more vessels) or code 
00.48 (Insertion of four or more vascular stents) were assigned to MS-
DRG 246 (formerly 557). In addition, claims containing ICD-9-CM 
procedure code 00.66 for PTCA, and code 36.06 (Insertion of non-drug 
eluting coronary artery stent(s)), and code 00.43 or code 00.48 were 
assigned to MS-DRG 248 (formerly 555). We also made conforming changes 
to the MS-DRG titles as follows: MS-DRG 246 was titled ``Percutaneous 
Cardiovascular Procedures with Drug-Eluting Stent(s) with MCC or 4 or 
more Vessels/Stents''. MS-DRG 248 was titled ``Percutaneous 
Cardiovascular Procedures with Non-Drug-Eluting Stent(s) with MCC or 4 
or more Vessels/Stents''. The title for MS-DRGs 247 (formerly 558) and 
249 (formerly 556) remained unchanged. In FY 2018 IPPS/LTCH PPS Final 
rule (82 FR 38024) we finalized our proposal to revise the title of MS- 
DRG 246 to ``Percutaneous Cardiovascular Procedures with Drug- Eluting 
Stent with MCC or 4+ Arteries or Stents'' and the title of MS-DRG 248 
to ``Percutaneous Cardiovascular Procedures with Non-Drug-Eluting Stent 
with MCC or 4+ Arteries or Stents'' to better reflect the ICD-10-PCS 
terminology of ``arteries'' versus ``vessels'' as used in the procedure 
code titles within the classification.
    We also again note the distinction between drug-eluting and non-
drug eluting intraluminal devices is found elsewhere in the ICD-10-PCS 
procedure code classification. This distinction is not limited to 
procedures describing coronary interventions. A more extensive analysis 
is needed to assess the potential impacts across the MS-DRGs to avoid 
unintended consequences or missed opportunities in most appropriately 
capturing the resource utilization and clinical coherence for this 
subset of procedures.

[[Page 44850]]

    In response to the commenter's concern that the existence of a 
payment differential between drug-eluting and bare-metal stents 
continues to prevent access for patients, as we have stated in prior 
rulemaking, it is not appropriate for facilities to deny treatment to 
beneficiaries needing a specific type of therapy or treatment that 
potentially involves increased costs. In response to the commenter's 
request that CMS complete its analysis of the classification in time 
for the FY 2023 IPPS proposed rule, we note that the comprehensive 
procedure code review will be a multi-year project. As indicated in 
section II.D.11. of the preamble of the proposed rule and this final 
rule, we will provide more detail on this analysis and the methodology 
for conducting this review in future rulemaking.
    After consideration of the public comments we received, and for the 
reasons discussed, we are not making changes in this final rule to the 
MS-DRG assignments of claims involving the insertion of coronary stents 
in percutaneous coronary interventions, and we will further consider 
this issue in future rulemaking.
6. MDC 08 (Diseases and Disorders of the Musculoskeletal System and 
Connective Tissue)
a. Knee Joint Procedures
    In the FY 2022 IPPS/LTCH PPS proposed rule (86 FR 25122), we 
discussed a request we received to examine the procedure code 
combinations for procedures describing a right knee joint removal and 
replacement and procedures describing a left knee joint removal and 
replacement in MS-DRGs 466, 467, and 468 (Revision of Hip or Knee 
Replacement with MCC, with CC, and without CC/MCC, respectively). 
According to the requestor, when using the MS-DRG GROUPER software 
version 37, the left knee joint procedure combinations group correctly 
to MS-DRG 468, while the exact same right knee procedure code 
combinations group incorrectly to MS-DRG 465 (Wound Debridement and 
Skin Graft Except Hand for Musculoskeletal and Connective Tissue 
Disorders without CC/MCC).
    The requestor provided the following procedure codes that describe 
the procedure code combinations for the left knee joint removal and 
replacement procedures currently assigned to MS-DRGs 466, 467, and 468.
BILLING CODE 4120-01-P
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BILLING CODE 4120-01-C
    The requestor also provided the following procedure codes that 
describe the procedure code combinations for right knee joint removal 
and replacement procedures for CMS' review and consideration.
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[[Page 44851]]

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BILLING CODE 4120-01-C
    In the proposed rule, we noted that we reviewed the procedure code 
combinations listed and agree with the requestor that the procedure 
codes that describe the procedure code combinations for right knee 
joint removal and replacement procedures were inadvertently excluded 
from the logic for MS-DRGs 466, 467, and 468.
    We also noted that during our review of the previously listed 
procedure code combinations describing removal and replacement of the 
right and left knee joints, we identified additional MS-DRGs in which 
the listed procedure code combinations for the left knee joint are in 
the logic, however, the listed procedure code combinations for the 
right knee joint were inadvertently excluded from the logic. 
Specifically, the listed procedure code combinations describing removal 
and replacement of the left knee joint are also included in the logic 
for case assignment to MS-DRGs 461 and 462 (Bilateral or Multiple Major 
Joint Procedures of Lower Extremity with and without MCC, respectively) 
in MDC 08 and in the logic for case assignment to MS-DRGs 628, 629, and 
630 (Other Endocrine, Nutritional and Metabolic O.R. Procedures with 
MCC, with CC, and without CC/MCC, respectively) in MDC 10 (Endocrine, 
Nutritional and Metabolic Diseases and Disorders). Our clinical 
advisors stated that the procedure code combinations describing removal 
and replacement of the right knee joint should be added to MS-DRGs 461, 
462, 466, 467, and 468 in MDC 08 and MS-DRGs 628, 629, and 630 in MDC 
10 for consistency with the procedure code combinations describing 
removal and replacement of the left knee joint that are currently 
assigned to those MS-DRGs. We stated that adding these procedure codes 
will improve clinical coherence and ensure more appropriate MS-DRG 
assignment for these cases.
    Therefore, for FY 2022, we proposed to add the three procedure code 
combinations listed previously describing removal and replacement of 
the right knee joint that were inadvertently omitted from the logic to 
MS-DRGs 461, 462, 466, 467, and 468 in MDC 08 and MS-DRGs 628, 629, and 
630 in MDC 10.
    Comment: Several commenters supported the proposal to add the three 
procedure code combinations listed previously describing removal and 
replacement of the right knee joint that were inadvertently omitted 
from the logic to MS-DRGs 461, 462, 466, 467, and 468 in MDC 08 and to 
MS-DRGs 628, 629, and 630 in MDC 10. A few commenters also recommended 
that CMS conduct further review to determine whether additional 
combinations may be currently excluded from the logic for these MS-
DRGs.
    Another commenter who supported our proposal stated they found the 
following 11 additional combinations that appeared to be missing from 
the logic for MS-DRGs 628, 629, and 630 in MDC 10.
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[[Page 44852]]

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BILLING CODE 4120-01-C
    This commenter also noted the difficulty in analyzing the logic 
list as some code combinations display the Removal code first and other

[[Page 44853]]

combinations display the Replacement code first.
    Response: We appreciate the commenters' support. We thank the 
commenters for their feedback and agree with the commenter's findings 
of the 11 additional code combinations inadvertently missing from the 
logic for MS-DRGs 628, 629, and 630 in MDC 10. We performed further 
analysis to determine if other combinations may be inadvertently 
missing and did not find any.
    In response to the commenter's feedback regarding the format in 
which the Removal and Replacement codes are displayed in the logic, we 
note that we are working with our contractor, 3M HIS, to evaluate 
modifications to the logic list in these MS-DRGs that are defined by 
such combinations and reflected in the ICD-10 MS-DRG Definitions Manual 
to refine how the logic list may be better displayed.
    After consideration of the public comments received, we are 
finalizing our proposal to add the three procedure code combinations 
listed previously describing removal and replacement of the right knee 
joint that were inadvertently omitted from the logic to MS-DRGs 461, 
462, 466, 467, and 468 in MDC 08 and MS-DRGs 628, 629, and 630 in MDC 
10 and are adding the 11 additional code combinations listed that were 
provided by the commenter to the logic for MS-DRGs 628, 629, and 630 in 
MDC 10 for FY 2022.
b. Pelvic Trauma With Internal Fixation
    In the FY 2022 IPPS/LTCH PPS proposed rule (86 FR 25123), we 
discussed a request we received to reassign cases reporting a diagnosis 
code describing a pelvic fracture in combination with a procedure code 
describing repair of a pelvic fracture with internal fixation, from the 
lower (NonCC) severity level MS-DRG of its current base MS-DRG 
assignment to the higher (MCC) severity level MS-DRG of its current 
base MS-DRG assignment. According to the requestor, there has been 
steady growth in the volume of internal fixation procedures performed 
for pelvic fractures since 2008. The requestor stated that due to this 
growth rate and the anticipated increase in utilization of these 
internal fixation devices in these procedures in the future that CMS 
should reconsider the payment structure for these cases it referred to 
as ``internal fixation for pelvic trauma''.
    The requestor provided data for the Healthcare Common Procedural 
Coding System (HCPCS) code G0413 (Percutaneous skeletal fixation of 
posterior pelvic bone fracture and/or dislocation, for fracture 
patterns which disrupt the pelvic ring, unilateral or bilateral, 
(includes ileum, sacroiliac joint and/or sacrum) and Current Procedural 
Terminology (CPT) code 22848 (Pelvic fixation (attachment of caudal end 
of instrumentation to pelvic bony structures) other than sacrum) from 
2008 through 2018 that it cross walked to ICD-10-PCS procedure codes. 
The requestor stated that this CPT coded data indicated that physicians 
have used pelvic fracture fixation, and pelvic instrumentation, for an 
increasing number of trauma/fracture repair cases, demonstrating 
expanded use of these devices in the pelvic area overall.
    The requestor reported that sacral fractures are often 
underdiagnosed and once the diagnosis is made, bedrest is common, 
although prolonged bedrest is not recommended for the elderly. In 
addition, the requestor stated that pelvic fractures may be isolated or 
they may be associated with surrounding structures. For example, the 
requester reported that the sacroiliac joint is involved in 
approximately 30 to 35% of pelvic fracture cases. According to the 
requestor, the standard of care has also transitioned, from bedrest-
only to surgery, and current medical practice has evolved to lower the 
threshold for fracture repair surgery. For instance, the requestor 
stated that smaller 5mm fractures that were once left untreated now 
have standard treatment protocols involving the use of pelvic 
instrumentation. As a result, the requestor asserted that there will be 
greater utilization of internal fixation devices to treat these smaller 
pelvic fractures.
    The requestor provided the following procedure codes that it stated 
describe procedures involving the use of internal fixation devices for 
pelvic fracture repair.
BILLING CODE 4120-01-P
[GRAPHIC] [TIFF OMITTED] TR13AU21.056

BILLING CODE 4120-01-C
    The requestor also provided the following diagnosis code 
subcategories that it stated identify diagnoses describing pelvic 
fracture.
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[[Page 44854]]

[GRAPHIC] [TIFF OMITTED] TR13AU21.057

BILLING CODE 4120-01-C
    The requestor performed its own analysis of claims data and 
reported findings for cases reporting a combination of the diagnosis 
codes found in the listed diagnosis code subcategories and the listed 
procedure codes (internal fixation for pelvic trauma) for MS-DRGs 515, 
516, and 517 (Other Musculoskeletal System and Connective Tissue O.R. 
Procedures with MCC, with CC, and without CC/MCC, respectively); MS-
DRGs 907, 908, and 909 (Other O.R. Procedures for Injuries with MCC, 
with CC, and without CC/MCC, respectively); and MS-DRGs 957, 958, and 
959 (Other O.R. Procedures for Multiple Significant Trauma with MCC, 
with CC, and without CC/MCC, respectively). According to the requestor, 
its findings support reassignment of these internal fixation for pelvic 
trauma cases from the lower severity level MS-DRG 517 to the higher 
severity level MS-DRG 515, from the lower severity level MS-DRG 909 to 
the higher severity level 907, and from the lower severity level MS-DRG 
959 to the higher severity level 957. The requestor suggested that 
approximately 2,000 cases would be impacted by its recommendation to 
reassign internal fixation for pelvic trauma cases. The requestor also 
stated that these internal fixation for pelvic trauma cases currently 
result in a high rate of CMS outlier payments to institutions that 
perform a high volume of these procedures. Finally, the requestor 
stated that there is precedent for reassignment of cases from the lower 
severity level MS-DRGs to the higher severity level MS-DRG for cases 
involving the use of a device in orthopedic surgery. The requestor 
provided the examples of total ankle replacement procedures, spinal 
disc replacement procedures and neurostimulator implantation procedures 
to demonstrate how CMS has previously reassigned cases from the lower 
severity level MS-DRG to the higher severity level MS-DRG.
    We noted in the proposed rule that we first examined the claims 
data from the March 2020 update of the FY 2019 MedPAR file and the 
September 2020 update of the FY 2020 MedPAR file for all cases in MS-
DRGs 515, 516, and 517; MS-DRGs 907, 908, and 909; and MS-DRGs 957, 
958, and 959. Our findings are shown in the following tables.
BILLING CODE 4120-01-P
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[[Page 44855]]


[GRAPHIC] [TIFF OMITTED] TR13AU21.059

BILLING CODE 4120-01-C
    We then examined claims data from the March 2020 update of the FY 
2019 MedPAR file and the September 2020 update of the FY 2020 MedPAR 
file for cases reporting any combination of the diagnosis and procedure 
codes that the requestor provided to identify internal fixation for 
pelvic trauma cases in MS-DRGs 515, 516, and 517; MS-DRGs 907, 908, and 
909; and MS-DRGs 957, 958, and 959.
    We noted in the proposed rule that our analysis identified two 
types of cases in which the combination of a diagnosis code and a 
procedure code (that the requestor provided to identify internal 
fixation for pelvic trauma cases) was reported. The first type of case 
consisted of a diagnosis code describing a pelvic fracture reported in 
combination with a single procedure code describing repair of a pelvic 
fracture with internal fixation on a claim, and the second type of case 
consisted of a diagnosis code describing a pelvic fracture reported in 
combination with two procedure codes describing repair of a pelvic 
fracture with internal fixation (for example, one for the right side 
and one for the left side) on a claim. These cases are described as 
single and bilateral internal fixation procedures for pelvic trauma, 
respectively. We refer the reader to Tables 6P.1h and 6P.1i associated 
with the proposed rule and this final rule (which are available via the 
internet on the CMS website at: https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/AcuteInpatientPPS) for the list of diagnosis 
and procedure code combinations reflecting single internal fixation for 
pelvic trauma procedures reported by case ID in each MS-DRG, by fiscal 
year, along with the detailed claims analysis. We refer the reader to 
Tables 6P.1j and 6P.1k associated with the proposed rule and this final 
rule (which are available via the internet on the CMS website at: 
https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/AcuteInpatientPPS) for the list of diagnosis and procedure code 
combinations reflecting bilateral internal fixation for pelvic trauma 
procedures reported by case ID in each MS-DRG, by fiscal year, along 
with the detailed claims analysis. For example, Table 6P.1h shows the 
claims data analysis findings from the March 2020 update of the FY 2019 
MedPAR file. Line 2 identifies the section for single cases reported in 
MS-DRG 515, line 13 identifies the section for single cases reported in 
MS-DRG 516, and line 42 identifies the single cases reported in MS-DRG 
517. The following table summarizes the information found in each 
column of the tables.
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[[Page 44856]]


BILLING CODE 4120-01-C
    As shown in Table 6P.1h, line 4, column A, displays the Case ID 
``Single-A'' for the first case; column B displays MS-DRG 515; column C 
displays the diagnosis code S32.111A; column D displays the description 
of the diagnosis code (Minimally displaced Zone 1 fracture of sacrum, 
initial encounter for closed fracture); column E displays the procedure 
code 0QS234Z; column F displays the description of the procedure code 
(Reposition right pelvic bone with internal fixation device, 
percutaneous approach); column G displays the case count 1; column H 
displays an average length of stay of 3.0 days ; column I displays 
average costs of $8,433 for the case; column J displays the frequency 
of the procedure reported was one (1) occurrence; column K displays a 
3.0 day length of stay for the case; and column L displays $8,433 for 
the cost of the case.
    We also noted that in our analysis of the claims data from the 
March 2020 update of the FY 2019 MedPAR file, we found that there were 
no cases reporting any combination of the diagnosis codes and procedure 
codes previously listed in MS-DRGs 907, 908, and 909 or MS-DRGs 957, 
958, and 959. Our findings are shown in the following table for any 
cases found to report a diagnosis code describing a pelvic trauma in 
combination with a procedure code describing single internal fixation 
in MS-DRGs 515, 516, and 517.
BILLING CODE 4120-01-P
[GRAPHIC] [TIFF OMITTED] TR13AU21.061

BILLING CODE 4120-01-C
    As shown in the table, there were only three cases found in MS-DRG 
517 reporting single internal fixation for pelvic trauma procedures, 
with an average length of stay of 5.33 days and average costs of 
$12,147. The average length of stay is longer and the average costs of 
these three cases higher compared to the average length of stay and the 
average costs for all cases in MS-DRG 517 (5.33 days versus 2.6 days 
and $12,147 versus $10,316, respectively); however, overall, we believe 
the data findings are comparable. We stated that our clinical advisors 
did not support reassignment of the three cases from MS-DRG 517 to MS-
DRG 515 based on the claims data analysis and also stated it would not 
be appropriate to reassign these cases into the higher severity level 
MS-DRG in the absence of a MCC and noted that the cases would not be 
clinically coherent with regard to resource utilization.
    In the proposed rule we noted that in our analysis of the claims 
data from the March 2020 update of the FY 2019 MedPAR file for cases in 
which a bilateral internal fixation for pelvic trauma procedure was 
performed, we identified one case in MS-DRG 517. As shown in Table 
6P.1j, the average length of stay for this case was 4.0 days and the 
average costs were $24,258, which is longer than the average length of 
stay and greater than the average costs for all cases in MS-DRG 517 
(2.6 days and $10,316, respectively). We also identified cases 
reporting various code combinations for MS-DRGs 515 and 516, and 
provide the details in Table 6P.1j associated with the proposed rule 
and this final rule (which is available via the internet on the CMS 
website at: https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/AcuteInpatientPPS).
    We also noted that in our analysis of the claims data from the 
September 2020 update of the FY 2020 MedPAR file we found that there 
were no cases reporting any combination of the diagnosis codes and 
procedure codes previously listed in MS-DRG 909 or in MS-DRGs 957, 958, 
and 959. Our findings are shown in the following table for any cases 
found to report a diagnosis code describing a pelvic trauma in 
combination with a procedure code describing single internal fixation 
in MS-DRGs 515, 516, 517, 907, and 908.
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BILLING CODE 4120-01-C
    As shown in the table, there were only four cases found in MS-DRG 
517 reporting single internal fixation for pelvic trauma procedures, 
with an average length of stay of 2.5 days and average costs of 
$10,136. For the same reasons described previously based on the FY 2019 
analysis, our clinical advisors did not support reassignment of the 
cases in the lower severity level MS-DRG 517 to the higher severity 
level MS-DRG 515. In addition, the average length of stay and average 
costs for these four cases reporting single internal fixation for 
pelvic trauma procedures are less than the average length of stay and 
average costs for all the cases in MS-DRG 517 (2.5 days versus 2.6 days 
and $10,136 versus $11,301, respectively); however, overall, we believe 
the data findings are comparable.
    As indicated in the proposed rule, in our analysis of the claims 
data from the September 2020 update of the FY 2020 MedPAR file for 
cases in which a bilateral internal fixation for pelvic trauma 
procedure was performed, we identified one case in MS-DRG 517. As shown 
in Table 6P.1k, the average length of stay for this case was 2.0 days 
and the average costs were $10,103, which is shorter than the average 
length of stay and less than the average costs for all cases in MS-DRG 
517 (2.6 days and $11,301, respectively). We also identified cases 
reporting various combinations for MS-DRGs 515, 516 and MS-DRG 907, and 
provide the details in Table 6P.1k associated with the proposed rule 
and this final rule (which is available via the internet on the CMS 
website at: https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/AcuteInpatientPPS).
    We stated we believe further analyses of these internal fixation 
for pelvic trauma cases in the claims data is warranted. We noted that 
our analysis for both the single and bilateral cases was centered on 
the reporting of a principal diagnosis code describing a pelvic trauma 
(fracture) in combination with a procedure code describing internal 
fixation based on the codes provided by the requestor. However, we also 
identified cases in the claims data in which a pelvic trauma diagnosis 
code was reported as a secondary diagnosis code in combination with a 
procedure code describing internal fixation and believe these cases 
require further evaluation. In addition, during our review of the 
diagnosis and procedure codes that the requestor provided, we 
identified diagnosis codes that we believe do not warrant consideration 
for purposes of this request and additional procedure codes that 
describe internal fixation for pelvic trauma procedures, which we 
believe do warrant further analysis. For example, as previously noted, 
the requestor provided the subcategories for the diagnosis codes that 
it requested we consider for analysis. We do not agree that diagnosis 
codes describing a pelvic fracture that include the term ``sequela'' 
should be considered in the analysis to examine this request because, 
in the ICD-10-CM classification, the term sequela is defined as the 
residual effect (condition produced) after the acute phase of an 
illness or injury has terminated.
    As noted in the proposed rule, we referred the reader to Table 
6P.1g for the list of diagnosis codes that are included in the 
diagnosis subcategories provided by the requestor and the list of 
procedure codes provided by the requestor, which also contains the 
procedure codes we identified. We stated that additional time is needed 
for data analysis given the volume of these code combinations and 
corresponding data. We also stated we believe that additional time is 
needed to allow for further analysis of the claims data to determine 
the causes of the fractures and other possible contributing factors 
with respect to the length of stay and costs of these cases, as well as 
the rate of outlier payments as identified by the requestor. We noted 
that our clinical advisors also believe that future data findings may 
demonstrate additional variance in resource utilization for this 
patient population. We further noted that, as discussed in the FY 2021 
IPPS/LTCH PPS final rule, we finalized the addition of 161 procedure 
codes to MS-DRGs 957, 958, and 959 in MDC 24 (Multiple Significant 
Trauma) that include the insertion of internal fixation devices. We 
stated we believe it would be beneficial to examine future claims data 
to determine if there is a change in the volume of cases in those 
specific MS-DRGs as a result of that update. For these reasons, we 
proposed to maintain the structure of MS-DRGs 515, 516, and 517; MS-
DRGs 907, 908, and 909; and MS-DRGs 957, 958, and 959 for FY 2022.
    Comment: Some commenters agreed with CMS that additional analysis 
would be beneficial for the reasons discussed in the proposed rule. A 
commenter also suggested that as part of the additional analysis, CMS 
should also analyze cases involving trauma activations. According to 
the commenter, the most common reason for treatment of Medicare 
patients by a trauma center is falls with a high rate of associated 
fractures, especially hip fractures. This commenter stated that in

[[Page 44858]]

addition to trauma programs' readiness, activation and coordinated 
care, designated and verified programs are required to engage in injury 
prevention. The commenter further stated their belief that since falls 
are the single largest traumatic event for Medicare beneficiaries and 
trauma centers, CMS should engage in policies designed to prevent falls 
and mitigate the incidence of hip and extremity fractures which are a 
major source of disability for seniors. The commenter provided examples 
such as making beneficiary data available on ED visits and hospital 
admissions for falls sorted by geographic location and the treating 
hospital and including the source of admission for these beneficiaries. 
The commenter stated that with appropriate incentives, hospitals could 
direct injury prevention efforts in collaboration with community 
organizations, nursing facilities and senior centers to assist with 
proven fall prevention interventions such as installing safety 
equipment (for example, grab bars and railings), introducing exercise 
programs and promoting safe routines for activities of daily living. 
The commenter also stated that other approaches could involve providing 
payment for prevention activities targeted at patients who present with 
a first or recurrent fall in an attempt to avoid a future, more severe 
injury that could result in a debilitating hip and/or extremity 
fracture. This commenter expressed interest in collaborating further 
with CMS and other stakeholders on these initiatives.
    Response: We appreciate the commenters' support. We also thank the 
commenter for their recommendation to examine trauma activation in 
connection with the additional analysis planned for pelvic fracture 
repair cases and for the various options presented for injury 
prevention strategies. We look forward to further engagement with 
stakeholders on this topic.
    Comment: Other commenters suggested that CMS reconsider the request 
to reassign cases reporting a diagnosis code describing a pelvic 
fracture in combination with a procedure code describing repair of a 
pelvic fracture with internal fixation, from the lower (NonCC) severity 
level MS-DRG of its current base MS-DRG assignment to the higher (MCC) 
severity level MS-DRG for FY 2022. According to a commenter, as new 
technologies are made available intended to surgically treat many 
pelvic fracture patients who previously may have been treated medically 
in the inpatient setting, hospitals may bear a disproportionate share 
of these costs until the MS-DRGs are calibrated. This commenter stated 
that providing a reassignment now would help mitigate the financial 
strain for hospitals supporting these procedure types, and would 
benefit the Medicare program in its potential to reduce outlier 
payments. The commenter maintained that CMS could initially limit the 
reassignment to specific DRGs, or to specific combinations of procedure 
and diagnosis codes at this time, and review the data in a future 
rulemaking period.
    Another commenter conducted its own analysis and indicated its 
findings support reassignment for FY 2022. Alternatively, this 
commenter also stated they looked forward to updating CMS with 
additional data to support future reassignment options.
    Response: We appreciate the commenters' feedback and the additional 
analysis conducted. It is not clear from the commenter's analysis which 
specific code combinations generated the results provided. As we noted 
in the proposed rule, among other factors, there are specific codes and 
code combinations requiring further review as we identified additional 
codes that the requestor did not include in their initial submission. 
We will continue to work with stakeholders as we evaluate the data for 
these cases and consider future modifications to the structure of the 
MS-DRGs.
    After consideration of the public comments received, we are 
finalizing our proposal to maintain the structure of MS-DRGs 515, 516, 
and 517; MS-DRGs 907, 908, and 909; and MS-DRGs 957, 958, and 959 for 
FY 2022.
7. MDC 11 (Diseases and Disorders of the Kidney and Urinary Tract): 
Chronic Renal Replacement Therapy (CRRT)
    In the FY 2022 IPPS/LTCH PPS proposed rule (86 FR 25128 through 
25138), we discussed a request we received to create new MS-DRGs for 
cases where the patient receives continuous renal replacement therapy 
(CRRT) during the inpatient stay. According to the requestor, hospitals 
incur higher costs related to CRRT and current MS-DRG definitions do 
not adequately account for the clinical and resource requirements of 
CRRT. The requestor stated Medicare payment is insufficient to cover 
the costs of administering CRRT, creating a disincentive in offering 
this dialysis modality and is a barrier to further adoption of CRRT. 
The requestor suggested that the following two new MS-DRGs be created:

 Suggested New MS-DRG XXX--Continuous Renal Replacement Therapy 
with CC/MCC; and
 Suggested New MS-DRG XXX--Continuous Renal Replacement Therapy 
without CC/MCC.

    Renal replacement therapy (RRT) replaces kidney function by 
exchanging solute and removing fluid from the blood as a means to 
prevent or treat renal failure in patients with acute kidney injury 
(AKI). Modalities of renal support include CRRT, conventional 
intermittent hemodialysis (IHD), and prolonged intermittent renal 
replacement therapies (PIRRTs), which are a hybrid of CRRT and IHD. IHD 
provides solute clearance and filtration during relatively brief 
treatment sessions, generally lasting from three to five hours. CRRT 
provides gradual fluid removal and solute clearance over prolonged 
treatment times, typically over a 24-hour period, mimicking the natural 
function of the kidney to allow for the continuous removal or 
replacement of fluid. The most common CRRT modalities are continuous 
venovenous hemofiltration, continuous venovenous hemodialysis, and 
continuous venovenous hemodiafiltration.
    According to the requestor, CRRT is used primarily to treat 
critically ill, hospitalized patients who experience AKI requiring more 
intensive and continuous treatment than other dialysis modalities. The 
requestor stated that CRRT offers fluid balance and convective 
clearance that may be precisely adjusted for each patient, and has been 
associated with a higher likelihood of kidney recovery as compared to 
other modalities of RRT. The requestor asserted that IHD may worsen the 
neurological status of patients with acute brain injury or other causes 
of increased intracranial pressure by compromising their cerebral 
perfusion by raising intracranial pressure. The ongoing modulation of 
fluid balance and targeted fluid management capabilities of CRRT 
enables its use in situations other than renal failure. According to 
the requestor, CRRT, a slow continuous therapy, is preferred for 
patients who are hemodynamically unstable because it helps prevent the 
hemodynamic fluctuations common with the more rapid IHD. In light of 
the COVID-19 pandemic, the requestor noted the National Institutes of 
Health's Coronavirus Disease 2019 (COVID-19) Treatment Guidelines and 
The American Society of Nephrology recommend CRRT as the preferred 
renal replacement therapy for critically ill, COVID-19 patients 
experiencing AKI, who develop indications for renal replacement 
therapy, due to the

[[Page 44859]]

hemodynamic instability often experienced in this condition.
    The requestor acknowledged that under the current MS-DRG 
definitions, Medicare cases with beneficiaries receiving CRRT are 
assigned to more than 300 MS-DRGs. Although these beneficiaries are 
clinically similar in that they are critically ill patients who 
experience AKI requiring more intensive and continuous treatment than 
other dialysis modalities, the principal diagnoses for their inpatient 
stays vary. The requestor stated their analysis of the variability in 
principal diagnosis of the cases examined with beneficiaries receiving 
CRRT indicated that, in general, IHD tends to be used more for patients 
with chronic illnesses, and CRRT tends to be used for more acute 
injuries and end of life scenarios. Therefore, the requestor suggested 
that CMS create new MS-DRGs specific to CRRT, without regard to 
principal diagnosis, in order to group the resource intensive, 
clinically coherent, CRRT cases together in contrast to the existing 
GROUPER definitions.
    According to the requestor, continuing to assign CRRT to existing 
MS-DRGs would be clinically inappropriate and remain financially 
devastating to providers even when treating the most routine, 
uncomplicated CRRT patients. The requestor performed its own data 
analysis and stated hospitals lose over $22,000 per CRRT case on 
average, even when outliers are considered, which they state is a 
shortfall of more than 30 percent. The requestor asserted these losses 
create a disincentive for providers to offer CRRT despite its clinical 
benefits. The requestor also asserted the magnitude of financial losses 
associated with the provision of CRRT at the current level of MS-DRG 
payment could force many hospitals to examine the capacity and scope of 
their CRRT programs if facilities continue to determine that the 
financial burden of treating Medicare beneficiaries with CRRT is more 
than the facility can sustain. As COVID-19 continues to strain hospital 
resources, the requestor asserts the availability of CRRT should not be 
impeded by inadequate MS-DRG payments related to CRRT.
    In the proposed rule, we noted that the following ICD-10-PCS 
procedure code identifies the performance of CRRT.
BILLING CODE 4120-01-P
[GRAPHIC] [TIFF OMITTED] TR13AU21.063

BILLING CODE 4120-01-C
    In the ICD-10 MS-DRGs Definitions Manual Version 38.1, procedure 
code 5A1D90Z is currently recognized as a non-O.R. procedure that 
affects the MS-DRG to which it is assigned. We indicated that our 
clinical advisors agreed that the principal diagnosis assigned for 
inpatient admissions where continuous renal replacement of therapy is 
utilized can vary. To examine the impact of the use of CRRT in response 
to this request, we examined claims data from the March 2020 update of 
the FY 2019 MedPAR file for the top ten MS-DRGs reporting the use of 
CRRT. Our findings are reflected in the following table:
BILLING CODE 4120-01-P

[[Page 44860]]

[GRAPHIC] [TIFF OMITTED] TR13AU21.064

BILLING CODE 4120-01-C
    As shown in this table, our data findings demonstrate the average 
lengths of stay were longer and the average costs were higher for the 
cases

[[Page 44861]]

reporting the use of CRRT when compared to all cases in their 
respective MS-DRG. We note that the claims data demonstrate that the 
MS-DRG with the largest number of cases reporting CRRT is MS-DRG 871 
with 2,912 cases. Of the top 10 MS-DRGs reporting CRRT, the MS-DRG with 
the smallest number of cases is MS-DRG 682 with 401 cases. The average 
length of stay of this subset of cases ranges from a high of 35.5 days 
in MS-DRG 004 to a low of 7.9 days in MS-DRG 871 for cases reporting 
the use of CRRT. The average costs of this subset of cases ranges from 
a high of $174,085 in MS-DRG 003 to a low of $27,681 in MS-DRG 871 for 
cases reporting the use of CRRT.
    We also examined claims data from the September 2020 update of the 
FY 2020 MedPAR file for the top ten MS-DRGs reporting the use of CRRT. 
Our similar findings are reflected in the following table:
BILLING CODE 4120-01-P
[GRAPHIC] [TIFF OMITTED] TR13AU21.065


[[Page 44862]]


[GRAPHIC] [TIFF OMITTED] TR13AU21.066

BILLING CODE 4120-01-C
    As shown in this table, our data findings show that the average 
lengths of stay were longer and the average costs were higher for the 
cases reporting the use of CRRT when compared to all cases in their 
respective MS-DRG. We noted that the claims data demonstrate that the 
MS-DRG with the largest number of cases reporting CRRT is MS-DRG 871 
with 3,023 cases. Of the top 10 MS-DRGs reporting CRRT, the MS-DRG with 
the smallest number of cases is MS-DRG 219 with 374 cases. The average 
length of stay of this subset of cases ranges from a high of 34.9 days 
in MS-DRG 004 to a low of 7.9 days in MS-DRG 871 for cases reporting 
the use of CRRT. The average costs of this subset of cases ranges from 
a high of $182,952 in MS-DRG 003 to a low of $29,248 in MS-DRG 871 for 
cases reporting the use of CRRT.
    We indicated in the proposed rule that, while the results of the 
claims analysis indicate that the average costs and average lengths of 
stay for cases reporting the use of CRRT are higher compared to the 
average costs for all cases in their assigned MS-DRG, we were unable to 
ascertain from the claims data the resource use specifically 
attributable to CRRT during a hospital stay. We noted that there is 
large variability in the differences in average costs from MS-DRG to 
MS-DRG, indicating there may have been other factors contributing to 
the higher costs. When reviewing consumption of hospital resources for 
this subset of cases, the claims data clearly demonstrate the patients 
typically have a major complication or co-morbid (MCC) condition 
reported based on the MS-DRGs assigned. The claims data also reflect, 
based on the top ten MS-DRGS, that the procedure frequently occurs in 
cases with other procedures with higher than average resource use such 
as mechanical ventilation, tracheostomy, extracorporeal membrane 
oxygenation (ECMO) and other major cardiovascular procedures that also 
may

[[Page 44863]]

be contributing to the higher average costs for these cases.
    To further examine the variability in cases reporting the use of 
CRRT, we also reviewed the claims data to identify the number 
(frequency) and types of principal diagnoses that were reported to 
determine what factors may also be contributing to the higher average 
costs for these cases.
    Our findings for the top 10 principal diagnoses that were reported 
within the claims data from the March 2020 update of the FY 2019 MedPAR 
file for this subset of cases is shown in the following table:
[GRAPHIC] [TIFF OMITTED] TR13AU21.067

    The claims data in this table reflects a wide variance with regard 
to the frequency and types of principal diagnoses that were reported 
along with the procedure code describing the use of CRRT. We noted that 
the claims data demonstrate that the diagnosis with the largest number 
of cases reporting CRRT is A41.9 (Sepsis, unspecified organism) with 
4,226 cases. Of the top 10 principal diagnoses reporting CRRT, the 
diagnosis with the smallest number of cases is A41.01 (Sepsis due to 
Methicillin susceptible Staphylococcus aureus) with 271 cases. The 
average length of stay of this subset of cases ranges from a high of 20 
days with a diagnosis of I13.0 (Hypertensive heart and chronic kidney 
disease with heart failure and stage 1 through stage 4 chronic kidney 
disease, or unspecified chronic kidney disease) to a low of 12.6 days 
with a diagnosis of A41.9 (Sepsis, unspecified organism) for cases 
reporting the use of CRRT. The average costs of this subset of cases 
ranges from a high of $85,557 with a diagnosis of I21.4 (Non-ST 
elevation (NSTEMI) myocardial infarction) to a low of $40,908 with a 
diagnosis of N17.9 (Acute kidney failure, unspecified) for cases 
reporting the use of CRRT.
    Our findings for the top 10 principal diagnoses that were reported 
within the claims data from the September 2020 update of the FY 2020 
MedPAR file for this subset of cases are shown in the following table:

[[Page 44864]]

[GRAPHIC] [TIFF OMITTED] TR13AU21.068

    The claims data in this table also reflect a wide variance with 
regard to the frequency and types of principal diagnoses that were 
reported along with the procedure code describing the use of CRRT. As 
shown, the claims data demonstrate that the diagnosis with the largest 
number of cases reporting CRRT is A41.9 (Sepsis, unspecified organism) 
with 4,128 cases. Of the top 10 principal diagnoses reporting CRRT, the 
diagnosis with the smallest number of cases is N17.0 (Acute kidney 
failure with tubular necrosis) with 270 cases. The average length of 
stay of this subset of cases ranges from a high of 21.4 days with a 
diagnosis of U07.1 (COVID-19) to a low of 11.8 days with a diagnosis of 
J96.01 (Acute respiratory failure with hypoxia) for cases reporting the 
use of CRRT. The average costs of this subset of cases ranges from a 
high of $86,717 with a diagnosis of I21.4 (Non-ST elevation (NSTEMI) 
myocardial infarction) to a low of $48,882 with a diagnosis of J96.01 
(Acute respiratory failure with hypoxia) for cases reporting the use of 
CRRT.
    As indicated in the proposed rule, to evaluate the frequency with 
which the use of CRRT is reported for different clinical scenarios, we 
examined claims from the March 2020 update of the FY 2019 MedPAR file 
across each of the 25 MDCs to determine the number of cases reporting 
the use of CRRT. Our findings are shown in this table.
BILLING CODE 4120-01-P

[[Page 44865]]

[GRAPHIC] [TIFF OMITTED] TR13AU21.069


[[Page 44866]]


[GRAPHIC] [TIFF OMITTED] TR13AU21.070

BILLING CODE 4120-01-C
    As shown in the table, the top five MDCs with the largest number of 
cases reporting CRRT are MDC 18, with 6,761 cases; MDC 05, with 6,027 
cases; MDC 04, with 1,370 cases; MDC 11, with 1,134 cases; and MDC 06, 
with 987 cases. The top five MDCs with the highest average costs for 
cases reporting the use of CRRT were MDC 13, with average costs of 
$131,252; MDC 22, with average costs of $104,749; MDC 17, with average 
costs of $95,309; MDC 07, with average costs of $87,272; and MDC 05, 
with average costs of $86,024. The claims data indicate that the 
average length of stay ranges from a high of 47.3 days in MDC 13 to a 
low of 8 days in MDC 14 for cases reporting the use of CRRT across each 
of the 25 MDCs.
    We also examined claims from the September 2020 update of the FY 
2020 MedPAR file across each of the 25 MDCs to determine the number of 
cases

[[Page 44867]]

reporting the use of CRRT. Our findings are shown in this table.
BILLING CODE 4120-01-P
[GRAPHIC] [TIFF OMITTED] TR13AU21.071


[[Page 44868]]


[GRAPHIC] [TIFF OMITTED] TR13AU21.072

BILLING CODE 4120-01-C
    As shown in the table, the top five MDCs with the largest number of 
cases reporting CRRT are MDC 18, with 7,678 cases; MDC 05, with 5,516 
cases; MDC

[[Page 44869]]

04, with 2,191 cases; MDC 11, with 1,066 cases; and MDC 06, with 838 
cases. The top five MDCs with the highest average costs for cases 
reporting the use of CRRT were MDC 22, with average costs of $139,244; 
MDC 17, with average costs of $88,182; MDC 05, with average costs of 
$87,875; MDC 07, with average costs of $86,894; and MDC 08, with 
average costs of $ 77,515. The claims data indicate that the average 
length of stay ranges from a high of 26.7 days in MDC 22 to a low of 11 
days in MDC 20 for cases reporting the use of CRRT across each of the 
25 MDCs.
    We indicated in the proposed rule that our clinical advisors 
reviewed the clinical issues and the claims data, and did not support 
creating new MS-DRGs for CRRT without regard to principal diagnosis. 
Our clinical advisors noted that more than one modality for RRT can be 
utilized for managing patients with AKI given the needs of the patient. 
For example, a patient may initially start on CRRT when they are 
hemodynamically unstable, but transition to IHD as their condition is 
managed during the admission. While patients requiring CRRT can be more 
resource intensive, we stated it would not be practical to create new 
MS-DRGs specifically for this subset of patients given the various 
clinical presentations for which CRRT may be utilized, and the 
variation of costs in their assigned MS-DRGs. We further indicated that 
we believed that additional analysis and efforts toward a broader 
approach to refining the MS-DRGs for cases of patients requiring renal 
replacement therapy would be needed to address the concerns expressed 
by the requestor. These data do show cases reporting the use of CRRT 
can present greater treatment difficulty. However, when reviewing 
consumption of hospital resources for this subset of cases, the claims 
data also suggest that the increased costs may be attributable to the 
severity of illness of the patient and other circumstances of the 
admission.
    In summary, we indicated in the proposed rule that the claims data 
reflect a wide variance with regard to the frequency and average costs 
for cases reporting the use of CRRT. Depending on the number of cases 
in each MS-DRG, it is difficult to detect patterns of complexity and 
resource intensity. We indicated we believed the creation of new MS-
DRGs for cases with procedure codes reporting the use of CRRT has the 
potential for creating instability in the relative weights and 
disrupting the integrity of the MS-DRG system. Therefore, we did not 
propose to create new MS-DRGs for cases reporting the use of continuous 
renal replacement therapy.
    Comment: A commenter supported CMS' proposal and stated they agreed 
that new MS-DRGs should not be created for continuous renal replacement 
therapy without regard to principal diagnosis. Another commenter stated 
that CMS should group cases reporting the use of continuous renal 
replacement therapy along with ICD-10-CM diagnosis codes N17.8 (Other 
acute kidney failure) or N17.9 (Acute kidney failure, unspecified) to 
the highest (MCC) severity level MS-DRG of its current base MS-DRG 
assignment. The commenter noted that both N17.8 and N17.9 (Acute kidney 
failure, unspecified) are designated as a ``CC'' when reported as a 
secondary diagnosis. This commenter also stated that while CRRT is not 
a new technology, given its increased costs, CRRT should be considered 
for a permanent ``add-on'' payment that compensates hospitals for the 
higher costs of caring for these patients.
    Response: We appreciate the commenters' support. With regard to the 
commenter's statement that cases reporting the use of continuous renal 
replacement therapy along with ICD-10-CM diagnosis codes N17.8 (Other 
acute kidney failure) or N17.9 (Acute kidney failure, unspecified) 
should be grouped to the highest (MCC) severity level MS-DRG of its 
current base MS-DRG assignment, we consider this comment to be outside 
the scope of the proposal discussed. We may consider additional claims 
data analysis for these procedures in future rulemaking. After 
consideration of the public comments we received, we are finalizing our 
proposal to not create new MS-DRGs for cases reporting the use of 
continuous renal replacement therapy for FY 2022.
8. MDC 16 (Diseases and Disorders of Blood, Blood Forming Organs and 
Immunologic Disorders)
a. ANDEXXA[supreg] (Coagulation Factor Xa (Recombinant), Inactivated-
zhzo)
    ANDEXXA[supreg] (Coagulation Factor Xa (Recombinant), Inactivated-
zhzo) is a recombinant decoy protein that rapidly reverses the 
anticoagulant effects of two direct oral anticoagulants, apixaban and 
rivaroxaban, when reversal of anticoagulation is needed due to life-
threatening or uncontrolled bleeding in indications such as 
intracranial hemorrhages (ICHs) and gastrointestinal bleeds (GIBs). 
ANDEXXA[supreg] received FDA approval on May 3, 2018. When administered 
as a bolus followed by continuous infusion, ANDEXXA[supreg] blocks the 
anticoagulants ability to inhibit FXa. ANDEXXA[supreg] was approved for 
new technology add on payments in FY 2019 (83 FR 41362). We refer 
readers to section II.H.5.j. of the preamble of the FY 2019 IPPS/LTCH 
PPS final rule (83 FR 41355 through 41362), and section II.H.4.k. of 
the preamble of the FY 2020 IPPS/LTCH PPS final rule (84 FR 42193 
through 42194) for a complete discussion of the new technology add on 
payment application and payment amount for ANDEXXA[supreg] for FY 2019 
and FY 2020.
    In section II.H.4.i. of the preamble of the FY 2021 IPPS/LTCH PPS 
final rule (85 FR 58614 through 58615), we noted the 3-year anniversary 
date of the entry of ANDEXXA[supreg] onto the U.S. market (May 3, 2021) 
will occur in the second half of FY 2021. We stated in general, we 
extend new technology add-on payments for an additional year only if 
the 3-year anniversary date of the product's entry onto the U.S. market 
occurs in the latter half of the upcoming fiscal year. After 
consideration of the public comments received, we finalized our 
proposal to continue new technology add-on payments for this technology 
for FY 2021.
    In the FY 2022 IPPS/LTCH PPS proposed rule (86 FR 25138 through 
25146), we discussed a request we received from the manufacturer to 
review potential access issues in the inpatient setting for this drug 
in the future. The requestor acknowledged that CMS approved the new 
technology add-on payment for ANDEXXA[supreg] beginning in FY 2019 and 
noted that FY 2021 will be the last year before the add-on payments 
expire. According to the requestor, ANDEXXA[supreg] is the only 
indicated factor Xa inhibitor reversal agent, and the requestor stated 
a concern for the future of access to ANDEXXA[supreg] for patients 
experiencing uncontrolled bleeds caused by factor Xa inhibitors. The 
requestor stated their claims modeling showed a significant drop in 
hospital payment for cases involving use of ANDEXXA[supreg] following 
the expiration of new technology add-on payments. Specifically, after 
new technology add-on payments expire, the requestor stated their model 
projects that approximately 59% of cases are likely to be paid less 
than the wholesale acquisition costs for ANDEXXA[supreg].
    We noted in the proposed rule that the following ICD-10-PCS 
procedure codes identify the intravenous administration of 
ANDEXXA[supreg].

[[Page 44870]]

[GRAPHIC] [TIFF OMITTED] TR13AU21.073

    In the ICD-10 MS-DRGs Definitions Manual Version 38.1, procedure 
codes XW03372 and XW04372 are designated as non-O.R. procedures for 
purposes of MS-DRG assignment. We indicated that our clinical advisors 
agreed that the principal diagnosis assigned for inpatient admissions 
where the intravenous administration of ANDEXXA[supreg] is indicated 
can vary.
    To evaluate the frequency with which the intravenous administration 
of ANDEXXA[supreg] is reported for different clinical scenarios in 
response to this request, we examined claims data from the March 2020 
update of the FY 2019 MedPAR file across the Pre-MDC category, each of 
the 25 MDCs and the surgical class referred to as ``unrelated operating 
room procedures'' to determine the number of cases reporting the use of 
ANDEXXA[supreg]. Our findings are shown in the following table.
BILLING CODE 4120-01-P

[[Page 44871]]

[GRAPHIC] [TIFF OMITTED] TR13AU21.074


[[Page 44872]]


[GRAPHIC] [TIFF OMITTED] TR13AU21.075

BILLING CODE 4120-01-C
    As shown in the table, there were 461 cases reporting the 
intravenous administration of ANDEXXA[supreg] with procedure codes 
XW03372 or XW04372. The top five MDCs with the largest number of cases 
reporting ANDEXXA[supreg] are MDC 01, with 250 cases; MDC 06 with 53 
cases; MDC 05, with 33 cases; MDC 18, with 25 cases; and the Pre-MDC 
category, with 16 cases. The claims data indicate that the average 
costs range from a high of $107,741 in the Pre-MDC category to a low of 
$22,242 in MDC 09 for cases reporting the use of ANDEXXA[supreg] across 
the claims data. The claims data also indicates that the average length 
of stay ranges from a high of 19.9 days in the Pre-MDC category to a 
low of 4 days in MDC 09 for cases reporting the use of ANDEXXA[supreg].
    We also examined claims data from the September 2020 update of the 
FY 2020 MedPAR file across the Pre-MDC category, each of the 25 MDCs 
and the surgical class referred to as ``unrelated operating room 
procedures'' to determine the number of cases reporting the use of 
ANDEXXA[supreg]. Our findings are shown in the following table.
BILLING CODE 4120-01-P

[[Page 44873]]

[GRAPHIC] [TIFF OMITTED] TR13AU21.076


[[Page 44874]]


[GRAPHIC] [TIFF OMITTED] TR13AU21.077

BILLING CODE 4120-01-C
    As shown in the table, there were 719 cases reporting the 
intravenous administration of ANDEXXA[supreg] with procedure codes 
XW03372 or XW04372. The top five MDCs with the largest number of cases 
reporting ANDEXXA[supreg] are MDC 01, with 364 cases; MDC 06 with 98 
cases; MDC 18, with 52 cases; MDC 05, with 50 cases; and MDC 24, with 
30 cases. The claims data indicate that the average costs range from a 
high of $123,750 in the Pre-MDC category to a low of $27,922 in MDC 09 
for cases reporting the use of ANDEXXA[supreg] across the claims data. 
The claims data also indicates that the average length of stay ranges 
from a high of 25 days in the Pre-MDC category to a low of 4.2 days in 
MDC 21 for cases reporting the use of ANDEXXA[supreg] across the claims 
data.
    As discussed in the proposed rule, to further examine the impact of 
the intravenous administration of ANDEXXA[supreg], we examined claims 
data from the March 2020 update of the FY 2019 MedPAR file for the top 
ten MS-DRGs reporting procedure codes XW03372 or XW04372. Our findings 
are reflected in the following table:
BILLING CODE 4120-01-P

[[Page 44875]]

[GRAPHIC] [TIFF OMITTED] TR13AU21.078


[[Page 44876]]


[GRAPHIC] [TIFF OMITTED] TR13AU21.079

BILLING CODE 4120-01-C
    As shown in this table, the claims data demonstrate that the MS-DRG 
with the largest number of cases reporting ANDEXXA[supreg] is MS-DRG 
064 with 78 cases. Of the top 10 MS-DRGs reporting ANDEXXA[supreg], the 
MS-DRG with the smallest number of cases is MS-DRG 003 with 13 cases. 
The average length of stay of this subset of cases ranges from a high 
of 21.5 days in MS-DRG 003 to a low of 4.2 days in MS-DRG 086 for cases 
reporting the use of ANDEXXA[supreg]. The average costs of this subset 
of cases ranges from a high of $117,265 in MS-DRG 003 to a low of 
$26,992 in MS-DRG 083 for cases reporting the use of ANDEXXA[supreg]. 
We noted while our data findings demonstrate the average costs were 
higher for the cases reporting the intravenous administration of 
ANDEXXA[supreg] when compared to all cases in their respective MS-DRG, 
these cases represent a very small percentage of the total number of 
cases reported in these MS-DRGs. We also noted that the top 10 MS-DRGs 
identified only account for 239 of the 461 cases in total that were 
identified in the March 2020 update of the FY 2019 MedPAR file 
reporting ICD-10-PCS codes XW03372 or XW04372. The remainder of the 
cases are distributed in small numbers across the MS-DRGs.
    We also examined claims data from the September 2020 update of the 
FY 2020 MedPAR file for the top ten MS-DRGs reporting procedure codes 
XW03372 or XW04372. Our findings are reflected in the following table:
BILLING CODE 4120-01-P

[[Page 44877]]

[GRAPHIC] [TIFF OMITTED] TR13AU21.080

BILLING CODE 4120-01-C
    As shown in this table, the claims data demonstrate that the MS-DRG 
with the largest number of cases reporting ANDEXXA[supreg] is MS-DRG 
064 with 111 cases. Of the top 10 MS-DRGs reporting ANDEXXA[supreg], 
the MS-DRG with the smallest number of cases is MS-DRG 083 with 23 
cases. The average length of stay of this subset of cases ranges from a 
high of 10 days in MS-DRG 023 to a low of 3.5 days in MS-DRG 378 for 
cases reporting the use of ANDEXXA[supreg].

[[Page 44878]]

The average costs of this subset of cases ranges from a high of $59,478 
in MS-DRG 025 to a low of $24,348 in MS-DRG 378 for cases reporting the 
use of ANDEXXA[supreg]. As with our analysis of the FY 2019 claims 
data, while these data findings demonstrate the average costs were 
higher for the cases reporting the intravenous administration of 
ANDEXXA[supreg] when compared to all cases in their respective MS-DRG, 
these cases represent a very small percentage of the total number of 
cases reported in these MS-DRGs. We also noted that the top 10 MS-DRGs 
identified only account for 385 of the 719 cases in total that were 
identified in the September 2020 update of the FY 2020 MedPAR file 
reporting ICD-10-PCS codes XW03372 or XW04372. The remainder of the 
cases are distributed in small numbers across the MS-DRGs.
    After reviewing the claims data, we indicated in the proposed rule 
that we believe it is premature to consider a proposal for cases 
involving ANDEXXA[supreg] therapy for FY 2022. We noted that while the 
March 2020 update of the FY 2019 MedPAR file and the September 2020 
update of the FY 2020 MedPAR file do contain claims reporting the 
procedure codes identifying the intravenous administration of 
ANDEXXA[supreg], the number of cases is small across the MDCs and MS-
DRGs. We also noted the claims data also reflects a wide variance with 
regard to the frequency and average costs for these cases reporting the 
use of ANDEXXA[supreg]. Moreover, we indicated we were unable to 
identify another MS-DRG that would be a more appropriate MS-DRG 
assignment for these cases based on the indication for this therapeutic 
drug. As noted previously, ANDEXXA[supreg] reverses the anticoagulant 
effects of apixaban and rivaroxaban, when reversal of anticoagulation 
is needed due to life-threatening or uncontrolled bleeding. The 
underlying cause of the life-threatening or uncontrolled bleeding can 
vary which means the principal diagnosis assigned for inpatient 
admissions where ANDEXXA[supreg] is administered can vary. The MS-DRGs 
are a classification system intended to group together diagnoses and 
procedures with similar clinical characteristics and utilization of 
resources. As discussed in the proposed rule, we generally seek to 
identify sufficiently large sets of claims data with a resource/cost 
similarity and clinical similarity in developing diagnostic-related 
groups rather than smaller subsets based on the drugs administered. In 
reviewing this issue, we indicated our clinical advisors expressed 
concern regarding making potential MS-DRG changes based on a specific, 
single therapeutic agent, identified by unique procedure codes rather 
than based on a group of related procedure codes that can be reported 
to describe that same type or class of treatment or technology, which 
is more consistent with the intent of the MS-DRGs.
    We indicated that we recognized that the average costs of the small 
numbers of cases involving the intravenous administration of 
ANDEXXA[supreg] are greater when compared to the average costs of all 
cases in their respective MS-DRG. We noted that the MS-DRG system is a 
system of averages and it is expected that within the diagnostic 
related groups, some cases may demonstrate higher than average costs, 
while other cases may demonstrate lower than average costs. We further 
noted that section 1886(d)(5)(A) of the Act provides for Medicare 
payments to Medicare-participating hospitals in addition to the basic 
prospective payments for cases incurring extraordinarily high costs.
    In the proposed rule, we acknowledged the importance of ensuring 
that patients diagnosed with an indication for a factor Xa inhibitor 
reversal agent have adequate access to care and receive the necessary 
treatment. While we are sensitive to the requestors' concerns about 
continued access to treatment for beneficiaries who require the 
reversal of anticoagulation due to life-threatening or uncontrolled 
bleeding, we indicated additional time is needed to explore options and 
other mechanisms through which to address low volume high-cost drugs 
outside of the MS-DRGs.
    Furthermore, we noted that we were proposing to continue new 
technology add-on payments for ANDEXXA[supreg] for FY 2022. We refer 
the reader to section II.F.4.b of the preamble of the proposed rule and 
this final rule for further discussion regarding our proposal to allow 
a one-time extension of new technology add-on payments for FY 2022 for 
15 technologies for which the new technology add-on payment would 
otherwise be discontinued, in connection with our proposal to use the 
FY 2019 data to develop the proposed FY 2022 relative weights, as well 
as our finalization of that proposal.
    Therefore, for the reasons stated previously, for FY 2022 we did 
not propose any MS-DRG changes for cases involving the intravenous 
administration of ANDEXXA[supreg].
    Comment: Commenters expressed appreciation for the consideration 
CMS provided. These commenters acknowledged that ANDEXXA[supreg] 
presents a unique challenge because MS-DRGs are a classification system 
for grouping diagnoses and procedures with similar clinical 
characteristics and utilization of resources. Another commenter agreed 
that the underlying cause of life-threatening or uncontrolled bleeding 
can vary and stated that cases involving the use of ANDEXXA[supreg] 
(coagulation factor Xa (recombinant), inactivated-zhzo) do not fit 
neatly within another MS-DRG. These commenters also agreed that options 
and mechanisms through which to address low volume high-cost drugs 
should be explored outside of the MS-DRG classification.
    Response: We appreciate the commenters' support, and intend to 
continue to consider these issues. For the reasons summarized earlier, 
and after consideration of the public comments we received, we are not 
making any MS-DRG changes for cases involving the intravenous 
administration of ANDEXXA[supreg] for FY 2022.
b. Cytokine Release Syndrome (CRS) Logic
    In the FY 2021 IPPS/LTCH PPS final rule (85 FR 58557 through 
58561), we finalized modifications to the proposed severity level 
designations for a subset of the diagnosis codes describing Cytokine 
Release Syndrome (CRS) based upon further review of the conditions and 
in response to public comments. We provided the following table to 
display the finalized severity level designations and stated that we 
will continue to monitor the CRS codes and their impact on resource use 
once the claims data become available to determine if further 
modifications to the severity level are warranted.

[[Page 44879]]

[GRAPHIC] [TIFF OMITTED] TR13AU21.081

    In connection with the finalized severity level designations for 
the listed CRS codes, we also finalized modifications to the ICD-10 MS-
DRG GROUPER logic V38 for MS-DRGs 814, 815, and 816 
(Reticuloendothelial and Immunity Disorders with MCC, with CC, and 
without CC/MCC, respectively) to conform to the updates the CDC 
finalized in the ICD-10-CM Tabular List instructions for assigning and 
reporting the CRS codes effective with discharges on and after October 
1, 2020. The following modifications to the GROUPER logic were 
finalized effective with discharges on and after October 1, 2020, for 
case assignment involving CRS following CAR T-cell therapy to MS-DRGs 
814, 815, and 816. We noted that the GROUPER logic for MS-DRGs 814, 
815, and 816 will include a principal diagnosis of T80.89XA with a 
secondary diagnosis of any CRS code as shown.

Principal Diagnosis
    T80.89XA Other complications following infusion, transfusion and 
therapeutic injection, initial encounter
    with
Secondary Diagnosis
    D89.831 Cytokine release syndrome, grade 1
    D89.832 Cytokine release syndrome, grade 2
    D89.833 Cytokine release syndrome, grade 3
    D89.834 Cytokine release syndrome, grade 4
    D89.835 Cytokine release syndrome, grade 5
    D89.839 Cytokine release syndrome, grade unspecified

    As discussed in section II.D.13 of the preamble of the proposed 
rule and this final rule, Table 6A.--New Diagnosis Codes, lists the new 
diagnosis codes that have been approved to date and will be effective 
with discharges on and after October 1, 2021. Included in Table 6A are 
the following codes that describe complication of immune effector 
cellular therapy identifying the timeframe of the encounter.
[GRAPHIC] [TIFF OMITTED] TR13AU21.082

    Also included in Table 6A are the following diagnosis codes that 
describe immune effector cell-associated neurotoxicity syndrome 
(ICANS), with varying degrees of severity.
[GRAPHIC] [TIFF OMITTED] TR13AU21.083

    Consistent with the Tabular List instruction for these two sets of 
diagnosis codes as presented and discussed by the CDC at the September 
8-9, 2020 ICD-10 Coordination and Maintenance Committee meeting, the 
diagnosis codes describing a complication of the immune effector 
cellular therapy (T80.82XA, T80.82XD, and T80.82XS) are to be sequenced 
first, followed by the applicable diagnosis code to identify the 
specified condition resulting from the complication. For example, the 
types of complications that may result from immune effector

[[Page 44880]]

cellular therapy treatment (for example, CAR T-cell therapy) include 
ICANS or CRS, as described by the listed diagnosis codes. Accordingly, 
the CDC included the following instructional note in the Tabular List 
modifications for code T80.82--

``Use additional code to identify the specific complication, such as:
    cytokine release syndrome (D89.83-)
    immune effector cell-associated neurotoxicity syndrome (G92.0-)''

    Materials relating to the discussions involving the diagnosis codes 
from the September 8-9, 2020 ICD-10 Coordination and Maintenance 
Committee meeting can be obtained from the CDC website at: https://www.cdc.gov/nchs/icd/icd10cm_maintenance.htm.
    As noted previously, the current logic for case assignment 
involving CRS following CAR T-cell therapy to MS-DRGs 814, 815, and 816 
includes a principal diagnosis of T80.89XA with a secondary diagnosis 
of any CRS code. However, with the finalization of new diagnosis code 
T80.82-, diagnosis code T80.89XA would no longer be reported and these 
cases would instead report new diagnosis code T80.82XA, effective with 
discharges on and after October 1, 2021. As shown in Table 6A 
associated with the proposed rule, we proposed to assign diagnosis code 
T80.82XA to MDC 16 (Diseases and Disorders of Blood, Blood Forming 
Organs, and Immunologic Disorders) in MS-DRGs 814, 815, and 816. We 
stated that if the MDC and MS-DRG assignment for new diagnosis code 
T80.82XA is finalized, the current logic for MS-DRGs 814, 815, and 816 
that includes a principal diagnosis code of T80.89XA with a secondary 
diagnosis code of any CRS code would no longer be appropriate or 
necessary.
    Therefore, we proposed to revise the structure of MS-DRGs 814, 815, 
and 816 by removing the logic that includes a principal diagnosis of 
T80.89XA with a secondary diagnosis of any CRS code from MS-DRGs 814, 
815, and 816 effective FY 2022.
    Comment: Commenters supported the proposed revision to the 
structure of MS-DRGs 814, 815, and 816 to remove the logic that 
includes a principal diagnosis of T80.89XA with a secondary diagnosis 
of any CRS code from MS-DRGs 814, 815, and 816. Commenters also 
supported the proposed assignment of new diagnosis code T80.82XA to MS-
DRGs 814, 815, and 816 in MDC 16.
    Response: We appreciate the commenters' support.
    Comment: A commenter requested that CMS explain its rationale for 
MS-DRG assignment of the listed diagnosis codes describing complication 
of immune effector cellular therapy (T80.82XA, T80.82XD, and T80.82XS) 
and the codes describing immune effector cell-associated neurotoxicity 
syndrome (ICANS), with varying degrees of severity (G92.00, G92.01, 
G92.02, G92.03, G92.04, and G92.05). Specifically, the commenter 
questioned why CMS limited assignment to these MS-DRGs and if 
consideration could be given for the codes to be identified as CCs or 
MCCs for any MS-DRG.
    Response: As discussed in prior rulemaking and in the proposed rule 
(86 FR 25186), we use our established process which involves examining 
the MS-DRG assignment and the attributes (severity level and O.R. 
status) of the predecessor diagnosis or procedure code, as applicable, 
to inform our proposed assignments and designations. Specifically, we 
review the predecessor code and MS-DRG assignment most closely 
associated with the new diagnosis or procedure code, and in the absence 
of claims data, we consider other factors that may be relevant to the 
MS-DRG assignment, including the severity of illness, treatment 
difficulty, complexity of service and the resources utilized in the 
diagnosis and/or treatment of the condition. We note that this process 
does not automatically result in the new diagnosis or procedure code 
being proposed for assignment to the same MS-DRG or to have the same 
designation as the predecessor code. We encourage the commenter to also 
review the FY 2022 Conversion Table that was made publicly available 
via the internet on the CDC website at: https://www.cdc.gov/nchs/icd/icd10cm.htm, the V38.1 ICD-10 MS-DRG Definitions Manual that is 
available via the internet on the CMS website at: https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/AcuteInpatientPPS/MS-DRG-Classifications-and-Software, and Table 6A.--New Diagnosis Codes 
associated with the proposed and final rules (available via the 
internet on the CMS website at: https://www.cms.gov/medicare/acute-inpatient-pps/fy-2022-ipps-proposed-rule-home-page#Tables) for 
information regarding MDC, MS-DRG and severity level assignment for 
these diagnosis codes. As shown in the Conversion Table, the 
predecessor code for new diagnosis code T80.82XA is diagnosis code 
T80.89XA; as shown in Appendix B--Diagnosis Code/MDC/MS-DRG Index of 
the V38.1 ICD-10 MS-DRG Definitions Manual, diagnosis code T80.89XA is 
assigned to MDC 16 in MS-DRGs 814-816; and as shown in Table 6A.- New 
Diagnosis Codes, the finalized severity level assignments for the 
diagnosis codes inquired about are as follows:
[GRAPHIC] [TIFF OMITTED] TR13AU21.084


[[Page 44881]]


    Effective October 1, 2021, when diagnosis code G92.03, G92.04 or 
G92.05 are reported as a secondary diagnosis, the GROUPER logic would 
recognize any one of these codes as a CC and the appropriate ``with 
CC'' MS-DRG would be assigned.
    After consideration of the public comments we received, we are 
finalizing our proposal to assign diagnosis code T80.82XA to MDC 16 
(Diseases and Disorders of Blood, Blood Forming Organs, and Immunologic 
Disorders) in MS-DRGs 814, 815, and 816. We are also finalizing our 
proposal to revise the structure of MS-DRGs 814, 815, and 816 by 
removing the logic that includes a principal diagnosis of T80.89XA with 
a secondary diagnosis of any CRS code from MS-DRGs 814, 815, and 816 
effective FY 2022.
9. MDC 17 (Myeloproliferative Diseases and Disorders, and Poorly 
Differentiated Neoplasms): Inferior Vena Cava Filter Procedures
    In the FY 2021 IPPS/LTCH PPS final rule (85 FR 58517 through 
58520), we discussed the ICD-10-PCS codes that describe the insertion 
of an intraluminal device into the inferior vena cava that are listed 
in the following table.
[GRAPHIC] [TIFF OMITTED] TR13AU21.085

    We finalized a change in the designation of ICD-10-PCS procedure 
code 06H03DZ from O.R. procedure to non-O.R. procedure and maintained 
the O.R. designation of procedure codes 06H00DZ and 06H04DZ. In that 
discussion, we noted our clinical advisors supported changing the O.R. 
designation of procedures describing insertion of an intraluminal 
device into the inferior vena cava performed via a percutaneous 
approach since the procedure does not require the resources of an 
operating room, while concurring that procedures describing the 
insertion of an intraluminal device into the inferior vena cava 
performed via an open or a percutaneous endoscopic approach could 
require greater resources than a procedure describing insertion of an 
intraluminal device into the inferior vena cava performed via a 
percutaneous approach. We also noted that the goals of changing the 
designation of procedures from non-O.R. to O.R., or vice versa, are to 
better clinically represent the resources involved in caring for these 
patients and to enhance the overall accuracy of the system and not 
whether the change in designation would impact payment in a particular 
direction.
    In the FY 2022 IPPS/LTCH PPS proposed rule (86 FR 25147 through 
25149), we discussed a request we received to revise MS-DRGs 829 and 
830 (Myeloproliferative Disorders or Poorly Differentiated Neoplasms 
with Other Procedures with and without CC/MCC, respectively) by 
removing the current two-way severity level split and creating a three-
way severity level split in response to this final policy. The 
requestor respectfully disagreed with the FY 2021 IPPS/LTCH PPS final 
rule decision to change the designation of the procedure code 
describing the insertion of an inferior vena cava intraluminal device 
via percutaneous approach to a non-O.R. procedure, and stated vena cava 
filters are most often placed in interventional radiology suites and 
require a high level of skill to prevent rupture of the vena cava; and 
although they are long-term devices, they must be placed skillfully to 
allow for removal later if needed.
    According to the requestor, it is a conundrum that patients with 
principal and secondary diagnoses that qualify for medical MS-DRGs 837 
(Chemotherapy with Acute Leukemia as Secondary Diagnosis or with High 
Dose Chemotherapy Agent with MCC), MS-DRG 838 (Chemotherapy with Acute 
Leukemia as Secondary Diagnosis with CC or High Dose Chemotherapy 
Agent), and MS-DRG 839 (Chemotherapy with Acute Leukemia as Secondary 
Diagnosis without CC/MCC) group to lower weighted surgical MS-DRGs 829 
and 830 (Myeloproliferative Disorders or Poorly Differentiated 
Neoplasms with Other Procedures with and without CC/MCC, respectively) 
when a non-major O.R. procedure is performed. The requestor stated the 
difference in relative weights might be occurring because of the two-
way split within MS-DRGs 829 and 830 and the three-way split within MS-
DRGs 837, 838 and 839. The requestor theorized that removing the 
current two-way severity level split of MS-DRGs 829 and 830 and 
creating a three-way severity level split could help resolve the 
relative weight discrepancy when any non-major O.R. procedures are 
performed during hospitalizations for chemotherapy for acute leukemia.
    This requestor also suggested that if CMS' analysis did not support 
creating a three-way split for MS-DRGs 829 and 830, exclusion of PCS 
code 06H03DZ from the list of qualifying procedures and reinstatement 
of O.R. procedure status to appropriately compensate providers for the 
cost of devices and

[[Page 44882]]

resources to place inferior vena cava filters across the patient 
population should be proposed.
    As indicated in the proposed rule, to evaluate the request to 
create a three-way severity split MS-DRG for cases reporting 
myeloproliferative disorders or poorly differentiated neoplasms with 
other procedures, consistent with our established process, we conducted 
an analysis of base MS-DRG 829. This analysis includes 2 years of 
MedPAR claims data to compare the data results from 1 year to the next 
to avoid making determinations about whether additional severity levels 
are warranted based on an isolated year's data fluctuation and also, to 
validate that the established severity levels within a base MS-DRG are 
supported.
    Therefore, we reviewed the claims data for base MS-DRG 829 using 
the September 2018 update of the FY 2018 MedPAR file and the March 2020 
update of the FY 2019 MedPAR file, which were used in our analysis of 
claims data for MS-DRG reclassification requests for FY 2020 and FY 
2022, respectively. Our findings are shown in the table:
[GRAPHIC] [TIFF OMITTED] TR13AU21.086

    We applied the criteria to create subgroups for the three-way 
severity level split. We found that the criterion that there be at 
least 500 cases for each subgroup was not met based on the data in both 
the FY 2018 and FY 2019 MedPAR files, as shown in the table for both 
years. Specifically, for the ``with MCC'', ``with CC'', and ``without 
CC/MCC'' split, there were only 333 cases in the ``without CC/MCC'' 
subgroup based on the data in the FY 2019 MedPAR file and only 333 
cases in the ``without CC/MCC'' subgroup based on the data in the FY 
2018 MedPAR file. Accordingly, the claims data do not support a three-
way severity level split for base MS-DRG 829.
    We also reviewed the claims data for base MS-DRG 829 using the 
September 2019 update of the FY 2019 MedPAR file and the September 2020 
update of the FY 2020 MedPAR file, which were used in our analysis of 
claims data for MS-DRG reclassification requests for FY 2021 and FY 
2022, respectively. Our findings are shown in the table:
[GRAPHIC] [TIFF OMITTED] TR13AU21.087

    We applied the criteria to create subgroups for the three-way 
severity level split. We found that the criterion that there be at 
least 500 cases for each subgroup was not met based on the data in both 
the FY 2019 and FY 2020 MedPAR files, as shown in the table for both 
years. Specifically, for the ``with MCC'', ``with CC'', and ``without 
CC/MCC'' split, there were only 303 cases in the ``without CC/MCC'' 
subgroup based on the data in the FY 2020 MedPAR file and, as 
previously noted, only 333 cases in the ``without CC/MCC'' subgroup 
based on the data in the FY 2019 MedPAR file. As shown in both sets of 
data and stated previously, the claims data do not support a three-way 
severity level split for base MS-DRG 829.
    As discussed in the proposed rule, in response to the request to 
exclude ICD-10-PCS code 06H03DZ from a list of qualifying procedures if 
CMS' analysis did not support creating a three-way split for MS-DRGs 
829 and 830, we noted that by definition, procedure codes designated as 
non-O.R. procedures, not further classified as ``affecting the MS-DRG 
assignment'', do not influence the MS-DRG assignment. As stated 
previously, in the FY 2021 IPPS/LTCH PPS final rule we finalized our 
proposal to change the designation of ICD-10-PCS procedure code 06H03DZ 
from O.R. procedure to non-O.R. procedure, therefore as a non-O.R. 
procedure, there is no need to exclude ICD-10-PCS code 06H03DZ from a 
list of qualifying procedure codes for MS-DRGs 829 and 830.
    In response to the request to reinstate the O.R. procedure 
designation of ICD-10-PCS code 06H03DZ if CMS' analysis did not support 
creating a three-way split for MS-DRGs 829 and 830, we indicated the 
change in designation from O.R. procedure to non-O.R. procedure was 
recent, only becoming effective October 1, 2020. We indicated our 
clinical advisors continued to indicate that code 06H03DZ, describing 
the percutaneous insertion of an intraluminal device into the inferior 
vena cava, does not require the resources of an operating room, that 
the procedure to insert an IVC filter percutaneously is not surgical in 
nature and that the resources involved in furnishing this procedure are 
comparable to the related ICD-10-PCS procedure codes that describe the 
insertion of infusion devices into the inferior vena cava that are 
currently designated as non-O.R. procedures. We noted our clinical 
advisors stated that our FY 2021 final policy resulted in an O.R. 
designation of 06H03DZ that better reflects the associated technical 
complexity and hospital resource use of this procedure. We also noted 
that we continue to explore alternatives on how we may restructure the 
current O.R. and non-O.R. designations for procedures by leveraging the 
detail that is now available in the ICD-10 claims data, as discussed in 
the FY 2021 IPPS/LTCH PPS final rule and in section II.D.11. of the 
preamble of the proposed rule and this final rule. We indicated we 
continue to develop our process and methodology, and that we will 
provide more detail in future rulemaking.

[[Page 44883]]

    In summary, based on the results of our analysis, for FY 2022, we 
proposed to maintain the current structure of MS-DRGs 829 and 830.
    Comment: Commenters expressed support for CMS' proposal to maintain 
the current structure of MS-DRGs 829 and 830 (Myeloproliferative 
Disorders or Poorly Differentiated Neoplasms with Other Procedures with 
and without CC/MCC, respectively) and not create a three-way severity 
level split.
    Response: We thank the commenters for their support.
    After consideration of the public comments we received, we are 
finalizing our proposal to maintain the current structure of MS-DRGs 
829 and 830, without modification, for FY 2022.
10. Review of Procedure Codes in MS-DRGs 981 Through 983 and 987 
Through 989
    We annually conduct a review of procedures producing assignment to 
MS-DRGs 981 through 983 (Extensive O.R. Procedure Unrelated to 
Principal Diagnosis with MCC, with CC, and without CC/MCC, 
respectively) or MS-DRGs 987 through 989 (Non-Extensive O.R. Procedure 
Unrelated to Principal Diagnosis with MCC, with CC, and without CC/MCC, 
respectively) on the basis of volume, by procedure, to see if it would 
be appropriate to move cases reporting these procedure codes out of 
these MS-DRGs into one of the surgical MS-DRGs for the MDC into which 
the principal diagnosis falls. The data are arrayed in two ways for 
comparison purposes. We look at a frequency count of each major 
operative procedure code. We also compare procedures across MDCs by 
volume of procedure codes within each MDC. We use this information to 
determine which procedure codes and diagnosis codes to examine.
    We identify those procedures occurring in conjunction with certain 
principal diagnoses with sufficient frequency to justify adding them to 
one of the surgical MS-DRGs for the MDC in which the diagnosis falls. 
We also consider whether it would be more appropriate to move the 
principal diagnosis codes into the MDC to which the procedure is 
currently assigned.
    In addition to this internal review, we also consider requests that 
we receive to examine cases found to group to MS-DRGs 981 through 983 
or MS-DRGs 987 through 989 to determine if it would be appropriate to 
add procedure codes to one of the surgical MS DRGs for the MDC into 
which the principal diagnosis falls or to move the principal diagnosis 
to the surgical MS DRGs to which the procedure codes are assigned.
    Based on the results of our review of the claims data from the 
March 2020 update of the FY 2019 MedPAR file and the September 2020 
update of the FY 2020 MedPAR file, as well as our review of the 
requests that we received to examine cases found to group to MS-DRGs 
981 through 983 or MS-DRGs 987 through 989, we proposed to move the 
cases reporting the procedures and/or principal diagnosis codes 
described in this section of this rule from MS-DRGs 981 through 983 or 
MS-DRGs 987 through 989 into one of the surgical MS-DRGs for the MDC 
into which the principal diagnosis or procedure is assigned.
    As discussed in section II.D.3.b. of the preamble of the proposed 
rule and this final rule, we received a request to reassign cases with 
procedures describing control of bleeding in the cranial cavity when 
reported with a central nervous system diagnosis from MS-DRGs 981, 982, 
and 983 (Extensive O.R. Procedure Unrelated to Principal Diagnosis with 
MCC, with CC, and without CC/MCC, respectively) to MDC 01 (Diseases and 
Disorders of the Central Nervous System) in MS-DRGs 25, 26, and 27 
(Craniotomy and Endovascular Intracranial Procedures with MCC, with CC, 
and without CC/MCC, respectively (for example, ``craniotomy'' MS-DRGs). 
We noted that in addition to MS-DRGs 25, 26, and 27, MS-DRG 23 
(Craniotomy with Major Device Implant or Acute Complex CNS Principal 
Diagnosis with MCC or Chemotherapy Implant or Epilepsy with 
Neurostimulator) and MS-DRG 24 (Craniotomy with Major Device Implant or 
Acute Complex CNS Principal Diagnosis without MCC) also include 
procedures performed on structures located within the cranial cavity 
and are included in the range of MS-DRGs known as the ``craniotomy'' 
MS-DRGs in MDC 01.
    The management and treatment for bleeding (or hemorrhage) within 
the cranial cavity varies depending on the location, cause and the 
severity (or extent) of the bleed. Common causes include head trauma or 
cerebral aneurysm. Control of bleeding in the cranial cavity procedures 
are identified by ICD-10-PCS procedure codes 0W310ZZ (Control bleeding 
in cranial cavity, open approach), 0W313ZZ (Control bleeding in cranial 
cavity, percutaneous approach) and 0W314ZZ (Control bleeding in cranial 
cavity, percutaneous endoscopic approach) and are currently assigned to 
the following MDCs and MS-DRGs.
BILLING CODE 4120-01-P

[[Page 44884]]

[GRAPHIC] [TIFF OMITTED] TR13AU21.088


[[Page 44885]]


[GRAPHIC] [TIFF OMITTED] TR13AU21.089

BILLING CODE 4120-01-C
    According to the requestor, procedures performed within the cranial 
cavity always involve drilling or cutting through the skull regardless 
of the approach, therefore the three procedure codes identified 
(0W310ZZ, 0W313ZZ, and 0W314ZZ) warrant assignment to the 
``craniotomy'' MS-DRGs.
    We stated in the proposed rule that our analysis of this grouping 
issue confirmed that when a procedure describing control of bleeding in 
the cranial cavity is reported with a principal diagnosis from MDC 01, 
these cases group to MS-DRGs 981, 982, and 983. Whenever there is a 
surgical procedure reported on the claim that is unrelated to the MDC 
to which the case was assigned based on the principal diagnosis, it 
results in a MS-DRG assignment to a surgical class referred to as 
``unrelated operating room procedures''.
    As noted in the proposed rule, we examined claims data from the 
March 2020 update of the FY 2019 MedPAR file and the September 2020 
update of the FY 2020 MedPAR file for cases reporting any one of the 
three procedure codes (0W310ZZ, 0W313ZZ or 0W314ZZ) in MS-DRGs 981 
through 983 with a principal diagnosis from MDC 01. Our findings are 
shown in the following tables.
[GRAPHIC] [TIFF OMITTED] TR13AU21.090


[[Page 44886]]


[GRAPHIC] [TIFF OMITTED] TR13AU21.091

    As noted previously, the requestor asked that we consider 
reassignment of these cases to the craniotomy MS-DRGs (identified as 
MS-DRGs 23, 24, 25, 26, and 27). We therefore examined the data for all 
cases in MS-DRGs 23, 24, 25, 26, and 27. Our findings are shown in the 
following tables.
[GRAPHIC] [TIFF OMITTED] TR13AU21.092

[GRAPHIC] [TIFF OMITTED] TR13AU21.093

    As shown, in our analyses of the claims data for MS-DRGs 981 
through 983, we found a total of ten cases reporting procedures 
describing control of bleeding in cranial cavity with a principal 
diagnosis from MDC 01 in the March 2020 update of the FY 2019 MedPAR 
file, and a total of two cases reporting procedures describing control 
of bleeding in cranial cavity with a principal diagnosis from MDC 01 in 
the September 2020 update of the FY 2020 MedPAR file.
    As noted in the proposed rule, our clinical advisors stated these 
procedures

[[Page 44887]]

describing control of bleeding in the cranial cavity are consistent 
with the existing procedure codes included in the logic for case 
assignment to MS-DRGs 25, 26, and 27, in addition to MS-DRG 23 
(Craniotomy with Major Device Implant or Acute Complex CNS Principal 
Diagnosis with MCC or Chemotherapy Implant or Epilepsy with 
Neurostimulator) and MS-DRG 24 (Craniotomy with Major Device Implant or 
Acute Complex CNS Principal Diagnosis without MCC) that also describe 
procedures performed on structures located within the cranial cavity 
and are included in the range of MS-DRGs known as the ``craniotomy'' 
MS-DRGs. While the claims analysis based on the March 2020 update of 
the FY 2019 MedPAR file identified only ten cases and the September 
2020 update of the FY 2020 MedPAR file identified only two cases for 
which these procedures were reported as a stand-alone procedure 
resulting in assignment to MS-DRGs 981 through 983, and the average 
length of stay and average costs for these cases vary in comparison to 
the average length of stay and average costs of all cases in MS-DRGs 
23, 24, 25, 26, and 27, given the nature of head trauma cases, the 
resource use would be expected to vary based on the extent of the 
patient's injuries. We stated in the proposed rule that we believed it 
is clinically appropriate to add these procedure codes describing 
control of bleeding in the cranial cavity to MS-DRGs 23, 24, 25, 26, 
and 27 in MDC 01.
    Therefore, we proposed to add procedure codes 0W310ZZ, 0W313ZZ, and 
0W314ZZ to MDC 01 in MS-DRGs 23, 24, 25, 26, and 27 (``craniotomy'' MS-
DRGs) for FY 2022.
    Comment: Commenters agreed with our proposal to add procedure codes 
0W310ZZ, 0W313ZZ, and 0W314ZZ to MDC 01 in MS-DRGs 23, 24, 25, 26, and 
27.
    Response: We thank the commenters for their support.
    After consideration of the public comments received, we are 
finalizing our proposal to add procedure codes 0W310ZZ, 0W313ZZ, and 
0W314ZZ describing bleeding in the cranial cavity to MDC 01 in MS-DRGs 
23, 24, 25, 26, and 27 for FY 2022.
    We also review the list of ICD-10-PCS procedures that, when in 
combination with their principal diagnosis code, result in assignment 
to MS-DRGs 981 through 983, or 987 through 989, to ascertain whether 
any of those procedures should be reassigned from one of those two 
groups of MS-DRGs to the other group of MS-DRGs based on average costs 
and the length of stay. We look at the data for trends such as shifts 
in treatment practice or reporting practice that would make the 
resulting MS-DRG assignment illogical. If we find these shifts, we 
would propose to move cases to keep the MS-DRGs clinically similar or 
to provide payment for the cases in a similar manner.
    In addition to this internal review, we also consider requests that 
we receive to examine cases found to group to MS-DRGs 981 through 983 
or MS-DRGs 987 through 989 to determine if it would be appropriate for 
the cases to be reassigned from one of the MS-DRG groups to the other.
    Based on the results of our review of the claims data from the 
March 2020 update of the FY 2019 MedPAR file and the September 2020 
update of the FY 2020 MedPAR file, as well as our review of the 
requests that we received to examine cases found to group to MS-DRGs 
981 through 983 or MS-DRGs 987 through 989, we proposed to move the 
cases reporting the procedures codes described in this section of this 
rule from MS-DRGs 981 through 983 to MS-DRGs 987 through 989.
    As discussed in section II.D.3.a. of the preamble of the proposed 
rule and this final rule, we received a request that we understood to 
be for our consideration of the reassignment of the following three 
procedure codes from Extensive O.R. procedures to Non-extensive O.R. 
procedures.
[GRAPHIC] [TIFF OMITTED] TR13AU21.094

    As stated in the proposed rule, in conducting our review of this 
request, our clinical advisors noted that ICD-10-PCS codes 0JB60ZZ, 
0JB70ZZ, and 0JB80ZZ currently group to MS-DRGs 981 through 983 when 
reported with a principal diagnosis that is not assigned to one of the 
MDCs to which these procedure codes are assigned. While our claims 
analysis of both the March 2020 update of the FY 2019 MedPAR file and 
the September 2020 update of the FY 2020 MedPAR file did not identify 
any cases reporting any one of the three listed procedure codes in MS-
DRGs 981, 982, or 983, we stated that our clinical advisors believe 
that these procedures would be more appropriately designated as Non-
extensive procedures because they are more consistent with other 
procedures on the Non-extensive procedure code list. They stated that 
these procedures do not consume the resources or require a similar 
level of technical complexity as the procedures on the Extensive O.R. 
procedures list.
    Therefore, we proposed to reassign the three procedure codes listed 
from MS-DRGs 981, 982, and 983 (Extensive O.R. Procedure Unrelated to 
Principal Diagnosis with MCC, with CC, without CC/MCC, respectively) to 
MS-DRGs 987, 988, and 989 (Non-Extensive Procedure Unrelated to 
Principal Diagnosis with MCC, with CC, without CC/MCC, respectively) 
for FY 2022.
    Comment: Commenters supported our proposal to reassign procedure 
codes 0JB60ZZ, 0JB70ZZ, and 0JB80ZZ from MS-DRGs 981, 982, and 983 to 
MS-DRGs 987, 988, and 989.
    Response: We appreciate the commenters' support.
    After consideration of the public comments received, we are 
finalizing our proposal to reassign procedure codes 0JB60ZZ, 0JB70ZZ, 
and 0JB80ZZ describing excision of subcutaneous tissue from the chest, 
back, and abdomen, respectively, from MS-DRGs 981, 982, and 983 to MS-
DRGs 987, 988, and 989 for FY 2022.
    As discussed in section II.D.4.b. of the preamble of the proposed 
rule and this final rule, we identified 17 procedure codes describing 
laser interstitial thermal therapy (LITT) that are currently designated 
as extensive O.R. procedures. In addition to those 17 procedure codes, 
we identified additional procedure codes describing LITT of various 
body parts that are also designated as extensive O.R. procedures. The 
ICD-10-PCS codes describing LITT of various body parts are as follows.
BILLING CODE 4120-01-P

[[Page 44888]]

[GRAPHIC] [TIFF OMITTED] TR13AU21.095

BILLING CODE 4210-01-C
    Whenever one of these listed procedure codes is reported on a claim 
that is unrelated to the MDC to which the case was assigned based on 
the principal diagnosis, it currently results in assignment to MS-DRGs 
981, 982, and 983 (Extensive O.R. Procedure Unrelated to Principal 
Diagnosis with MCC, with CC, without CC/MCC, respectively). Our 
clinical advisors stated that all of the listed procedure codes warrant 
redesignation from the extensive procedure list and MS-DRGs 981, 982, 
and 983 to the non-extensive procedure list and to MS-DRGs 987, 988, 
and 989 (Non-Extensive Procedure Unrelated to Principal Diagnosis with 
MCC, with CC, without CC/MCC, respectively). Specifically, our clinical 
advisors stated the procedures described by these codes are minimally 
invasive and are consistent with other ablation (root operation 
Destruction) type procedures that are designated as non-extensive 
procedures in the ICD-10-PCS classification.
    As noted in the proposed rule, in our analysis of claims from the 
March 2020 update of the FY 2019 MedPAR file, we identified a total of 
six cases reporting procedure codes describing LITT of various body 
sites in MS-DRGs 981, 982, and 983 with an average length of stay of 
2.5 days and average costs of $7,734. Specifically, we found one case 
reporting procedure code DVY0KZZ (Laser interstitial thermal therapy of 
prostate) in MS-DRG 981 with an average length of stay of 4.0 days and 
average costs of $7,348. For MS-DRG 982, we found five cases in which 
procedure codes describing LITT of various body sites were reported. 
The first case reported procedure code D0Y0KZZ (Laser interstitial 
thermal therapy of brain) with an average length of stay of 1.0 day and 
average costs of $4,142, the second case reported procedure code 
D0Y6KZZ (Laser interstitial thermal therapy of spinal cord) with an 
average length of stay of 3.0 days and average costs of $20,007, the 
third case reported procedure code DDY1KZZ (Laser interstitial thermal 
therapy of stomach) with an average length of stay of 2.0 days and 
average

[[Page 44889]]

costs of $3,424, the fourth case reported procedure code DDY7KZZ (Laser 
interstitial thermal therapy of rectum) with an average length of stay 
of 3.0 days and average costs of $3,735, and the fifth case reported 
procedure code DVY0KZZ (Laser interstitial thermal therapy of prostate) 
with an average length of stay of 2.0 days and average costs of $7,750. 
There were no cases found to report procedures describing LITT in MS-
DRG 983. Our findings are summarized in the following table.
[GRAPHIC] [TIFF OMITTED] TR13AU21.096

    In the proposed rule, we stated that for our analysis of claims 
from the September 2020 update of the FY 2020 MedPAR file, we 
identified one case reporting procedure code D0Y6KZZ (Laser 
interstitial thermal therapy of spinal cord) with an average length of 
stay of 6 days and average costs of $5,130, and two cases reporting 
procedure code DVY0KZZ (Laser interstitial thermal therapy of prostate) 
with an average length of stay of 8.5 days and average costs of $20,329 
in MS-DRGs 981, 982, or 983. Although our claims analysis identified a 
limited number of cases reporting procedures describing LITT, we stated 
that our clinical advisors believe that these procedures would be more 
appropriately designated as Non-extensive procedures because they are 
more consistent with other procedures on the Non-extensive procedure 
code list.
    Therefore, we proposed to reassign the listed procedure codes 
describing LITT of various body parts from MS-DRGs 981, 982, and 983 
(Extensive O.R. Procedures Unrelated to Principal Diagnosis with MCC, 
with CC, and without CC/MCC, respectively) to MS-DRGs 987, 988, and 989 
(Non-extensive O.R. Procedures Unrelated to Principal Diagnosis with 
MCC, with CC, and without CC/MCC, respectively) for FY 2022.
    Comment: Commenters agreed with our proposal to reassign the listed 
procedure codes describing LITT of various body parts from MS-DRGs 981, 
982, and 983 to MS-DRGs 987, 988, and 989.
    Response: We thank the commenters for their support.
    After consideration of the public comments received, we are 
finalizing our proposal to reassign the listed procedure codes 
describing LITT of various body parts from MS-DRGs 981, 982, and 983 to 
MS-DRGs 987, 988, and 989, without modification, for FY 2022.
    As also discussed in section II.D.4.b. of the preamble of the 
proposed rule and this final rule, we identified five procedure codes 
describing repair of the esophagus that are currently designated as 
extensive O.R. procedures. The procedure codes are 0DQ50ZZ (Repair 
esophagus, open approach), 0DQ53ZZ (Repair esophagus, percutaneous 
approach), 0DQ54ZZ (Repair esophagus, percutaneous endoscopic 
approach), 0DQ57ZZ (Repair esophagus, via natural or artificial 
opening), and 0DQ58ZZ (Repair esophagus, via natural or artificial 
opening endoscopic). Whenever one of these five procedure codes is 
reported on a claim that is unrelated to the MDC to which the case was 
assigned based on the principal diagnosis, it currently results in 
assignment to MS-DRGs 981, 982, and 983 (Extensive O.R. Procedure 
Unrelated to Principal Diagnosis with MCC, with CC, without CC/MCC, 
respectively). Our clinical advisors stated that three of these five 
procedures warrant redesignation from the extensive procedure list and 
MS-DRGs 981, 982, and 983 to the non-extensive procedure list and to 
MS-DRGs 987, 988, and 989 (Non-Extensive Procedure Unrelated to 
Principal Diagnosis with MCC, with CC, without CC/MCC, respectively). 
Specifically, our clinical advisors stated the procedures identified by 
procedure codes 0DQ53ZZ, 0DQ57ZZ, and 0DQ58ZZ do not involve the same 
utilization of resources with respect to the performance of the 
procedure in comparison to the procedures identified by procedure codes 
0DQ50ZZ and 0DQ540ZZ. In our analysis of claims from the March 2020 
update of the FY 2019 MedPAR file, we identified three cases reporting 
procedure code 0DQ58ZZ in MS-DRGs 981, 982, and 983 with an average 
length of stay of 14 days and average costs of $34,894. In our analysis 
of claims from the September 2020 update of the FY 2020 MedPAR file, we 
identified two cases reporting procedure code 0DQ58ZZ in MS-DRGs 981, 
982, or 983 with an average length of stay of 8 days and average costs 
of $12,037. We stated that our clinical advisors believe that these 
procedures would be more appropriately designated as Non-extensive 
procedures because they are more consistent with other procedures on 
the Non-extensive procedure code list. Therefore, we proposed to 
reassign these three procedure codes (0DQ53ZZ, 0DQ57ZZ, and 0DQ58ZZ) 
from MS-DRGs 981, 982, and 983 (Extensive O.R. Procedures Unrelated to 
Principal Diagnosis with MCC, with CC, and without CC/MCC, 
respectively) to MS-DRGs 987, 988, and 989 (Non-extensive O.R. 
Procedures Unrelated to Principal Diagnosis with MCC, with CC, and 
without CC/MCC, respectively) for FY 2022.

[[Page 44890]]

    Comment: Commenters supported our proposal to reassign procedure 
codes 0DQ53ZZ, 0DQ57ZZ, and 0DQ58ZZ from MS-DRGs 981, 982, and 983 to 
MS-DRGs 987, 988, and 989.
    Response: We appreciate the commenters' support.
    After consideration of the public comments received, we are 
finalizing our proposal to reassign the procedure codes describing 
repair of the esophagus via percutaneous approach, natural or 
artificial opening approach, and natural or artificial opening 
endoscopic approach, from MS-DRGs 981, 982, and 983 to MS-DRGs 987, 
988, and 989, without modification, for FY 2022.
    As discussed in section II.D.11.c.24. of the preamble of the 
proposed rule, we identified procedure code 0T9D0ZZ (Drainage of 
urethra, open approach) during our review of procedure code 0U9L0ZZ 
(Drainage of vestibular gland, open approach), which is currently 
designated as a non-O.R. procedure. We noted that the procedure 
described by procedure code 0T9D0ZZ represents the male equivalent of 
the female procedure described by procedure code 0U9L0ZZ. Procedure 
code 0T9D0ZZ is currently designated as an extensive O.R. procedure and 
is reported to describe procedures performed on the Cowper's 
(bulbourethral) gland in males. Whenever this procedure code is 
reported on a claim that is unrelated to the MDC to which the case was 
assigned based on the principal diagnosis, it currently results in 
assignment to MS-DRGs 981, 982, and 983 (Extensive O.R. Procedure 
Unrelated to Principal Diagnosis with MCC, with CC, without CC/MCC, 
respectively).
    In the proposed rule we noted that our clinical advisors stated 
that this procedure warrants redesignation from the extensive procedure 
list and MS-DRGs 981, 982, and 983 to the non-extensive procedure list 
and to MS-DRGs 987, 988, and 989 (Non-Extensive Procedure Unrelated to 
Principal Diagnosis with MCC, with CC, without CC/MCC, respectively). 
Specifically, our clinical advisors stated that the procedure described 
by procedure code 0T9D0ZZ continues to warrant an O.R. designation 
because it is performed on deeper structures and requires a higher 
level of technical skill and it is a more complex procedure when 
compared to the non-O.R. procedure described by procedure code 0U9L0ZZ, 
however, abscess formation in the Cowper's (bulbourethral) glands is 
uncommon and can often be treated with ultrasound guided percutaneous 
aspiration. The need for open surgical management is rare and includes 
chronic infection unresponsive to non-operative management and 
complicated acute infection such as perineal fistula formation. Open 
surgical management would require use of the operating room for both 
appropriate anesthesia and for the resources required to perform the 
more invasive perineal surgical dissection. Therefore, we stated that 
our clinical advisors believe a non-extensive O.R. designation is 
suitable for this procedure.
    We noted in the proposed rule that we analyzed claims data from the 
March 2020 update of the FY 2019 MedPAR file and the September 2020 
update of the FY 2020 MedPAR file for cases reporting procedure code 
0T9D0ZZ in MS-DRGs 981, 982, and 983. We found one case in MS-DRG 981 
with an average length of stay of 8.0 days and average costs of $23,566 
in the March 2020 update of the FY 2019 MedPAR file, and no cases in 
the September 2020 update of the FY 2020 MedPAR file. Although our 
claims analysis identified only one case reporting procedure code 
0T9D0ZZ, we stated in the proposed rule that our clinical advisors 
believe that these procedures would be more appropriately designated as 
Non-extensive procedures because they are more consistent with other 
procedures on the Non-extensive procedure code list.
    Therefore, we proposed to reassign procedure code 0T9D0ZZ from MS-
DRGs 981, 982, and 983 (Extensive O.R. Procedures Unrelated to 
Principal Diagnosis with MCC, with CC, and without CC/MCC, 
respectively) to MS-DRGs 987, 988, and 989 (Non-extensive O.R. 
Procedures Unrelated to Principal Diagnosis with MCC, with CC, and 
without CC/MCC, respectively) for FY 2022.
    Comment: Commenters supported our proposal to reassign procedure 
code 0T9D0ZZ from MS-DRGs 981, 982, and 983 to MS-DRGs 987, 988, and 
989.
    Response: We thank the commenters for their support.
    After consideration of the public comments received, we are 
finalizing our proposal to reassign procedure code 0T9D0ZZ from MS-DRGs 
981, 982, and 983 to MS-DRGs 987, 988, and 989, without modification, 
for FY 2022.
11. Operating Room (O.R.) and Non-O.R. Issues
a. Background
    Under the IPPS MS-DRGs (and former CMS MS-DRGs), we have a list of 
procedure codes that are considered operating room (O.R.) procedures. 
Historically, we developed this list using physician panels that 
classified each procedure code based on the procedure and its effect on 
consumption of hospital resources. For example, generally the presence 
of a surgical procedure which required the use of the operating room 
would be expected to have a significant effect on the type of hospital 
resources (for example, operating room, recovery room, and anesthesia) 
used by a patient, and therefore, these patients were considered 
surgical. Because the claims data generally available do not precisely 
indicate whether a patient was taken to the operating room, surgical 
patients were identified based on the procedures that were performed. 
Generally, if the procedure was not expected to require the use of the 
operating room, the patient would be considered medical (non-O.R.).
    Currently, each ICD-10-PCS procedure code has designations that 
determine whether and in what way the presence of that procedure on a 
claim impacts the MS-DRG assignment. First, each ICD-10-PCS procedure 
code is either designated as an O.R. procedure for purposes of MS-DRG 
assignment (``O.R. procedures'') or is not designated as an O.R. 
procedure for purposes of MS-DRG assignment (``non-O.R. procedures''). 
Second, for each procedure that is designated as an O.R. procedure, 
that O.R. procedure is further classified as either extensive or non-
extensive. Third, for each procedure that is designated as a non-O.R. 
procedure, that non-O.R. procedure is further classified as either 
affecting the MS-DRG assignment or not affecting the MS-DRG assignment. 
We refer to these designations that do affect MS-DRG assignment as 
``non O.R. affecting the MS-DRG.'' For new procedure codes that have 
been finalized through the ICD-10 Coordination and Maintenance 
Committee meeting process and are proposed to be classified as O.R. 
procedures or non-O.R. procedures affecting the MS-DRG, our clinical 
advisors recommend the MS-DRG assignment which is then made available 
in association with the proposed rule (Table 6B.--New Procedure Codes) 
and subject to public comment. These proposed assignments are generally 
based on the assignment of predecessor codes or the assignment of 
similar codes. For example, we generally examine the MS-DRG assignment 
for similar procedures, such as the other approaches for that 
procedure, to determine the most appropriate MS-DRG assignment for 
procedures proposed to be newly designated as O.R. procedures. As 
discussed in section II.D.13 of the preamble of this final rule, we are

[[Page 44891]]

making Table 6B.--New Procedure Codes--FY 2022 available on the CMS 
website at: https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/AcuteInpatientPPS/index.html. We also refer readers to the ICD-
10 MS-DRG Version 38.1 Definitions Manual at: https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/AcuteInpatientPPS/MS-DRG-Classifications-and-Software.html for detailed information regarding 
the designation of procedures as O.R. or non-O.R. (affecting the MS-
DRG) in Appendix E--Operating Room Procedures and Procedure Code/MS-DRG 
Index.
    In the FY 2020 IPPS/LTCH PPS proposed rule, we stated that, given 
the long period of time that has elapsed since the original O.R. 
(extensive and non-extensive) and non-O.R. designations were 
established, the incremental changes that have occurred to these O.R. 
and non-O.R. procedure code lists, and changes in the way inpatient 
care is delivered, we plan to conduct a comprehensive, systematic 
review of the ICD-10-PCS procedure codes. This will be a multi year 
project during which we will also review the process for determining 
when a procedure is considered an operating room procedure. For 
example, we may restructure the current O.R. and non O.R. designations 
for procedures by leveraging the detail that is now available in the 
ICD-10 claims data. We refer readers to the discussion regarding the 
designation of procedure codes in the FY 2018 IPPS/LTCH PPS final rule 
(82 FR 38066) where we stated that the determination of when a 
procedure code should be designated as an O.R. procedure has become a 
much more complex task. This is, in part, due to the number of various 
approaches available in the ICD-10-PCS classification, as well as 
changes in medical practice. While we have typically evaluated 
procedures on the basis of whether or not they would be performed in an 
operating room, we believe that there may be other factors to consider 
with regard to resource utilization, particularly with the 
implementation of ICD-10.
    We discussed in the FY 2020 IPPS/LTCH PPS proposed rule that as a 
result of this planned review and potential restructuring, procedures 
that are currently designated as O.R. procedures may no longer warrant 
that designation, and conversely, procedures that are currently 
designated as non-O.R. procedures may warrant an O.R. type of 
designation. We intend to consider the resources used and how a 
procedure should affect the MS-DRG assignment. We may also consider the 
effect of specific surgical approaches to evaluate whether to subdivide 
specific MS-DRGs based on a specific surgical approach. We plan to 
utilize our available MedPAR claims data as a basis for this review and 
the input of our clinical advisors. As part of this comprehensive 
review of the procedure codes, we also intend to evaluate the MS-DRG 
assignment of the procedures and the current surgical hierarchy because 
both of these factor into the process of refining the ICD-10 MS-DRGs to 
better recognize complexity of service and resource utilization.
    In the FY 2021 IPPS/LTCH PPS final rule (85 FR 58540 through 
58541), we provided a summary of the comments we had received in 
response to our request for feedback on what factors or criteria to 
consider in determining whether a procedure is designated as an O.R. 
procedure in the ICD-10-PCS classification system for future 
consideration.
    We stated in the proposed rule that in consideration of the PHE, we 
believe it may be appropriate to allow additional time for the claims 
data to stabilize prior to selecting the timeframe to analyze for this 
review. Additional time is also necessary as we continue to develop our 
process and methodology. Therefore, stated that we will provide more 
detail on this analysis and the methodology for conducting this review 
in future rulemaking.
    Comment: Several commenters agreed it is appropriate to allow 
additional time for the claims data to stabilize prior to selecting the 
timeframe to analyze for the comprehensive procedure code review.
    Response: In the FY 2022 IPPS/LTCH PPS proposed rule and this final 
rule, we are addressing requests that we received regarding changing 
the designation of specific ICD-10-PCS procedure codes from non-O.R. to 
O.R. procedures, or changing the designation from O.R. procedure to 
non-O.R. procedure. In this section of the rule we discuss the process 
that was utilized for evaluating the requests that were received for FY 
2022 consideration. For each procedure, our clinical advisors 
considered--
     Whether the procedure would typically require the 
resources of an operating room;
     Whether it is an extensive or a nonextensive procedure; 
and
     To which MS-DRGs the procedure should be assigned.
    We note that many MS-DRGs require the presence of any O.R. 
procedure. As a result, cases with a principal diagnosis associated 
with a particular MS-DRG would, by default, be grouped to that MS-DRG. 
Therefore, we do not list these MS-DRGs in our discussion in this 
section of this rule. Instead, we only discuss MS-DRGs that require 
explicitly adding the relevant procedure codes to the GROUPER logic in 
order for those procedure codes to affect the MS-DRG assignment as 
intended. In cases where we proposed to change the designation of 
procedure codes from non-O.R. procedures to O.R. procedures, we also 
proposed one or more MS-DRGs with which these procedures are clinically 
aligned and to which the procedure code would be assigned.
    In addition, cases that contain O.R. procedures will map to MS-DRG 
981, 982, or 983 (Extensive O.R. Procedure Unrelated to Principal 
Diagnosis with MCC, with CC, and without CC/MCC, respectively) or MS-
DRG 987, 988, or 989 (Non-Extensive O.R. Procedure Unrelated to 
Principal Diagnosis with MCC, with CC, and without CC/MCC, 
respectively) when they do not contain a principal diagnosis that 
corresponds to one of the MDCs to which that procedure is assigned. 
These procedures need not be assigned to MS-DRGs 981 through 989 in 
order for this to occur. Therefore, if requestors included some or all 
of MS-DRGs 981 through 989 in their request or included MS-DRGs that 
require the presence of any O.R. procedure, we did not specifically 
address that aspect in summarizing their request or our response to the 
request in this section of this rule.
    For procedures that would not typically require the resources of an 
operating room, our clinical advisors determined if the procedure 
should affect the MS-DRG assignment.
    As indicated in the proposed rule, we received several requests to 
change the designation of specific ICD-10-PCS procedure codes from non-
O.R. procedures to O.R. procedures, or to change the designation from 
O.R. procedures to non-O.R. procedures. In this section of this rule, 
as we did in the proposed rule, we detail and respond to some of those 
requests and, further, summarize and respond to the public comments we 
received in response to our proposals, if applicable. With regard to 
the remaining requests, as stated in the proposed rule, our clinical 
advisors believe it is appropriate to consider these requests as part 
of our comprehensive review of the procedure codes as previously 
discussed.
    With respect to some of the comments received in response to our 
discussion of several requests to change the designation of specific 
ICD-10-PCS procedure codes from non-O.R.

[[Page 44892]]

procedures to O.R. procedures, we wish to clarify that when we state 
that a current non-O.R. procedure is frequently or generally performed 
in the outpatient setting, we are indicating that the resources 
involved in the performance of the procedure are such that, it does not 
specifically require an inpatient admission and is typically not the 
underlying reason for the admission, nor a major factor in the 
consumption of resources for an inpatient admission. While an inpatient 
provider may elect to perform a specific procedure in the operating 
room or a procedure room, that does not constitute automatic 
designation of the procedure as an O.R. procedure under the IPPS. 
Alternatively, a procedure that is performed at the bedside does not 
constitute automatic designation of the procedure as a non-O.R. 
procedure under the IPPS. In addition, when we state that a current 
non-O.R. procedure is typically performed in conjunction with another 
O.R. procedure, we are indicating that there is generally another O.R. 
procedure reported on the claim that is primarily responsible for 
impacting the utilization of resources for that admission.
b. O.R. Procedures to Non-O.R. Procedures
(1) Open Drainage of Subcutaneous Tissue and Fascia
    One requestor identified the following ICD-10-PCS procedure code 
that describes the open drainage of right lower leg subcutaneous tissue 
and fascia, shown in the following table.
[GRAPHIC] [TIFF OMITTED] TR13AU21.097

    In the ICD-10 MS-DRG Version 38.1 Definitions Manual, this ICD-10-
PCS procedure code is currently recognized as an O.R. procedure for 
purposes of MS-DRG assignment. The requestor noted that this procedure 
consumes resources comparable to related ICD-10-PCS procedure code 
0J9N00Z (Drainage of right lower leg subcutaneous tissue and fascia 
with drainage device, open approach) that describes the open drainage 
of right lower leg subcutaneous tissue and fascia with a drainage 
device, which is currently designated as a non-O.R. procedure. The 
requestor stated that these comparable procedures should be recognized 
similarly for purposes of MS-DRG assignment.
    In the proposed rule, we noted that during our review of this 
issue, we identified 21 ICD-10-PCS procedure codes that describe the 
open drainage of subcutaneous tissue and fascia, shown in the following 
table that are clinically similar to ICD-10-PCS code 0J9N0ZZ, and are 
also designated as O.R. procedures in the ICD-10 MS-DRG Version 38.1 
Definitions Manual.
BILLING CODE 4120-01-P

[[Page 44893]]

[GRAPHIC] [TIFF OMITTED] TR13AU21.098

    We stated we reviewed these procedures and that our clinical 
advisors agreed that procedures that describe the open drainage of 
subcutaneous tissue and fascia consume resources comparable to the 
related ICD-10-PCS procedure codes that describe the open drainage of 
subcutaneous tissue and fascia with a drainage device that are 
currently designated as non-O.R. procedures. We stated that these 
procedures do not typically require the resources of an operating room, 
and are not surgical in nature. Therefore, we proposed to remove the 22 
codes listed in the following table from the FY 2022 ICD-10 MS-DRGs 
Version 39 Definitions Manual in Appendix E--Operating Room Procedures 
and Procedure Code/MS-DRG Index as O.R. procedures. We stated in the 
proposed rule that, under this proposal, these procedures would no 
longer impact MS-DRG assignment.

[[Page 44894]]

[GRAPHIC] [TIFF OMITTED] TR13AU21.099

BILLING CODE 4210-01-C
    Comment: Commenters supported CMS' proposal to change the 
designation of the 22 procedure codes describing open drainage of 
subcutaneous tissue and fascia from O.R. procedures to non-O.R. 
procedures.
    Response: We appreciate the commenters for their support.
    Comment: Other commenters opposed CMS' proposal. Commenters stated 
that these procedures are indeed performed in the operating room under 
general anesthesia, are surgical in nature, and significantly increase 
costs. A commenter also stated that ICD-10-PCS codes describing open 
drainage ``with drainage device'' are rarely (if ever) assigned because 
when drains are placed at the conclusion of open drainage procedures, 
drains are considered integral to the performance of a procedure. Some 
commenters acknowledged there may be certain circumstances in which 
these procedures do not require an operating room but note they are not 
consistently conducive to being performed at bedside, especially when 
the patient is not able to tolerate the procedure, or when performed in 
for community hospitals that do not have hybrid O.R.s or special 
procedure rooms. A commenter stated that a review of the cases at their 
facility shows that approximately 80% of the procedures describing open 
drainage of subcutaneous tissue and fascia are performed in an O.R. 
setting requiring anesthesia, with a much lesser percentage performed 
at the bedside.
    Another commenter noted in the FY 2018 IPPS proposed rule, these 
same 22 ICD-10-PCS codes were identified and a commenter opposed the 
proposal to redesignate these codes at that time. In response to the 
issues raised by this commenter, CMS agreed in the FY 2018 IPPS final 
rule to maintain the designation of the 22 procedure codes. This 
commenter stated the rationale to maintain these 22 codes as O.R. 
procedures has not changed and that there is no safe way to effectively 
drain an infection involving the subfascial plane without the resources 
of an O.R.
    Response: Our clinical advisors reviewed the commenters' concerns 
and state that treatment practices have continued to shift since FY 
2018 rulemaking. Procedures describing the open drainage of 
subcutaneous tissue and fascia can now be safely performed in the 
outpatient setting and when performed during a hospitalization, it is 
typically in conjunction with another O.R. procedure. In cases where 
procedures describing open drainage of subcutaneous tissue and fascia 
are the only procedures performed in an admission, the admission is 
quite likely due to need for IV antibiotics as opposed to the need for 
operating room resources in an inpatient setting. Our clinical advisors 
continue to state that these procedures consume resources comparable to 
the related ICD-10-PCS procedure codes that describe the open drainage 
of subcutaneous tissue and fascia with a drainage device that are 
currently designated as non-O.R. procedures. In response to the comment 
that ICD-10-PCS codes describing open drainage ``with drainage device'' 
are rarely (if ever) assigned, while we agree there are limited 
scenarios in which the qualifier ``with drainage device'' is 
applicable, we note coding is dependent on the documentation in the 
medical record.
    In response to the comments that differentiate when these 
procedures are performed at bedside versus in hybrid O.R.s versus in 
special procedure rooms, we note that the designation of procedure as a 
non-O.R. procedure is

[[Page 44895]]

not determined solely by the location in the facility in which the 
procedure was performed. While the site in which the procedure is 
performed and the procedural approach are important considerations in 
the designation of a procedure, other clinical factors such as 
procedure complexity, resource utilization, and need for anesthesia 
administration are also relevant to whether a procedure would typically 
require the resources of an operating room. In that regard, our 
clinical advisors state procedure codes that describe the open drainage 
of subcutaneous tissue and fascia do not reflect the technical 
complexity or resource intensity in comparison to other procedures that 
are designated as O.R. procedures. As noted by the commenters, while 
there are circumstances where performing open drainage in the operating 
room under sedation or general anesthesia may be necessary, open 
drainage procedures can be performed at the bedside or settings other 
than an operating room under general anesthesia.
    We also note we have identified that the designation of the 22 
procedure codes that describe the open drainage of subcutaneous tissue 
and fascia as O.R. procedures is a result of a replication error in 
transitioning to ICD-10. This replication error led to ICD-10-PCS 
procedure codes that describe the open drainage of subcutaneous tissue 
and fascia being listed as comparable translations for ICD-9-CM code 
83.09 (Other incision of soft tissue), which was designated as a non-
extensive O.R. procedure under the ICD-9-CM MS-DRGs Version 32. 
Conversely, this replication error led ICD-10-PCS procedure codes that 
describe the open drainage of subcutaneous tissue and fascia with a 
drainage device being listed as comparable translations for ICD-9-CM 
code 86.04 (Other incision with drainage of skin and subcutaneous 
tissue) which was designated as a non-O.R. procedure under the ICD-9-CM 
MS-DRGs Version 32. Designating the 22 procedure codes that describe 
the open drainage of subcutaneous tissue and fascia as non-O.R. 
procedures will result in a more accurate replication of the comparable 
procedure, under the ICD-9-CM MS-DRGs Version 32 which was 86.04, not 
83.09 and is more aligned with current shifts in treatment practices.
    After consideration of the public comments we received, for the 
reasons stated, we are finalizing our proposal, without modification, 
to change the designation of the 22 procedure codes listed in the 
preceding table from O.R. procedures to non-O.R. procedures, effective 
October 1, 2021.
c. Non-O.R. Procedures to O.R. Procedures
(1) Percutaneous Introduction of Substance Into Cranial Cavity and 
Brain
    One requestor identified ICD-10-PCS procedure code XW0Q316 
(Introduction of eladocagene exuparvovec into cranial cavity and brain, 
percutaneous approach, new technology group 6) that the requestor 
stated is currently not recognized as an O.R. procedure for purposes of 
MS-DRG assignment. The requestor recommended that this procedure be 
designated as an O.R. procedure because the procedure requires 
traversing the skull in order to place a substance within the cranial 
cavity or brain. The requestor noted that CMS disagreed with 
designating this procedure as an O.R. procedure last year in the 
absence of claims data; however, the requestor stated that because the 
skull must be opened by drilling or cutting a burr hole through the 
skull, this procedure warrants O.R. status similar to other 
transcranial procedures performed with an open or percutaneous approach 
that are classified as O.R. procedures.
    We noted in the proposed rule that in the ICD-10 MS-DRGs 
Definitions Manual Version 38.1, procedure code XW0Q316 is currently 
designated as a non-O.R. procedure for purposes of MS-DRG assignment. 
We agreed with the requestor that procedure code XW0Q316 describes a 
procedure that involves the creation of a burr hole in the skull. In 
the FY 2021 IPPS/LTCH PPS final rule (85 FR 58579 through 58580), we 
stated that, consistent with our annual process of assigning new 
procedure codes to MDCs and MS-DRGs, and designating a procedure as an 
O.R. or non-O.R. procedure, we reviewed the predecessor procedure code 
assignment. The predecessor code for procedure code XW0Q316 is 
procedure code 3E0Q3GC (Introduction of other therapeutic substance 
into cranial cavity and brain, percutaneous approach) which is 
designated as a non-O.R. procedure. In the absence of claims data, our 
clinical advisors also considered the indication for the specific 
procedure being described by the new procedure code, the treatment 
difficulty, and the resources utilized.
    We stated in the proposed rule that upon further review and 
consideration, our clinical advisors agreed that procedure code XW0Q316 
describing a procedure that is performed by creating a burr hole in the 
skull warrants designation as an O.R. procedure consistent with other 
percutaneous procedures performed on the cranial cavity and brain body 
parts. Therefore, we proposed to add this procedure code to the FY 2022 
ICD-10 MS-DRGs Version 39 Definitions Manual in Appendix E--Operating 
Room Procedures and Procedure Code/MS-DRG Index as an O.R. procedure, 
assigned to MS-DRGs 628, 629, and 630 (Other Endocrine, Nutritional and 
Metabolic O.R. Procedures with MCC, with CC, and without CC/MCC, 
respectively) in MDC 10 (Endocrine, Nutritional and Metabolic Diseases 
and Disorders) and to MS-DRGs 987, 988, and 989 (Non-Extensive O.R. 
Procedure Unrelated to Principal Diagnosis with MCC, with CC and 
without MCC/CC, respectively).
    Comment: Commenters agreed with our proposal to designate procedure 
code XW0Q316 as an O.R. procedure.
    Response: After consideration of the public comments we received, 
we are finalizing our proposal to change the designation of procedure 
code XW0Q316 from a non-O.R. procedure to an O.R. procedure, effective 
October 1, 2021.
(2) Open Drainage of Maxilla and Mandible
    One requestor identified three ICD-10-PCS procedure codes that 
describe the open drainage of maxilla or mandible that the requestor 
stated are currently not recognized as O.R. procedures for purposes of 
MS-DRG assignment. The three procedure codes are listed in the 
following table.

[[Page 44896]]

[GRAPHIC] [TIFF OMITTED] TR13AU21.100

    The requestor stated that procedures that describe the open 
drainage of the maxilla or mandible should be designated as O.R. 
procedures because these procedures, indicated for diagnoses such as 
subperiosteal abscesses, are performed in the operating room under 
general anesthesia and involve making open incisions through muscle and 
stripping away the periosteum. The requestor identified procedure codes 
0W950ZZ (Drainage of lower jaw, open approach) and 0W940ZZ (Drainage of 
upper jaw, open approach) that are currently designated as O.R. 
procedures. The requestor noted that ICD-10-PCS guidelines instruct 
that the procedure codes in Anatomical Regions, General, can be used 
when the procedure is performed on an anatomical region rather than a 
specific body part, or on the rare occasion when no information is 
available to support assignment of a code to a specific body part. The 
requestor stated that because bone is a specific body part in ICD-10-
PCS, procedure codes should be assigned for subperiosteal drainage of 
mandible and maxilla bones from table 0N9, Drainage of Head and Facial 
Bones, instead of codes from table 0W9, Drainage of Anatomical Regions, 
General, when these procedures are performed. Therefore, the requestor 
stated that procedure codes 0N9R0ZZ, 0N9T0ZZ, and 0N9V0ZZ should also 
be recognized as O.R. procedures for purposes of MS-DRG assignment.
    In the ICD-10 MS-DRGs Definitions Manual Version 38.1, procedure 
codes 0N9R0ZZ, 0N9T0ZZ, and 0N9V0ZZ are currently designated as non-
O.R. procedures for purposes of MS-DRG assignment. In the proposed 
rule, we stated that our clinical advisors reviewed this issue and 
disagreed that the procedures describing the open drainage of the 
maxilla or mandible are typically performed in the operating room under 
general anesthesia. Our clinical advisors stated that these procedures 
can be done in an oral surgeon's office or an outpatient setting and 
are rarely performed in the inpatient setting. Our clinical advisors 
also stated a correlation cannot be made between procedures performed 
in general anatomic regions and procedures performed in specific body 
parts because these procedures coded with the general anatomic regions 
body part represent a broader range of procedures that cannot be coded 
to a specific body part. Therefore, we proposed to maintain the current 
non-O.R. designation of ICD-10-PCS procedure codes 0N9R0ZZ, 0N9T0ZZ, 
and 0N9V0ZZ.
    Comment: A commenter supported CMS' proposal to maintain the 
current non-O.R. designation for procedure codes describing open 
drainage of maxilla or mandible.
    Response: We appreciate the commenters' support.
    Comment: Another commenter opposed CMS' proposal to maintain the 
current non-O.R. designation of ICD-10-PCS procedure codes 0N9R0ZZ, 
0N9T0ZZ, and 0N9V0ZZ and stated that the treatment of jaw infections 
requires open drainage of jaw bones performed in the operating room 
under anesthesia in conjunction with intravenous antibiotics to prevent 
sepsis. This commenter stated that procedures that are typically 
performed in the outpatient surgical setting should be designated as 
O.R. procedures and that the frequency in which procedures are 
performed in the inpatient setting should not determine the 
designation. The commenter asserted that when these procedures are 
necessitated during inpatient stays, providers should be compensated 
for operating room resources because the payment of infrequent 
surgeries as non-O.R. procedures results in significant uncompensated 
surgical resources for facilities.
    Response: Our clinical advisors reviewed the commenters' concerns 
and continue to support maintaining the current non-O.R. designation 
for procedure codes describing open drainage of maxilla or mandible and 
disagree that the procedures describing the open drainage of the 
maxilla or mandible typically require the resources of an operating 
room. Our clinical advisors state that if admission is required for the 
treatment of a jaw infection as the commenter suggested, the admission 
is quite likely due to need for IV antibiotics as opposed to the need 
for operating room resources in an inpatient setting.
    With regard to the comments about the implications for 
reimbursement, we note that the goals of changing the designation of 
procedures from non-O.R. to O.R., or vice versa, are to better 
clinically represent the resources involved in caring for these 
patients and to enhance the overall accuracy of the system. Therefore, 
decisions to change an O.R. designation are based on whether such a 
change would accomplish those goals and not whether the change in 
designation would impact the payment in a particular direction.
    After consideration of the public comments we received, for the 
reasons stated, we are finalizing our proposal to maintain the current 
non-O.R. designation of ICD-10-PCS procedure codes 0N9R0ZZ, 0N9T0ZZ, 
and 0N9V0ZZ, without modification, for FY 2022.
(3) Thoracoscopic Extirpation of Pleural Cavities
    One requestor identified ICD-10-PCS procedure codes 0WC94ZZ 
(Extirpation of matter from right pleural cavity, percutaneous 
endoscopic approach) and 0WCB4ZZ (Extirpation of matter from left 
pleural cavity, percutaneous endoscopic approach) that the requestor 
stated are currently not recognized as O.R. procedures for purposes of 
MS-DRG assignment. The requestor stated that these procedures should be 
designated as O.R. procedures because they are thoracoscopic procedures 
that are always performed in the operating room under general 
anesthesia. The requestor stated procedure codes 0W994ZZ (Drainage of 
right pleural cavity, percutaneous endoscopic approach) and 0W9B4ZZ 
(Drainage of left pleural cavity, percutaneous endoscopic approach) are 
currently designated as O.R. procedures, therefore procedure codes 
0WC94ZZ and 0WCB4ZZ should also be recognized as O.R. procedures for 
purposes of MS-DRG assignment because they utilize the same resources.
    In the ICD-10 MS-DRGs Definitions Manual Version 38.1, procedure 
codes 0WC94ZZ and 0WCB4ZZ are currently designated as non-O.R. 
procedures for purposes of MS-DRG assignment. We stated in the proposed 
rule that our clinical advisors reviewed this issue and

[[Page 44897]]

disagreed that procedure codes describing the thoracoscopic drainage of 
the pleural cavities should necessarily have the same designation as 
procedure codes describing the thoracoscopic extirpation of matter from 
the pleural cavities. We noted that our review of the designation of 
ICD-10-PCS codes as an O.R. procedure or a non-O.R. procedure considers 
the resources used as well as whether that procedure should affect the 
MS-DRG assignment, and if so, in what way. Our clinical advisors stated 
that thoracoscopic drainage of the pleural cavities is performed for 
distinct indications in clinically different scenarios. Our clinical 
advisors further stated that drainage is the process of taking out, or 
letting out, fluids and/or gases from a body part and is typically 
performed in the pleural cavity for indications such as congestive 
heart failure, infection, hemothorax and empyema. In contrast, the 
procedures describing the thoracoscopic extirpation of the pleural 
cavities are performed for a wider range of indications because the 
solid matter removed may be an abnormal byproduct of a biological 
function or a foreign body. Our clinical advisors noted that the 
thoracoscopic extirpation of the pleural cavities is generally 
performed with other procedures such as heart transplant, lung 
transplant mechanical ventilation, and other major chest procedures and 
would not be the main reason for inpatient hospitalization or be 
considered the principal driver of resource expenditure.
    Therefore, we proposed to maintain the current non-O.R. designation 
of ICD-10-PCS procedure codes 0WC94ZZ and 0WCB4ZZ.
    Comment: A commenter supported CMS' proposal to maintain the 
current non-O.R. designation for procedure codes describing the 
thoracoscopic extirpation of matter from the pleural cavities.
    Response: We appreciate the commenters' support.
    Comment: Another commenter opposed CMS' proposal to maintain the 
non-O.R. designation of ICD-10-PCS procedure codes 0WC94ZZ and 0WCB4ZZ. 
The commenter stated that procedure codes describing the thoracoscopic 
extirpation of matter from the pleural cavities can indeed be primary 
surgical procedures in procedures such as when the thoracoscopic 
evacuation of a traumatic hemothorax is performed during 
hospitalization, and stated that all thoracoscopic lung procedures 
should be designated as O.R. procedures because they are performed in 
the operating room and require general anesthesia with one lung 
ventilation. This commenter also stated that ICD-10-PCS codes for 
thoracoscopic drainage of pleural cavities have been appropriately 
designated as O.R. procedures, and the only difference between root 
operations ``Drainage'' and ``Extirpation'' is strictly the consistency 
of the substance removed.
    Response: Our clinical advisors reviewed the commenters' concerns 
and continue to support maintaining the current non-O.R. designation 
for procedure codes of ICD-10-PCS procedure codes 0WC94ZZ and 0WCB4ZZ 
because the resources involved in furnishing these procedures does not 
warrant designation as O.R. procedures. Our clinical advisors continue 
to state the thoracoscopic extirpation of the pleural cavities is 
generally performed with other procedures such as heart transplant, 
lung transplant mechanical ventilation, and other major chest 
procedures and would not be the main reason for inpatient 
hospitalization or be considered the principal driver of resource 
expenditure. Our clinical advisors also do not agree that unilaterally 
all thoracoscopic lung procedures should be designated as O.R. 
procedures.
    Our clinical advisors reiterate that thoracoscopic drainage of the 
pleural cavities and thoracoscopic extirpation of the pleural cavities 
are performed for distinct indications in clinically different 
scenarios and disagree with the suggestion that the only difference 
between the PCS root operations ``Drainage'' and ``Extirpation'' is the 
consistency of the substance removed. Rather, drainage procedures take 
out, or let out, fluids and/or gases from a body part and are typically 
performed in the pleural cavity for indications such as congestive 
heart failure, infection, hemothorax and empyema. Extirpation 
procedures are not limited to removing blood clots. In contrast, the 
procedures describing the thoracoscopic extirpation of the pleural 
cavities are performed for a wider range of indications because the 
solid matter removed may be an abnormal byproduct of a biological 
function or a foreign body.
    In response to the commenter that stated highlighted the 
thoracoscopic evacuation of a traumatic hemothorax as an example of how 
these procedures can indeed be primary surgical procedures, we note 
hemothorax is defined as a collection of blood in the pleural cavity. 
The thoracoscopic evacuation of a hemothorax would meet the ICD-10-PCS 
definition of a ``Drainage'' procedure. The procedure codes describing 
the drainage of the pleural cavity were not the subject of this 
request.
    After consideration of the public comments we received, for the 
reasons stated, we are finalizing our proposal to maintain the current 
non-O.R. designation of ICD-10-PCS procedure codes 0WC94ZZ and 0WCB4ZZ, 
without modification, for FY 2022.
(4) Open Pleural Biopsy
    One requestor identified ICD-10-PCS procedure codes 0BBN0ZX 
(Excision of right pleura, open approach, diagnostic) and 0BBP0ZX 
(Excision of left pleura, open approach, diagnostic), that describe an 
open pleural biopsy that the requestor stated are performed in the 
operating room with general anesthesia. The requestor also stated that 
procedure codes 0BBN0ZZ (Excision of right pleura, open approach) and 
0BBP0ZZ (Excision of left pleura, open approach) describing open 
pleural biopsy for non-diagnostic purposes are justifiably designated 
as O.R. procedures. According to the requestor, these procedure codes 
describing an open pleural biopsy should be designated as O.R. 
procedures regardless of whether they are performed for diagnostic or 
therapeutic purposes.
    In the proposed rule we noted that under the ICD-10-PCS procedure 
classification, biopsy procedures are identified by the 7th digit 
qualifier value ``diagnostic'' in the code description. In response to 
the requestor's suggestion that procedures performed for a pleural 
biopsy by an open approach, regardless of whether it is a diagnostic or 
therapeutic procedure, should be designated as an O.R. procedure, we 
examined procedure codes 0BBN0ZX, 0BBN0ZZ, 0BBP0ZX, and 0BBP0ZZ.
    We also noted that in the ICD-10 MS-DRGs Definitions Manual Version 
38.1, procedure codes 0BBN0ZZ and 0BBP0ZZ are currently designated as 
O.R. procedures, however, procedure codes 0BBN0ZX and 0BBP0ZX are not 
recognized as O.R. procedures for purposes of MS-DRG assignment. We 
agreed with the requestor that procedure codes 0BBN0ZX and 0BBP0ZX 
would typically require the resources of an operating room. We stated 
that our clinical advisors also agreed that procedure codes 0BBN0ZX and 
0BBP0ZX would typically require the resources of an operating room. 
Therefore, we proposed to add these 2 procedure codes to the FY 2022 
ICD-10 MS-DRGs Version 39 Definitions Manual in Appendix E--Operating 
Room Procedures and Procedure Code/MS-DRG Index as O.R. procedures, 
assigned to MS-DRGs 166, 167, and 168

[[Page 44898]]

(Other Respiratory System O.R. Procedures with MCC, with CC, and 
without CC/MCC, respectively) in MDC 04 (Diseases and Disorders of the 
Respiratory System).
    Comment: Commenters supported our proposal to designate procedure 
codes 0BBN0ZX and 0BBP0ZX as O.R. procedures.
    Response: After consideration of the public comments we received, 
we are finalizing our proposal to change the designation of procedure 
codes 0BBN0ZX and 0BBP0ZX from non-O.R. procedures to O.R. procedures, 
without modification, effective October 1, 2021.
(5) Percutaneous Revision of Intraluminal Devices
    One requestor identified five ICD-10-PCS procedure codes that 
describe the percutaneous revision of intraluminal vascular devices 
that the requestor stated are currently not recognized as O.R. 
procedures for purposes of MS-DRG assignment. The five procedure codes 
are listed in the following table.
[GRAPHIC] [TIFF OMITTED] TR13AU21.101

    The requestor stated that the procedure codes that describe the 
percutaneous revision of intraluminal vascular devices within arteries, 
veins, and great vessels should be designated as O.R. procedures to 
compensate for the resources needed to perform these procedures. The 
requestor also stated procedures to reattach, realign, or otherwise 
revise intraluminal devices percutaneously require anesthesia, 
specialized equipment for intravascular visualization, significant 
skill, and time, therefore, it is important for these codes to be 
designated with O.R. procedure status.
    In the ICD-10 MS-DRGs Definitions Manual Version 38.1, procedure 
codes 02WY3DZ, 03WY3DZ, 04WY3DZ, 05WY3DZ, and 06WY3DZ are currently 
designated as non-O.R. procedures for purposes of MS-DRG assignment. We 
stated in the proposed rule that we agreed with the requestor that 
these five ICD-10-PCS procedure codes typically require the resources 
of an operating room. Therefore, to the FY 2022 ICD-10 MS-DRG Version 
39 Definitions Manual in Appendix E--Operating Room Procedures and 
Procedure Code/MS-DRG Index, we proposed to add code 02WY3DZ as an O.R. 
procedure assigned to MS-DRGs 270, 271, and 272 (Other Major 
Cardiovascular Procedures, with MCC, with CC, and without CC/MCC, 
respectively) in MDC 05 (Diseases and Disorders of the Circulatory 
System). We also proposed to add codes 03WY3DZ, 04WY3DZ, 05WY3DZ, and 
06WY3DZ as O.R. procedures assigned to MS-DRGs 252, 253, and 254 (Other 
Vascular Procedures with MCC, with CC, and without CC/MCC, 
respectively) in MDC 05 (Diseases and Disorders of the Circulatory 
System).
    Comment: Commenters supported our proposal to designate ICD-10-PCS 
procedure codes 02WY3DZ, 03WY3DZ, 04WY3DZ, 05WY3DZ, and 06WY3DZ as O.R. 
procedures. A commenter noted that they agreed that these procedures do 
typically require the resources of an operating room.
    Response: After consideration of the public comments we received, 
we are finalizing our proposal to change the designation of procedure 
code 02WY3DZ from a non-O.R. procedure to an O.R. procedure, effective 
October 1, 2021, without modification. We are also finalizing our 
proposal to change the designation of procedure codes 03WY3DZ, 04WY3DZ, 
05WY3DZ, and 06WY3DZ from non-O.R. procedures to O.R. procedure, 
without modification, effective October 1, 2021.
(6) Occlusion of Left Atrial Appendage
    One requestor identified nine ICD-10-PCS procedure codes that 
describe left atrial appendage closure (LAAC) procedures that the 
requestor stated are currently not recognized as O.R. procedures for 
purposes of MS-DRG assignment in all instances. The nine procedure 
codes are listed in the following table.

[[Page 44899]]

[GRAPHIC] [TIFF OMITTED] TR13AU21.102

    The requestor stated that these procedures are currently designated 
as non-O.R. procedures that route to surgical MS-DRGs only when 
assigned in combination with a principal diagnosis within MDC 05 
(Diseases and Disorders of the Circulatory System). The requestor 
stated these procedures should also be designated as O.R. procedures 
when assigned in combination with diagnoses outside of the circulatory 
system, such as sepsis or trauma, to compensate for the associated 
resource use, skill requirements, and device costs.
    In the ICD-10 MS-DRG Version 38.1 Definitions Manual, the nine ICD-
10-PCS procedure codes that describe left atrial appendage closure are 
currently recognized as non-O.R. procedures that affect the MS-DRG to 
which they are assigned. We refer readers to section II.D.5.d of the 
preamble of this final rule, where we address ICD-10-PCS procedure 
codes 02L70CK, 02L70DK, and 02L70ZK that describe a LAAC procedure 
performed with an open approach. These codes were discussed in response 
to a request to reassign these codes to MS-DRGs 228 and 229 (Other 
Cardiothoracic Procedures with and without MCC, respectively). In 
section II.D.5.d of this final rule we also summarize and respond to 
the comments regarding our proposal to maintain the assignment of these 
codes in MS-DRGs 273 and 274 (Percutaneous and Other Intracardiac 
Procedures with and without MCC, respectively) in MDC 05 for the 
reasons discussed, and discuss our finalization of that proposal.
    We stated in the proposed rule that our clinical advisors reviewed 
this related issue and believed the current designation of LAAC 
procedures as non-O.R. procedures that affect the assignment for MS-
DRGs 273 and 274 is clinically appropriate to account for the subset of 
patients undergoing left atrial appendage closure specifically. LAAC is 
indicated and approved as a treatment option for patients diagnosed 
with atrial fibrillation, a heart rhythm disorder that can lead to 
cardiovascular blood clot formation, who are also at increased risk for 
stroke. LAAC procedures block off the left atrial appendage to prevent 
emboli that may form in the left atrial appendage from exiting and 
traveling to other sites in the vascular system, thereby preventing the 
occurrence of ischemic stroke and systemic thromboembolism. We noted 
the ICD-10-CM diagnosis codes used to report atrial fibrillation are 
currently assigned to MDC 05 (Diseases and Disorders of the Circulatory 
System). We stated our clinical advisors believed that circumstances in 
which a patient is admitted for a principal diagnosis outside of MDC 05 
and a left atrial appendage closure is performed as the only surgical 
procedure in the same admission are infrequent, and if they do occur, 
the LAAC procedure would not be a significant contributing factor in 
the increased intensity of resources needed for facilities to manage 
these complex cases. Our clinical advisors further stated LAAC 
procedures generally do not require the resources of an operating room. 
LAAC procedures are most often performed percutaneously in settings 
such as cardiac catheterization laboratories and take approximately one 
hour. We stated when performed with an open approach or percutaneous 
endoscopic approach, these procedures share similar factors such as 
complexity, and resource utilization with all other LAAC procedures. 
Therefore, we proposed to maintain the current designation of ICD-10-
PCS procedure codes 02L70CK, 02L70DK, 02L70ZK, 02L73CK, 02L73DK, 
02L73ZK, 02L74CK, 02L74DK, and 02L74ZK as non-O.R. procedures affecting 
the MS-DRGs to which they are assigned.
    Comment: Commenters supported maintaining the current designation 
of procedure codes describing left atrial appendage closure as non-O.R. 
procedures affecting the MS-DRGs to which they are assigned. Another 
commenter stated although they believe it would be reasonable for these 
PCS codes to be designated as O.R. procedures in the event they are 
necessitated during a hospitalization with a principal diagnosis 
outside of MDC 05, their own data analysis showed when performed, cases 
reporting LAAC procedures are being assigned to MS-DRGs 273 and 274 or 
into higher-weighted cardiac MS-DRGs corresponding with other cardiac 
procedures performed during the same stay.
    Response: After consideration of the public comments we received, 
we are finalizing our proposal to maintain the current designation of 
ICD-10-PCS procedure codes 02L70CK, 02L70DK, 02L70ZK, 02L73CK, 02L73DK, 
02L73ZK, 02L74CK, 02L74DK, and 02L74ZK as non-O.R. procedures affecting 
the MS-DRGs to which they are assigned, without modification, for FY 
2022.

[[Page 44900]]

(7) Arthroscopic Drainage of Joints
    One requestor identified six ICD-10-PCS procedure codes that 
describe the percutaneous endoscopic drainage of joints that the 
requestor stated are currently not recognized as O.R. procedures for 
purposes of MS-DRG assignment. The six procedure codes are listed in 
the following table.
[GRAPHIC] [TIFF OMITTED] TR13AU21.103

    The requestor stated that these procedures should be designated as 
O.R. procedures because procedures describing the arthroscopic drainage 
of major joints such as knee, hip, and shoulder are performed in the 
operating room under general anesthesia. The requestor stated these 
procedures are indicated for conditions such as symptomatic septic/
pyogenic arthritis, which can require inpatient admission for 
intravenous antibiotics and arthroscopic drainage to resolve infection. 
Therefore, the requestor stated it is reasonable for these arthroscopic 
procedures to be designated as O.R. procedures to compensate for 
operating room resources.
    In the ICD-10 MS-DRGs Definitions Manual Version 38.1, procedure 
codes 0S9C4ZZ, 0S9D4ZZ, 0S994ZZ, 0S9B4ZZ, 0R9J4ZZ, and 0R9K4ZZ are 
currently designated as non-O.R. procedures for purposes of MS-DRG 
assignment. In the proposed rule, we stated our clinical advisors 
reviewed this issue and disagreed that procedures describing the 
percutaneous endoscopic drainage of major joints such as knee, hip, and 
shoulder are typically performed in the operating room under general 
anesthesia. With development of better instrumentation and surgical 
techniques, many patients now have arthroscopic procedures performed in 
an outpatient setting and return home several hours after the 
procedure. Our clinical advisors also stated the percutaneous 
endoscopic drainage of joints can be performed using local or regional 
anesthesia, and general anesthesia is not always required. We stated 
that in cases where the patient is admitted for diagnoses such as 
septic/pyogenic arthritis, as identified by the requestor, the 
requirement for intravenous antibiotics would be the main reason for 
admission because the percutaneous endoscopic drainage procedure could 
be done as an outpatient. Therefore, we proposed to maintain the 
current non-O.R. designation of ICD-10-PCS procedure codes 0S9C4ZZ, 
0S9D4ZZ, 0S994ZZ, 0S9B4ZZ, 0R9J4ZZ, and 0R9K4ZZ.
    Comment: A commenter supported CMS' proposal to maintain the non-
O.R. designation of procedure codes describing percutaneous endoscopic 
drainage of shoulder, knee, and hip joints.
    Response: We appreciate the commenters' support.
    Comment: A commenter opposed CMS' proposal to maintain the current 
non-O.R. designation of ICD-10-PCS procedure codes 0S9C4ZZ, 0S9D4ZZ, 
0S994ZZ, 0S9B4ZZ, 0R9J4ZZ, and 0R9K4ZZ. This commenter stated that an 
O.R. designation should not be determined based on whether or not a 
surgery is most often performed as an outpatient or based on the type 
anesthesia required during the surgery. This commenter also noted that 
some patients who undergo outpatient surgery require inpatient 
admission instead of release home. The commenter stated that retention 
of non-O.R. procedure status for surgeries most often performed as 
outpatient results in providers not being reimbursed for surgical 
resources when patients require conversion to inpatient, while those 
discharged from outpatient surgery are paid a surgical APC. The 
commenter also included a portion of an operative report from its 
facility to demonstrate that an arthroscopic drainage procedure was 
performed under general anesthesia at their facility.
    Response: Our clinical advisors reviewed the commenters' concerns 
and continue to support maintaining the current non-O.R. designation 
for ICD-10-PCS procedure codes 0S9C4ZZ, 0S9D4ZZ, 0S994ZZ, 0S9B4ZZ, 
0R9J4ZZ, and 0R9K4ZZ. In reviewing the operative report included in the 
comment, our clinical advisors note that using a single isolated case, 
with only an operative report provided and without other diagnostic 
information on the patient, does not provide a clear picture of the 
circumstances of that admission, nor does it inform whether the 
procedure requires the resources of an operating room more broadly. For 
any procedure, there may be instances where performing this procedure 
is best done in the setting of an operative room using general 
anesthesia. However, when looking more broadly at the procedure being 
described by the ICD-10-PCS codes 0S9C4ZZ, 0S9D4ZZ, 0S994ZZ, 0S9B4ZZ, 
0R9J4ZZ, and 0R9K4ZZ, our clinical advisors state in most instances, 
the percutaneous endoscopic drainage of joints does not require the 
resources of an operative room.
    With regard to the comments about the implications for 
reimbursement when cases are converted from outpatient to inpatient, we 
note that the goals of changing the designation of procedures from non-
O.R. to O.R., or vice versa, are to better clinically represent the 
resources involved in caring for these patients and to enhance the 
overall accuracy of the system.
    Therefore, after consideration of the public comments we received, 
for the reasons stated, we are finalizing our proposal to maintain the 
current non-O.R. designation of ICD-10-PCS procedure codes 0S9C4ZZ, 
0S9D4ZZ, 0S994ZZ, 0S9B4ZZ, 0R9J4ZZ, and 0R9K4ZZ, without modification, 
for FY 2022.
(8) Arthroscopic Irrigation of Joints
    One requestor identified ICD-10-PCS procedure codes 3E1U48X 
(Irrigation of joints using irrigating substance, percutaneous 
endoscopic approach, diagnostic) and 3E1U48Z (Irrigation of joints 
using irrigating substance,

[[Page 44901]]

percutaneous endoscopic approach) that the requestor stated are 
currently not recognized as O.R. procedures for purposes of MS-DRG 
assignment. The requestor stated that these procedures should be 
designated as O.R. procedures because the arthroscopic irrigation of 
joints such as knee, hip, and shoulder is performed in the operating 
room under general anesthesia. The requestor states procedure codes 
3E1U48X and 3E1U48Z are used to describe surgical joint irrigations in 
the absence of more definitive procedures, therefore procedure codes 
3E1U48X and 3E1U48Z should be recognized as O.R. procedures for 
purposes of MS-DRG assignment.
    In the ICD-10 MS-DRGs Definitions Manual Version 38.1, procedure 
codes 3E1U48X and 3E1U48Z are currently designated as non-O.R. 
procedures for purposes of MS-DRG assignment. In the proposed rule, we 
stated that our clinical advisors reviewed this issue and disagreed 
that procedure codes describing the arthroscopic irrigation of joints 
should be designated as O.R. procedures. Our clinical advisors noted 
the arthroscopic irrigation of joints is rarely performed independently 
as a standalone procedure in the inpatient setting to be considered the 
principal driver of resource expenditure in those admissions. Instead, 
the arthroscopic irrigation of joints is generally performed with other 
definitive procedures such as debridement or synovectomy. We noted that 
in the operative note sent by the requestor to support the requested 
change in O.R. status, the arthroscopic irrigation of the joint was 
performed along with a surgical debridement procedure. Therefore, we 
proposed to maintain the current non-O.R. designation of ICD-10-PCS 
procedure codes 3E1U48X and 3E1U48Z.
    Comment: A commenter supported CMS' proposal to maintain the non-
O.R. designation of procedure codes describing arthroscopic irrigation 
of joints.
    Response: We appreciate the commenters' support.
    Comment: Another commenter opposed CMS' proposal to maintain the 
non-O.R. designation of ICD-10-PCS procedure codes 3E1U48X and 3E1U48Z. 
This commenter acknowledged that arthroscopic irrigations may be 
performed with other definitive procedures such as bone debridement and 
synovectomy, but stated that some are indeed performed as sole 
definitive operating room procedures. This commenter stated there are 
no other PCS codes for irrigational debridement of joints; when minor 
debridement is performed in conjunction with more significant primary 
procedures, minor debridement is considered inherent and not separately 
reportable.
    Response: We appreciate the commenters' feedback. We are unclear 
from the comment why the commenter references the ICD-10-PCS guidelines 
related to debridement procedures, as this topic relates to the 
arthroscopic irrigation of joints. Our clinical advisors reviewed the 
commenters' concerns and continue to note the arthroscopic irrigation 
of joints is rarely performed independently as a standalone procedure 
in the inpatient setting to be considered the principal driver of 
resource expenditure in those admissions.
    After consideration of the public comments we received, we are 
finalizing our proposal to maintain the current non-O.R. designation of 
ICD-10-PCS procedure codes 3E1U48X and 3E1U48Z, without modification, 
for FY 2022.
(9) Percutaneous Reposition With Internal Fixation
    One requestor identified four ICD-10-PCS procedure codes describing 
procedures performed on the sacroiliac and hip joints that involve 
percutaneous repositioning with internal fixation that the requestor 
stated are not recognized as O.R. procedures for purposes of MS-DRG 
assignment but warrant an O.R. designation. The procedure codes are 
listed in the following table.
[GRAPHIC] [TIFF OMITTED] TR13AU21.104

    We stated in the proposed rule that our clinical advisors reviewed 
the procedures described by these four procedure codes and agreed that 
these percutaneous reposition procedures involving internal fixation in 
the sacroiliac and hip joint warrant an O.R. designation. They noted 
that these procedures are major operations that would require the 
resources of an operating room, involve a higher level of technical 
complexity and a greater utilization of hospital resources.
    Therefore, we proposed to add the two procedure codes describing 
percutaneous reposition of the sacroiliac joint with internal fixation 
procedures (0SS734Z and 0SS834Z) to the FY 2022 ICD-10 MS-DRGs Version 
39 Definitions Manual in Appendix E--Operating Room Procedures and 
Procedure Code/MS-DRG Index as O.R. procedures, assigned to MS-DRGs 
515, 516, and 517 (Other Musculoskeletal System and Connective Tissue 
O.R. Procedures with MCC, with CC, and without CC/MCC, respectively) in 
MDC 08 (Diseases and Disorders of the Musculoskeletal System and 
Connective Tissue) and to MS-DRGs 987, 988, and 989 (Non-Extensive O.R. 
Procedure Unrelated to Principal Diagnosis with MCC, with CC and 
without MCC/CC, respectively). We also proposed to add the two 
procedure codes describing percutaneous reposition of the hip joint 
with internal fixation procedures (0SS934Z and 0SSB34Z) to the FY 2022 
ICD-10 MS-DRGs Version 39 Definitions Manual in Appendix E--Operating 
Room Procedures and Procedure Code/MS- DRG Index as O.R. procedures, 
assigned to MS-DRGs 480, 481, and 482 (Hip and Femur Procedures Except 
Major Joint with MCC, with CC, and without CC/MCC, respectively) in MDC 
08 (Diseases and Disorders of the Musculoskeletal System

[[Page 44902]]

and Connective Tissue) and to MS-DRGs 987, 988, and 989 (Non-Extensive 
O.R. Procedure Unrelated to Principal Diagnosis with MCC, with CC and 
without MCC/CC, respectively).
    Comment: Commenters supported our proposal to designate procedure 
codes 0SS734Z, 0SS834Z, 0SS934Z and 0SSB34Z as O.R. procedures.
    Response: After consideration of the public comments we received, 
we are finalizing our proposal to change the designation of procedure 
codes 0SS734Z, 0SS834Z, 0SS934Z and 0SSB34Z from non-O.R. procedures to 
O.R. procedures, without modification, effective October 1, 2021.
(10) Open Insertion and Removal of Spacer Into Shoulder Joint
    One requestor identified four ICD-10-PCS procedure codes describing 
procedures performed on the shoulder joint that involve the insertion 
or removal of a spacer by an open approach that the requestor stated 
are not recognized as O.R. procedures for purposes of MS-DRG 
assignment. The procedure codes are listed in the following table.
[GRAPHIC] [TIFF OMITTED] TR13AU21.105

    According to the requestor, insertion and removal of joint spacers 
from the hips and knees are designated with an O.R. procedure status 
and although similar procedures performed on the shoulder joint may be 
performed less frequently, these procedures warrant an O.R. designation 
because they are performed in the operating room under general 
anesthesia.
    In the proposed rule we stated that during our review, we noted 
that the following procedure codes describing procedures performed on 
the shoulder joint that involve the insertion or removal of a spacer by 
a percutaneous endoscopic approach are also not recognized as O.R. 
procedures for purposes of MS-DRG assignment.
[GRAPHIC] [TIFF OMITTED] TR13AU21.106

    We stated that our clinical advisors reviewed the procedures 
described by these eight procedure codes and agreed that these 
procedures involving the insertion or removal of a spacer in the 
shoulder joint with an open or percutaneous endoscopic approach warrant 
an O.R. designation. They noted that the insertion of a spacer is 
typically performed to treat an infection at the site of a previously 
placed prosthesis and the removal of a spacer is typically performed 
once the infection is healed and the site is ready for a new prosthetic 
replacement or to exchange for a new spacer if the infection is not yet 
healed.
    Therefore, we proposed to add the listed procedure codes describing 
the insertion or removal of spacer in the shoulder joint to the FY 2022 
ICD-10 MS-DRGs Version 39 Definitions Manual in Appendix E--Operating 
Room Procedures and Procedure Code/MS-DRG Index as O.R. procedures, 
assigned to MS-DRGs 510, 511, and 512 (Shoulder, Elbow or Forearm 
Procedures, Except Major Joint Procedures with MCC, with CC, and 
without CC/MCC, respectively) in MDC 08 (Diseases and Disorders of the 
Musculoskeletal System and Connective Tissue) and to MS-DRGs 987, 988, 
and 989 (Non-Extensive O.R. Procedure Unrelated to Principal Diagnosis 
with MCC, with CC and without MCC/CC, respectively).
    Comment: Commenters supported our proposal to designate the listed 
procedure codes as O.R. procedures.
    Response: We appreciate the commenters' support.
    After consideration of the public comments we received, we are 
finalizing our proposal to change the designation of procedure codes 
0RHK08Z, 0RHJ08Z, 0RPK08Z, 0RPJ08Z, 0RPJ48Z, 0RPK48Z, 0RHJ48Z, and 
0RHK48Z from non-O.R. procedures to O.R. procedures, without 
modification, effective October 1, 2021.
(11) Open/Percutaneous Extirpation of Jaw
    One requestor identified four ICD-10-PCS procedure codes that 
describe the extirpation of matter from the upper or lower jaw that the 
requestor stated are currently not recognized as O.R. procedures for 
purposes of MS-DRG assignment. The four procedure codes are listed in 
the following table.

[[Page 44903]]

[GRAPHIC] [TIFF OMITTED] TR13AU21.107

    The requestor stated that the procedure codes that describe the 
extirpation of matter from the upper or lower jaw by an open or 
percutaneous endoscopic approach should be designated as O.R. 
procedures. The requestor stated these procedures would commonly be 
performed under general anesthesia and require the resources of an 
operating room. The requestor also stated that these ICD-10-PCS codes 
were specifically created to describe the surgical evacuation of solid 
matter from deep jaw structures therefore, it is important for these 
codes to be designated with O.R. procedure status.
    In the ICD-10 MS-DRGs Definitions Manual Version 38.1, procedure 
codes 0WC40ZZ, 0WC44ZZ, 0WC50ZZ, 0WC54ZZ are currently designated as 
non-O.R. procedures for purposes of MS-DRG assignment. We stated in the 
proposed rule that we agreed with the requestor that these four ICD-10-
PCS procedure codes typically require the resources of an operating 
room. Therefore, to the FY 2022 ICD-10 MS-DRG Version 39 Definitions 
Manual in Appendix E--Operating Room Procedures and Procedure Code/MS-
DRG Index, we proposed to add codes 0WC40ZZ, 0WC44ZZ, 0WC50ZZ, 0WC54ZZ 
as O.R. procedures assigned to MS-DRGs 143, 144 and 145 (Other Ear, 
Nose, Mouth and Throat O.R. procedures, with MCC, with CC, and without 
CC/MCC, respectively) in MDC 03 (Diseases and Disorders of the Ear, 
Nose, Mouth and Throat).
    Comment: Commenters supported our proposal to designate ICD-10-PCS 
procedure codes 0WC40ZZ, 0WC44ZZ, 0WC50ZZ, and 0WC54ZZ as O.R. 
procedures. A commenter noted that they agreed that these procedures do 
typically require the resources of an operating room.
    Response: We appreciate the commenters' support.
    After consideration of the public comments we received, we are 
finalizing our proposal to change the designation of procedure codes 
0WC40ZZ, 0WC44ZZ, 0WC50ZZ, 0WC54ZZ from non-O.R. procedures to O.R. 
procedures, without modification, effective October 1, 2021.
(12) Open Extirpation of Subcutaneous Tissue and Fascia
    One requestor identified 22 ICD-10-PCS procedure codes that 
describe the open extirpation of matter from the subcutaneous tissue 
and fascia that the requestor stated are currently not recognized as 
O.R. procedures for purposes of MS-DRG assignment. The 22 procedure 
codes are listed in the following table.
BILLING CODE 4120-01-P

[[Page 44904]]

[GRAPHIC] [TIFF OMITTED] TR13AU21.108

BILLING CODE 4120-01-C
    The requestor stated that procedure codes that describe the open 
extirpation of matter from the subcutaneous tissue and fascia should be 
designated as O.R. procedures because these procedures are performed 
through open incisions with direct visualization of subcutaneous tissue 
and fascia in the operating room under general anesthesia. The 
requestor noted procedure codes that describe the open drainage of 
subcutaneous tissue and fascia and use comparable resources are 
currently designated as O.R. procedures. The requestor noted that root 
operation ``Drainage'' is assigned when fluid is drained; and root 
operation of ``Extirpation'' is assigned when any of the substance 
evacuated is solid. The requestor stated whether the evacuated 
substance is fluid, gelatinous, or solid, a procedure involving an open 
incision with direct visualization of subcutaneous tissue and fascia 
for evacuation of substances should be classified as an O.R. procedure. 
Therefore, the requestor stated that these procedures should also be 
recognized as O.R. procedures for purposes of MS-DRG assignment.
    In the ICD-10 MS-DRGs Definitions Manual Version 38.1, the 22 ICD-
10-PCS procedure codes listed in the table are currently designated as 
non-O.R. procedures for purposes of MS-DRG assignment. We stated in the 
proposed rule that while we disagreed that drainage procedures are 
comparable to extirpation procedures, we agreed with the requestor that 
these 22 ICD-10-PCS procedure codes typically require the resources of 
an operating room. We noted that our clinical advisors stated that 
drainage is the process of taking out, or letting out, fluids and/or 
gases from a body part and is typically performed for indications such 
as abscess, infection, and other systemic conditions. In contrast, 
extirpation procedures are performed for a wider range of indications 
because the solid matter removed may be an abnormal byproduct of a 
biological function or a retained foreign body. Therefore, to the FY 
2022 ICD-10 MS-DRG Version 39 Definitions Manual in Appendix E--
Operating Room Procedures and Procedure Code/MS-DRG Index, we proposed 
to add the 22 ICD-10-PCS listed previously as O.R. procedures assigned 
to MS-DRGs 579, 580 and 581 (Other Skin, Subcutaneous Tissue and Breast 
Procedures, with MCC, with CC, and without CC/MCC, respectively) in MDC 
09 (Diseases and Disorders of the Skin, Subcutaneous Tissue and Breast) 
and MS-DRGs 907, 908, and 909 (Other O.R. Procedures for Injuries with 
MCC, with CC, and without CC/MCC, respectively) in MDC 21 (Injuries, 
Poisonings and Toxic Effects of Drugs).
    Comment: Commenters supported our proposal to designate 22 ICD-10-
PCS procedure codes that describe the open extirpation of matter from 
the subcutaneous tissue and fascia as O.R. procedures. A commenter 
noted that they agreed that open incision with direct visualization of 
subcutaneous tissue and fascia for the evacuation of a substance 
typically requires the resources of an operating room.
    Response: We appreciate the commenters' support.
    After consideration of the public comments we received, we are 
finalizing our proposal to change the designation of the 22 procedure 
codes

[[Page 44905]]

listed in the preceding table from non-O.R. procedures to O.R. 
procedures, without modification, effective October 1, 2021.
(13) Open Revision and Removal of Devices From Subcutaneous Tissue and 
Fascia
    One requestor identified six ICD-10-PCS procedure codes describing 
open revision and removal of neurostimulator generators, monitoring 
devices, and totally implantable vascular access devices (TIVADs) 
procedures that are not currently designated as O.R. procedures for 
purposes of MS-DRG assignment. The six procedure codes are listed in 
the following table.
[GRAPHIC] [TIFF OMITTED] TR13AU21.109

    The requestor stated that although removal of these devices is 
often performed in outpatient surgery, device complications can require 
removal or revision during inpatient hospitalizations. The requestor 
indicated it is reasonable for these open procedures to be designated 
as O.R. procedures to compensate for operating room resources during 
such inpatient stays.
    In the proposed rule we stated that our clinical advisors reviewed 
this request and did not agree that these procedures warrant an O.R. 
designation. They noted that these procedures are generally performed 
in the outpatient setting and when performed during a hospitalization, 
it is typically in conjunction with another O.R. procedure. Therefore, 
we proposed to maintain the current non-O.R. designation for procedure 
codes 0JPT0MZ, 0JPT02Z, 0JPT0WZ, 0JWT0MZ, 0JWT0WZ, and 0JWT03Z for FY 
2022.
    Comment: Commenters supported our proposal to maintain the non-O.R. 
designation for procedure codes 0JPT0MZ, 0JPT02Z, 0JPT0WZ, 0JWT0MZ, 
0JWT0WZ, and 0JWT03Z.
    Response: We appreciate the commenters' support.
    After consideration of the public comments we received, we are 
finalizing our proposal to maintain the non-O.R. designation for 
procedure codes 0JPT0MZ, 0JPT02Z, 0JPT0WZ, 0JWT0MZ, 0JWT0WZ, and 
0JWT03Z, effective October 1, 2021.
(14) Open Insertion of Feeding Device
    One requestor identified ICD-10-PCS procedure code 0DHA0UZ 
(Insertion of feeding device into jejunum, open approach) that the 
requestor stated is currently not recognized as an O.R. procedure for 
purposes of MS-DRG assignment. The requestor stated the open insertion 
of a feeding device into the jejunum should be designated as an O.R. 
procedure because this procedure is performed in the operating room 
under general anesthesia. The requestor noted comparable procedure code 
0DH60UZ (Insertion of feeding device into stomach, open approach) is 
currently designated as an O.R. procedure. Therefore, the requestor 
stated that procedure code 0DHA0UZ should also be recognized as an O.R. 
procedure for purposes of MS-DRG assignment.
    We stated in the proposed rule that our analysis of this issue 
confirmed that in the ICD-10 MS-DRG Version 38.1 Definitions Manual, 
for purposes of MS-DRG assignment, 0DHA0UZ is recognized as a non-O.R. 
procedure and 0DH60UZ is currently recognized as an O.R. procedure. We 
stated that in reviewing this request, we also identified the following 
four related codes:
[GRAPHIC] [TIFF OMITTED] TR13AU21.110


[[Page 44906]]


    In the ICD-10 MS-DRGs Version 38.1, these four ICD-10-PCS codes are 
currently recognized as non-O.R. procedure for purposes of MS-DRG 
assignment. In the proposal rule, we stated that while we agreed with 
the requestor that procedures describing the open insertion of a 
feeding device into the jejunum are comparable to procedures describing 
the open insertion of a feeding device into the stomach, we did not 
agree that these procedures should be designated as O.R. procedures. 
Our clinical advisors stated the procedures that describe the open 
insertion of a feeding device into the jejunum or the stomach should 
instead have the same designation as the related ICD-10-PCS procedure 
codes that describe the open insertion of a feeding device into the 
esophagus, small intestine, duodenum and ileum that are currently 
designated as non-O.R. procedures.
    We noted with advancements in procedural techniques, feeding 
devices are most commonly placed using a percutaneous endoscopic 
approach. Our clinical advisors further stated feeding devices are 
usually not placed using an open surgical approach; this approach is 
generally only used if the patient requires another surgical procedure 
at the same time. When placed at the same time as another surgical 
procedure, our clinical advisors stated the surgical procedure, as the 
main determinant of resource use for those cases, should drive the MS-
DRG assignment, not the procedure that describes the open insertion of 
a feeding device. For these reasons, our clinical advisors stated 
procedures that describe the open insertion of a feeding device in the 
gastrointestinal system should all have the same non-O.R. designation 
in the ICD-10 MS-DRGs Version 39 for coherence.
    Therefore, we proposed to maintain the current non-O.R. designation 
of ICD-10-PCS procedure code 0DHA0UZ. We also proposed to remove ICD-
10-PCS procedure code 0DH60UZ from the FY 2022 ICD-10 MS-DRG Version 39 
Definitions Manual in Appendix E--Operating Room Procedures and 
Procedure Code/MS-DRG Index as an O.R. procedure. We stated in the 
proposed rule that, under this proposal, this procedure would no longer 
impact MS-DRG assignment.
    Comment: A commenter supported CMS' proposal and stated they agreed 
that neither the procedure code describing open insertion of feeding 
device into stomach nor the procedure code describing open insertion of 
feeding device into jejunum should be designated as an O.R. procedure.
    Response: We appreciate the commenters' support.
    Comment: Other commenters opposed CMS' proposal. A commenter stated 
that ICD-10-PCS procedure codes that describe the open insertion of a 
feeding device should be designated as O.R. procedures because they 
require operating room resources with general anesthesia, and involve 
incision through the abdominal wall and into the peritoneal cavity with 
direct visualization. The commenter noted that these procedures may be 
performed as standalone procedures in patients who are unable to have 
feeding tubes placed by percutaneous or percutaneous endoscopic 
approaches because of anatomy, prior surgeries, and adhesions. Another 
commenter stated that open feeding tube insertions are associated with 
higher resource use, are prone to more complications, have higher 
mortality rates, and can have extended recovery times and these 
procedures should have an OR designation to accurately reflect the 
resource use for the patient.
    Response: We appreciate the commenters' feedback and concern. In 
response to the comment that these procedures may be performed as 
standalone procedures in patients who are unable to have feeding tubes 
placed by percutaneous or percutaneous endoscopic approaches, our 
clinical advisors note there may be instances when performing any 
procedure is best done in the setting of an operative room using 
general anesthesia. However, when looking more broadly at the 
procedures being described, and the manner in which these procedures 
are most often performed and their associated resource use our clinical 
advisors believe that the open insertion of a feeding device in the 
gastrointestinal system do not warrant an O.R. designation. They noted 
that these procedures, when performed during a hospitalization, are 
typically in conjunction with another O.R. procedure and maintain that 
procedures that describe the open insertion of a feeding device into 
the esophagus, stomach, small intestine, duodenum, jejunum and ileum 
are all clinically aligned. Accordingly, our clinical advisors state 
procedures that describe the open insertion of a feeding device in the 
gastrointestinal system should all have the same non-O.R. designation 
in the ICD-10 MS-DRGs Version 39 for coherence.
    After consideration of the public comments we received, for the 
reasons stated, we are finalizing our proposal to maintain the current 
non-O.R. designation of ICD-10-PCS procedure code 0DHA0UZ for FY 2022, 
without modification. We are also finalizing our proposal to change the 
designation of ICD-10-PCS procedure code 0DH60UZ from O.R. procedure to 
non-O.R. procedure, without modification, effective October 1, 2021.
(15) Laparoscopic Insertion of Feeding Tube
    One requestor identified ICD-10-PCS procedure codes 0DH64UZ 
(Insertion of feeding device into stomach, percutaneous endoscopic 
approach) and 0DHA4UZ (Insertion of feeding device into jejunum, 
percutaneous endoscopic approach) that the requestor stated are 
currently not recognized as O.R. procedures for purposes of MS-DRG 
assignment. The requestor stated the procedures describing the 
percutaneous endoscopic insertion of a feeding device into the stomach 
or the jejunum should be designated as O.R. procedures because these 
procedures are performed in the operating room under general 
anesthesia. The requestor stated all laparoscopic procedures, 
regardless if they are diagnostic or therapeutic, should be classified 
as O.R. procedures to compensate for operating room resources.
    In the proposed rule, we stated our analysis of this issue 
confirmed that in the ICD-10 MS-DRG Version 38.1 Definitions Manual, 
0DH64UZ and 0DHA4UZ are currently designated as non-O.R. procedures for 
purposes of MS-DRG assignment. We stated in reviewing this request, we 
also identified the following four related codes:

[[Page 44907]]

[GRAPHIC] [TIFF OMITTED] TR13AU21.111

    In the ICD-10 MS-DRGs Version 38.1, these four ICD-10-PCS codes are 
currently recognized as non-O.R. procedures for purposes of MS-DRG 
assignment. We stated in the proposed rule that our clinical advisors 
reviewed this request and did not agree that unilaterally all 
laparoscopic procedures should be designated as O.R. procedures. We 
stated that while the procedural approach is an important consideration 
in the designation of a procedure, there are other clinical factors 
such as the site of procedure, the procedure complexity, and resource 
utilization that should also be considered. In this regard, our 
clinical advisors indicated that codes 0DH64UZ and 0DHA4UZ describing 
the percutaneous endoscopic insertion of a feeding device into the 
stomach or the jejunum, do not require the resources of an operating 
room, are not surgical in nature, and are generally performed in the 
outpatient setting. The percutaneous endoscopic insertion of a feeding 
device also does not require general anesthesia. As opposed to being 
rendered unconscious, patients can receive a local anesthetic (usually 
a lidocaine spray), an intravenous (IV) pain reliever, and a mild 
sedative if needed. Patients receiving these devices usually return 
home the same day after placement, unless they are in the hospital for 
treatment of another condition.
    Our clinical advisors stated the percutaneous endoscopic insertion 
of a feeding device into the stomach or the jejunum is comparable to 
the related ICD-10-PCS procedure codes that describe the insertion of 
feeding devices of other gastrointestinal system body parts that are 
currently designated as non-O.R. procedures. We stated our clinical 
advisors believed all procedures that describe the percutaneous 
endoscopic insertion of a feeding device in the gastrointestinal system 
should continue to have the same non-O.R. designation in the ICD-10 MS-
DRGs Version 39 for coherence. Therefore, for the reasons discussed, we 
proposed to maintain the current non-O.R. designation of ICD-10-PCS 
procedure codes 0DH64UZ and 0DHA4UZ.
    Comment: A commenter supported CMS' proposal and stated they agreed 
that all procedures that describe the percutaneous endoscopic insertion 
of a feeding device in the gastrointestinal system should continue to 
have the same non-O.R. designation.
    Response: We appreciate the commenters' support.
    Comment: Other commenters opposed CMS' proposal. A commenter stated 
that ICD-10-PCS procedure codes that describe the percutaneous 
endoscopic insertion of a feeding device should be designated as O.R. 
procedures. This commenter stated that laparoscopic procedures, whether 
performed inpatient or outpatient, are indeed surgical procedures which 
require general anesthesia, have increased procedural risks, and 
require high skill and specialized equipment. The commenter stated that 
when necessitated during inpatient stays, even if infrequent, providers 
should be compensated for operating room resources. Another commenter 
stated that these procedures require the use of an operating room and 
should be classified in a manner that reflects the resources expended 
by the facility in the care and treatment of the patient.
    Response: We appreciate the commenters' feedback and concern. Our 
clinical advisors reviewed the commenters' concerns and continue to 
state the percutaneous endoscopic insertion of a feeding device into 
the stomach or the jejunum, does not require the resources of an 
operating room or general anesthesia. Our advisors state these 
procedures are not surgical in nature, and because treatment practices 
have shifted are generally performed in the outpatient setting. When 
performed in the inpatient setting, patients are generally in the 
hospital for the treatment of another condition as opposed to the need 
for operating room resources in an inpatient setting. Accordingly, when 
considering clinical factors such as the site of procedure, the 
procedure complexity, and resource utilization, when performed in the 
inpatient setting, they believe the non-O.R. designation of procedure 
codes describing the percutaneous endoscopic insertion of a feeding 
device is supported.
    Therefore, after consideration of the public comments we received, 
we are finalizing our proposal to maintain the current non-O.R. 
designation of ICD-10-PCS procedure codes 0DH64UZ and 0DHA4UZ, without 
modification, for FY 2022.
(16) Endoscopic Fragmentation and Extirpation of Matter of Urinary 
Tract
    As discussed in the proposed rule, one requestor sent two separate 
but related requests related to endoscopic procedures performed in the 
urinary system. With regard to the first request, the requestor 
identified six ICD-10-PCS procedure codes that describe endoscopic 
fragmentation in the kidney pelvis, ureter, bladder, and bladder neck 
that the requestor stated are currently not recognized as O.R. 
procedures for purposes of MS-DRG assignment. The six procedure codes 
are listed in the following table.

[[Page 44908]]

[GRAPHIC] [TIFF OMITTED] TR13AU21.112

    The requestor stated that these procedures should be designated as 
O.R. procedures because procedures such as the endoscopic fragmentation 
of calculi within the kidney pelvis, ureter, bladder, and bladder neck 
are performed in the operating room under anesthesia. The requestor 
stated that procedures that describe the endoscopic extirpation of 
calculi from the kidney pelvis or ureter use comparable resources, and 
are designated as O.R. procedures. Therefore, the requestor asserted it 
is reasonable that procedure codes that describe endoscopic 
fragmentation in kidney pelvis, ureter, bladder, and bladder neck also 
be designated as O.R. procedures.
    In the ICD-10 MS-DRGs Definitions Manual Version 38.1, procedure 
codes 0TF38ZZ, 0TF48ZZ, 0TF68ZZ, 0TF78ZZ, 0TFB8ZZ, and 0TFC8ZZ are 
designated as non-O.R. procedures for purposes of MS-DRG assignment. We 
stated in the proposed rule that our clinical advisors reviewed this 
issue and disagreed that procedures describing the endoscopic 
fragmentation of calculi within the kidney pelvis, ureter, bladder, and 
bladder neck are typically performed in the operating room. We stated 
that in endoscopic fragmentation procedures in the kidney pelvis, 
ureter, bladder, and bladder neck, the scope is passed through a 
natural or artificial orifice. The procedure is not surgical in nature 
and involves no skin incisions. With advancements in scope size, 
deflection capabilities, video imaging, and instrumentation, many 
patients now have these endoscopic urinary procedures performed in an 
outpatient setting, instead of the inpatient setting. Therefore, we 
proposed to maintain the current non-O.R. designation of ICD-10-PCS 
procedure codes 0TF38ZZ, 0TF48ZZ, 0TF68ZZ, 0TF78ZZ, 0TFB8ZZ, and 
0TFC8ZZ.
    In the second request, the requestor also identified two ICD-10-PCS 
procedure codes that describe endoscopic extirpation of matter from the 
bladder and bladder neck that the requestor stated are also currently 
not recognized as O.R. procedures for purposes of MS-DRG assignment. 
The two procedure codes are listed in the following table.
[GRAPHIC] [TIFF OMITTED] TR13AU21.113

    The requestor stated that these procedures also should be 
designated as O.R. procedures because they performed in the operating 
room under anesthesia.
    In the ICD-10 MS-DRGs Definitions Manual Version 38.1, procedure 
codes 0TCB8ZZ and 0TCC8ZZ are currently designated as a non-O.R. 
procedure for purposes of MS-DRG assignment. As indicated in the 
proposed rule, in response to the second request to designate 0TCB8ZZ 
and 0TCC8ZZ as O.R. procedures and in response to the requestor's 
suggestion that resource consumption is comparable in procedures 
describing endoscopic fragmentation in the urinary system and 
procedures describing the endoscopic extirpation in the urinary system, 
we examined the following procedure codes:

[[Page 44909]]

[GRAPHIC] [TIFF OMITTED] TR13AU21.114

BILLING CODE 4120-01-C
    In the ICD-10 MS-DRG Version 38.1 Definitions Manual, these six 
ICD-10-PCS procedure codes are currently recognized as O.R. procedures 
for purposes of MS-DRG assignment. We stated in the proposed rule that 
our clinical advisors indicated that these procedures are not surgical 
in nature. In endoscopic extirpation procedures, the scope enters the 
urinary tract through the urethra, which is the tube that carries urine 
out of the body, or through an artificial orifice. Our clinical 
advisors further stated the urinary system is one conduit so the scope 
continues to pass through the urethra, bladder, and into the ureter or 
kidney (if necessary) to access the stone. For that reason, we stated 
the procedures describing endoscopic extirpation from a urinary body 
part should all have the same non-O.R. designation in the ICD-10 MS-
DRGs Version 39 for coherence.
    Therefore, we proposed to maintain the current non-O.R. designation 
of ICD-10-PCS procedure codes 0TCB8ZZ and 0TCC8ZZ. We also proposed to 
remove ICD-10-PCS procedure codes 0TC08ZZ, 0TC18ZZ, 0TC38ZZ, 0TC48ZZ, 
0TC68ZZ, and 0TC78ZZ from the FY 2022 ICD-10 MS-DRG Version 39 
Definitions Manual in Appendix E--Operating Room Procedures and 
Procedure Code/MS-DRG Index as O.R. procedures. We stated in the 
proposed rule that, under this proposal, these procedures would no 
longer impact MS-DRG assignment.
    Comment: Commenters supported CMS' proposal. A commenter stated 
they supported maintaining the non-O.R. designation of procedure codes 
describing fragmentation in the kidney pelvis, ureter, bladder, and 
bladder neck via natural or artificial opening endoscopic approach. 
This commenter supported maintaining the non-O.R. designation of the 
procedure codes describing endoscopic extirpation of matter from the 
bladder and bladder neck and removing six procedure codes describing 
endoscopic extirpation of matter from the kidney, kidney pelvis, and 
ureter from the O.R. procedure list. This commenter stated they agreed 
that procedures describing endoscopic extirpation from a urinary body 
part should all have the same non-O.R. designation.
    Response: We appreciate the commenters' support.
    Comment: Other commenters opposed CMS' proposal. These commenters 
stated endoscopic kidney and ureter procedures traverse narrow tubular 
structures and require the operating room with specialized equipment, 
positioning, image-guidance, and general anesthesia to obtain the 
surgical precision and satisfactory pain control that cannot be 
provided at the bedside. A commenter stated that although providers 
attempt to manage conditions that might warrant the performance of 
these procedures in the outpatient setting, some patients fail 
outpatient preventative measures and require both medical and surgical 
interventions in an inpatient setting.
    Response: We appreciate the commenters' feedback and concern.
    Our clinical advisors reviewed the commenters' concerns and state 
with development of better instrumentation and surgical techniques, 
many patients now have endoscopic fragmentation procedures and 
endoscopic extirpation procedures performed in an outpatient setting. 
In response to the comment that these procedures cannot be provided at 
the bedside, we wish to clarify the designation of a procedure as a 
non-O.R. procedure is not limited to procedures that can be performed 
at the patient's bedside. While the site in which the procedure is 
performed and the procedural approach are important considerations in 
the designation of a procedure, there are other clinical factors such 
as procedure complexity, resource utilization, and need for anesthesia 
administration that should also be considered. In this regard, our 
clinical advisors state endoscopic fragmentation procedures and 
endoscopic extirpation procedures are not surgical in nature, because 
treatment practices have shifted and they do not generally require the 
resources of an operating room or general anesthesia in an inpatient 
setting.
    After consideration of the public comments we received, for the 
reasons stated, we are, without modification, (1) finalizing our 
proposal to maintain the current non-O.R. designation of ICD-10-PCS 
procedure codes 0TF38ZZ, 0TF48ZZ, 0TF68ZZ, 0TF78ZZ, 0TFB8ZZ, and 
0TFC8ZZ for FY 2022 and (2) finalizing our proposal to maintain the 
current non-O.R. designation of ICD-10-PCS procedure codes 0TCB8ZZ and 
0TCC8ZZ for FY 2022. We are also finalizing our proposal to change the 
designation of ICD-10-PCS procedure codes 0TC08ZZ, 0TC18ZZ, 0TC38ZZ, 
0TC48ZZ, 0TC68ZZ, and 0TC78ZZ from O.R. procedures to non-O.R. 
procedures, without modification, effective October 1, 2021.
(17) Endoscopic Removal of Ureteral Stent
    One requestor identified ICD-10-PCS procedure code 0TP98DZ (Removal 
of intraluminal device from ureter, via natural or artificial opening 
endoscopic) that the requestor stated is not recognized as an O.R. 
procedure for

[[Page 44910]]

purposes of MS-DRG assignment. The requestor suggested that this 
procedure warrants an O.R. designation because the procedure code 
describes a procedure that is performed in the operating room with 
anesthesia. The requestor stated that while most ureteral stents can be 
removed by string, some complicated cases require endoscopic removal 
using forceps in the operating room under general anesthesia and may be 
performed during inpatient stays precipitated by severe urinary tract 
infection, sepsis, or urinary obstructions. The requestor asserted that 
procedure codes for insertion of ureteral stent(s) via a ureteroscopic, 
endoscopic approach have been justifiably designated as O.R. procedures 
because they are performed in the O.R. under anesthesia. Therefore, the 
requestor suggested it is reasonable for endoscopic removal of the 
stent to be designated with OR procedure status to compensate for 
operating room resources and anesthesia.
    We stated in the proposed rule that our clinical advisors reviewed 
this procedure and did not agree that it warrants an O.R. designation. 
They noted that this procedure is generally not the focus of the 
admission when it is performed and does not reflect the technical 
complexity or resource intensity in comparison to other procedures that 
are designated as O.R. procedures. Therefore, we proposed to maintain 
the current non-O.R. designation for procedure code 0TP98DZ for FY 
2022.
    Comment: Commenters supported our proposal to maintain the non-O.R. 
designation for procedure code 0TP98DZ.
    Response: We appreciate the commenters' support.
    Comment: A commenter did not support our proposal based on the 
rationale provided. According to the commenter, patients may be 
admitted with sepsis and/or urinary tract infections associated with 
ureteral stents and require joint focuses of treatment consisting of 
removal of a stent(s) and intravenous antibiotics. The commenter stated 
that patients who require stent removal during hospitalization are 
those who have chronic diagnoses, altered anatomy, or encrusted stents 
that prevent removal from being performed elsewhere.
    Response: Our clinical advisors maintain that generally, the 
procedure to remove a ureteral stent endoscopically is not the focus or 
driver of resources for an inpatient admission. With respect to 
patients who may be admitted with or acquire an infection during the 
hospitalization, it is understood that these patients typically consume 
additional resources, however, our clinical advisors do not believe 
that the endoscopic removal of a ureteral stent is a contributing 
factor. For those patients who have a chronic diagnosis, altered 
anatomy or an encrusted stent requiring stent removal specifically in 
an inpatient setting, we believe additional analysis may be 
advantageous to determine if a subset of the claims reporting these 
conditions warrant any modifications to the GROUPER logic. However, the 
commenter did not provide a list of the specific ICD-10-CM diagnoses 
describing these conditions for CMS to consider in its analysis for FY 
2022. We intend to work with the commenter and examine this issue for 
consideration in future rulemaking.
    After consideration of the public comments we received, we are 
finalizing our proposal to maintain the non-O.R. designation for 
procedure code 0TP98DZ, effective October 1, 2021.
(18) Endoscopic/Transorifice Inspection of Ureter
    One requestor identified ICD-10-PCS procedure code 0TJ98ZZ 
(Inspection of ureter, via natural or artificial opening endoscopic), 
that describes procedures involving endoscopic viewing of the ureter 
that the requestor stated is currently not recognized as an O.R. 
procedure for purposes of MS-DRG assignment.
    The requestor stated this ureteroscopy procedure is performed in 
the operating room with anesthesia. According to the requestor, the 
inspection of ureter procedure code is assigned when obstruction is 
found during the ureteroscopy and procedures to break up 
(fragmentation), remove calculi (extirpation), or place a ureteral 
stent cannot be performed.
    In the proposed rule we stated that our clinical advisors reviewed 
this procedure and disagree that it warrants an O.R. designation. They 
noted that this procedure typically does not require hospitalization 
and is generally not the reason for the patient's admission since it is 
often performed in connection with another O.R. procedure when it is 
performed. Therefore, we proposed to maintain the current non-O.R. 
designation for procedure code 0TJ98ZZ for FY 2022.
    Comment: Commenters supported our proposal to maintain the non-O.R. 
designation for procedure code 0TJ98ZZ.
    Response: We appreciate the commenters' support.
    Comment: A commenter did not support our proposal to maintain the 
non-O.R. designation for procedure code 0TJ98ZZ based on the rationale 
that this procedure typically does not require hospitalization and is 
generally not the reason for the patient's admission since it is often 
performed in connection with another O.R. procedure. According to the 
commenter, whether or not a procedure is most often performed as an 
outpatient should not be the determining factor for designating O.R. 
status.
    Response: Our clinical advisors maintain that typically, this 
procedure is not the basis for an inpatient admission and as noted 
earlier in this section, when we state a current non-O.R. procedure is 
typically performed in conjunction with another O.R. procedure, we are 
indicating that there is generally another O.R. procedure reported on 
the claim that is primarily responsible for impacting the utilization 
of resources for that admission. We wish to clarify that statements 
indicating a procedure is most often performed as an outpatient or in 
an outpatient setting are not the single determining factor in our 
proposals to maintain or modify the designation of a procedure code 
from O.R. to non-O.R. or vice versa, rather, the proposals set forth in 
rulemaking are based on a combination of clinical judgment and data, 
when applicable.
    After consideration of the public comments we received, we are 
finalizing our proposal to maintain the non-O.R. designation for 
procedure code 0TJ98ZZ, without modification, effective October 1, 
2021.
(19) Endoscopic Biopsy of Ureter and Kidney
    One requestor identified six ICD-10-PCS procedure codes that 
describe endoscopic biopsy procedures performed on the ureter and 
kidney structures that the requestor stated are currently not 
recognized as O.R. procedures for purposes of MS-DRG assignment. 
According to the requestor, regardless of whether it is a diagnostic or 
therapeutic procedure, these procedures should be designated as O.R. 
procedures because the procedures utilize operating room, anesthesia 
and recovery room resources. The requestor stated that after the 
surgeon places the scope into the bladder that ureteral orifices must 
be identified and instruments carefully navigated to obtain excisional 
biopsies from within the ureter or further within the kidney. The six 
procedure codes are listed in the following table.

[[Page 44911]]

[GRAPHIC] [TIFF OMITTED] TR13AU21.115

In the proposed rule we noted that under the ICD-10-PCS procedure 
classification, biopsy procedures are identified by the 7th digit 
qualifier value ``diagnostic'' in the code description.
    We also noted that our clinical advisors do not agree that 
endoscopic biopsy procedures performed on the ureter and kidney 
structures warrant an O.R. designation. They stated these procedures 
are typically not the focus for the patient's admission and are 
frequently performed in conjunction with another O.R. procedure. 
Therefore, we proposed to maintain the current non-O.R. designation for 
procedure codes 0TB08ZX, 0TB18ZX, 0TB38ZX, 0TB48ZX, 0TB68ZX, and 
0TB78ZX for FY 2022.
    Comment: Commenters supported our proposal to maintain the non-O.R. 
designation for procedure codes 0TB08ZX, 0TB18ZX, 0TB38ZX, 0TB48ZX, 
0TB68ZX, 0TB78ZX.
    Response: We appreciate the commenters' support.
    Comment: A commenter did not support our proposal. According to the 
commenter, urinary obstructions and associated urinary tract infections 
with or without sepsis can necessitate inpatient admissions, and 
abnormalities on imaging can raise suspicion for malignancy requiring 
biopsy for diagnosis and treatment. The commenter stated that when 
these procedures are standalone procedures performed during inpatient 
hospitalizations, they warrant O.R. procedure status for the same 
reasons as the procedures describing endoscopic fragmentation or 
extirpation of the urinary tract described previously.
    Response: We appreciate the commenter's feedback. Similar to the 
reasons discussed for procedures describing the endoscopic 
fragmentation or extirpation of the urinary tract, our clinical 
advisors maintained that with the development of better instrumentation 
and surgical techniques, many patients now have endoscopic procedures 
involving urinary tract structures performed in an outpatient setting. 
In addition, they stated that these procedures are not surgical in 
nature.
    After consideration of the public comments we received, we are 
finalizing our proposal to maintain the non-O.R. designation for 
procedure codes 0TB08ZX, 0TB18ZX, 0TB38ZX, 0TB48ZX, 0TB68ZX, and 
0TB78ZX, without modification, effective October 1, 2021.
(20) Transorifice Insertion of Ureteral Stent
    One requestor identified three ICD-10-PCS procedure codes that the 
requestor stated are not recognized as O.R. procedures for purposes of 
MS-DRG assignment. The requestor suggested that the procedure described 
by these procedure codes warrants an O.R. designation because it 
involves the insertion of an indwelling ureteral stent through a 
nephrostomy with image-guidance in the interventional radiology suite. 
According to the requestor, image-guided technology now allows 
placement of ureteral stents through nephrostomy tracts. The requestor 
stated this procedure may or may not be performed in the operating 
room, however, it involves placement of device(s), interventional 
radiology resources, sedation, and continuous monitoring of vital 
signs. The three procedure codes are shown in the following table.
[GRAPHIC] [TIFF OMITTED] TR13AU21.116

    In the proposed rule we stated that our clinical advisors reviewed 
this request and do not agree that this procedure warrants an O.R. 
designation. They noted that this procedure is not surgical in nature, 
does not require the resources of an operating room and is not a 
technically complex procedure requiring increased hospital resources. 
Therefore, we proposed to maintain the current non-O.R. designation for 
procedure codes 0T767DZ, 0T777DZ, and 0T787DZ for FY 2022.
    Comment: Commenters supported our proposal to maintain the non-O.R. 
designation for procedure codes 0T767DZ, 0T777DZ, and 0T787DZ.
    Response: We appreciate the commenters' support.
    After consideration of the public comments we received, we are 
finalizing our proposal to maintain the non-O.R. designation for 
procedure codes 0T767DZ, 0T777DZ, and 0T787DZ, without modification, 
effective October 1, 2021.

[[Page 44912]]

(21) Percutaneous Insertion of Ureteral Stent
    One requestor identified three ICD-10-PCS procedure codes that the 
requestor stated are not recognized as O.R. procedures for purposes of 
MS-DRG assignment. The requestor suggested that the procedure described 
by these procedure codes warrants an O.R. designation because the 
procedure is typically performed following a failed ureteral stent 
insertion procedure in the operating room, which can only be reported 
as a cystoscopy or ureteroscopy, neither of which are designated as 
O.R. procedures. According to the requestor, percutaneous ureteral 
stenting through the abdominal wall is subsequently performed in an 
interventional radiology suite with image-guidance, sedation, and 
continuous vital sign monitoring. The three procedure codes are shown 
in the following table.
[GRAPHIC] [TIFF OMITTED] TR13AU21.117

    In the proposed rule we stated that our clinical advisors reviewed 
this request and do not agree that the procedure warrants an O.R. 
designation. They noted that this procedure is not surgical in nature, 
does not involve technical complexity or require the resources of an 
operating room. Therefore, we proposed to maintain the current non-O.R. 
designation for procedure codes 0T763DZ, 0T773DZ, and 0T783DZ for FY 
2022.
    Comment: Commenters supported our proposal to maintain the non-O.R. 
designation for procedure codes 0T763DZ, 0T773DZ, and 0T783DZ.
    Response: We appreciate the commenters' support.
    After consideration of the public comments we received, we are 
finalizing our proposal to maintain the non-O.R. designation for 
procedure codes 0T763DZ, 0T773DZ, and 0T783DZ, without modification, 
effective October 1, 2021.
(22) Endoscopic Dilation of Urethra
    One requestor identified ICD-10-PCS procedure code 0T7D8DZ 
(Dilation of urethra with intraluminal device, via natural or 
artificial opening endoscopic) that the requestor stated is not 
recognized as an O.R. procedure for purposes of MS-DRG assignment. The 
requestor suggested that this procedure warrants an O.R. designation 
because the procedure code describes a procedure that utilizes the 
UroLift[supreg] System, a minimally invasive technology to treat lower 
urinary tract symptoms (LUTS) due to benign prostatic hyperplasia 
(BPH). According to the requestor, the technology is placed 
endoscopically within the prostatic urethra in the operating room under 
anesthesia.
    In the proposed rule we stated that our clinical advisors reviewed 
this request and do not agree that the procedure warrants an O.R. 
designation. They noted that this procedure is performed without 
incision, resection or thermal injury to the prostate and is primarily 
performed in the outpatient setting. It is generally not the cause for 
the patient's admission and utilization of resources when it is 
performed. Therefore, we proposed to maintain the current non-O.R. 
designation for procedure code 0T7D8DZ for FY 2022.
    Comment: Commenters supported our proposal to maintain the non-O.R. 
designation for procedure code 0T7D8DZ.
    Response: We appreciate the commenters' support.
    Comment: A commenter did not support our proposal to maintain the 
non-O.R. designation for procedure code 0T7D8DZ based on the rationale 
that this procedure is primarily performed in the outpatient setting 
and is generally not the cause for the patient's admission and 
utilization of resources. According to the commenter, whether or not a 
procedure is most often performed as an outpatient should not be the 
determining factor in O.R status. The commenter asserted that in its 
review of procedures currently assigned to MS-DRGs 671 and 672, the 
procedure described by procedure code 0T7D8DZ utilizes comparable O.R. 
resources.
    Response: We thank the commenter for their feedback. Our clinical 
advisors maintain that typically, this procedure is not the basis for 
an inpatient admission and if performed, it does not increase the 
consumption of hospital resources to warrant O.R. status. With regard 
to the list of procedures currently assigned to MS-DRGs 671 and 672 and 
the assertion that code 0T7D8DZ utilizes comparable O.R. resources, as 
stated in previous rulemaking, as well as, the preamble of the FY 2022 
IPPS/LTCH PPS proposed rule and this final rule, we are in the process 
of reviewing prior stakeholder feedback on criteria and factors to 
consider on what constitutes a procedure being designated as O.R versus 
non-O.R. as a component of our broader comprehensive procedure code 
review. We are allowing additional time for the claims data to 
stabilize prior to selecting the timeframe to analyze for this review 
considering the PHE, and to develop our proposed methodology. 
Therefore, we will be examining all the procedures currently assigned 
to MS-DRGs 671 and 672 in connection with that process and discuss if 
modifications to the designation of code 0T7D8DZ are warranted.
    After consideration of the public comments we received, we are 
finalizing our proposal to maintain the non-O.R. designation for 
procedure code 0T7D8DZ, without modification, effective October 1, 
2021.
(23) Open Repair of Scrotum
    One requestor identified ICD-10-PCS procedure code 0VQ50ZZ (Repair 
scrotum, open approach) that the requestor stated is not recognized as 
an O.R. procedure for purposes of MS-DRG assignment. The requestor 
suggested that this procedure warrants an O.R. designation because it 
involves repair of scrotal tissue deeper than the skin with direct 
visualization and utilizes general anesthesia in the operating room.
    We noted in the proposed rule that our clinical advisors do not 
agree that open repair of the scrotum merits an O.R. designation. They 
stated this procedure would not typically require the resources of an 
operating room and would generally not be a contributing factor 
impacting hospital resource use during the patient's admission when it 
is performed. Therefore, we proposed to maintain the current non-O.R. 
designation for procedure code 0VQ50ZZ for FY 2022.

[[Page 44913]]

    Comment: Commenters supported our proposal to maintain the non-O.R. 
designation for procedure code 0VQ50ZZ.
    Response: We appreciate the commenters' support.
    After consideration of the public comments we received, we are 
finalizing our proposal to maintain the non-O.R. designation for 
procedure code 0VQ50ZZ, without modification, effective October 1, 
2021.
(24) Open Drainage of Vestibular Gland
    One requestor identified ICD-10-PCS procedure code 0U9L0ZZ 
(Drainage of vestibular gland, open approach) that describes a 
procedure commonly performed for the treatment of an abscess that the 
requestor stated is performed in the operating room under general 
anesthesia and therefore warrants an O.R designation. The requestor 
stated this procedure is comparable to the procedure described by 
procedure code 0UBL0ZZ (Excision of vestibular gland, open approach) 
which is currently designated as an O.R. procedure.
    We stated in the proposed rule that during our review of procedure 
code 0U9L0ZZ, we also examined procedure codes 0U9L0ZX (Drainage of 
vestibular gland, open approach, diagnostic), 0U9LXZX (Drainage of 
vestibular gland, external approach, diagnostic), and 0UBL0ZZ. 
Separately, we reviewed procedure code 0T9D0ZZ (Drainage of urethra, 
open approach) because it represents the male equivalent of the female 
procedure described by procedure code 0U9L0ZZ.
    In the ICD-10 MS-DRGs Definitions Manual Version 38.1, procedure 
codes 0T9D0ZZ, 0U9L0ZX, 0U9LXZX, and 0UBL0ZZ are currently designated 
as O.R. procedures, however, procedure code 0U9L0ZZ is not recognized 
as an O.R. procedure for purposes of MS-DRG assignment. In the proposed 
rule we stated that we examined procedure code 0U9L0ZZ and do not 
believe this drainage procedure warrants an O.R. designation, nor do we 
agree that this drainage of the vestibular gland procedure (0U9L0ZZ) is 
comparable to an excision of the vestibular gland procedure (0UBL0ZZ), 
which is currently designated as an O.R. procedure.
    In the ICD-10-PCS classification, drainage is defined as taking or 
letting out fluids and/or gases from a body part and excision is 
defined as cutting out or off, without replacement, a portion of a body 
part. Therefore, the classification specifically defines and 
distinguishes the underlying objectives of each distinct procedure. In 
the proposed rule we noted that our clinical advisors stated a drainage 
procedure is frequently performed in the outpatient setting and is 
generally not the cause for the patient's admission and utilization of 
resources when it is performed. Drainage of the vestibular gland, also 
known as Bartholin's glands, is typically indicated when a cyst or 
abscess is present and may or may not involve the placement of a Word 
catheter. Conversely, excision of the vestibular gland is not 
considered an office-based procedure and is generally reserved for a 
vulvar mass or for patients who have not responded to more conservative 
attempts to create a drainage tract. In addition, after review, our 
clinical advisors recommended changing the O.R. status for procedure 
codes 0U9L0ZX and 0U9LXZX from O.R. to non-O.R. for similar reasons. 
These procedures do not typically require the resources of an operating 
room.
    Therefore, we proposed to remove procedure codes 0U9L0ZX and 
0U9LXZX from the FY 2022 ICD-10 MS-DRGs Version 39 Definitions Manual 
in Appendix E- Operating Room Procedures and Procedure Code/MS-DRG 
Index as O.R. procedures and noted that under this proposal, these 
procedure codes would no longer impact MS-DRG assignment. We refer the 
reader to section II.D.10 of the preamble of the proposed rule and this 
final rule for further discussion related to procedure code 0T9D0ZZ.
    Comment: Commenters supported our proposal to maintain the non-O.R. 
designation of procedure code 0U9L0ZZ and to change the designation of 
procedure codes 0U9L0ZX and 0U9LXZX from O.R. to non-O.R.
    Response: We appreciate the commenters' support.
    After consideration of the public comments we received, we are 
finalizing our proposal to maintain the non-O.R. designation of 
procedure code 0U9L0ZZ and to change the designation of procedure codes 
0U9L0ZX and 0U9LXZX from O.R. to non-O.R., effective October 1, 2021.
(25) Transvaginal Repair of Vagina
    One requestor identified ICD-10-PCS procedure code 0UQG7ZZ (Repair 
vagina, via natural or artificial opening) that the requestor stated is 
currently not recognized as an O.R. procedure for purposes of MS-DRG 
assignment. The requestor stated that procedures described by this code 
such as the non-obstetric transvaginal repair of the vaginal cuff and 
the non-obstetric transvaginal repair of vaginal lacerations should be 
designated as O.R. procedures because these procedures are performed in 
the operating room under general anesthesia. The requestor noted 
procedure codes 0USG7ZZ (Reposition vagina, via natural or artificial 
opening), 0UBG7ZZ (Excision of vagina, via natural or artificial 
opening), and 0UQG8ZZ (Repair vagina, via natural or artificial opening 
endoscopic) are currently designated as O.R. procedures, therefore 
procedure code 0UQG7ZZ should also be recognized as an O.R. procedure 
for purposes of MS-DRG assignment.
    In the ICD-10 MS-DRGs Definitions Manual Version 38.1, procedure 
code 0UQG7ZZ is currently designated as a non-O.R. procedure for 
purposes of MS-DRG assignment. In the proposed rule, we stated that our 
clinical advisors reviewed this issue and disagreed that a correlation 
can be made between procedures described as the transvaginal repair of 
the vagina and the procedures described by ICD-10-PCS codes 0USG7ZZ, 
0UBG7ZZ, and 0UQG8ZZ. We stated that the root operation ``repair'' 
represents a broad range of procedures for restoring the anatomic 
structure of a body part such as suture of lacerations, while the root 
operations ``reposition,'' and ``excision'' define procedures with more 
distinct objectives. Also, the approach ``via natural or artificial 
opening'', for example, transvaginal, is defined as the entry of 
instrumentation through a natural or artificial external opening to 
reach the site of the procedure while the ``via natural or artificial 
opening endoscopic approach'' is defined as the entry of 
instrumentation (for example a scope) through a natural or artificial 
external opening to both reach and visualize the site of the procedure. 
We stated that our clinical advisors also disagreed that procedures 
described as the transvaginal repair of the vagina are typically 
performed in the operating room under general anesthesia. Our clinical 
advisors stated transvaginal repair can be performed using regional 
anesthesia, used to numb only the area of the body that requires 
surgery instead of rendering the patient unconscious. Therefore, for 
the reasons described, we proposed to maintain the current non-O.R. 
designation of ICD-10-PCS procedure code 0UQG7ZZ.
    Comment: Commenters supported CMS' proposal to maintain the non-
O.R. designation of a procedure code describing repair of vagina via 
natural or artificial opening.
    Response: We appreciate the commenters' support.
    Comment: Other commenters opposed CMS' proposal to maintain the 
non-O.R. designation of ICD-10-PCS procedure code 0UQG7ZZ. A commenter 
stated

[[Page 44914]]

procedures such as vaginal cuff revisions must be performed in the 
operating room under general anesthesia because a sterile surgical 
environment remains required for surgeons to accomplish this procedure 
before safely discharging patients. Another commenter stated that 
transvaginal repair of the vagina is typically an emergent procedure 
and for the safety of the patient, the procedure is best performed in 
the operating room under general anesthesia so the patient can stay 
relaxed. This commenter also stated that when this procedure is 
performed for indications such as vaginal cuff dehiscence, it is common 
that a concurrent procedure may be indicated to ensure there was not 
compromised/ischemic bowel since is imperative that the bowel is kept 
out of the field while the cuff is closed.
    Response: We appreciate the commenters' feedback and concern.
    Our clinical advisors reviewed the commenters' concerns and 
continue to support maintaining the current non-O.R. designation for 
ICD-10-PCS procedure code 0UQG7ZZ. While our clinical advisors agree 
that procedures described as the transvaginal repair of the vagina are 
often performed in conjunction with another O.R. procedure, they do not 
agree that this procedure warrants an O.R. designation. They stated 
these procedures are typically not the focus for the patient's 
admission, and that the other definitive procedures performed with the 
transvaginal repair of the vagina in the inpatient setting would be 
considered the principal driver of resource expenditure in those 
admissions.
    After consideration of the public comments we received, we are 
finalizing our proposal to maintain the current non-O.R. designation of 
ICD-10-PCS procedure code 0UQG7ZZ, without modification, for FY 2022.
(26) Percutaneous Tunneled Vascular Access Devices
    One requestor identified ten ICD-10-PCS procedure codes describing 
percutaneous insertion of tunneled vascular access devices into various 
body parts that the requestor stated are not recognized as an O.R. 
procedure for purposes of MS-DRG assignment. The requestor suggested 
that these procedures warrant an O.R. designation because they are 
placed in an interventional radiology suite or in the operating room 
under anesthesia. The ten procedure codes are shown in the following 
table.
[GRAPHIC] [TIFF OMITTED] TR13AU21.118

    According to the requestor, it does not make sense for tunneled 
vascular access devices to group to procedural MS-DRGs in limited 
circumstances as is the case currently with the logic in MDC 9 
(Diseases and Disorders of the Skin, Subcutaneous Tissue and Breast) 
and MDC 11 (Diseases and Disorders of the Kidney and Urinary Tract). 
The requestor stated that these procedures should be grouping to 
procedural MS-DRGs across all MDCs.
    In the proposed rule we noted that we have addressed requests 
related to these procedures in previous rulemaking (85 FR 58511 through 
58517). We also stated that our clinical advisors reviewed this request 
and disagreed that procedures performed to insert a tunneled vascular 
access device should group to procedural MS-DRGs across all MDCs. They 
stated that these percutaneous procedures are generally performed in 
the outpatient setting and when performed during a hospitalization, 
they are frequently performed in combination with another O.R. 
procedure. Therefore, we proposed to maintain the current non-O.R. 
status

[[Page 44915]]

for the ten procedure codes listed previously for FY 2022.
    Comment: Commenters supported our proposal to maintain the non-O.R. 
designation for procedure codes 0JH63XZ, 0JH83XZ, 0JHD3XZ, 0JHF3XZ, 
0JHG3XZ, 0JHH3XZ, 0JHL3XZ, 0JHM3XZ, 0JHN3XZ and 0JHP3XZ.
    Response: We appreciate the commenters' support.
    After consideration of the public comments we received, we are 
finalizing our proposal to maintain the non-O.R. designation for 
procedure codes 0JH63XZ, 0JH83XZ, 0JHD3XZ, 0JHF3XZ, 0JHG3XZ, 0JHH3XZ, 
0JHL3XZ, 0JHM3XZ, 0JHN3XZ and 0JHP3XZ, effective October 1, 2021.
12. Changes to the MS-DRG Diagnosis Codes for FY 2022
a. Background of the CC List and the CC Exclusions List
    Under the IPPS MS-DRG classification system, we have developed a 
standard list of diagnoses that are considered CCs. Historically, we 
developed this list using physician panels that classified each 
diagnosis code based on whether the diagnosis, when present as a 
secondary condition, would be considered a substantial complication or 
comorbidity. A substantial complication or comorbidity was defined as a 
condition that, because of its presence with a specific principal 
diagnosis, would cause an increase in the length-of-stay by at least 1 
day in at least 75 percent of the patients. However, depending on the 
principal diagnosis of the patient, some diagnoses on the basic list of 
complications and comorbidities may be excluded if they are closely 
related to the principal diagnosis. In FY 2008, we evaluated each 
diagnosis code to determine its impact on resource use and to determine 
the most appropriate CC subclassification (NonCC, CC, or MCC) 
assignment. We refer readers to sections II.D.2. and 3. of the preamble 
of the FY 2008 IPPS final rule with comment period for a discussion of 
the refinement of CCs in relation to the MS-DRGs we adopted for FY 2008 
(72 FR 47152 through 47171).
b. Overview of Comprehensive CC/MCC Analysis
    In the FY 2008 IPPS/LTCH PPS final rule (72 FR 47159), we described 
our process for establishing three different levels of CC severity into 
which we would subdivide the diagnosis codes. The categorization of 
diagnoses as a MCC, a CC, or a NonCC was accomplished using an 
iterative approach in which each diagnosis was evaluated to determine 
the extent to which its presence as a secondary diagnosis resulted in 
increased hospital resource use. We refer readers to the FY 2008 IPPS/
LTCH PPS final rule (72 FR 47159) for a complete discussion of our 
approach. Since the comprehensive analysis was completed for FY 2008, 
we have evaluated diagnosis codes individually when assigning severity 
levels to new codes and when receiving requests to change the severity 
level of specific diagnosis codes.
    We noted in the FY 2020 IPPS/LTCH PPS proposed rule (84 FR 19235 
through 19246) that with the transition to ICD-10-CM and the 
significant changes that have occurred to diagnosis codes since the FY 
2008 review, we believed it was necessary to conduct a comprehensive 
analysis once again. Based on this analysis, we proposed changes to the 
severity level designations for 1,492 ICD-10-CM diagnosis codes and 
invited public comments on those proposals. As summarized in the FY 
2020 IPPS/LTCH PPS final rule, many commenters expressed concern with 
the proposed severity level designation changes overall and recommended 
that CMS conduct further analysis prior to finalizing any proposals. 
After careful consideration of the public comments we received, as 
discussed further in the FY 2020 final rule, we generally did not 
finalize our proposed changes to the severity designations for the ICD-
10-CM diagnosis codes, other than the changes to the severity level 
designations for the diagnosis codes in category Z16- (Resistance to 
antimicrobial drugs) from a NonCC to a CC. We stated that postponing 
adoption of the proposed comprehensive changes in the severity level 
designations would allow further opportunity to provide additional 
background to the public on the methodology utilized and clinical 
rationale applied across diagnostic categories to assist the public in 
its review. We refer readers to the FY 2020 IPPS/LTCH PPS final rule 
(84 FR 42150 through 42152) for a complete discussion of our response 
to public comments regarding the proposed severity level designation 
changes for FY 2020.
    We discussed in the FY 2021 IPPS/LTCH PPS final rule (85 FR 58550 
through 58554) that we plan to continue a comprehensive CC/MCC 
analysis, using a combination of mathematical analysis of claims data 
as discussed in the FY 2020 IPPS/LTCH PPS proposed rule (84 FR 19235) 
and the application of nine guiding principles and plan to present the 
findings and proposals in future rulemaking. The nine guiding 
principles are as follows:
     Represents end of life/near death or has reached an 
advanced stage associated with systemic physiologic decompensation and 
debility.
     Denotes organ system instability or failure.
     Involves a chronic illness with susceptibility to 
exacerbations or abrupt decline.
     Serves as a marker for advanced disease states across 
multiple different comorbid conditions.
     Reflects systemic impact.
     Post-operative/post-procedure condition/complication 
impacting recovery.
     Typically requires higher level of care (that is, 
intensive monitoring, greater number of caregivers, additional testing, 
intensive care unit care, extended length of stay).
     Impedes patient cooperation and/or management of care.
     Recent (last 10 years) change in best practice, or in 
practice guidelines and review of the extent to which these changes 
have led to concomitant changes in expected resource use.
    We refer readers to the FY 2021 IPPS/LTCH PPS final rule for a 
complete discussion of our response to public comments regarding the 
nine guiding principles. We continue to solicit feedback regarding 
these guiding principles, as well as other possible ways we can 
incorporate meaningful indicators of clinical severity. When providing 
additional feedback or comments, we encourage the public to provide a 
detailed explanation of how applying a suggested concept or principle 
would ensure that the severity designation appropriately reflects 
resource use for any diagnosis code.
    As discussed in the FY 2022 IPPS/LTCH PPS proposed rule (86 FR 
25175), for new diagnosis codes approved for FY 2022, consistent with 
our annual process for designating a severity level (MCC, CC or NonCC) 
for new diagnosis codes, we first review the predecessor code 
designation, followed by review and consideration of other factors that 
may be relevant to the severity level designation, including the 
severity of illness, treatment difficulty, complexity of service and 
the resources utilized in the diagnosis and/or treatment of the 
condition. We noted that this process does not automatically result in 
the new diagnosis code having the same designation as the predecessor 
code. We refer the reader to II.D.13 of this final rule for the 
discussion of the proposed changes to the ICD-10-CM and ICD-10-PCS 
coding systems for FY 2022.

[[Page 44916]]

    In the FY 2022 IPPS/LTCH PPS proposed rule, we noted that we 
received several requests to change the severity level designations of 
specific ICD-10-CM diagnosis codes. We stated our clinical advisors 
believed it was appropriate to consider these requests in connection 
with our continued comprehensive CC/MCC analysis in future rulemaking, 
rather than proposing to change the designation of individual ICD-10-CM 
diagnosis codes at this time. As discussed in the proposed rule and 
noted earlier in this section, we plan to continue a comprehensive CC/
MCC analysis, using a combination of mathematical analysis of claims 
data and the application of nine guiding principles. We will consider 
these individual requests received for changes to severity level 
designations as we continue our comprehensive CC/MCC analysis and will 
provide more detail in future rulemaking.
    Comment: A commenter stated they agreed with the decision by CMS to 
withhold its recommendations pending a complete discussion of how the 
comprehensive CC/MCC analysis in future rulemaking is to be 
constructed. This commenter also stated they appreciated CMS' 
publication of the guiding principles of what should constitute a CC or 
MCC.
    Response: We appreciate the commenters'' support. In response to 
the comment that the guiding principles indicate what should constitute 
a CC or MCC, as noted in the FY 2021 IPPS/LTCH PPS final rule, we do 
not believe the nine guiding principles would be mostly applicable, or 
only applicable, to CC or MCC conditions. In applying the nine guiding 
principles in our review of the appropriate severity level designation, 
the intention is not to require that a diagnosis code satisfy each 
principle, or a specific number of principles in assessing whether to 
designate a secondary diagnosis code as a NonCC versus a CC versus a 
MCC. Rather, the severity level determinations would be based on the 
consideration of the clinical factors captured by these principles as 
well as the empirical analysis of the additional resources associated 
with the secondary diagnosis.
    Comment: Other commenters expressed their willingness to partner 
with CMS to provide their expertise to assist in the continuation of a 
comprehensive CC/MCC analysis. These commenters requested that CMS post 
another secondary diagnosis impact on resource use file so that the 
public can determine how individual ICD-10-CM diagnosis codes affect 
resource use when reported as secondary diagnoses. A commenter stated 
providing this information will help prepare the public and inform the 
feedback and advice summitted by the public in the IPPS comment periods 
of future rulemaking.
    Response: While CMS has already convened an internal workgroup 
comprised of clinicians, consultants, coding specialists and other 
policy analysts, we welcome additional public feedback. Commenters can 
continue to submit their recommendations to the following email 
address: [email protected] by November 1, 2021.
    In response to the request that CMS make an updated impact on 
resource use file available, we note that in May 2021, we made an 
updated impact on resource use file available so that the public can 
review the mathematical data for the impact on resource use generated 
using claims from the FY 2019 MedPAR file and the FY 2020 MedPAR file. 
The link to this file is posted on the CMS website at https://
www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/
AcuteInpatientPPS/MS[dash]DRG-Classifications-and-Software.
c. Potential Change to Severity Level Designation for Unspecified 
Diagnosis Codes for FY 2022
    As discussed in the FY 2022 IPPS/LTCH PPS proposed rule (86 FR 
25175 through 25180), as another interval step as we continue to 
address the comprehensive review of the severity designations of ICD-
10-CM diagnosis codes in which we have been engaged over the past two 
years, we requested public comments on a potential change to the 
severity level designations for ``unspecified'' ICD-10-CM diagnosis 
codes that we were considering adopting for FY 2022. Specifically, we 
noted we were considering changing the severity level designation of 
all ``unspecified'' diagnosis codes to a NonCC where there are other 
codes available in that code subcategory that further specify the 
anatomic site, effective for FY 2022, after consideration of the public 
comments we receive in response to the proposed rule.
    We noted that according to the ICD-10-CM Official Guidelines for 
Coding and Reporting, codes titled ``unspecified'' are for use when the 
information in the medical record is insufficient to assign a more 
specific code. In our review of severity level designation of the codes 
in the ICD-10-CM classification, we stated we noted 3,490 
``unspecified'' diagnosis codes designated as either CC or MCC, where 
there are other codes available in that code subcategory that further 
specify the anatomic site with an equivalent severity level 
designation. For example, ICD-10-CM code L89.003 (Pressure ulcer of 
unspecified elbow, stage 3) is currently designated as a MCC. In the 
same code subcategory of L89.0- (Pressure ulcer of elbow), ICD-10-CM 
codes L89.013 (Pressure ulcer of right elbow, stage 3) and code L89.023 
(Pressure ulcer of left elbow, stage 3) are also designed as MCCs.
    In the FY 2008 IPPS/LTCH PPS final rule (72 FR 47159), we described 
the categorization of diagnoses as an MCC, a CC, or a NonCC, 
accomplished using an iterative approach in which each diagnosis was 
evaluated to determine the extent to which its presence as a secondary 
diagnosis resulted in increased hospital resource use. As such, the 
designation of CC or MCC is intended to account for the increased 
resources required to address a condition as a secondary diagnosis. The 
usage of ``unspecified'' diagnosis codes where there are other codes 
available in that code subcategory that further specify the anatomic 
site may contribute to and eventually result in less reliable data for 
researching clinical outcomes. If documentation is not available to 
code to the highest level of specificity as to the laterality of the 
condition treated, and an unspecified code is reported by the hospital, 
it may be harder to quantify in the claims data what additional 
resources were expended to address that condition in terms of requiring 
clinical evaluation, therapeutic treatment, diagnostic procedures, 
extended length of hospital stay, increased nursing care and/or 
monitoring.
    As stated in the proposed rule and previously, we discussed in the 
FY 2021 IPPS/LTCH PPS final rule (85 FR 58550 through 58554) that we 
plan to continue a comprehensive CC/MCC analysis, using a combination 
of mathematical analysis of claims data, and the application of nine 
guiding principles, and plan to present the findings and proposals in 
future rulemaking. As patients present with a variety of diagnoses, in 
examining the secondary diagnoses, we stated we would consider what 
additional resources are required, that surpasses those that are 
already being utilized to address the principal diagnosis and/or other 
secondary diagnoses that might also be present on the claim. The goal 
of our comprehensive analysis is to create stratification for 
reimbursing inpatient hospitalization in the fewest amount of 
categories with the most explanatory power in a clinically cohesive 
way. We stated in the FY 2022 proposed rule that we believed more 
robust claims data

[[Page 44917]]

would facilitate this effort to determine the impact on resource use 
and inform our decision-making in determining the most appropriate CC 
subclass (NonCC, CC, or MCC) assignment for each diagnosis as a 
secondary diagnosis. As part of this effort, we solicited comments on 
adopting a change to the severity level designation of the 3,490 
``unspecified'' diagnosis codes currently designated as either CC or 
MCC, where there are other codes available in that code subcategory 
that further specify the anatomic site, to a NonCC for FY 2022.
    As discussed in the HIPAA Administrative Simplification: 
Modification to Medical Data Code Set Standards To Adopt ICD-10-CM and 
ICD-10-PCS proposed rule (73 FR 49796 through 49803), in proposing the 
adoption of ICD-10-CM and ICD-10-PCS, we listed that the addition of 
laterality in ICD-10-CM--specifying which organ or part of the body is 
involved when the location could be on the right, the left, or could be 
bilateral, was one of several improvements over ICD-9-CM. We also noted 
that in comparison to ICD-9-CM, ICD-10-CM diagnosis codes are very 
specific and that this specificity improves the richness of data for 
analysis and improves the accuracy of data used for medical research. 
In the Modifications to Medical Data Code Set Standards To Adopt ICD-
10-CM and ICD-10-PCS final rule (74 FR 3328 through 3362), we adopted 
the ICD-10-CM and ICD-10-PCS as medical data code sets under HIPAA, 
replacing ICD-9-CM Volumes 1 and 2, and Volume 3 and noted that ICD-10-
CM and ICD-10-PCS provide specific diagnosis and treatment information 
that can improve quality measurements and patient safety, and the 
evaluation of medical processes and outcomes. We stated in the FY 2022 
proposed rule that we continue to believe that reporting the most 
specific diagnosis codes supported by the available medical record 
documentation and clinical knowledge of the patient's health condition 
would more accurately reflect the health care encounter and improve the 
reliability and validity of the coded data.
    We also stated we believe that changing the severity level for 
these ``unspecified codes'' as compared to the more specific codes in 
the same subcategory recognizing laterality would leverage the 
additional specificity available under the ICD-10 system, by fostering 
the reporting of the most specific diagnosis codes supported by the 
available medical record documentation and clinical knowledge of the 
patient's health condition to more accurately reflect each health care 
encounter and improve the reliability and validity of the coded data. 
However, in consideration of the PHE, and to the extent that some 
providers may not currently have programs in place that focus on 
improving documentation, we requested public comments on making this 
change to the severity level designation for these unspecified ICD-10-
CM diagnosis codes for FY 2022.
    We refer the reader to table 6P.2a associated with the proposed 
rule for a detailed list of the diagnosis codes for which we solicited 
comments on a change in severity level. As noted in the proposed rule, 
we also made available the data describing the impact on resource use 
when reported as a secondary diagnosis for all 3,490 ICD-10-CM 
unspecified diagnosis codes. While these claims data were not used in 
our identification of the ``unspecified'' diagnosis codes for which 
there are other codes available in the code subcategory that further 
specify the anatomic site, as stated in the proposed rule and earlier 
in this section, these data are consistent with data historically used 
to mathematically measure impact on resource use for secondary 
diagnoses, and the data which we plan to use in combination with 
application of the nine guiding principles as we continue a 
comprehensive CC/MCC analysis. Therefore, we displayed the data on 
these unspecified codes in order to facilitate public comment on these 
potential changes in the severity level designation for these codes.
    In Table 6P.2a associated with the proposed rule, column C displays 
the FY 2020 severity level designation for these diagnosis codes in MS-
DRG Grouper Version 37.2. Column D displays CMS' current FY 2021 
severity level designation in MS-DRG Grouper Version 38.1 and column E 
displays the potential changes to the severity level designation that 
we stated we were considering adopting. Columns F-O show data on the 
impact on resource use generated using discharge claims from the 
September 2019 update of the FY 2019 MedPAR file and MS-DRG Grouper 
Version 37.2. Columns Q-Z show data on the impact on resource use 
generated using discharge claims from the September 2020 update of the 
FY 2020 MedPAR file and MS-DRG Grouper Version 38.1.
    For further information on the data on the impact on resource use 
as displayed in Columns F-O and Columns Q-Z, we refer readers to the FY 
2008 IPPS/LTCH PPS final rule (72 FR 47159) for a complete discussion 
of the methodology utilized to mathematically measure the impact on 
resource use. Also, as discussed in the FY 2021 IPPS/LTCH PPS proposed 
rule (85 FR 32550), to provide the public with more information on the 
CC/MCC comprehensive analysis discussed in the FY 2020 IPPS/LTCH PPS 
proposed and final rules, CMS hosted a listening session on October 8, 
2019. The listening session included a review of this methodology 
utilized to mathematically measure the impact on resource use. We refer 
readers to https://www.cms.gov/Outreach-and-Education/Outreach/OpenDoorForums/PodcastAndTranscripts.html for the transcript and audio 
file of the listening session. We also refer readers to https://www.cms.gov/Medicare/MedicareFee-for-Service-Payment/AcuteInpatientPPS/MS-DRG-Classifications-and-Software.html for the supplementary file 
containing the data describing the impact on resource use of specific 
ICD-10-CM diagnosis codes when reported as a secondary diagnosis that 
was made available for the listening session. We note that the 
supplementary file that was made available for the listening session 
contains the mathematical data for the impact on resource use generated 
using claims from the FY 2018 MedPAR file. We have also made available 
on the CMS website an updated impact on resource use file so that the 
public can review the mathematical data for the impact on resource use 
generated using claims from the FY 2019 MedPAR file and the FY 2020 
MedPAR file.
    This table shows the Version 38.1 ICD-10 MS-DRG categorization of 
diagnosis codes by severity level.
BILLING CODE 4120-01-P

[[Page 44918]]

[GRAPHIC] [TIFF OMITTED] TR13AU21.119

    As stated in the proposed rule, we requested public comments on a 
modification to the Version 38.1 severity level subclass assignments 
for 4.8 percent of the ICD-10-CM diagnosis codes, potentially effective 
with the Version 39 ICD-10 MS-DRG MCC/CC list. The following table 
compares the Version 38.1 ICD-10 MS-DRG MCC/CC list and the potential 
Version 39 ICD-10 MS-DRG MCC/CC list. There are 17,957 diagnosis codes 
on the Version 38.1 MCC/CC lists. These potential MCC/CC severity level 
changes would reduce the number of diagnosis codes on the MCC/CC lists 
to 14,467 (2,771 + 11,696).
[GRAPHIC] [TIFF OMITTED] TR13AU21.120

    The net result of these potential changes to the Version 39 ICD-10 
MS-DRG MCC/CC list, for the 72,621 diagnosis codes in the ICD-10-CM 
classification, would be a decrease of 507 (3,278 - 2,771) codes 
designated as an MCC, a decrease of 2,983 (14,679 - 11,696) codes 
designated as a CC, and an increase of 3,490 (58,154 - 54,664) codes 
designated as a NonCC.
    The following table compares the Version 38.1 ICD-10 MS-DRG 
severity level list and the potential Version 39 ICD-10 MS-DRG severity 
level list by each of the 22 chapters of the ICD-10-CM classification 
to display how each chapter of ICD-10-CM might be affected by these 
modifications.

[[Page 44919]]

[GRAPHIC] [TIFF OMITTED] TR13AU21.121


[[Page 44920]]


[GRAPHIC] [TIFF OMITTED] TR13AU21.122

    As shown in the table, the Diseases of the Musculoskeletal System 
and Connective Tissue (M00-M99) chapter of ICD-10-CM would have the 
largest percentage reduction in codes designated as CC/MCC. Twelve 
chapters would have a zero percentage change to the percentage of codes 
designated as CC/MCC.
    As stated in the proposed rule and previously, we requested public 
comments on our possible adoption of a change to the severity level 
designation of these 3,490 ``unspecified'' diagnosis codes currently 
designated as either CC or MCC, where there are other codes available 
in that code subcategory that further specify the anatomic site, to a 
NonCC, potentially effective with the Version 39 ICD-10 MS-DRG MCC/CC 
list. As part of this request, we stated we would be interested in 
comments regarding whether this modification might present operational 
challenges and how we might otherwise foster the reporting of the most 
specific diagnosis codes supported by the available medical record 
documentation and clinical knowledge of the patient's health condition 
to more accurately reflect each health care encounter and improve the 
reliability and validity of the coded data.
    In this FY 2022 IPPS/LTCH PPS final rule, we present a summation of 
the comments we received on our possible adoption of a change to the 
severity level designation of the 3,490 ``unspecified'' diagnosis codes 
currently designated as either CC or MCC, where there are other codes 
available in that code subcategory that further specify the anatomic 
site, to a NonCC, potentially effective with the Version 39 ICD-10 MS-
DRG MCC/CC list and our responses to those comments. We appreciate 
commenters for sharing their views and their willingness to support CMS 
in our efforts to continue a comprehensive CC/MCC analysis.
    Comment: Many commenters supported CMS' possible adoption of a 
change to the severity level designation of the 3,490 ``unspecified'' 
diagnosis codes to a NonCC when there are more specific codes available 
in that code subcategory that recognize laterality. Some commenters 
stated it is reasonable to expect that laterality would be documented 
in the hospital inpatient setting in most cases. A commenter stated 
that they agreed that reporting the most specific diagnosis codes 
supported by the available medical record documentation and clinical 
knowledge of the patient's health condition would more accurately 
reflect the healthcare encounter and improve the reliability and 
validity of the coded data. This commenter further stated the 
anticipated benefits of the ICD-10-CM transition (including better data 
for measuring quality and safety of patient care, assessing patient 
outcomes, determining disease severity for risk and severity 
adjustment, and conducting analyses and research) cannot be realized if 
healthcare encounters are not coded and documented to the highest 
possible level of specificity. A commenter stated that they appreciated 
that CMS is considering changing the severity designation of 
``unspecified'' diagnosis codes where a more specific code describing 
laterality is available as they have observed that the presence of 
these codes in the classification has become a challenge when 
determining how to code based on vague medical record documentation. 
Another commenter stated they supported CMS' aim to encourage diagnosis 
coding to the highest level of specificity available, and stated 
specifically, if there are codes that can be used to indicate 
laterality, then those codes should be reported rather than an 
unspecified code.
    Response: We appreciate the commenters' support.
    Comment: Other commenters questioned the need for such a change. 
Commenters stated the use of unspecified codes in reporting diagnoses 
that describe the patient's condition does not diminish the resources 
required to care for patients. A commenter requested that CMS provide 
insight pertaining to how the laterality of the condition impacts the 
severity of the diagnosis. Another commenter stated the treatment plans 
developed by providers to address diagnoses remains the same, 
regardless of the laterality affected. Another commenter stated that 
the laterality of a condition does not clinically impact the severity 
of the diagnosis or make it less costly to treat, and that it also does 
not offer any more value to the reported data.
    Response: We appreciate the commenter's' feedback.
    To clarify how the concept of laterality is reflected in the claims 
data and the importance in accurately reporting this information we 
provide the following examples of diagnosis codes and their impact on 
resource use as represented in the claims data when reported as a 
secondary diagnosis.
    The following table reflects the impact on resource use data using 
the September 2019 update of the FY 2019 MedPAR file for diagnosis 
codes that describe stage 3 pressure ulcers of the hip. We refer 
readers to the FY 2008 IPPS/LTCH PPS final rule (72 FR 47159) for a 
complete discussion of our historical approach to mathematically

[[Page 44921]]

evaluate the extent to which the presence of an ICD-10-CM code as a 
secondary diagnosis resulted in increased hospital resource use, and 
the explanation of the columns in the table.
[GRAPHIC] [TIFF OMITTED] TR13AU21.123

    As shown in the table, the three diagnosis codes that describe 
stage 3 pressure ulcers of the hip are designated as MCCs in Version 
38.1 of the ICD-10 MS-DRGs. When examining diagnosis code L89.213 
(Pressure ulcer of right hip, stage 3), the value in column C1is closer 
to 2.0 than to 1.0. The data suggests that when stage 3 pressure ulcers 
of the right hip are reported as a secondary diagnosis, the resources 
involved in caring for these patients are more aligned with a CC than a 
NonCC or an MCC, as explained in the FY 2008 IPPS/LTCH PPS final rule 
(72 FR 47159). However, when examining diagnosis codes L89.223 
(Pressure ulcer of left hip, stage 3) and L89.203 (Pressure ulcer of 
unspecified hip, stage 3), the C1 values are generally closer to 1, 
which suggest the resources involved in caring for stage 3 pressure 
ulcers of the left hip or an unspecified hip are more aligned with a 
NonCC severity level than a CC or an MCC severity level.
    The following table reflects the impact on resource use data using 
the September 2020 update of the FY 2020 MedPAR file for the same three 
diagnosis codes.
[GRAPHIC] [TIFF OMITTED] TR13AU21.124

BILLING CODE 4120-01-C
    When examining this data file, we find opposite results. The C1 
values for diagnosis code L89.213 (Pressure ulcer of right hip, stage 
3) is generally close to 1 and the C2 values for L89.213 and L89.203 
(Pressure ulcer of unspecified hip, stage 3) are generally close to 2, 
both of which suggest the resources involved in caring for stage 3 
pressure ulcers of the right hip or an unspecified hip are more aligned 
with a NonCC severity level than a CC or an MCC severity level. 
However, when examining diagnosis code L89.223 (Pressure ulcer of left 
hip, stage 3), the value in column C1 is closer to 2.0, which suggests 
that when stage 3 pressure ulcers of the left hip are reported as a 
secondary diagnosis, the resources involved in caring for these 
patients are more aligned with a CC than either a NonCC or an MCC.
    As we have noted in prior rulemaking, these mathematical constructs 
are used as guides in conjunction with the judgment of our clinical 
advisors to classify each secondary diagnosis reviewed. We present 
these data to highlight that when taking laterality into account, the 
resources expended in caring for certain conditions may not be as 
equally expressed in the claims data as some commenters may suggest and 
to demonstrate how reporting the most specific diagnosis codes 
supported by the available medical record documentation and clinical 
knowledge of the patient's health condition could

[[Page 44922]]

more accurately reflect the health care encounter and improve the 
reliability and validity of the coded data the 108 cases and 56 cases 
that reported a stage 3 pressure ulcer of an unspecified hip as a 
secondary diagnosis in the FY 2019 and FY 2020 MedPAR file, 
respectively, may each reflect an opportunity to potentially have 
reported more specific and valuable data that could be used in 
evaluating the impact of resource use in the claims data, had the 
laterality been specified.
    We also note that in Table 6P.2a associated with the proposed rule, 
of the 3,490 diagnosis codes listed, when reviewing the total counts in 
the data on the impact on resource use generated using discharge claims 
from the September 2019 update of the FY 2019 MedPAR file and the 
September 2020 update of the FY 2020 MedPAR file, only 36 and 38 ICD-
10-CM codes respectively, were reported in numbers greater than 500 in 
the claims data. The remaining codes were generally all reported in 
small numbers. In fact, in as shown in table 6P.2a, 2,772 and 2,767 of 
these codes were reported zero times in the claims data when reviewing 
the impact on resource use generated using discharge claims from the 
September 2019 update of the FY 2019 MedPAR file and the September 2020 
update of the FY 2020 MedPAR file, respectively.
    As noted in the proposed rule, this consideration of a possible 
adoption to change the severity level designation of certain 
unspecified codes was to foster the reporting of the most specific 
diagnosis codes supported by the available medical record documentation 
and clinical knowledge of the patient's health condition to more 
accurately reflect each health care encounter and improve the 
reliability and validity of the coded data. These findings demonstrate 
providers are already appropriately documenting laterality in most 
instances.
    Comment: Other commenters noted that laterality is not one of CMS' 
long-standing criteria for determining the severity level of a 
condition. These commenters stated the presence (or absence) of 
laterality is not a factor in the nine guiding principles for 
establishing the severity level of an ICD-10 code. Therefore, these 
commenters suggested that CMS withdraw its possible adoption of a 
change, as the agency's own principles for establishing the severity 
level of an ICD-10 code do not support this change.
    Response: In prior rulemaking, our clinical advisors reviewed the 
resource use impact reports and suggested modifications to the initial 
CC subclass assignments when clinically appropriate based on review of 
the mathematical data as well as consideration of the clinical nature 
of each of the secondary diagnoses and the severity level of clinically 
similar diagnoses. As discussed in the proposed rule and noted earlier 
in this section, we plan to continue a comprehensive CC/MCC analysis, 
using a combination of mathematical analysis of claims data and the 
application of nine guiding principles. We believe the possible 
adoption of a change to the severity level designation of diagnosis 
codes when there are more specific codes available in that code 
subcategory that recognize laterality will have the downstream effect 
of strengthening the data used in such analysis. In regards to the 
comment that laterality in not listed as a factor in the nine guiding 
principles, our clinical advisors state that determining laterality is 
inherent to the guiding principle that states ``typically requires 
higher level of care (that is, intensive monitoring, greater number of 
caregivers, additional testing, intensive care unit care, extended 
length of stay).'' If a higher level of care is required to address the 
diagnosis as a secondary diagnosis, then the laterality affected in 
most instances should be able to be determined in the course of the 
associated intensive monitoring, greater number of caregivers, and/or 
additional testing in most instances. We also note that if a procedure 
is performed to address a diagnosis as a secondary diagnosis, the 
laterality must be known and documented in order to assign an ICD-10-
PCS code because ICD-10-PCS requires the use of laterality since 
``unspecified'' is not an anatomical option in the procedure 
classification.
    Comment: A commenter requested that CMS provide transparency in 
reference to the table that displays the distribution of volume within 
these codes for a better representation of the impact. The commenter 
noted that the table indicates that only 4% of the neoplasm codes would 
be impacted under the proposal; however, when reviewing the 
distribution of cases, the commenter stated that it appears that 
neoplasms were actually heavily impacted with the highest volume of 
cases.
    Response: We note that the table displayed in the proposed rule 
compares the Version 38.1 ICD-10 MS-DRG severity level list and the 
potential Version 39 ICD-10 MS-DRG severity level list by each of the 
22 chapters of the ICD-10-CM classification to display how each chapter 
of ICD-10-CM might be affected by these modifications. This table was 
not intended to represent an analysis of the claims reporting the 3,490 
codes as listed.
    Comment: A few commenters suggested that CMS analyze the frequency 
of use of unspecified codes, their impact on resource utilization, and 
also the typical documentation practices for acute stays with these 
conditions which may or may not include specificity before changing the 
severity designation of these codes. These commenters recommended that 
CMS conduct an analysis of how often the unspecified codes in question 
are actually used; how much resources they consume; and the standard 
documentation for the patient stays associated with the use of these 
codes.
    Response: Table 6P.2a associated with the proposed rule contained 
data describing the impact on resource use when reported as a secondary 
diagnosis for all 3,490 ICD-10-CM unspecified diagnosis codes, 
generated using discharge claims from the September 2019 update of the 
FY 2019 MedPAR file and the September 2020 update of the FY 2020 MedPAR 
file, including the number of cases reporting these unspecified codes 
We note that we have made complete impact on resource use files 
available so that the public can review the mathematical data for the 
impact on resource use generated using claims from the FY 2018 MedPAR 
file, FY 2019 MedPAR file and the FY 2020 MedPAR file. The link to 
these files is posted on the CMS website at https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/AcuteInpatientPPS/MS-DRG-Classifications-and-Software.
    In response to the comment that CMS review the typical 
documentation practices for acute stays with these conditions, we note 
that medical professionals' documentation is already open to scrutiny 
by many, including employers, Federal and State reviewers, and 
auditors. We encourage providers to continue to focus efforts on 
improving their respective facilities medical record documentation 
practices.
    Comment: Some commenters disagreed with the possible adoption of a 
change to the severity level designation of individual diagnosis codes 
listed in Table 6P. 2a associated with the proposed rule.
    Many commenters opposed the inclusion of diagnosis codes that 
describe neoplasms in the list of codes. Commenters stated cancer 
patients typically are more complex than other types of patients, and 
often their cancer leads to greater resource utilization even when 
coded with an unspecified code. These commenters noted that while the 
neoplasm may still be under active

[[Page 44923]]

treatment, the specific side of the neoplasm may not be documented if 
the patient is admitted for a different, unrelated condition such as 
trauma or infections. Also, there are instances where patients with a 
known primary cancer are often evaluated, tested, and treated for a 
clinically likely yet unspecified secondary cancer site. These 
commenters stated in these cases, the lack of specificity is warranted, 
and the clinical presentation is still aligned with a CC or MCC. A 
commenter specifically identified code C56.9, Malignant neoplasm of 
unspecified ovary, and stated this code should remain a CC because some 
patients have extensive intraperitoneal metastases typical of 
(presumed) ovarian primary, and have pelvic involvement so extensive 
that resection is unable to be performed, and laterality is unable to 
be determined.
    Response: Our clinical advisors reviewed this condition described 
by code C56.9 and agree with the commenters that this and other 
unspecified diagnosis codes that describe neoplasms should not be 
included in the list of unspecified diagnosis codes for consideration 
for a possible adoption of a change to the severity level designation. 
They agree that in certain presentations, the laterality affected might 
be difficult to determine in certain instances. Our clinical advisors 
believe the severity level designations for this subset of codes would 
be better addressed as part of our comprehensive CC/MCC analysis, using 
a combination of mathematical analysis of claims data and the 
application of nine guiding principles.
    Comment: A commenter identified diagnosis codes S02.113A, S02.113B, 
and S02.113K that describe unspecified occipital condyle fractures 
listed in Table 6P.2a associated with the proposed rule. The commenter 
noted that the ICD-10-CM classification does not have diagnosis codes 
that specify laterality when the type of occipital fracture (for 
example, Type 1, Type II, Type III) is unknown or unobtainable. Because 
unspecified codes must be assigned when the type of fracture is 
unknown, even when laterality is documented, the commenter suggested 
that these codes should be removed from the list of codes under 
consideration and retain their CC and MCC designations.
    Response: We agree with the commenter that in subcategory S02.11 of 
the ICD-10-CM classification, there are no codes available that further 
specify laterality in the code description when the type of occipital 
condyle fracture is unknown. We further examined the list of diagnosis 
codes listed in Table 6P.2a, and noted diagnosis codes S02.119A, 
S02.119B and S02.119K that describe unspecified fractures of the 
occiput. Our clinical advisors noted that there are also no codes 
available in that classification that further specify laterality in the 
code description when the type of occipital fracture is unknown. 
Accordingly, our clinical advisors believe that these codes should not 
be included in the list of unspecified diagnosis codes for 
consideration for a possible adoption of a change to the severity level 
designation.
    Comment: A commenter noted that ICD-10-CM diagnosis codes S82.001N 
and S82.001R that describe a fracture of the right patella were 
included in the list of codes in Table 6P.2a. The commenter stated 
these codes should be removed from Table 6P.2a because the laterality 
of ``right'' is specified within the code description.
    Response: We appreciate the commenter noting that two diagnosis 
codes describing fractures affecting the right patella were included in 
Table 6P.2a associated with the proposed rule. We note that this was an 
inadvertent error. We further examined the list of diagnosis codes in 
Table 6P.2a, and noted diagnosis codes S78.911A and S78.921A that 
describe complete and partial traumatic amputation of right hip and 
thigh, respectively, were also inadvertently included in the list of 
``unspecified'' diagnosis codes currently designated as either CC or 
MCC, where there are other codes available in that code subcategory 
that further specify the anatomic site.
    Comment: A commenter stated they disagreed with removing the 
severity designation of an unspecified code that is internal to the 
body and cannot be visualized externally. This would include all of the 
codes involving conditions of internal organs, vessels or body parts 
(for example, neoplasm, DVT, etc.).
    Response: In response to this comment, we further examined the list 
of diagnosis codes in Table 6P.2a, and note the following:
     Our clinical advisors noted that codes S02.118A, S02.118B, 
and S02.118Kwhich describe other fractures of occiput, S04.819A which 
describes an injury of olfactory [1st] nerve, and S04.9XXA which 
describes an injury of unspecified cranial nerve were listed in Table 
6P.2a. Our clinical advisors stated that in cases of traumatic injury, 
laterality may not be easily identified in occipital fractures or 
injuries to olfactory or cranial nerves.
     Our clinical advisors noted codes S32.9XXA, S32.9XXB, and 
S32.9XXK that describe fractures of unspecified parts of lumbosacral 
spine and pelvis; codes S36.209A, S36.249A, S36.259A, and S36.269A that 
describe injury and laceration to unspecified parts of the pancreas; 
code S36.509A that describes an unspecified injury of an unspecified 
part of colon; code S36.90XA that describes an unspecified injury of an 
unspecified intra-abdominal organ; code S37.90XA that describes an 
unspecified injury of unspecified urinary and pelvic organ; code 
T27.3XXA that describes a burn of an unspecified part of the 
respiratory tract; and T27.7XXA that describes a corrosion of an 
unspecified part of the respiratory tract were listed in Table 6P.2a. 
Our clinical advisors note that while we encourage the reporting and 
coding to the highest possible level of specificity based on 
documentation, the codes listed in Table 6P.2a were intended to be 
limited to ``unspecified'' diagnosis codes currently designated as 
either CC or MCC, where there are other codes available in that code 
subcategory that further specify the anatomic site involved, when the 
location could be on the right, the left, or could be bilateral; and 
not parts of body sites.
    Therefore, after further consideration, and for the reasons noted, 
we believe that the 58 ICD-10-CM diagnosis codes listed in the 
following table should not be included for consideration of changing 
the severity level designation as part of the list of ``unspecified'' 
diagnosis codes currently designated as either CC or MCC, where there 
are other codes available in that code subcategory that further specify 
the anatomic site.
BILLING CODE 4120-01-P

[[Page 44924]]

[GRAPHIC] [TIFF OMITTED] TR13AU21.125


[[Page 44925]]


[GRAPHIC] [TIFF OMITTED] TR13AU21.126

BILLING CODE 4120-01-C
    Comment: Some commenters suggested that CMS can meet its goal to 
improve coding specificity through other mechanisms, such as working 
with the Cooperating Parties for ICD-10 to update coding guidelines to 
allow coding specificity from other clinical staff documentation. These 
commenters indicated they are supportive of CMS' efforts but believe 
CMS should first focus on provider outreach and education and consider 
updating the ICD-10-CM Official Guidelines for Coding and Reporting. 
Commenters

[[Page 44926]]

noted the ICD-10-CM Official Guidelines require that these codes be 
based only on provider documentation for the current encounter and 
prohibits coders from using previous encounters or problem lists to 
obtain the required specificity. These commenters stated if the coding 
guidelines from the Cooperating Parties were updated in advance of any 
severity level designation changes being finalized, the use of 
unspecified codes would likely diminish. Another commenter stated that 
unless the ICD-10-CM guidelines are liberalized so that code assignment 
can be obtained from other documents other than provider documentation 
for that encounter, the possible adoption of a change to the severity 
level designation will create undue burden. Another commenter noted 
without an update to the coding guidelines, hospitals will need to 
expand their clinical documentation improvement programs to prompt 
physicians to change their documentation practices on each applicable 
hospital encounter.
    Response: The ICD-10-CM Official Guidelines for Coding and 
Reporting have been revised effective October 1, 2021 to provide 
additional guidance as it relates to the source documentation for code 
assignment. We believe this update will alleviate the concerns 
expressed by these commenters. Specifically, Section I.B.13 of the 
guidelines have been updated to state ``when laterality is not 
documented by the patient's provider, code assignment for the affected 
side may be based on medical record documentation from other 
clinicians. If there is conflicting medical record documentation 
regarding the affected side, the patient's attending provider should be 
queried for clarification. Codes for ``unspecified'' side should rarely 
be used, such as when the documentation in the record is insufficient 
to determine the affected side and it is not possible to obtain 
clarification. In this context, ``clinicians'' other than the patient's 
provider refer to healthcare professionals permitted, based on 
regulatory or accreditation requirements or internal hospital policies, 
to document in a patient's official medical record.'' Corresponding 
revisions to the guidelines can also be found in section I.B.14. 
Therefore, we believe that the updates made to the coding guidelines 
address that aspect of the commenters' concerns.
    We encourage the commenters to review the Official ICD-10-CM Coding 
Guidelines, which can be found on the CDC website at: http://www.cdc.gov/nchs/icd/icd10.htm.
    Comment: A number of commenters recommended (or urged) CMS to delay 
any possible change to the designation of these codes for at least two 
years to give hospitals and their physicians time to prepare. These 
commenters stated a change of this magnitude should not be implemented 
without giving providers time to restructure physician documentation 
improvement plans and to provide additional education to physicians and 
coders related to documentation practices. These commenters also stated 
a delay will give hospitals the time needed to update computer-assisted 
coding systems to incorporate this change to reduce the administrative 
burden on physicians related to documentation. Other commenters stated 
more time is needed before finalizing any policy decisions since this 
change impacts the quality and risk of mortality scores generated by 
commercial insurers who often follow CMS' coding and MS-DRG changes. 
Another commenter stated that this is a significant change from an 
operational perspective that, if implemented, will create significant 
administrative burden for hospitals at a time when administrative and 
clinical resources are still stretched thin by the COVID-19 PHE.
    Response: We appreciate the commenter's concern's after 
consideration of the public comments we received, we are maintaining 
the severity level designation of all ``unspecified'' diagnosis codes 
currently designated as a CC or MCC where there are other codes 
available in that code subcategory that further specify the anatomic 
site for FY 2022. Instead, we are finalizing the Unspecified code MCE 
edit option as discussed in the proposed rule, which we believe 
provides additional time to educate providers while not affecting the 
payment the provider is eligible to receive. We refer the reader to 
section II.D.14.e. of the preamble of this final rule, for the complete 
discussion.
    While we remain committed to fostering the documentation and 
reporting of the most specific diagnosis codes supported by the 
available medical record documentation and clinical knowledge of the 
patient's health condition, we believe additional time is needed before 
adopting a change to the severity level designation of all 
``unspecified'' diagnosis codes to a NonCC where there are other codes 
available in that code subcategory that further specify the anatomic 
site. This time will allow the industry an opportunity to educate 
coders on the updated guidelines and to offer assistance on proper 
documentation to providers.
    We continue to be interested in receiving feedback on how we might 
otherwise foster the documentation and reporting of the most specific 
diagnosis codes supported by the available medical record documentation 
and clinical knowledge of the patient's health condition to more 
accurately reflect each health care encounter and improve the 
reliability and validity of the coded data. Comments should be directed 
to the MS-DRG Classification Change Mailbox located at: 
[email protected].
d. Additions and Deletions to the Diagnosis Code Severity Levels for FY 
2022
    In the FY 2022 IPPS/LTCH PPS proposed rule (86 FR 25180) we noted 
the following tables identify the proposed additions and deletions to 
the diagnosis code MCC severity levels list and the proposed additions 
and deletions to the diagnosis code CC severity levels list for FY 2022 
and are available via the internet on the CMS website at: https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/AcuteInpatientPPS/index.html.

Table 6I.1--Proposed Additions to the MCC List--FY 2022;
Table 6I.2--Proposed Deletions to the MCC List--FY 2022; and
Table 6J.1--Proposed Additions to the CC List--FY 2022.

    Comment: Commenters agreed with the proposed additions and 
deletions to the MCC and CC lists as shown in tables 6I.1, 6I.2, and 
6J.1 associated with the proposed rule.
    Response: We appreciate the commenters' support.
    The following tables associated with this final rule reflect the 
finalized severity levels under Version 39 of the ICD-10 MS-DRGs for FY 
2022 and are available via the internet on the CMS website at: https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/AcuteInpatientPPS/index.html.

Table 6I. --Complete MCC List--FY 2022;
Table 6I.1--Additions to the MCC List--FY 2022;
Table 6I.2--Deletions to the MCC List--FY 2022;
Table 6J. --Complete CC List--FY 2022;
Table 6J.1--Additions to the CC List--FY 2022; and
Table 6J.2--Deletions to the CC List--FY 2022.
    We note that in the FY 2022 IPPS/LTCH PPS proposed rule there was 
not

[[Page 44927]]

a Table 6J.2--Proposed Deletions to the CC List--FY 2022 listed because 
we were not specifically proposing to delete any diagnosis codes from 
the current CC list effective with discharges on October 1, 2021 for FY 
2022. However, we have included Table 6J.2 in association with this 
final rule for completeness, to display diagnosis code M35.8 (Other 
specified systemic involvement of connective tissue) that was 
previously designated as a CC in FY 2020 and was deleted effective 
January 1, 2021 due to the creation of diagnosis codes, M35.81 
(Multisystem inflammatory syndrome) and M35.89 (Other specified 
systemic involvement of connective tissue) effective January 1, 2021 as 
displayed in the footnote of Table 6A.--New Diagnosis Codes --FY 2022. 
Similar to the process we described in the FY 2021 IPPS/LTCH PPS 
proposed rule (85 FR 32559), where we solicited comments and provided 
the public an opportunity to comment on the severity level designations 
(in addition to the MDC and MS-DRG assignments) that had been 
implemented for the two diagnosis codes (U07.0 and U07.1) effective 
with discharges on and after April 1, 2020 (FY 2020) for FY 2021 
consideration, in the FY 2022 IPPS/LTCH PPS proposed rule (86 FR 25191 
through 25192), we provided the list of six diagnosis codes that were 
effective with discharges on and after January 1, 2021in Table 6A.--New 
Diagnosis Codes--FY 2022 associated with the proposed rule and 
likewise, provided the public an opportunity to comment on the severity 
level designations (in addition to the MDC and MS-DRG assignments) that 
had been implemented for those six diagnosis codes, for FY 2022 
consideration. We did not receive any comments suggesting changes to 
the severity level (or MDC and MS-DRG assignments) for diagnosis codes 
M35.81 or M35.89 that were implemented on January 1, 2021, therefore, 
as shown in Table 6A.-New Diagnosis Codes-FY 2022 associated with this 
final rule, we are maintaining the CC severity level for these two 
diagnosis codes and displaying in Table 6J.2--Deletions to the CC 
List--FY 2022 also associated with this final rule, the corresponding 
deletion of diagnosis code M35.8 from the CC list that was implemented 
January 1, 2021 for completeness.
e. CC Exclusions List for FY 2022
    In the September 1, 1987 final notice (52 FR 33143) concerning 
changes to the DRG classification system, we modified the GROUPER logic 
so that certain diagnoses included on the standard list of CCs would 
not be considered valid CCs in combination with a particular principal 
diagnosis. We created the CC Exclusions List for the following reasons: 
(1) To preclude coding of CCs for closely related conditions; (2) to 
preclude duplicative or inconsistent coding from being treated as CCs; 
and (3) to ensure that cases are appropriately classified between the 
complicated and uncomplicated DRGs in a pair.
    In the May 19, 1987 proposed notice (52 FR 18877) and the September 
1, 1987 final notice (52 FR 33154), we explained that the excluded 
secondary diagnoses were established using the following five 
principles:
     Chronic and acute manifestations of the same condition 
should not be considered CCs for one another;
     Specific and nonspecific (that is, not otherwise specified 
(NOS)) diagnosis codes for the same condition should not be considered 
CCs for one another;
     Codes for the same condition that cannot coexist, such as 
partial/total, unilateral/bilateral, obstructed/unobstructed, and 
benign/malignant, should not be considered CCs for one another;
     Codes for the same condition in anatomically proximal 
sites should not be considered CCs for one another; and
     Closely related conditions should not be considered CCs 
for one another.
    The creation of the CC Exclusions List was a major project 
involving hundreds of codes. We have continued to review the remaining 
CCs to identify additional exclusions and to remove diagnoses from the 
master list that have been shown not to meet the definition of a CC. We 
refer readers to the FY 2014 IPPS/LTCH PPS final rule (78 FR 50541 
through 50544) for detailed information regarding revisions that were 
made to the CC and CC Exclusion Lists under the ICD-9-CM MS-DRGs.
    The ICD-10 MS-DRGs Version 38.1 CC Exclusion List is included as 
Appendix C in the ICD-10 MS-DRG Definitions Manual, which is available 
via the internet on the CMS website at: https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/AcuteInpatientPPS/index.html, and 
includes two lists identified as Part 1 and Part 2. Part 1 is the list 
of all diagnosis codes that are defined as a CC or MCC when reported as 
a secondary diagnosis. For all diagnosis codes on the list, a link is 
provided to a collection of diagnosis codes which, when reported as the 
principal diagnosis, would cause the CC or MCC diagnosis to be 
considered as a NonCC. Part 2 is the list of diagnosis codes designated 
as a MCC only for patients discharged alive; otherwise, they are 
assigned as a NonCC.
    In the FY 2022 IPPS/LTCH PPS proposed rule (86 FR 25175 through 
25180) we discussed our request for public comments on potential 
changes to the severity level for 3,490 diagnosis codes describing an 
``unspecified'' anatomic site, from a CC severity level to a NonCC 
severity level, for FY 2022. We referred the reader to Table 6P.3a 
associated with the proposed rule (which is available via the internet 
on the CMS website at https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/AcuteInpatientPPS/index.html) for the list of the 3,490 
diagnosis codes that are currently listed in Part 1 of the CC 
Exclusions List and are defined as a CC when reported as a secondary 
diagnosis. Table 6P.3a is divided into several tabs, with the first tab 
titled ``SDX Codes and Exclu Categories'' containing columns A, B, and 
C. Column A (titled ``ICD-10-CM Code'') lists the ``unspecified'' 
diagnosis codes that are currently listed in Part 1 of Appendix C of 
the CC Exclusions List, column B (titled ``Description'') lists the 
narrative description of each diagnosis code, and column C (titled 
Exclusion Category) contains a hyperlink to the collection of diagnosis 
codes which, when reported as the principal diagnosis, would cause the 
CC diagnosis to be considered as a NonCC. For example, for line 2, 
Column A displays diagnosis code C34.00, column B displays ``Malignant 
neoplasm of unspecified main bronchus'' and column C displays a 
hyperlink to Exclusion Category number 280. When the user clicks on the 
hyperlink for number 280, they are directed to another tab labeled 
``PDX Category 280'' that contains the list of diagnosis codes which, 
when reported as the principal diagnosis, would cause the corresponding 
CC diagnosis to be considered as a NonCC. In connection with the 
request for public comments on the potential changes to the severity 
level for 3,490 diagnosis codes describing an ``unspecified'' anatomic 
site, from a CC severity level to a NonCC severity level for FY 2022, 
Table 6P.3a was made available for readers to review and consider the 
list of the 3,490 ``unspecified'' diagnosis codes that are currently 
included in Part 1 of the CC Exclusions List and the principal 
diagnosis exclusion category with which they are currently associated. 
In the proposed rule we stated that if we were to finalize the 
potential changes to the severity level for the 3,490 diagnosis codes 
describing an ``unspecified'' anatomic site from a CC severity level to

[[Page 44928]]

a NonCC severity level for FY 2022, we would also finalize the removal 
of these codes from the CC Exclusions List for FY 2022. As discussed 
previously, we are not finalizing the changes to the severity level for 
the 3,490 diagnosis codes describing an ``unspecified'' anatomic site 
from a CC severity level to a NonCC severity level for FY 2022, and 
therefore we are also not finalizing the removal of these codes from 
the CC Exclusions List for FY 2022.
    In the proposed rule we discussed three requests we received 
related to the CC Exclusions List logic.
    We received a request to review the secondary diagnoses that are 
excluded as a CC or MCC in the CC Exclusions List logic when any one of 
the following three diagnosis codes is reported as the principal 
diagnosis.
BILLING CODE 4120-01-P
[GRAPHIC] [TIFF OMITTED] TR13AU21.127

    According to the requestor, in the ICD-10 MS-DRGs version 37.2 CC 
Exclusions List logic, the predecessor code for the listed diagnosis 
codes, diagnosis code O99.89 (Other specified diseases and conditions 
complicating pregnancy, childbirth and the puerperium) is listed in the 
collection of principal diagnosis list number 1000, therefore, when a 
CC or MCC secondary diagnosis associated with that principal diagnosis 
list describes a condition as occurring in pregnancy, childbirth or the 
puerperium, the CC Exclusions List logic will render that diagnosis 
code as a NonCC. The requestor stated that because diagnosis code 
O99.89 under version 37.2 of the ICD-10 MS-DRGs is now a subcategory 
under version 38.1 of the ICD-10 MS-DRGs, with three unique diagnosis 
codes to specify which obstetric stage the patient is in, that further 
analysis of the new diagnosis codes (O99.891, O99.892, and O99.893) 
should occur to determine if changes to the collection of principal 
diagnosis list is warranted. The requestor provided three examples for 
CMS to review and consider for possible changes to the CC Exclusions 
List logic.
    In the first example, the requestor noted that diagnosis code O72.1 
(Other immediate postpartum hemorrhage) is listed as a CC secondary 
diagnosis associated with the collection of principal diagnosis list 
number 1000, and that under the ICD-10 MS-DRGs version 38.1 CC 
Exclusions List logic, the diagnosis listed in principal diagnosis 
collection 1000 is now diagnosis code O99.893 (Other specified diseases 
and conditions complicating puerperium). Thus, both diagnosis codes 
(O72.1 and O99.893) are describing conditions occurring specifically in 
the postpartum or puerperium period. The postpartum period is defined 
as the period beginning immediately after delivery and continues for 
six weeks following delivery. A postpartum complication is any 
complication occurring within the six-week period. The requestor stated 
that because diagnosis code O72.1 is assigned for documented postpartum 
uterine atony with hemorrhage when it occurs immediately following the 
delivery of the baby and placenta, that CMS should review diagnosis 
code O99.892 (Other specified diseases and conditions complicating 
childbirth) and determine if it should be added to the collection of 
principal diagnosis list number 1000 to cause diagnosis code O72.1 to 
be considered as a NonCC when diagnosis code O99.892 is reported as the 
principal diagnosis.
    In the second example, the requestor noted that diagnosis code 
O98.32 (Other infections with a predominantly sexual mode of 
transmission complicating childbirth) is associated with principal 
diagnosis collection number 1012. The requestor also noted that 
principal diagnosis collection number 1012 does not list diagnosis 
codes O99.891, O99.892, or O99.893 as a principal diagnosis to exclude 
the CC secondary diagnosis code O98.32, however, it does list diagnosis 
codes O98.311 (Other infections with a predominantly sexual mode of 
transmission complicating pregnancy, first trimester), O98.312 (Other 
infections with a predominantly sexual mode of transmission 
complicating pregnancy, second trimester), and O98.313 (Other 
infections with a predominantly sexual mode of transmission 
complicating pregnancy, third trimester) as a principal diagnosis to 
exclude the CC secondary diagnosis code O98.32. The requestor 
recommended CMS review diagnosis codes O98.32 (Other infections with a 
predominantly sexual mode of transmission complicating childbirth) and 
O98.33 (Other infections with a predominantly sexual mode of 
transmission complicating the puerperium), to determine if diagnosis 
codes O99.891, O99.892 or O99.893, when reported as a principal 
diagnosis, should exclude CC secondary diagnosis codes O98.32 and 
O98.33. Thus, the requestor suggested CMS consider if it is appropriate 
to add diagnosis codes O99.891, O99.892 and O99.893 to principal 
diagnosis collection number 1012 to cause diagnosis code O98.32 to be 
considered as a NonCC when diagnosis codes O99.891, O99.892 or O99.893 
are reported as the principal diagnosis.
    In the third example, the requestor noted that diagnosis code O87.2 
(Hemorrhoids in the puerperium) is associated with principal diagnosis 
collection number 4041. The requestor also noted that principal 
diagnosis collection number 4041 lists diagnosis code O99.893 as a 
principal diagnosis to exclude the CC diagnosis code O87.2, however, it 
does not list diagnosis code O99.892. The requestor further noted that 
the ``Includes'' note at Category O87 (Venous complications and 
hemorrhoids in the puerperium) in the FY 2021 ICD-10-CM Tabular List 
includes ``venous complications in labor, delivery and the 
puerperium'', therefore, diagnosis code O87.2 would also be reported 
for documented hemorrhoids during labor and delivery. The requestor 
recommended CMS review diagnosis code O99.892 to determine if, when 
reported as a principal diagnosis, it should exclude CC diagnosis code 
O87.2. Thus, the requestor suggested CMS consider if it is appropriate 
to add diagnosis code O99.892 to principal diagnosis collection number 
4041 to cause diagnosis code O87.2 to be considered as a NonCC when 
diagnosis code O99.892 is reported as the principal diagnosis.
    We stated in the proposed rule that we reviewed diagnosis codes 
O99.891, O99.892 and O99.893 with respect to the principal diagnosis 
collection list

[[Page 44929]]

and because these diagnosis codes are specifically describing ``other 
specified diseases and conditions complicating pregnancy, childbirth, 
and the puerperium,'' respectively, we do not believe that any of these 
three diagnosis codes, when reported as a principal diagnosis, should 
exclude any CC secondary diagnosis. In cases where any one of these 
three diagnosis codes is reported as a principal diagnosis, which are 
generally anticipated to be rare, it is understood that there is not a 
more specific diagnosis code available in the classification to report 
as the principal diagnosis that identifies the underlying or associated 
cause of the disease or the condition complicating the specific 
obstetric stage (pregnancy, childbirth, or puerperium), hence the 
``other specified'' in the code title. Specifically, the title of 
category O99 is ``Other maternal diseases classifiable elsewhere but 
complicating pregnancy, childbirth and the puerperium'' and there are 
nine subcategories, each of which is generally associated with a single 
organ system or etiology, with the exception of the ``other specified'' 
subcategory (O99.8) as displayed in the following table.
[GRAPHIC] [TIFF OMITTED] TR13AU21.128

    The instructional note at category O99 states ``use additional code 
to identify specific condition'' and included at each subcategory 
(O99.0-O99.7) are a range of codes that refer to diagnoses that are 
associated with the condition in the title of the subcategory that are 
to be reported in addition to the applicable code within the respective 
subcategory. For example, at subcategory O99.0 (Anemia complicating 
pregnancy, childbirth, and the puerperium), the range of associated 
codes to identify the specific condition (for example, type of anemia) 
includes conditions in diagnosis code range D50-D64, meaning that when 
any one of the diagnosis codes under subcategory O99.0 describing 
anemia complicating a specific obstetric stage (pregnancy, childbirth, 
or puerperium) is reported, a code within the D50-D64 code range to 
identify the specific type of anemia would also be expected to be 
reported when supported by the medical record documentation. It is 
therefore reasonable to associate the two conditions (one from 
subcategory O99.0 and one from code range D50-D64) when reported on a 
claim. However, the same cannot be stated for subcategory O99.8. There 
is no range of associated codes from which users are instructed to 
report located at this particular subcategory in addition to the 
specific code under sub-subcategory O99.89 (Other specified diseases 
and conditions complicating pregnancy, childbirth and the puerperium). 
We note that subcategory O99.8 and sub-subcategory O99.89 have the same 
title. Therefore, when a diagnosis code from other than that sub-
subcategory is reported that describes a condition occurring in any one 
of the obstetric stages (pregnancy, childbirth, or puerperium) it is 
not clear if the condition can reasonably be associated to correspond 
to the ``other specified diseases and conditions'' diagnosis. In 
addition, the code ranges included at subcategory O99.8 are D00-D48, 
H00-H95, M00-N99, and Q00-Q99. Consequently, diagnosis codes within 
those code ranges would be expected to be reported with one of the 
diagnosis codes under subcategory O99.8 when reported as a principal 
diagnosis.
    In all three of the requestor's examples, the diagnosis codes 
provided for CMS to review and consider are located in the ``O'' code 
range (O72.1, O98.32, and O87.2 in addition to O99.891, O99.892, and 
O99.893). As noted previously, the code ranges included at subcategory 
O99.8 as listed, do not include any codes in the ``O'' code range. Upon 
review of the diagnosis codes provided by the requestor, it is also 
reasonable to expect that any one of those diagnosis codes (O72.1, 
O98.32, and O87.2) could be

[[Page 44930]]

reported as a principal diagnosis alone. For instance, there are no 
instructional notes at diagnosis code O72.1 that preclude that 
diagnosis code from being reported as the principal diagnosis.
    We stated in the proposed rule that during our review of the CC 
Exclusions List logic in response to the requestor's recommendations, 
we also identified some diagnosis codes describing the specific 
trimester of pregnancy that we believe warrant further examination. We 
noted that we were unable to fully evaluate these conditions for FY 
2022, therefore, we will continue to analyze for future rulemaking.
    For the reasons discussed, we stated in the proposed rule that we 
do not believe that any of the three diagnosis codes (O99.891, O99.892, 
and O99.893), when reported as a principal diagnosis, should exclude 
any CC secondary diagnosis. Therefore, we proposed to remove diagnosis 
codes O99.891, O99.892, and O99.893 from the CC Exclusions List logic 
principal diagnosis collection lists. Specifically, we proposed to 
remove those diagnosis codes from the following principal diagnosis 
collection list numbers 0085, 0954, 0956 through 0963, 0972, 0988, 0991 
through 0998, 1000 through 1002, 1004, 1006, 1009, 1011, 1014, 1015, 
1019, 3999, 4000, 4002 through 4006, 4008, 4010, through 4013, 4017, 
4020, 4021, 4023 through 4026, 4030, 4031, 4033 through 4043, 4050 
through 4054, 4059 through 4063, 4065 and 4067, effective FY 2022.
    We did not receive any comments opposing our proposal, therefore, 
we are finalizing the removal of diagnosis codes O99.891, O99.892, and 
O99.893 from the CC Exclusions List logic principal diagnosis 
collection lists identified for FY 2022.
    In the proposed rule we also discussed a request we received to 
review diagnosis codes describing oxygen dependence, chronic 
obstructive pulmonary disease with exacerbation, and chronic 
respiratory failure with regard to assignment in MS-DRG 191 (Chronic 
Obstructive Pulmonary Disease with CC) and to consider whether any 
changes to principal diagnosis collection number 0744 in the CC 
Exclusions List logic are warranted.
    The requestor provided diagnosis codes J44.1 (Chronic obstructive 
pulmonary disease with (acute) exacerbation), J96.11 (Chronic 
respiratory failure with hypoxia (CC)) and Z99.81 (Dependence on 
supplemental oxygen) for CMS to review. Specifically, the requestor 
suggested that if oxygen dependence, by definition, is clinically 
inherent to chronic respiratory failure, then CMS should consider 
adding diagnosis code J44.1 to the CC Exclusions List logic principal 
diagnosis collection list number 0744 and cause diagnosis code J96.11 
to be considered as a NonCC when J44.1 is reported as the principal 
diagnosis.
    We stated in the proposed rule that we reviewed the diagnosis codes 
and MS-DRG assignment as the requestor suggested. We confirmed that 
when diagnosis code J44.1 is reported as the principal diagnosis with 
the CC secondary diagnosis code J96.11, and secondary diagnosis code 
Z99.81, the resulting MS-DRG assignment is MS-DRG 191. We stated our 
belief that diagnosis code J96.11 should continue to group as a CC, to 
the ``with CC'' MS-DRG 191, when reported as a secondary diagnosis code 
with diagnosis code J44.1 reported as the principal diagnosis. We 
disagreed with the requestor's suggestion that every oxygen-dependent 
COPD patient has chronic respiratory failure, and that separately 
reporting the chronic respiratory failure is clinically redundant. 
Patients can be oxygen-dependent with COPD and not have a diagnosis of 
chronic respiratory failure. Therefore, we proposed to maintain the 
structure of principal diagnosis collection list number 0744 in the CC 
Exclusions List logic for FY 2022.
    We did not receive any comments opposing our proposal, therefore, 
we are finalizing the proposal to maintain the structure of principal 
diagnosis collection list number 0744 in the CC Exclusions List logic 
for FY 2022.
    Lastly, in the proposed rule we discussed a request we received to 
reconsider the MCC exclusions for diagnosis code I11.0 (Hypertensive 
heart disease with heart failure) when reported as the principal 
diagnosis. According to the requestor, there appears to be an 
inconsistency for the CC Exclusions List logic. Specifically, the 
requestor noted that when diagnosis code I11.0 is reported as the 
principal diagnosis, it causes the following MCC secondary diagnosis 
codes to be considered as a NonCC.
[GRAPHIC] [TIFF OMITTED] TR13AU21.129

    However, the requestor stated that diagnosis codes I50.21 (Acute 
systolic (congestive) heart failure) and I50.31 (Acute diastolic 
(congestive) heart failure) are not excluded from acting as MCCs when 
diagnosis code I11.0 is reported as the principal diagnosis. The 
requestor also stated that all diagnosis codes in category I50 (Heart 
Failure) share common etiologies and demonstrate comparable severity of 
illness. Therefore, the requestor suggested that none of the conditions 
in this category (I50) should be excluded from acting as a MCC when 
diagnosis code I11.0 is reported as a principal diagnosis.
    In the proposed rule we stated that we examined all the diagnosis 
codes in category I50 with regard to the CC Exclusions List logic. In 
addition to diagnosis code I11.0, we also reviewed diagnosis code I13.2 
(Hypertensive heart and chronic kidney disease with heart failure and 
with stage 5 chronic kidney disease, or end stage renal disease) when 
reported as a principal diagnosis because that diagnosis code also has 
the Tabular instruction ``use additional code to identify the type of 
heart failure''.
    We found additional inconsistencies in the CC secondary diagnosis 
heart failure codes where some diagnoses were excluded depending on the 
principal diagnosis reported and others were not excluded. As a result, 
we proposed to revise the CC Exclusions Logic list for diagnosis codes 
I11.0 and

[[Page 44931]]

I13.2 when reported as a principal diagnosis to ensure they are 
consistent in the CC and MCC diagnoses they exclude. In the proposed 
rule we showed the findings for each diagnosis code in category I50 in 
the following table with respect to the current severity level (MCC, CC 
or NonCC), if it is currently excluded as a CC or MCC when reported 
with either diagnosis code I11.0 or I13.2 as the principal diagnosis, 
and our proposal under the CC Exclusions List logic for FY 2022.
[GRAPHIC] [TIFF OMITTED] TR13AU21.130


[[Page 44932]]


[GRAPHIC] [TIFF OMITTED] TR13AU21.131

    Comment: Several commenters agreed with our proposal to revise the 
CC Exclusions List logic for diagnosis codes I11.0 and I13.2 when 
either code is reported as a principal diagnosis. A commenter also 
suggested that the changes made for diagnosis code I13.2 should be made 
for diagnosis code I13.0 (Hypertensive heart and chronic kidney

[[Page 44933]]

disease with heart failure and stage 1 through stage 4 chronic kidney 
disease, or unspecified chronic kidney disease).
    Response: With regard to the commenter's suggestion that changes 
made for diagnosis code I13.2 should also be made for diagnosis code 
I13.0, we appreciate the feedback. We were unable to fully evaluate the 
request for FY 2022 consideration, therefore, we will examine this 
issue for future rulemaking and determine if there are other diagnoses 
that should also be considered further.
    After consideration of the comments received, we are finalizing our 
proposal to revise the CC Exclusions Logic list for diagnosis codes 
I11.0 and I13.2 when reported as a principal diagnosis, without 
modification, for FY 2022.
    We also proposed additional changes to the ICD-10 MS-DRGs Version 
39 CC Exclusion List based on the diagnosis and procedure code updates 
as discussed in section II.D.13. of the FY 2022 IPPS/LTCH PPS proposed 
rule and set forth in Tables 6G.1, 6G.2, 6H.1, and 6H.2 associated with 
the proposed rule and available via the internet on the CMS website at 
https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/AcuteInpatientPPS/index.html.
    Comment: A commenter stated they did not agree with the proposed 
MCC exclusion for new diagnosis codes S06.A0XA (Traumatic brain 
compression without herniation, initial encounter) and S06.A1XA 
(Traumatic brain compression with herniation, initial encounter) as 
shown in Tables 6G.1 and 6G.2 associated with the proposed rule, when 
reported with principal diagnoses from subcategories S06.1, S06.2, 
S06.3, S06.4, S06.5, or S06.6. According to the commenter, patients 
with brain compression secondary to traumatic intracranial injuries 
have significantly higher morbidity and mortality, longer length of 
stays, and greater consumption of resources than those without brain 
compression. The commenter identified that the current code for brain 
compression (G93.5) has been separately reportable as a MCC with 
principal diagnoses from subcategories S06.4, S06.5, and S06.6; and 
maintained that the new codes for brain compression should reasonably 
retain MCC severity. The commenter added that some epidural, subdural, 
and subarachnoid hemorrhages are small, easily monitored and without 
compression; but others result in significant brain compression with 
longer length of stays and greater consumption of resources with the 
MCC severity differentiating these groups of patients. The commenter 
asserted that brain compression should also be a MCC when reported with 
principal diagnoses from subcategories S06.2 (Diffuse traumatic brain 
injury) and S06.3 (Focal traumatic brain injury) for the same reasons.
    Lastly, the commenter stated that because diffuse traumatic brain 
injury with diffuse cerebral edema must be reported with a single code 
from subcategory S06.1- per the Excludes 1 note at subcategory S06.2-, 
it is additionally reasonable for brain compression to be a MCC 
severity with a principal diagnosis of traumatic cerebral edema (S06.1-
) in order to differentiate between patients with and without the life-
threatening complication of brain compression.
    Response: We appreciate the commenter's feedback. It is not clear 
from the commenter's statement if they were unable to differentiate the 
content between Table 6G.1 and Table 6G.2 associated with the proposed 
rule. We note that for Table 6G.1, each secondary diagnosis code 
proposed for addition to the CC Exclusion List is shown with an 
asterisk and the principal diagnoses proposed to exclude the secondary 
diagnosis code are provided in the indented column immediately 
following it. For Table 6G.2, each of the principal diagnosis codes for 
which there is a proposed CC exclusion is shown with an asterisk and 
the conditions proposed for addition to the CC Exclusion List that will 
not count as a CC are provided in an indented column immediately 
following the affected principal diagnosis. We believe the commenter 
may have inadvertently reviewed Table 6G.2 as if it were Table 6G.1. To 
clarify, diagnosis codes S06.A0XA and S06.A1XA, as shown in Table 6G.1 
with an asterisk, were proposed to be excluded from acting as a 
secondary diagnosis MCC when any one of the following diagnoses are 
reported as the principal diagnosis; G93.6 (Cerebral edema), G93.82 
(Brain death), S06.1X0A (Traumatic cerebral edema without loss of 
consciousness, initial encounter), S06.A0XA (Traumatic brain 
compression without herniation, initial encounter), and S06.A1XA 
(Traumatic brain compression with herniation, initial encounter). We 
are providing the following table to illustrate how the contents of 
Table 6G.1 associated with the proposed rule (and available via the 
internet on the CMS website at https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/AcuteInpatientPPS/index.html), are displayed 
for these codes. We note that Table 6G.1 does not include the decimal 
point for any of the diagnosis codes listed.
[GRAPHIC] [TIFF OMITTED] TR13AU21.132

BILLING CODE 4120-01-C
    As shown in the table, codes S06.A0XA and S06.A1XA are the 
secondary diagnosis codes that were proposed for addition to the CC 
Exclusion List as shown with an asterisk, and the principal diagnoses 
proposed to exclude these codes from acting as a MCC are provided in 
the indented column immediately following each. Therefore, our proposal 
was not to exclude codes S06.A0XA and S06.A1XA from acting as a MCC 
when reported with principal diagnoses from subcategories S06.2, S06.3, 
S06.4, S06.5, or S06.6, as there are no codes from those subcategories 
listed in the table. With respect to subcategory S06.1, as shown in the 
table, diagnosis code S06.1X0A is listed as a principal diagnosis that 
would exclude codes S06.A0XA and S06.A1XA from acting as a MCC when 
reported as a secondary diagnosis, as proposed.
    We acknowledge that diffuse traumatic brain injury with diffuse 
cerebral edema must be reported with a single code from subcategory 
S06.1- per the Excludes 1 note at subcategory S06.2-, therefore, we 
consulted with staff at the Centers for Disease Control's (CDC's) 
National Center for Health Statistics (NCHS) because NCHS has the

[[Page 44934]]

lead responsibility for the ICD-10-CM diagnosis codes. The NCHS' staff 
confirmed that the Excludes 1 note at subcategory S06.2- requires 
further clinical review and consideration. We also examined the 
predecessor code for new diagnosis codes S06.A0XA and S06.A1XA, (code 
S06.1X0A), to identify the principal diagnosis collection list (list of 
principal diagnosis codes) that exclude code S06.1X0A from acting as a 
MCC and were the basis for the list of principal diagnosis codes 
proposed to exclude new diagnosis codes S06.A0XA and S06.A1XA from 
acting as a MCC when reported as a principal diagnosis. We note that 
code S06.1X0A is associated with principal diagnosis collection number 
3977 and includes diagnosis codes G93.6, G93.82, and S06.1X0A, 
consistent with the principal diagnosis exclusions proposed for new 
diagnosis codes S06.A0XA and S06.A1XA.
    We refer the reader to Table 6G.2 associated with the proposed rule 
(and available via the internet on the CMS website at https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/AcuteInpatientPPS/index.html), to review how codes S06.A0XA and 
S06.A1XA were displayed as principal diagnoses as shown with an 
asterisk, and the conditions proposed for addition to the CC Exclusion 
List to not count as a CC are provided in an indented column 
immediately following the affected principal diagnosis. Among the 
conditions proposed for addition to the CC Exclusion List to not count 
as a CC are those from subcategories S06.1, S06.2, S06.3, S06.4, S06.5, 
and S06.6. As such, we believe the commenter inadvertently reviewed 
Table 6G.2 as if it were Table 6G.1.
    After consideration of the public comments received, and until such 
time the CDC/NCHS staff can review the Excludes note at subcategory 
S06.2- further, we are finalizing our proposal to exclude diagnosis 
codes S06.A0XA and S06.A1XA from acting as a MCC when one of the listed 
diagnosis codes from Table 6G.1 is reported as a principal diagnosis 
and we are also finalizing our proposal to exclude the listed diagnosis 
codes in Table 6G.2 from acting as a MCC when diagnosis code S06.A0XA 
or S06.A1XA is reported as the principal diagnosis.
    As discussed in section II.D.13. of the preamble of this final 
rule, we are finalizing, without modification, the proposed assignments 
and designations for the diagnosis codes after consideration of the 
public comments received. Therefore, the finalized CC Exclusions List 
as displayed in Tables 6G.1, 6G.2, 6H.1, 6H.2, and 6K, associated with 
this final rule reflect the severity levels under V39 of the ICD-10 MS-
DRGs.
    We have developed Table 6G.1.--Secondary Diagnosis Order Additions 
to the CC Exclusions List--FY 2022; Table 6G.2.--Principal Diagnosis 
Order Additions to the CC Exclusions List--FY 2022; Table 6H.1.--
Secondary Diagnosis Order Deletions to the CC Exclusions List--FY 2022; 
and Table 6H.2.--Principal Diagnosis Order Deletions to the CC 
Exclusions List--FY 2022; and Table 6K. Complete List of CC Exclusions-
FY 2022.
    For Table 6G.1, each secondary diagnosis code finalized for 
addition to the CC Exclusion List is shown with an asterisk and the 
principal diagnoses finalized to exclude the secondary diagnosis code 
are provided in the indented column immediately following it. For Table 
6G.2, each of the principal diagnosis codes for which there is a CC 
exclusion is shown with an asterisk and the conditions finalized for 
addition to the CC Exclusion List that will not count as a CC are 
provided in an indented column immediately following the affected 
principal diagnosis. For Table 6H.1, each secondary diagnosis code 
finalized for deletion from the CC Exclusion List is shown with an 
asterisk followed by the principal diagnosis codes that currently 
exclude it. For Table 6H.2, each of the principal diagnosis codes is 
shown with an asterisk and the finalized deletions to the CC Exclusions 
List are provided in an indented column immediately following the 
affected principal diagnosis. Table 6K is a list of all of the codes 
that are defined as either CC or a MCC when used as a secondary 
diagnosis. Within the table each code is specifically indicated as CC 
or MCC. A table number is given to a collection of diagnosis codes 
which, when used as the principal diagnosis, will cause the CC or MCC 
to be considered as only a NonCC. Tables 6G.1., 6G.2., 6H.1., 6H.2, and 
6K. associated with this final rule are available via the internet on 
the CMS website at: https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/AcuteInpatientPPS/index.html.
    The ICD-10 MS-DRGs Version 39 CC Exclusion List is included as 
Appendix C of the Definitions Manual (available in two formats; text 
and HTML). The manuals are available via the internet on the CMS 
website at: https://www.cms.gov/Medicare/Medicare-Feefor-Service-Payment/AcuteInpatientPPS/MS-DRGClassifications-and-Software and each 
format includes two lists identified as Part 1 and Part 2. Part 1 is 
the list of all diagnosis codes that are defined as a CC or MCC when 
reported as a secondary diagnosis. For all diagnosis codes on the list, 
a link (HTML version) is provided to a collection of diagnosis codes 
which, when used as the principal diagnosis, would cause the CC or MCC 
diagnosis to be considered as a non-CC. Part 2 is the list of diagnosis 
codes designated as a MCC only for patients discharged alive; 
otherwise, they are assigned as a non-CC.
13. Changes to the ICD-10-CM and ICD-10-PCS Coding Systems
    To identify new, revised and deleted diagnosis and procedure codes, 
for FY 2022, we have developed Table 6A.--New Diagnosis Codes, Table 
6B.--New Procedure Codes, Table 6C.--Invalid Diagnosis Codes, Table 
6D.--Invalid Procedure Codes Table 6E.--Revised Diagnosis Code Titles, 
and Table 6F.--Revised Procedure Code Titles for this final rule.
    These tables are not published in the Addendum to the proposed rule 
or final rule, but are available via the internet on the CMS website 
at: https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/AcuteInpatientPPS/index.html as described in section VI. of the 
Addendum to this final rule. As discussed in section II.D.16. of the 
preamble of this final rule, the code titles are adopted as part of the 
ICD-10 (previously ICD-9-CM) Coordination and Maintenance Committee 
meeting process. Therefore, although we publish the code titles in the 
IPPS proposed and final rules, they are not subject to comment in the 
proposed or final rules.
    In the FY 2022 IPPS/LTCH PPS proposed rule (86 FR 25186) we 
proposed the MDC and MS-DRG assignments for the new diagnosis codes and 
procedure codes as set forth in Table 6A.--New Diagnosis Codes and 
Table 6B.--New Procedure Codes. We also stated that the proposed 
severity level designations for the new diagnosis codes are set forth 
in Table 6A. and the proposed O.R. status for the new procedure codes 
are set forth in Table 6B. Consistent with our established process, we 
examined the MS-DRG assignment and the attributes (severity level and 
O.R. status) of the predecessor diagnosis or procedure code, as 
applicable, to inform our proposed assignments and designations. 
Specifically, we reviewed the predecessor code and MS-DRG assignment 
most closely associated with the new diagnosis or procedure code, and 
in the absence of claims data, we considered other factors that may be

[[Page 44935]]

relevant to the MS-DRG assignment, including the severity of illness, 
treatment difficulty, complexity of service and the resources utilized 
in the diagnosis and/or treatment of the condition. We noted that this 
process does not automatically result in the new diagnosis or procedure 
code being proposed for assignment to the same MS-DRG or to have the 
same designation as the predecessor code.
    Comment: A commenter stated they did not agree with the proposed 
severity level for diagnosis code I5A (Non-ischemic myocardial injury 
(non-traumatic)) shown as a CC in Table 6A.--New Diagnosis Codes. 
According to the commenter, the 4th Universal Definition of MI states 
that a non-ischemic myocardial injury is diagnosed only with an 
elevated troponin. The commenter recommended that the CC severity level 
for this diagnosis code be changed to a NonCC and to allow the 
underlying cause of the non-ischemic myocardial injury to act as the CC 
or MCC instead.
    Response: We appreciate the commenter's feedback. Consistent with 
our annual process of assigning new diagnosis codes to MDCs, MS-DRGs, 
and designating a severity level (MCC, CC or NonCC), we reviewed the 
predecessor diagnosis code assignment for code I5A. The predecessor 
code for code I5A is diagnosis code I21.A9 (Other myocardial infarction 
type), which is designated as a MCC. Our clinical advisors did not 
agree with a MCC severity level assignment for code I5A because they 
stated nonischemic myocardial injury may be secondary to cardiac 
conditions such as myocarditis or non-cardiac conditions such as renal 
failure and the clinical evaluation and work up vary depending on the 
results of testing. Upon further review, they continue to believe that 
a CC severity level designation is warranted.
    Comment: A commenter stated they did not agree with the proposed 
designation of procedure codes 07DT0ZX (Extraction of bone marrow, open 
approach, diagnostic) and 07DT0ZZ (Extraction of bone marrow, open 
approach) shown as Non-O.R. procedures in Table 6B.--New Procedure 
Codes. According to the commenter, these procedures should be 
classified as O.R. procedures because open incision down to bone with 
direct visualization of bone marrow during extraction requires 
operating room resources and anesthesia.
    Response: We appreciate the commenter's feedback. Consistent with 
our annual process of assigning new procedure codes to MDCs, MS-DRGs, 
and classifying as an O.R. or Non-O.R. procedure, we reviewed the 
predecessor procedure code assignment for codes 07DT0ZX and 07DT0ZZ. 
The predecessor code for code 07DT0ZX is procedure code 079T0ZX 
(Drainage of bone marrow, open approach, diagnostic), which is 
designated as a Non-O.R. procedure and the predecessor code for code 
07DT0ZZ is 079T0ZZ (Drainage of bone marrow, open approach) which is 
also designated as a Non-O.R. procedure. Our clinical advisors did not 
agree with an O.R. designation because they stated open bone marrow 
biopsy procedures would rarely be performed and rarely be the primary 
cause for an inpatient admission contributing to resource consumption. 
They indicated that if performed, it is more likely they would be 
conducted in connection with another open surgical procedure.
    After consideration of the comments received, for FY 2022, we are 
maintaining the CC severity level for diagnosis code I5A and finalizing 
the Non-O.R. designation for procedure codes 07DT0ZX and 07DT0ZZ.
    We are making available on the CMS website at https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/AcuteInpatientPPS/index.html 
the following tables associated with this final rule:

 Table 6A.--New Diagnosis Codes-FY 2022;
 Table 6B.--New Procedure Codes--FY 2022;
 Table 6C.--Invalid Diagnosis Codes--FY 2022;
 Table 6D.--Invalid Procedure Codes--FY 2022;
 Table 6E.--Revised Diagnosis Code Titles--FY 2022;
 Table 6F.--Revised Procedure Code Titles--FY 2022;
 Table 6G.1.--Secondary Diagnosis Order Additions to the CC 
Exclusions List--FY 2022;
     Table 6G.2.--Principal Diagnosis Order Additions to the CC 
Exclusions List--FY 2022;
     Table 6H.1.--Secondary Diagnosis Order Deletions to the CC 
Exclusions List-FY 2022;
     Table 6H.2.--Principal Diagnosis Order Deletions to the CC 
Exclusions List--FY 2022;
     Table 6I.--Complete MCC List--FY 2022;
     Table 6I.1.--Additions to the MCC List--FY 2022;
     Table 6I.2.--Deletions to the MCC List--FY 2022;
     Table 6J.--Complete CC List--FY 2022;
     Table 6J.1.--Additions to the CC List--FY 2022;
     Table 6J.2.--Deletions to the CC List--FY 2022; and
     Table 6K.--Complete List of CC Exclusions--FY 2022
14. Changes to the Medicare Code Editor (MCE)
    The Medicare Code Editor (MCE) is a software program that detects 
and reports errors in the coding of Medicare claims data. Patient 
diagnoses, procedure(s), and demographic information are entered into 
the Medicare claims processing systems and are subjected to a series of 
automated screens. The MCE screens are designed to identify cases that 
require further review before classification into an MS-DRG.
    As discussed in the FY 2021 IPPS/LTCH PPS final rule (85 FR 58448), 
we made available the FY 2021 ICD-10 MCE Version 38 manual file. The 
manual contains the definitions of the Medicare code edits, including a 
description of each coding edit with the corresponding diagnosis and 
procedure code edit lists. The link to this MCE manual file, along with 
the link to the mainframe and computer software for the MCE Version 38 
(and ICD-10 MS-DRGs) are posted on the CMS website at https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/AcuteInpatientPPS/MS-DRG-Classifications-and-Software.
    In the FY 2022 IPPS/LTCH PPS proposed rule, we addressed the MCE 
requests we received by the November 1, 2020 deadline. We also 
discussed the proposals we were making based on our internal review and 
analysis. In this FY 2022 IPPS/LTCH PPS final rule, we present a 
summation of the comments we received in response to the MCE requests 
and proposals presented based on internal review and analyses in the 
proposed rule, our responses to those comments, and our finalized 
policies.
    In addition, as a result of new and modified code updates approved 
after the annual spring ICD-10 Coordination and Maintenance Committee 
meeting, we routinely make changes to the MCE. In the past, in both the 
IPPS proposed and final rules, we have only provided the list of 
changes to the MCE that were brought to our attention after the prior 
year's final rule. We historically have not listed the changes we have 
made to the MCE as a result of the new and modified codes approved 
after the annual spring ICD-10 Coordination and Maintenance Committee 
meeting. These changes are approved too late in the rulemaking schedule 
for inclusion in the proposed rule. Furthermore, although our MCE 
policies have been described in our proposed and final

[[Page 44936]]

rules, we have not provided the detail of each new or modified 
diagnosis and procedure code edit in the final rule. However, we make 
available the finalized Definitions of Medicare Code Edits (MCE) file. 
Therefore, we are making available the FY 2022 ICD-10 MCE Version 39 
Manual file, along with the link to the mainframe and computer software 
for the MCE Version 39 (and ICD-10 MS-DRGs), on the CMS website at 
https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/AcuteInpatientPPS/MS-DRG-Classifications-and-Software.
a. External Causes of Morbidity Codes as Principal Diagnosis
    In the MCE, the external cause codes (V, W, X, or Y codes) describe 
the circumstance causing an injury, not the nature of the injury, and 
therefore should not be used as a principal diagnosis.
    As discussed in section II.D.13. of the preamble of the proposed 
rule and section II.D.13. of this final rule, Table 6A.--New Diagnosis 
Codes, lists the diagnosis codes that have been approved to date which 
will be effective with discharges on and after October 1, 2021. We 
proposed to add the following new ICD-10-CM diagnosis codes to the 
External Causes of Morbidity edit code list.
BILLING CODE 4120-01-P
[GRAPHIC] [TIFF OMITTED] TR13AU21.133

    Comment: Commenters agreed with CMS' proposal to add the diagnosis 
codes listed in the previous table to the External Causes of Morbidity 
edit code list.
    Response: We appreciate the commenters' support.
    After consideration of the public comments we received, we are 
finalizing our proposal to add the diagnosis codes listed in the 
previous table to the External Causes of Morbidity edit code list under 
the ICD-10 MCE Version 39, effective October 1, 2021.
b. Age Conflict Edit
    In the MCE, the Age conflict edit exists to detect inconsistencies 
between a patient's age and any diagnosis on the patient's record; for 
example, a 5-year-old patient with benign prostatic hypertrophy or a 
78-year-old patient coded with a delivery. In these cases, the 
diagnosis is clinically and virtually impossible for a patient of the 
stated age. Therefore, either the diagnosis or the age is presumed to 
be incorrect. Currently, in the MCE, the following four age diagnosis 
categories appear under the Age conflict edit and are listed in the 
manual and written in the software program:
     Perinatal/Newborn--Age 0 years only; a subset of diagnoses 
which will only occur during the perinatal or newborn period of age 0 
(for example, tetanus neonatorum, health examination for newborn under 
8 days old).
     Pediatric--Age is 0-17 years inclusive (for example, 
Reye's syndrome, routine child health exam).
     Maternity--Age range is 9-64 years inclusive (for example, 
diabetes in pregnancy, antepartum pulmonary complication).
     Adult--Age range is 15-124 years inclusive (for example, 
senile delirium, mature cataract).
(1) Pediatric Diagnoses
    Under the ICD-10 MCE, the Pediatric diagnoses category for the Age 
conflict edit considers the age range of 0 to 17 years inclusive. For 
that reason, the diagnosis codes on this Age conflict edit list would 
be expected to apply to conditions or disorders specific to that age 
group only.
    As discussed in section II.D.13. of the preamble of the proposed 
rule and section II.D.13. of this final rule, Table 6A.--New Diagnosis 
Codes, lists the diagnosis codes that have been approved to date which 
will be effective with discharges on and after October 1, 2021. We 
proposed to add the following new ICD-10-CM diagnosis codes to the 
Pediatric diagnoses category code list under the Age conflict edit.
[GRAPHIC] [TIFF OMITTED] TR13AU21.134

    Comment: Commenters agreed with CMS' proposal to add the diagnosis 
codes listed in the previous table to the Pediatric diagnoses category 
code list under the Age Conflict edit.
    Response: We appreciate the commenters' support.
    After consideration of the public comments we received, we are 
finalizing our proposal to add the diagnosis codes listed in the 
previous table to the Pediatric diagnoses category code list under the 
Age Conflict edit in the ICD-10 MCE Version 39, effective October 1, 
2021.
c. Sex Conflict Edit
    In the MCE, the Sex conflict edit detects inconsistencies between a 
patient's sex and any diagnosis or procedure on the patient's record; 
for

[[Page 44937]]

example, a male patient with cervical cancer (diagnosis) or a female 
patient with a prostatectomy (procedure). In both instances, the 
indicated diagnosis or the procedure conflicts with the stated sex of 
the patient. Therefore, the patient's diagnosis, procedure, or sex is 
presumed to be incorrect.
(1) Diagnoses for Females Only Edit
    As discussed in section II.D.13. of the preamble of the proposed 
rule and section II.D.13. of this final rule, Table 6A.--New Diagnosis 
Codes, lists the new diagnosis codes that have been approved to date 
which will be effective with discharges on and after October 1, 2021. 
We proposed to add the following new ICD-10-CM diagnosis codes to the 
edit code list for the Diagnoses for Females Only edit.
[GRAPHIC] [TIFF OMITTED] TR13AU21.135

    Comment: Commenters supported the proposal to add the ICD-10-CM 
diagnosis codes listed in the previous table to the Diagnoses for 
Females Only edit code list.
    Response: We appreciate the commenters' support.
    After consideration of the public comments we received, we are 
finalizing our proposal to add the diagnosis codes listed in the 
previous table to the Diagnoses for Females Only edit code list under 
the ICD-10 MCE Version 39, effective October 1, 2021.
d. Unacceptable Principal Diagnosis Edit
    In the MCE, there are select codes that describe a circumstance 
which influences an individual's health status but does not actually 
describe a current illness or injury. There also are codes that are not 
specific manifestations but may be due to an underlying cause. These 
codes are considered unacceptable as a principal diagnosis. In limited 
situations, there are a few codes on the MCE Unacceptable Principal 
Diagnosis edit code list that are considered ``acceptable'' when a 
specified secondary diagnosis is also coded and reported on the claim.
    As discussed in section II.D.13. of the preamble of the proposed 
rule and section II.D.13. of this final rule, Table 6A.--New Diagnosis 
Codes, lists the new diagnosis codes that have been approved to date 
which will be effective with discharges on and after October 1, 2021. 
We stated in the proposed rule that as a result of proposed new 
instructional notes to ``Code first underlying disease'' (which 
indicate the proper sequencing order of the codes) for existing 
diagnosis codes found at subcategory M40.1 (Other secondary kyphosis) 
and subcategory M41.5 (Other secondary scoliosis) discussed at the 
September 8-9, 2020 ICD-10 Coordination and Maintenance Committee 
meeting, we were proposing to add the following new and, if those 
instructional notes were finalized, existing ICD-10-CM diagnosis codes 
at subcategories M40.1 and M41.5, to the Unacceptable Principal 
Diagnosis edit code list.

[[Page 44938]]

[GRAPHIC] [TIFF OMITTED] TR13AU21.136


[[Page 44939]]


[GRAPHIC] [TIFF OMITTED] TR13AU21.137

    Comment: Many commenters supported our proposal to add the 
diagnosis codes listed in the previous table to the Unacceptable 
Principal Diagnosis edit code list.
    Response: We appreciate the commenters' support.
    Comment: A commenter expressed disagreement with the proposal to 
add the listed diagnosis codes from subcategories M40.1 and M41.5 to 
the unacceptable principal diagnosis code edit list if the ``code first 
underlying disease'' notes are finalized. The commenter acknowledged 
that physicians can reasonably diagnose acquired, new onset scoliosis 
and/or kyphosis as ``secondary'' to an underlying condition; however, 
the commenter stated diagnostic workup must occur (usually as an 
outpatient) before the exact cause(s) can be determined, such as 
degenerative disc disease, spondylosis, osteoporosis, pathologic 
fracture, failed fusion, etc. According to the commenter, when there 
are two or more potential causes, physicians may be unable to identify 
one specific cause versus multifactorial causes and the commenter 
stated their concern that when queried for the underlying cause(s), the 
physician may respond that they are unable to determine. The commenter 
added that when secondary scoliosis and/or kyphosis are responsible for 
causing surgical hospitalizations, the ability to sequence these 
conditions as a principal diagnosis should remain when the underlying 
cause(s) cannot be obtained.
    The commenter referenced language from the ICD-10-CM Official 
Guidelines for Coding and Reporting, with an emphasis on section 
I.A.13. Etiology/manifestation convention (``code first'', ``use 
additional code'' and ``in diseases classified elsewhere'' notes) which 
essentially states that ``Code first'' and ``Use additional code'' 
notes are also used as sequencing rules in the classification for 
certain codes that are not part of an etiology manifestation 
combination and section I.B.7. Multiple coding for a single condition, 
which states ``code first'' notes are also under certain codes that are 
not specifically manifestation codes but may be due to an underlying 
cause. When there is a ``code first'' note and an underlying condition 
is present, the underlying condition should be sequenced first, if 
known.
    Response: We appreciate the commenters' feedback. We note that we 
consulted with the staff at the Centers for Disease Control and 
Prevention's (CDC's) National Center for Health Statistics (NCHS) 
because NCHS has the lead responsibility for the ICD-10-CM diagnosis 
codes. The NCHS' staff confirmed that the intent is that the listed 
diagnosis codes from subcategories M40.1 and M41.5 be reported as 
secondary diagnoses. The staff agreed that in cases where it could be 
more than one condition as the underlying cause (E.g. Multifactorial), 
that the guideline for the principal diagnosis could be applied. 
Section 11. C. (Two or more diagnoses that equally meet the definition 
for principal diagnosis.) in the ICD-10-CM Official Guidelines for 
Coding and Reporting.
    After consideration of the public comments that we received, we are 
finalizing our proposal to add the diagnosis codes listed in the 
previous table to the Unacceptable Principal Diagnosis edit code list 
under the ICD-10 MCE Version 39, effective October 1, 2021.
    In addition, as discussed in section II.D.13. of the preamble of 
the proposed rule and section II.D.13. of this final rule, Table 6C.--
Invalid Diagnosis Codes, lists the diagnosis codes that are no longer 
effective October 1, 2021. Included in this table are the following 
ICD-10-CM diagnosis codes that are currently listed on the Unacceptable 
Principal Diagnosis edit code list. We proposed to delete these codes 
from the Unacceptable Principal Diagnosis edit code list.
[GRAPHIC] [TIFF OMITTED] TR13AU21.138

    Comment: Commenters agreed with our proposal to remove the codes 
listed in the previous table from the Unacceptable Principal Diagnosis 
edit code list since they are no longer valid effective October 1, 
2021.
    Response: We appreciate the commenters' support.
    After consideration of the public comments that we received, we are 
finalizing our proposal to remove the diagnosis codes previously listed 
from

[[Page 44940]]

the Unacceptable Principal Diagnosis edit code list under the ICD-10 
MCE Version 39, effective October 1, 2021.
e. Unspecified Codes
    As discussed in section II.D.12.c. of the preamble of the proposed 
rule and this final rule, we requested public comments on a potential 
change to the severity level designations for ``unspecified'' ICD-10-CM 
diagnosis codes that we were considering adopting for FY 2022. In 
connection with that request, we also requested public comments on the 
potential creation of a new MCE code edit involving these 
``unspecified'' codes for FY 2022. Specifically, this MCE code edit 
could trigger when an ``unspecified'' diagnosis code currently 
designated as either a CC or MCC, that includes other codes available 
in that code subcategory that further specify the anatomic site, is 
entered. We referred the reader to table 6P.3a associated with the 
proposed rule (which is available via the internet on the CMS website 
at: http://www.cms.hhs.gov/Medicare/Medicare-Fee-for-Service-Payment/AcuteInpatientPPS/index.html) for the list of unspecified diagnosis 
codes that would be subject to this edit. We stated that this edit 
could signal to the provider that a more specific code is available to 
report. We also stated we believed this edit aligns with documentation 
improvement efforts and leverages the specificity within ICD-10. As 
part of our request for comment on the potential creation of this new 
MCE code edit for these ``unspecified'' codes, we noted we were 
interested in comments on how this MCE code edit may be developed for 
FY 2022 to more accurately reflect each health care encounter and 
improve the reliability and validity of the coded data.
    Comment: Many commenters expressed support for the creation of a 
new ``unspecified'' code edit where other codes in the subcategory 
(family) exist describing laterality, however, the commenters stated 
that the edit should be phased in with a subset of the ``unspecified'' 
codes at a time. The commenters also stated this approach would help 
provide training time for coding professionals and clinical 
documentation program staff on the potential changes to the severity 
level for the unspecified codes. A commenter stated a phased approach 
could also better prepare teams to adapt to potential operational 
challenges in addressing these edits industry wide. Another commenter 
who expressed support stated they agreed with the list of codes, with 
the exception of the neoplasm codes.
    Another commenter expressed support for the creation of a new 
``unspecified'' code MCE edit to align with the potential change to the 
severity level designation of ``unspecified'' diagnosis codes to a 
NonCC when there are other codes available in that code subcategory 
that further specify the anatomic site.
    Other commenters stated they appreciated CMS assisting hospitals to 
more accurately code and not negatively impact MS-DRG group assignment, 
however according to the commenters, edits at the time of claim 
submission will add significant administrative burden to hospitals. 
According to the commenters, it would necessitate every case being 
routed from billing staff back to coding staff and then coding staff 
having to query physicians to amend the medical record with 
specificity. The commenters stated they did not object to CMS 
instructing providers to no longer report unspecified codes if it was 
done in concert with updates to the coding guidelines. Commenters 
suggested a delay in the implementation of the edit to allow the 
Cooperating Parties for ICD-10 time to update the current guidelines to 
include reporting specificity (for example laterality) based on non-
physician clinical staff documentation.
    Other commenters recommended that CMS conduct an analysis of how 
often the unspecified codes that were listed in Table 6P.2a in 
association with the proposed rule are reported and how many resources 
they consume.
    Response: In response to the recommendation that CMS implement the 
edit using a phased approach to allow time for staff to prepare for 
potential changes to the severity level for the unspecified codes, we 
do not believe that a phased approach is necessary. As discussed in 
section II.D.12.c. of the preamble of this final rule, we are not 
finalizing any changes to the severity level designations for the 
unspecified codes that were subject to the potential change and listed 
in Table 6P.2a in association with the proposed rule (available via the 
internet on the CMS website at: https://www.cms.gov/medicare/medicare-
fee-for-service-payment/acuteinpatientpps), at this time. As also 
discussed in section II.D.12.c. of the preamble of this final rule, in 
response to public comments, we removed the diagnosis codes describing 
neoplasm of an unspecified site from the list of codes that were being 
considered for possible adoption of a change to the severity level 
designation.
    In response to commenters' concerns that an edit for 
``unspecified'' codes would create an administrative burden to 
hospitals, as it may result in additional physician queries, we note 
that the intent of the edit is not to create the need for physician 
queries. In anticipation of such potential concerns and suggested 
updates to the coding guidelines, we note that, as one of the four 
Cooperating Parties for ICD-10, we considered these issues in advance 
and updated the guidelines accordingly, as shown in the FY 2022 ICD-10-
CM Official Guidelines for Coding and Reporting (available via the 
internet on the CMS website at: https://www.cms.gov/medicare/icd-10/2022-icd-10-cm) and discussed in section II.D.12.c. of the preamble of 
this final rule. Specifically, as stated in section I.B.13. of the 
guidelines, ``When laterality is not documented by the patient's 
provider, code assignment for the affected side may be based on medical 
record documentation from other clinicians. If there is conflicting 
medical record documentation regarding the affected side, the patient's 
attending provider should be queried for clarification. Codes for 
``unspecified'' side should rarely be used, such as when the 
documentation in the record is insufficient to determine the affected 
side and it is not possible to obtain clarification.'' Corresponding 
revisions to the guidelines can also be found in section I.B.14. 
Therefore, we believe that the updates made to the coding guidelines 
address that aspect of the commenters' concerns.
    With respect to the commenters' recommendation that CMS conduct an 
analysis of how often the unspecified codes that were listed in Table 
6P.2a are reported and how many resources they consume, we refer to the 
discussion in section II.D.12.c. of the preamble of this final rule, 
and note that Table 6P.2a associated with the proposed rule 
specifically provided this information.
    After consideration of the public comments received, we are 
finalizing the implementation of a new code edit for ``unspecified'' 
codes, where there are other codes available in that code subcategory 
that further specify the anatomic site. As noted previously, the 
severity level of the unspecified diagnosis codes is unaffected and 
therefore this edit does not affect the payment the provider is 
eligible to receive. We also note that, in consideration of commenters' 
concerns that more time is needed to educate providers, the 
implementation date for this new edit is April 1, 2022. As such, we are 
finalizing the new edit for FY 2022, effective with discharges on and 
after April 1, 2022. Stakeholders can anticipate future information 
regarding

[[Page 44941]]

an updated version of the ICD-10 Medicare Severity Diagnosis Related 
Group (MS-DRG) GROUPER Software and Medicare Code Editor (MCE) ICD-10 
Software to be released by February 1, 2022 via the internet on the CMS 
website at: https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/AcuteInpatientPPS/MS-DRG-Classifications-and-Software.
    We are finalizing a new ``Unspecified Code Edit: to read as 
follows:
20. Unspecified Code Edit
    Unspecified codes exist in the ICD-10-CM classification for 
circumstances when documentation in the medical record does not provide 
the level of detail needed to support reporting a more specific code. 
However, in the inpatient setting, there should generally be very 
limited and rare circumstances for which the laterality (right, left, 
bilateral) of a condition is unable to be documented and reported.
    The following pages contain the list of unspecified ICD-10-CM 
diagnosis codes for which there is a more specific code to identify 
laterality (right, left, bilateral) within that code family.''
    The list of codes subject to this edit are identified in Table 
6P.3a associated with this final rule. In addition to the removal of 
the neoplasm codes from the unspecified codes list discussed 
previously, we also removed the following codes from consideration in 
response to public comments and further internal review, as discussed 
previously in connection with the potential change to the severity 
level designation.
BILLING CODE 4120-01-P

[[Page 44942]]

[GRAPHIC] [TIFF OMITTED] TR13AU21.139

BILLING CODE 4120-01-C
    When a code from the list displayed in Table 6P.3a is entered on 
the claim, the edit will be triggered. It is the provider's 
responsibility to determine if a more specific code from that 
subcategory is available in the medical

[[Page 44943]]

record documentation by a clinical provider. If, upon review, 
additional information to identify the laterality from the available 
medical record documentation by any other clinical provider is unable 
to be obtained or there is documentation in the record that the 
physician is clinically unable to determine the laterality because of 
the nature of the disease/condition, then the provider must enter that 
information into the remarks section. Specifically, the provider may 
enter ``UNABLE TO DET LAT 1'' to identify that they are unable to 
obtain additional information to specify laterality or they may enter 
``UNABLE TO DET LAT 2'' to identify that the physician is clinically 
unable to determine laterality.'' This action and language will enable 
the Medicare Administrative Contractor (MAC) to bypass the edit and 
process the claim accordingly. If there is no language entered into the 
remarks section as to the availability of additional information to 
specify laterality and the provider submits the claim for processing, 
the claim would then be returned to the provider.
f. Future Enhancement
    In the FY 2018 IPPS/LTCH PPS final rule (82 FR 38053 through 38054) 
we noted the importance of ensuring accuracy of the coded data from the 
reporting, collection, processing, coverage, payment and analysis 
aspects. Subsequently, in the FY 2019 IPPS/LTCH PPS proposed rule (83 
FR 20235) we stated that we engaged a contractor to assist in the 
review of the limited coverage and non-covered procedure edits in the 
MCE that may also be present in other claims processing systems that 
are utilized by our MACs. The MACs must adhere to criteria specified 
within the National Coverage Determinations (NCDs) and may implement 
their own edits in addition to what is already incorporated into the 
MCE, resulting in duplicate edits. The objective of this review is to 
identify where duplicate edits may exist and to determine what the 
impact might be if these edits were to be removed from the MCE.
    We have also noted that the purpose of the MCE is to ensure that 
errors and inconsistencies in the coded data are recognized during 
Medicare claims processing. As we indicated in the FY 2019 IPPS/LTCH 
PPS final rule (83 FR 41228), we are considering whether the inclusion 
of coverage edits in the MCE necessarily aligns with that specific goal 
because the focus of coverage edits is on whether or not a particular 
service is covered for payment purposes and not whether it was coded 
correctly.
    As we continue to evaluate the purpose and function of the MCE with 
respect to ICD-10, we encourage public input for future discussion. As 
we have discussed in prior rulemaking, we recognize a need to further 
examine the current list of edits and the definitions of those edits. 
We continue to encourage public comments on whether there are 
additional concerns with the current edits, including specific edits or 
language that should be removed or revised, edits that should be 
combined, or new edits that should be added to assist in detecting 
errors or inaccuracies in the coded data. Comments should be directed 
to the MS-DRG Classification Change Mailbox located at 
[email protected] by November 1, 2021.
15. Changes to Surgical Hierarchies
    Some inpatient stays entail multiple surgical procedures, each one 
of which, occurring by itself, could result in assignment of the case 
to a different MS-DRG within the MDC to which the principal diagnosis 
is assigned. Therefore, it is necessary to have a decision rule within 
the GROUPER by which these cases are assigned to a single MS-DRG. The 
surgical hierarchy, an ordering of surgical classes from most resource-
intensive to least resource-intensive, performs that function. 
Application of this hierarchy ensures that cases involving multiple 
surgical procedures are assigned to the MS-DRG associated with the most 
resource-intensive surgical class.
    A surgical class can be composed of one or more MS-DRGs. For 
example, in MDC 11, the surgical class ``kidney transplant'' consists 
of a single MS-DRG (MS-DRG 652) and the class ``major bladder 
procedures'' consists of three MS-DRGs (MS-DRGs 653, 654, and 655). 
Consequently, in many cases, the surgical hierarchy has an impact on 
more than one MS-DRG. The methodology for determining the most 
resource-intensive surgical class involves weighting the average 
resources for each MS-DRG by frequency to determine the weighted 
average resources for each surgical class. For example, assume surgical 
class A includes MS-DRGs 001 and 002 and surgical class B includes MS-
DRGs 003, 004, and 005. Assume also that the average costs of MS-DRG 
001 are higher than that of MS-DRG 003, but the average costs of MS-
DRGs 004 and 005 are higher than the average costs of MS-DRG 002. To 
determine whether surgical class A should be higher or lower than 
surgical class B in the surgical hierarchy, we would weigh the average 
costs of each MS-DRG in the class by frequency (that is, by the number 
of cases in the MS-DRG) to determine average resource consumption for 
the surgical class. The surgical classes would then be ordered from the 
class with the highest average resource utilization to that with the 
lowest, with the exception of ``other O.R. procedures'' as discussed in 
this final rule.
    This methodology may occasionally result in assignment of a case 
involving multiple procedures to the lower-weighted MS-DRG (in the 
highest, most resource-intensive surgical class) of the available 
alternatives. However, given that the logic underlying the surgical 
hierarchy provides that the GROUPER search for the procedure in the 
most resource-intensive surgical class, in cases involving multiple 
procedures, this result is sometimes unavoidable.
    We note that, notwithstanding the foregoing discussion, there are a 
few instances when a surgical class with a lower average cost is 
ordered above a surgical class with a higher average cost. For example, 
the ``other O.R. procedures'' surgical class is uniformly ordered last 
in the surgical hierarchy of each MDC in which it occurs, regardless of 
the fact that the average costs for the MS-DRG or MS-DRGs in that 
surgical class may be higher than those for other surgical classes in 
the MDC. The ``other O.R. procedures'' class is a group of procedures 
that are only infrequently related to the diagnoses in the MDC, but are 
still occasionally performed on patients with cases assigned to the MDC 
with these diagnoses. Therefore, assignment to these surgical classes 
should only occur if no other surgical class more closely related to 
the diagnoses in the MDC is appropriate.
    A second example occurs when the difference between the average 
costs for two surgical classes is very small. We have found that small 
differences generally do not warrant reordering of the hierarchy 
because, as a result of reassigning cases on the basis of the hierarchy 
change, the average costs are likely to shift such that the higher-
ordered surgical class has lower average costs than the class ordered 
below it.
    As discussed in the FY 2022 IPPS/LTCH PPS proposed rule, we 
received a request to examine the MS-DRG hierarchy within MDC 05 
(Diseases and Disorders of the Circulatory System). The requestor 
stated its request to review the hierarchy within MDC 05 was based on 
the relative weights within each MS-DRG subdivision which they stated 
are supportive of higher position within the hierarchy. The requestor 
stated that when multiple procedures are performed, it is

[[Page 44944]]

reasonable for providers to be compensated for the highest weighted 
procedure. The requestor did not specify which data year it analyzed to 
identify the relative weights. As discussed in the proposed rule and 
previously in this section, in reviewing the surgical hierarchy, we 
weigh the average costs of each MS-DRG in the class by frequency (that 
is, by the number of cases in the MS-DRG), not the relative weights of 
each MS-DRG as suggested by the requestor, to determine average 
resource consumption for the surgical class; therefore, consistent with 
our annual process, we stated we used the methodology as described 
previously to review the surgical hierarchy within MDC 05.
    Based on our review of the surgical hierarchy within MDC 05 in 
response to this request, and in response to the request we received to 
review the MS-DRG assignments for cases involving the surgical ablation 
procedure for atrial fibrillation as discussed in section II.D.5.e. of 
the preamble of the proposed rule and this final rule, we proposed to 
revise the surgical hierarchy for the MS-DRGs in MDC 05 for FY 2022. 
Specifically, we proposed to sequence MS-DRGs 231-236 above MS-DRGs 
222-227 and below MS-DRGs 216-221, sequence MS-DRGs 222-227 above MS-
DRGs 266-227 and below MS-DRGs 231-236, sequence MS-DRGs 266-267 above 
MS-DRGs 268-269 and below MS-DRGs 222-227, sequence MS-DRGs 228-229 
above MS-DRGs 319-320 and below MS-DRGs 268-269.
    Our proposal for Appendix D MS-DRG Surgical Hierarchy by MDC and 
MS-DRG of the ICD-10 MS-DRG Definitions Manual Version 39 is 
illustrated in the following table.
[GRAPHIC] [TIFF OMITTED] TR13AU21.141

    Comment: Commenters supported our proposal. A commenter stated that 
this reordering of the surgical hierarchy appears reasonable. However, 
other commenters opposed portions of our proposal and requested that 
CMS reconsider and maintain MS-DRGs 222-227 (Cardiac Defibrillator 
Implant) as higher in the surgical hierarchy than MS-DRGs 231-236 
(Coronary Bypass). These commenters stated that if CABG procedures are 
considered in the surgical hierarchy before procedures to insert a 
cardiac defibrillator implant, the majority of the cases would probably 
be assigned to MS-DRGs 235 and 236 (Coronary Bypass without Cardiac 
Catheterization with and without MCC, respectively), which would not 
account for the higher cost of the defibrillators.
    Another commenter stated while they agreed with the proposal to 
sequence MS-DRGs 231-236 above MS-DRGs 228 and 229 (Other 
Cardiothoracic Procedures), they stated that CMS did not provide 
specific discussion regarding the more extensive re-sequencing in MDC 
05 and suggested that CMS to hold on these revisions to the surgical 
hierarchy pending a clear and specific rationale for each, to which the 
public can respond. Another commenter proposed an alternative option by 
stating that it seemed more appropriate to sequence MS-DRG 245 (AICD 
Generator Procedures) above MS-DRGs 270--272 (Other Major 
Cardiovascular Procedures) and below MS-DRGs 228-229 (Other 
Cardiothoracic Procedures) and to sequence MS-DRGs 270-272 above MS-
DRGs 319-320 (Other Endovascular Cardiac Valve Procedures) and below 
MS-DRG 245. However, this commenter did not provide any rationale for 
their alternative option.
    Response: We appreciate the commenters' support.
    In response to the comment that CMS did not provide specific 
discussion, we note that we indicated in the proposed rule and 
previously in this section, that in reviewing the surgical hierarchy, 
we weigh the average costs of each MS-DRG in the class by frequency 
(that is, by the number of cases in the MS-DRG) to determine average 
resource consumption for the surgical class. Consistent with our annual 
process, we stated we used the methodology as described previously to 
review the surgical hierarchy within MDC 05.
    To compare and analyze the impact of our suggested modifications in 
response to the commenter's suggestion that we sequence MS-DRGs 222-227 
above MS-DRGs 231-236, we reviewed the surgical hierarchy once again. 
Specifically, we examined the redistribution of cases that is 
anticipated to occur as a result of the proposal to move MS-DRGs 231-
236 (Coronary Bypass) above MS-DRGs 222-227 (Cardiac Defibrillator 
Implant) in the surgical hierarchy of MDC 05 for Version 39 of the ICD-
10 MS-DRGs. We processed the claims data from the March 2020 update of 
the FY 2019 MedPAR file through the ICD-10 MS-DRG GROUPER Version 38 
and then processed the same claims data through the ICD-10 MS-DRG 
GROUPER Version 39 for comparison. The number of cases from this 
comparison that result in different MS-DRG assignments is the number of 
the cases that are anticipated to potentially shift or be 
redistributed. Our findings are shown in the following table.
BILLING CODE 4120-01-P

[[Page 44945]]

[GRAPHIC] [TIFF OMITTED] TR13AU21.142

BILLING CODE 4120-01-C
    We found that a small number of cases, 67 cases and 24 cases, are 
anticipated to potentially shift or be

[[Page 44946]]

redistributed into MS-DRGs 235 and 236, respectively.
    As we did with March 2020 update of the FY 2019 MedPAR file, we 
then examined the redistribution of cases that is anticipated to occur 
by processing the claims data, this time from the September 2020 update 
of the FY 2020 MedPAR file through the ICD-10 MS-DRG GROUPER Version 38 
and then processed the same claims data through the ICD-10 MS-DRG 
GROUPER Version 39 for comparison. Our findings are shown in the 
following table.
BILLING CODE 4120-01-P
[GRAPHIC] [TIFF OMITTED] TR13AU21.144


[[Page 44947]]


[GRAPHIC] [TIFF OMITTED] TR13AU21.145

BILLING CODE 4120-01-C
    Similarly, we found that a small number of cases, 84 cases and 23 
cases, are anticipated to potentially shift or be redistributed into 
MS-DRGs 235 and 236, respectively.
    Our clinical advisors reviewed these data and the commenter's 
concerns and state, as in open concomitant surgical ablation 
procedures, when a CABG procedure is performed along with the insertion 
of a cardiac defibrillator implant, the CABG component of the procedure 
is more technically complex than the procedure to insert the cardiac 
defibrillator implant. The redistribution of the small number of cases 
to MS-DRGs 235 and 236 as a result of the proposed hierarchy change 
more appropriately reflects resource utilization when multiple cardiac 
procedures are performed and will result in the most suitable MS-DRG 
assignment.
    In the absence of a compelling rationale to further modify our 
proposal as suggested by the alternate option provided by the 
commenter, our clinical advisors continue to state that the proposed 
revision to the surgical hierarchy leads to a grouping that is more 
coherent and better accounts for the resources expended to address the 
more complex procedures from other cases redistributed during the 
hierarchy change.

    Therefore, after consideration of the public comments we received, 
we are finalizing the proposed changes to the surgical hierarchy for 
the MS-DRGs in MDC 05 as illustrated in the table for the surgical 
hierarchy within Appendix D MS-DRG Surgical Hierarchy by MDC and MS-DRG 
of the ICD-10 MS-DRG Definitions Manual Version 39, without 
modification, for FY 2022.
16. Maintenance of the ICD-10-CM and ICD-10-PCS Coding Systems
    In September 1985, the ICD-9-CM Coordination and Maintenance 
Committee was formed. This is a Federal interdepartmental committee, 
co-chaired by the Centers for Disease Control and Prevention's (CDC) 
National Center for Health Statistics (NCHS) and CMS, charged with 
maintaining and updating the ICD-9-CM system. The final update to ICD-
9-CM codes was made on October 1, 2013. Thereafter, the name of the 
Committee was changed to the ICD-10 Coordination and Maintenance 
Committee, effective with the March 19-20, 2014 meeting. The ICD-10 
Coordination and Maintenance Committee addresses updates to the ICD-10-
CM and ICD-10-PCS coding systems. The Committee is jointly responsible 
for approving coding changes, and developing errata, addenda, and other 
modifications to the coding systems to reflect newly developed 
procedures and technologies and newly identified diseases. The 
Committee is also responsible for promoting the use of Federal and non-
Federal educational programs and other communication techniques with a 
view toward standardizing coding applications and upgrading the quality 
of the classification system.
    The official list of ICD-9-CM diagnosis and procedure codes by 
fiscal year can be found on the CMS website at: https://www.cms.gov/Medicare/Coding/ICD9ProviderDiagnosticCodes/codes. The official list of 
ICD-10-CM and ICD-10-PCS codes can be found on the CMS website at: 
http://www.cms.gov/Medicare/Coding/ICD10/index.html.
    The NCHS has lead responsibility for the ICD-10-CM and ICD-9-CM 
diagnosis codes included in the Tabular List and Alphabetic Index for 
Diseases, while CMS has lead responsibility for the ICD-10-PCS and ICD-
9-CM procedure codes included in the Tabular List and Alphabetic Index 
for Procedures.
    The Committee encourages participation in the previously stated 
process by health-related organizations. In this regard, the Committee 
holds public meetings for discussion of educational issues and proposed 
coding changes. These meetings provide an opportunity for 
representatives of

[[Page 44948]]

recognized organizations in the coding field, such as the American 
Health Information Management Association (AHIMA), the American 
Hospital Association (AHA), and various physician specialty groups, as 
well as individual physicians, health information management 
professionals, and other members of the public, to contribute ideas on 
coding matters. After considering the opinions expressed during the 
public meetings and in writing, the Committee formulates 
recommendations, which then must be approved by the agencies.
    The Committee presented proposals for coding changes for 
implementation in FY 2022 at a public meeting held on September 8-9, 
2020 and finalized the coding changes after consideration of comments 
received at the meetings and in writing by November 09, 2020.
    The Committee held its 2021 meeting on March 9-10, 2021. The 
deadline for submitting comments on the code proposals being considered 
for an October 1, 2021 implementation was April 9, 2021. It was 
announced at this meeting that any new diagnosis and procedure codes 
for which there was consensus of public support and for which complete 
tabular and indexing changes would be made by June 2021 would be 
included in the October 1, 2021 update to the ICD-10-CM diagnosis and 
ICD-10-PCS procedure code sets. As discussed in earlier sections of the 
preamble of this final rule, there are new, revised, and deleted ICD-
10-CM diagnosis codes and ICD-10-PCS procedure codes that are captured 
in Table 6A--New Diagnosis Codes, Table 6B--New Procedure Codes, Table 
6C--Invalid Diagnosis Codes, Table 6D--Invalid Procedure Codes, Table 
6E--Revised Diagnosis Code Titles and Table 6F--Revised Procedure Code 
Titles for this final rule, which are available via the internet on the 
CMS website at: http://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/AcuteInpatientPPS/index.html. The code titles are adopted as 
part of the ICD-10 (previously ICD-9-CM) Coordination and Maintenance 
Committee process. Therefore, although we make the code titles 
available for the IPPS proposed and final rules, they are not subject 
to comment in the proposed or final rule. Because of the length of 
these tables, they are not published in the Addendum to the proposed or 
final rule. Rather, they are available via the internet as discussed in 
section VI. of the Addendum to the proposed rule and this final rule.
    Recordings for the virtual meeting discussions of the procedure 
codes at the Committee's September 8-9, 2020 meeting and the March 9-
10, 2021 meeting can be obtained from the CMS website at: https://www.cms.gov/Medicare/Coding/ICD10/C-and-M-Meeting-Materials. The 
materials for the discussions relating to diagnosis codes at the 
September 8-9, 2020 meeting and March 9-10, 2021 meeting can be found 
at: http://www.cdc.gov/nchs/icd/icd10cm_maintenance.html. These 
websites also provide detailed information about the Committee, 
including information on requesting a new code, participating in a 
Committee meeting, timeline requirements and meeting dates.
    We encourage commenters to submit questions and comments on coding 
issues involving diagnosis codes via Email to: cdc.gov">nchsicd10cm@cdc.gov.
    Questions and comments concerning the procedure codes should be 
submitted via Email to: [email protected].
    We stated in the proposed rule that as a result of the ongoing 
COVID-19 public health emergency, the CDC implemented six new diagnosis 
codes describing conditions related to COVID-19 into the ICD-10-CM 
effective with discharges on and after January 1, 2021. The diagnosis 
codes are
[GRAPHIC] [TIFF OMITTED] TR13AU21.146

    We refer the reader to the CDC web page at https://www.cdc.gov/nchs/icd/icd10cm.htm for additional details regarding the 
implementation of these new diagnosis codes.
    As we discussed in the proposed rule, we provided the MS-DRG 
assignments for the six diagnosis codes effective with discharges on 
and after January 1, 2021, consistent with our established process for 
assigning new diagnosis codes. Specifically, we review the predecessor 
diagnosis code and MS-DRG assignment most closely associated with the 
new diagnosis code, and consider other factors that may be relevant to 
the MS-DRG assignment, including the severity of illness, treatment 
difficulty, and the resources utilized for the specific condition/
diagnosis. We note that this process does not automatically result in 
the new diagnosis code being assigned to the same MS-DRG as the 
predecessor code. The assignments for the previously listed diagnosis 
codes are reflected in Table 6A--New Diagnosis Codes associated with 
the proposed rule (which is available via the internet on the CMS 
website at https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/AcuteInpatientPPS). As with the other new diagnosis codes and 
MS-DRG assignments included in Table 6A of the proposed rule, we 
solicited public comments on the most appropriate MDC, MS-DRG, and 
severity level assignments for these codes for FY 2022, as well as any 
other options for the GROUPER logic.
    We did not receive any comments opposing the MDC, MS-DRG, and 
severity level assignments for the listed codes and are therefore, 
finalizing the assignments as reflected in Table 6A--New Diagnosis 
Codes in association with this final rule.
    In addition, we noted in the proposed rule that CMS implemented 21 
new procedure codes describing the introduction or infusion of 
therapeutics, including monoclonal antibodies and vaccines for COVID-19 
treatment, into the ICD-10-PCS effective with

[[Page 44949]]

discharges on and after January 01, 2021. The 21 procedure codes listed 
in this section of this rule are designated as non-O.R. and do not 
affect any MDC or MS-DRG assignment as shown in the following table.
BILLING CODE 4120-01-P
[GRAPHIC] [TIFF OMITTED] TR13AU21.147


[[Page 44950]]


BILLING CODE 4120-01-C
    The ICD-10 MS-DRG assignment for cases reporting any one of the 21 
procedure codes is dependent on the reported principal diagnosis, any 
secondary diagnoses defined as a CC or MCC, procedures or services 
performed, age, sex, and discharge status. The 21 procedure codes are 
reflected in Table 6B--New Procedure Codes associated with the proposed 
rule (which is available via the internet on the CMS website at https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/AcuteInpatientPPS.) As with the other new procedure codes and MS-DRG 
assignments included in Table 6B of the proposed rule, we solicited 
public comments on the most appropriate MDC, MS-DRG, and operating room 
status assignments for these codes for FY 2022, as well as any other 
options for the GROUPER logic.
    We did not receive any comments opposing the MDC, MS-DRG, and 
operating room status assignments for the listed codes and are 
therefore, finalizing the assignments as reflected in Table 6B--New 
Procedure Codes in association with this final rule.
    In the proposed rule we also noted that Change Request (CR) 11895, 
Transmittal 10654, titled ``Fiscal Year (FY) 2021 Annual Update to the 
Medicare Code Editor (MCE) and International Classification of 
Diseases, Tenth Revision, Clinical Modification (ICD-10-CM) and 
Procedure Coding System (ICD-10-PCS)'', was issued on March 12, 2021 
(available via the internet on the CMS website at: https://www.cms.gov/Regulations-and-Guidance/Guidance/Transmittals/Transmittals/r10654cp) 
regarding the release of an updated version of the ICD-10 MS-DRG 
GROUPER and Medicare Code Editor software, Version 38.1, effective with 
discharges on and after January 1, 2021, reflecting the new diagnosis 
and procedure codes. The updated software, along with the updated ICD-
10 MS-DRG V38.1 Definitions Manual and the Definitions of Medicare Code 
Edits V38.1 manual is available at https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/AcuteInpatientPPS/MS-DRG-Classifications-and-Software.
    In the September 7, 2001 final rule implementing the IPPS new 
technology add-on payments (66 FR 46906), we indicated we would attempt 
to include proposals for procedure codes that would describe new 
technology discussed and approved at the Spring meeting as part of the 
code revisions effective the following October.
    Section 503(a) of Public Law 108-173 included a requirement for 
updating diagnosis and procedure codes twice a year instead of a single 
update on October 1 of each year. This requirement was included as part 
of the amendments to the Act relating to recognition of new technology 
under the IPPS. Section 503(a) of Public Law 108-173 amended section 
1886(d)(5)(K) of the Act by adding a clause (vii) which states that the 
Secretary shall provide for the addition of new diagnosis and procedure 
codes on April 1 of each year, but the addition of such codes shall not 
require the Secretary to adjust the payment (or diagnosis-related group 
classification) until the fiscal year that begins after such date. This 
requirement improves the recognition of new technologies under the IPPS 
by providing information on these new technologies at an earlier date. 
Data will be available 6 months earlier than would be possible with 
updates occurring only once a year on October 1.
    While section 1886(d)(5)(K)(vii) of the Act states that the 
addition of new diagnosis and procedure codes on April 1 of each year 
shall not require the Secretary to adjust the payment, or DRG 
classification, under section 1886(d) of the Act until the fiscal year 
that begins after such date, we have to update the DRG software and 
other systems in order to recognize and accept the new codes. We also 
publicize the code changes and the need for a mid-year systems update 
by providers to identify the new codes. Hospitals also have to obtain 
the new code books and encoder updates, and make other system changes 
in order to identify and report the new codes.
    The ICD-10 (previously the ICD-9-CM) Coordination and Maintenance 
Committee holds its meetings in the spring and fall in order to update 
the codes and the applicable payment and reporting systems by October 1 
of each year. Items are placed on the agenda for the Committee meeting 
if the request is received at least 3 months prior to the meeting. This 
requirement allows time for staff to review and research the coding 
issues and prepare material for discussion at the meeting. It also 
allows time for the topic to be publicized in meeting announcements in 
the Federal Register as well as on the CMS website. A complete addendum 
describing details of all diagnosis and procedure coding changes, both 
tabular and index, is published on the CMS and NCHS websites in June of 
each year. Publishers of coding books and software use this information 
to modify their products that are used by health care providers. 
Historically, this 5-month time period has proved to be necessary for 
hospitals and other providers to update their systems.
    A discussion of this timeline and the need for changes are included 
in the December 4-5, 2005 ICD-9-CM Coordination and Maintenance 
Committee Meeting minutes. The public agreed that there was a need to 
hold the fall meetings earlier, in September or October, in order to 
meet the new implementation dates. The public provided comment that 
additional time would be needed to update hospital systems and obtain 
new code books and coding software. There was considerable concern 
expressed about the impact this April update would have on providers.
    In the FY 2005 IPPS final rule, we implemented section 
1886(d)(5)(K)(vii) of the Act, as added by section 503(a) of Pub. L. 
108-173, by developing a mechanism for approving, in time for the April 
update, diagnosis and procedure code revisions needed to describe new 
technologies and medical services for purposes of the new technology 
add-on payment process. We also established the following process for 
making these determinations. Topics considered during the Fall ICD-10 
(previously ICD-9-CM) Coordination and Maintenance Committee meeting 
are considered for an April 1 update if a strong and convincing case is 
made by the requestor during the Committee's public meeting. The 
request must identify the reason why a new code is needed in April for 
purposes of the new technology process. Meeting participants and those 
reviewing the Committee meeting materials are provided the opportunity 
to comment on this expedited request. All other topics are considered 
for the October 1 update. Participants of the Committee meeting and 
those reviewing the Committee meeting materials are encouraged to 
comment on all such requests. There were no code requests approved for 
an expedited April 1, 2021 implementation at the September 8-9, 2020 
Committee meetings. Therefore, there were no new codes implemented 
April 1, 2021.
    We noted in the proposed rule that during the March 9-10, 2021 ICD-
10 Coordination and Maintenance Committee meeting we announced our 
consideration of an April 1 implementation date for ICD-10-CM diagnosis 
and ICD-10-PCS procedure code updates, in addition to the current 
October 1 annual update for ICD-10-CM diagnosis codes and ICD-10-PCS 
procedure codes. We stated that this April 1 code update would be in 
addition to the existing April 1 update under section 
1886(d)(5)(k)(vii) of the Act for diagnosis or procedure code

[[Page 44951]]

revisions needed to describe new technologies and medical services for 
purposes of the new technology add-on payment process. As explained 
during the March 9-10, 2021 meeting, we stated we believe this 
additional April 1 implementation date for new codes would allow for 
earlier recognition of diagnoses, conditions, and illnesses as well as 
procedures, services, and treatments in the claims data. We also stated 
we believe this earlier recognition would be beneficial for purposes of 
reporting, data collection, tracking clinical outcomes, claims 
processing, surveillance, research, policy decisions and data 
interoperability. We noted, as previously summarized, that in 2005, in 
connection with the implementation of the current April 1 update for 
diagnosis or procedure code revisions for purposes of the new 
technology add-on payment process, stakeholders expressed concerns with 
an April 1 update, specifically with regard to the time needed to 
update hospital systems and obtain new code books and coding software. 
We further stated we believe that the advances in technology that have 
occurred since that time, including the use of electronic health 
records (EHRs), electronic coding books, and updated encoder software 
that are now utilized by the majority of providers, would alleviate 
those concerns and make a broader April 1 update more feasible today. 
Consistent with our established process for the existing April 1 update 
under section 1886(d)(5)(k)(vii) of the Act, if adopted, any new ICD-10 
code updates finalized for implementation on the following April 1 
would be announced in November of the prior year, which would provide a 
4-month timeframe for the public to receive notice about the diagnosis 
and/or procedure code updates with respect to the codes, code 
descriptions, code designations (severity level for diagnosis codes or 
O.R. status for procedure codes) and code assignment under the ICD-10 
MS-DRGs. As discussed during the March 9-10, 2021 meeting, all April 1 
code update files would be made publicly available by February 1, 
providing a 2-month timeframe for providers to incorporate systems 
updates. We also noted in the proposed rule that we do not anticipate 
any need for code book publishers to issue new code books as a result 
of an April 1 code update, if adopted. Rather, as was done in the past 
at the publisher's discretion, supplemental pages containing the code 
update information were made available and sent to purchasers of the 
code book products. We further noted that historically, coders would 
hand-write any updates or notes directly into their code books. In 
addition, we stated in the proposed rule that with the availability of 
electronic code book files, we would anticipate any April 1 code 
updates, if adopted, could be reasonably completed in the allotted 
timeframe. For these same reasons, we also stated we do not believe a 
5-month time period would continue to be needed to update providers' 
systems to reflect newly approved coding changes. We further noted that 
if an April 1 update were to be adopted, it could be through a phased 
approach, such that initially, the number and nature of the code 
updates would be fewer and less comprehensive as compared to the 
existing October 1 update. For example, it was discussed during the 
meeting that consideration could first be given to proposals identified 
as ``Addenda''. For diagnosis codes, the proposed addenda update 
typically consist primarily of minor revisions to the Index and Tabular 
List, such as corrections to typos and changes to instructional notes. 
For procedure codes, the proposed addenda update typically consist 
primarily of minor revisions to the Index and Tables, such as adding or 
deleting entries to describe a body part or approach value or making 
changes to the Substance and Device Keys. We stated we would use our 
established process to implement an April 1 code update, which would 
include presenting proposals for April 1 consideration at the September 
ICD-10 Coordination and Maintenance Committee meeting, requesting 
public comments, reviewing the public comments, finalizing codes, and 
announcing the new codes with their assignments consistent with the new 
GROUPER release information. We also stated that under our contemplated 
process, requestors would indicate whether they are submitting their 
code request for consideration for an April 1 implementation date, if 
adopted, or an October 1 implementation date. We further stated that 
the ICD-10 Coordination and Maintenance Committee would make efforts to 
accommodate the requested implementation date for each request 
submitted. However, the Committee would determine which requests would 
be presented for consideration for an April 1 implementation date or an 
October 1 implementation date. We refer the reader to the Agenda packet 
from the meeting at: https://www.cms.gov/Medicare/Coding/ICD10/C-and-M-Meeting-Materials for additional information regarding this 
announcement and our request for comments.
    We stated that if this new April 1 implementation date is adopted, 
we would assign the codes approved for the April 1 update to an MS-
DRG(s) using our established process for GROUPER assignments for new 
diagnosis and procedure codes. Specifically, consistent with our 
established process for assigning new diagnosis and procedure codes, we 
would review the predecessor code and MS-DRG assignment most closely 
associated with the new diagnosis or procedure code, and in the absence 
of claims data, we would consider other factors that may be relevant to 
the MS-DRG assignment, including the severity of illness, treatment 
difficulty, complexity of service and the resources utilized in the 
diagnosis and/or treatment of the condition. We noted that this process 
would not automatically result in the new diagnosis or procedure code 
being assigned to the same MS-DRG or having the same designation as the 
predecessor code.
    Comment: Several commenters expressed support for an April 1 
update, in addition to the October 1 annual update. The commenters 
encouraged the CDC/NCHS and CMS to develop policies that expedite the 
assignment of new diagnosis and procedure codes to meet the needs of 
clinical advancements. Other commenters commended CMS for its ongoing 
efforts to improve the timeliness of coding and payment decisions for 
new technologies, and expressed their support for an April 1 update as 
a key piece of those efforts. Some commenters stated that more timely 
coding updates will allow CMS additional time to analyze how therapies 
are utilized in the inpatient setting and will improve the completeness 
of claims data capture that includes volume, length of stay, and cost 
data that should lead to better informed rate-setting methodologies. 
According to the commenters, expedited coding could potentially reduce 
the amount of time required to stabilize payments to hospitals for 
utilizing first-in-class therapies. Many commenters agreed that an 
additional update for ICD-10 codes would allow for earlier recognition 
of diagnoses, conditions, and illnesses as well as procedures, 
services, and treatments in the claims data. A commenter stated they 
strongly support the timely and specific data capture of ICD-10-CM and 
ICD-10-PCS codes for the purposes of tracking rare diseases, research, 
tracking of social determinants of health (SDOH), advancing medicine 
through quality data, and for public health. This

[[Page 44952]]

commenter stated that processes are already in place for code updates 
in October and this new proposed update, if adopted, would not be a 
departure from that process, but would yield more timely implementation 
of important codes. According to the commenter, this would lessen the 
burden of putting all updates into one annual update in October. 
Another commenter emphasized that the availability of an April 1 
process for updating and implementing new technology related ICD-10-CM 
and ICD-10-PCS codes is especially important for encouraging access to 
transformative therapies, including novel cell and gene therapies-such 
as TIL therapies and chimeric antigen receptor (CAR) T-cell therapies. 
According to the commenter, these new technologies target some of the 
most serious medical conditions imaginable, offer treatment that is 
highly personalized to each individual patient, and carry vast 
transformational potential in terms of patient care and clinical 
outcomes. The commenter stated that to the extent CMS and CDC/NCHS are 
considering a phased-in implementation of the April 1 code 
implementation as the agencies suggested during the March 9-10, 2021 
ICD-10 Coordination and Maintenance Committee meeting, the commenter 
strongly urged the agencies to ensure that if adopted, the initial 
implementation permit new technology codes related to novel cell and 
gene therapies to be implemented effective April 1, as well as October 
1. The commenter asserted that these types of therapies are limited in 
number and there is a profound and unique need for the prompt 
availability of such therapies in order to encourage more timely 
beneficiary access to these potentially lifesaving new therapies.
    Another commenter expressed its support for the approach to 
integrating the potential April 1 implementation of new codes into the 
IPPS based on the MS-DRG policies in effect under the established 
process. According to the commenter, if adopted, this April 1 
implementation option could offer several specific advantages for MS-
DRG assignment for technologies receiving market approval too late to 
have coding and payment in place on October 1, particularly related to 
applications for new technology add-on payments. The commenter stated 
their belief that it also maintains the current public notice and 
comment rulemaking process for proposing, considering, and implementing 
decisions affecting MS-DRG assignments, with the additional flexibility 
to establish policies in anticipation of codes implemented on April 1. 
This commenter stated that its support for an April 1 implementation 
presumes that conditional decisions are established through prior 
notice and comment rulemaking.
    In response to the request for feedback on what criteria or factors 
should be taken into consideration for determining whether to consider 
a code request for an April 1 or October 1 implementation date, some 
commenters stated CMS should consider expedited access. Specifically, 
according to the commenters, CMS should work with manufacturers to 
identify an implementation date that most closely aligns with approval 
by the Food and Drug Administration as the implementation date of the 
new procedure code and consideration for a new technology add-on 
payment (NTAP) as well. By doing so, the commenters indicated CMS will 
take steps to align the IPPS and provider reimbursement with the pace 
of innovation. The commenters also stated CMS should consider new codes 
that are related to new therapies that will be up for regulatory 
approval, or for diagnoses that are new and important to public health 
(such as those from the COVID-19 PHE). The commenters stated it is 
better to have coding in place before, and certainly as soon as, a 
product is approved, and sooner rather than later when an emerging 
public health issue is identified. A commenter suggested that if a 
sponsor anticipates receiving approval from the Food and Drug 
Administration in the third quarter of the year, the ICD-10 code update 
could occur in April. Similarly, if an approval is anticipated in the 
first quarter, then the ICD-10 code update could occur October 1. 
According to the commenter, the Committee should strive to make data 
collection as accurate and timely as possible.
    Other commenters recommended that the Committee should consider the 
goal of facilitating and promoting patient access and well-being. These 
commenters stated the Committee should prioritize updates for which 
significant public feedback and corresponding medical literature 
indicate a pronounced need for expedited implementation to further 
understanding of particular conditions and advance clinical research on 
potential treatment options.
    A few commenters stated that although the coding changes associated 
with COVID-19 under the PHE have demonstrated it is possible to 
implement more frequent coding updates that are limited in number, 
significant adjustments were needed to incorporate the updates and 
resulted in operational issues for hospitals. These commenters 
suggested that CMS consider limiting the number of codes approved with 
respect to adoption of an April 1 implementation date for ICD-10-CM 
diagnosis and ICD-10-PCS procedure code updates, in addition to the 
current October 1 annual update. In addition to limited updates, other 
commenters specifically recommended that if adopted, April 1 code 
updates should be restricted to simple, straightforward changes, such 
as the Addenda proposals involving proposed updates to the Alphabetic 
Index and Tabular List of Diseases and the correction of errors. The 
commenters stated that clear and consistent criteria should be applied 
to determine the need for new codes such as consideration of a new or 
emerging disease/illness/condition, an innovative technology that is 
unable to be reported with existing codes, or codes related to 
proposals that have been presented at the Coordination and Maintenance 
Committee meetings more than one time as a repeat proposal due to 
public comments and feedback.
    Another commenter stated that consideration of an April 1 
implementation should include a public process, similar to HCPCS and 
rulemaking, that allows stakeholders to weigh in on both procedure code 
creation and MS-DRG assignment and provides stakeholders with CMS 
reasoning behind its decisions.
    With respect to the request for feedback on how an April 1 
implementation date may affect business processes, a few commenters 
stated their belief that, initially, there may be some increased work 
to ensure that the April 1 codes released (and the MS-DRG grouping 
assignments) are up to date in their systems. The commenters stated 
this effort would include checking with software vendors to ensure that 
they are also updating their software for the new codes and groupings. 
A commenter stated that the benefits of adding the new release cycle, 
however, will be well worth the time and resource investment at the 
beginning. According to the commenter, having codes released in a 
timely manner so that data can be collected sooner rather than later 
will give insights that could lead to a reduction in burden elsewhere. 
The commenter stated that modernization to existing codes so they match 
current physician documentation terminology and practices will also 
reduce coders' work downstream over time.
    A commenter stated that the addition of another cycle will enable 
ICD-10-CM diagnosis codes to be released in a more

[[Page 44953]]

timely manner to reflect new diseases or conditions and facilitate 
clinical research, as well as data collection, all of which would 
ultimately improve patient care. This commenter stated the adoption of 
an April 1 implementation is particularly important for diagnosis 
codes, since proposals discussed at the March meetings generally do not 
go into effect until October 1 of the following year, resulting in an 
18-month delay. According to the commenter, more timely releases of 
diagnosis codes would be crucial in the area of advanced cell therapy 
research, as it would facilitate better identification and tracking for 
this distinct subset of patients, which can advance clinical 
understanding and subsequently improve diagnostic and treatment 
standards.
    Some commenters who supported an April 1 implementation date also 
expressed concerns with having twice a year code updates. Specifically, 
commenters noted concerns with payor/vendor updates being incorporated 
timely, training and education, and the ability to comment on MS-DRG 
assignments. The commenters also requested additional clarity and 
transparency on how the agencies intend to communicate timelines and 
decisions on which coding requests would be considered for April 1 
versus October 1 during the ICD-10 Coordination and Maintenance 
Committee meetings.
    A few commenters opposed consideration of the April 1 
implementation date in addition to the October 1 annual update, for 
similar reasons described previously, as to how it may affect business 
processes. A commenter stated it will be a work intensive process in 
terms of systems updates, training time, and data comparison. A few 
commenters indicated they did not support an April 1 implementation and 
corresponding updated Grouper release without a comment period. A 
commenter stated the current GROUPER allows for a comment period prior 
to implementation in October (of the new GROUPER) and it is important 
to recognize that revisions may be made from the proposed and final 
GROUPER considerations especially for new codes. The commenter provided 
the example that for FY 2021 rulemaking, the comment period was 
important to allow CMS to consider provider feedback on the proposed 
MCC/CC designations for new ICD-10-CM diagnosis codes which also 
provided specificity for the grades of Cytokine Release Syndrome which 
were all proposed to be NonCC severity level. The commenter stated that 
after review of the comments, the diagnosis codes for Grades 3, 4, 5 
(D89.833, D89.834, D89.835) were revised and finalized by CMS to a CC 
Severity Level. This commenter also stated that the ICD-10-CM and ICD-
10-PCS code sets are not limited to the use of CMS providers as all 
providers utilize the ICD-10 codes and may not be able to turn around 
code updates as quickly as CMS. The commenter further stated that the 
code set is used to update computer systems, contracts, reimbursement 
systems and is not limited to MS-DRGs only. A few commenters expressed 
concern with operational challenges and stated that there are providers 
and commercial payors that currently do not incorporate the annual 
update timely, so it is important for systems to be able to adapt to 
the version of the code set in place for the provider. The commenters 
stated a second release date in April would result in addressing payor 
non-compliance twice a year. Other commenters who opposed adoption of 
an April 1 implementation date for code updates stated it would be 
costly for providers, payors, insurance companies and all healthcare 
organizations as it would involve purchase of code books, code tables, 
encoder updates and other related materials twice per year rather than 
once per year.
    A commenter who opposed the potential adoption of an April 1 code 
update submitted the following questions or statements about the 
process.
    1. What is the process and/or criteria that will be used in 
identifying which codes will be implemented in April versus October? Is 
it solely based on the date the submitter requested?
    2. Will both April and October proposed codes be covered in the 
ICD-10 Coordination and Maintenance Committee meetings?
    3. Right now, 99% of the codes proposed in March are not for the 
upcoming October 1 release but the following October 1 release (two 
years away). Will adding an April update increase the turnaround time 
for implementing a new code, that is, reducing it to a 1-year proposal 
to implementation versus a 2-year proposal to implementation?
    4. What will be the effective dates of the codes and guidelines 
added in April? Will this alter the effective dates of the October 
codes and guidelines?
Example:
April codes/guidelines--effective April 1, 2022 to September 30, 2022
October codes/guidelines--effective October 1, 2022 to March 31, 2023
OR
April codes/guidelines--effective April 1, 2022 to March 31, 2023
October codes/guidelines--effective October 1, 2022 to September 30, 
2023
    5. Can you provide examples of codes that would require immediate 
implementation, outside of a public health emergency? For 2020, there 
were at least three separate code updates outside the April and October 
``regular'' dates. If it is essential that a code be added to the 
classification, can this just occur on an as-needed basis, that is, due 
to public health emergency or pandemic situations, instead of having 
two regulatory updates?
    According to the commenter, although many were able to adjust to 
the changes that happened through 2020, a PHE presents very different 
circumstances compared to adding codes to the classification on an 
annual or semi-annual basis.
    6. How will this affect other regulatory agencies, payment systems 
and processes?
    How will rulemaking be affected, two proposed rules and two final 
rules?

 MS-DRGs
 APR-DRGs
 Medicaid
 HH Agencies--Patient-Driven Groupings Model
 SNF--Patient Driven Payment Model
 IRF PPS
 Medicare Advantage Plans--HCC
 Commercial HCCs
 OPPS
 Worker's Compensation
 Other state agencies
    We also received comments in response to this topic that we 
consider to be outside the scope of the request for feedback. Because 
we consider these public comments to be outside the scope of the 
proposed rule, we are not addressing them in this final rule.
    Response: We appreciate the commenters' support and feedback 
received on what criteria or factors the agencies (Committee) should 
consider for determining whether to consider a code request for an 
April 1 or October 1 implementation date, as well, as how it may impact 
provider's business processes. With respect to commenters' concerns 
regarding clarity and transparency in the process for how the agencies 
will communicate timelines and information on which code requests would 
be considered for April 1 versus an October 1 implementation date, we 
note that we provide detailed information regarding the ICD-10 
Coordination and Maintenance Committee meetings, including detailed 
timelines in the Agenda and meeting

[[Page 44954]]

materials made available on each agency's respective websites. Members 
of the public may refer to the prior meeting's Agenda and meeting 
materials for information about upcoming deadlines. Additionally, we 
discuss information related to the code updates as a result of 
proposals brought forth to the meetings in the annual IPPS rulemaking 
process. As noted in the preamble of this final rule, and discussed 
earlier in this section, the ICD-10 (previously the ICD-9-CM) 
Coordination and Maintenance Committee holds its meetings in the spring 
and fall in order to update the codes and the applicable payment and 
reporting systems by October 1 of each year. Items are placed on the 
agenda for the Committee meeting if the request is received at least 3 
months prior to the meeting. This requirement allows time for staff to 
review and research the coding issues and prepare material for 
discussion at the meeting. It also allows time for the topic to be 
publicized in meeting announcements in the Federal Register as well as 
on the CMS website. A complete addendum describing details of all 
diagnosis and procedure coding changes, both tabular and index, is 
published on the CMS and NCHS websites in June of each year. We note 
that, on July 26, 2021, the Federal Register Notice announcing the 
September 14-15, 2021 committee meetings was published with the 
tentative agenda items listed for both diagnosis and procedure code 
topics. This notice is located at https://www.federalregister.gov/documents/2021/07/26/2021-15801/national-center-for-health-statistics-nchs-icd-10-coordination-and-maintenance-candm-committee and 
specifically indicates for the ICD-10-PCS procedure code topics, which 
topics are associated with a new technology add-on payment application 
for FY 2023, as well as, which topic was requested for consideration of 
an April 1, 2022 implementation date. We note that there were no 
diagnosis code topics at the time of the development of the Federal 
Register Notice identified as requesting an April 1, 2022 
consideration. With respect to communication, in addition to the 
resources previously discussed, CMS maintains an ICD-10 Maintenance 
subscriber list to enable members of the public to remain informed of 
updates related to ICD-10. Instructions on how to join this subscriber 
list are available on the CMS website at: https://www.cms.gov/Medicare/Coding/ICD10/ICD-10-Coordination-and-Maintenance-Committee-Meetings

We believe the combination of these various resources provide the 
necessary level of transparency regarding information pertaining to the 
ICD-10 Coordination and Maintenance Committee meeting process.

    With regard to concerns about the ability to comment on the MS-DRG 
assignment of any new codes that may be considered for an April 1 
implementation, we note that our current and long-established process 
includes finalizing procedure codes that have been presented at the 
March meeting that were unable to be included in the proposed rule. 
(Diagnosis code proposals discussed at the March meeting are typically 
not considered for implementation until the following October (18 month 
delay)). As discussed throughout section II.D. of the preamble of the 
FY 2022 IPPS/LTCH PPS proposed and final rules, using our established 
process, we review the predecessor codes MDC, MS-DRG assignment and 
designation (severity level or O.R. versus Non-O.R.) and consider other 
relevant factors in the assignment of a new code under the IPPS ICD-10 
MS-DRGs. Members of the public have the opportunity to provide feedback 
on the assignment and designation of the codes if they disagree, which 
are then considered in the following or future year's rulemaking cycle. 
As discussed in more detail later in this section of this final rule, 
as shown in Table 6A.--New Diagnosis Codes associated with this final 
rule (and available via the internet on the CMS website at https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/AcuteInpatientPPS, there were diagnosis codes discussed at the March 9-
10, 2021 ICD-10 Coordination and Maintenance Committee meeting that 
were not finalized in time to include in the proposed rule. These 12 
codes are identified in Table 6A with an asterisk and have been 
assigned to the most appropriate MDC, MS-DRG, and severity level 
designation using our established process, for FY 2022. As noted 
previously, members of the public have the opportunity to provide 
feedback on the assignment and designation of the codes finalized after 
the March meeting if they disagree, which are then considered in the 
following or future year's rulemaking cycle.
    The process that was described for the MS-DRG assignment of new 
procedure codes (and/or diagnosis codes) that could potentially be 
finalized for an April 1 implementation is the same process that was 
utilized when the new diagnosis codes for COVID-19 and vaping related 
disorder were implemented April 1, 2020 and, as discussed earlier in 
this section, the MS-DRG assignments for the six diagnosis codes that 
were effective with discharges on and after January 1, 2021. We 
provided members of the public the opportunity to comment on the MDC, 
MS-DRG and severity level designation of the six diagnosis codes for FY 
2022 consideration in association with the proposed rule, and we did 
not receive any comments suggesting we consider alternative 
assignments. To summarize, with respect to an April 1 implementation 
date, the process as described would consist of the initial assignment 
for any code finalized for an April 1 implementation to be assigned to 
the most appropriate MDC, MS-DRG and designation using our established 
process which would be in effect from April 1 through September 30 of 
that same calendar and fiscal year, along with the opportunity for 
members of the public to comment (during the public comment period in 
association with the proposed rule for the upcoming fiscal year), on 
any alternate suggestions should they not agree with the initial 
assignment. As a commenter noted in its comments and discussed earlier 
in this section, the current GROUPER allows for a comment period prior 
to implementation in October (of the new GROUPER) and it is important 
to recognize that revisions may be made from the proposed and final 
GROUPER especially for new codes.
    With respect to commenters' concerns regarding training and 
education, as outlined in the materials and discussed during the March 
9-10, 2021 meetings, if adopted, any codes implemented effective April 
1 would be incorporated into the ICD-10-CM Official Guidelines for 
Coding and Reporting, if applicable, and coding advice would be 
published in AHA's Coding Clinic for ICD-10-CM/PCS publication. We note 
that the same opportunities, methods and options that are currently 
utilized to provide education and training on the code updates for the 
annual October update would also be available for an April 1 
implementation date. These include, but are not limited to, workshops, 
seminars, webinars, podcasts, presentations, electronic communications, 
announcements via social media, etc.
    In response to commenters' concerns regarding the ability of 
commercial payors to stay up to date on code changes if an April 1 
implementation date were to be adopted, we believe that these concerns 
can be mitigated with limited code updates using a phased in approach. 
In addition, outreach efforts to better understand why systems are

[[Page 44955]]

currently not being updated in a timely manner will help inform where 
process improvements can begin to ensure compliance. It is not clear to 
us if payors are not familiar with the HIPAA requirements for use of 
the current code set.
    With respect to concerns about increased costs related to the 
production and purchase of additional code books or software, we do not 
believe there is a specific need for publishers to produce new code 
books for the reasons discussed in the proposed rule. With regard to 
new software, we were not and have not been made aware of any 
significant challenges encountered by vendors or programmers during the 
PHE with the additional GROUPER releases that were made available.
    In response to the commenter's process questions, we have provided 
the following sample timeline from the March 9-10, 2021 ICD-10 
Coordination and Maintenance Committee meeting materials and are 
sharing here to illustrate the process.
Sample Timeline
June 11, 2021
    Deadline for requestors: Those members of the public requesting 
that topics be discussed at the September 14-15, 2021 ICD-10 
Coordination and Maintenance Committee Meeting, must have their 
requests submitted to CMS for procedures and NCHS for diagnoses.
    Requestors should indicate if they are submitting their code 
request for consideration for an April 1, 2022 implementation date, if 
adopted, or an October 1, 2022 implementation date.
    The ICD-10 Coordination and Maintenance Committee will make efforts 
to accommodate the requested implementation date for each request 
submitted, however, the Committee will determine which requests will be 
presented for consideration for an April 1, 2022 implementation date or 
an October 1, 2022 implementation date.
    *We are also seeking input on what factors the Committee should 
consider when determining which requests should be considered for 
either an April 1, 2022 or October 1, 2022 implementation date.
July 2021
    Federal Register notice for the September 14-15, 2021 ICD-10 
Coordination and Maintenance Committee Meeting will be published. This 
will include the tentative agenda.
August 2021
    FY 2022 Hospital Inpatient Prospective Payment System final rule is 
issued. This rule will also include links to tables listing all the 
final codes to be implemented on October 1, 2021.
    This rule can be accessed at: https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/AcuteInpatientPPS/index.html.
August 2021
    Tentative agenda for the Procedure portion of the September 14, 
2021 ICD-10 Coordination and Maintenance Committee Meeting will be 
posted on the CMS web page at: https://www.cms.gov/Medicare/Coding/ICD10/C-and-M-Meeting-Materials.html.
    Tentative agenda for the Diagnosis portion of the September 15, 
2021 ICD-10 Coordination and Maintenance Committee Meeting will be 
posted on the NCHS web page at: https://www.cdc.gov/nchs/icd/icd10cm_maintenance.htm.
    If adopted, topics being considered for an April 1 implementation 
will be identified.
August 9, 2021
    On-line registration opens for the September 14-15, 2021 ICD-10 
Coordination and Maintenance Committee Meeting at: https://www.eventbrite.com/e/icd-10-coordination-and-maintenance-committee-meeting-tickets.
    Please note that this meeting will be conducted virtually and 
registration is not required to attend. However, we are providing the 
ability to register on-line for those required to provide proof of 
attendance for continuing education purposes. The on-line registration 
will be available through September 9, 2021.
September 14-15, 2021
    The September 2021 ICD-10 Coordination and Maintenance Committee 
Meeting will be held fully virtual, with no in-person audience. Those 
who wish to attend must participate via Zoom Webinar or by dialing in.
September 2021
    Recordings and slide presentations of the September 14-15, 2021 
ICD-10 Coordination and Maintenance Committee Meeting will be posted on 
the following web pages:
    Diagnosis code portion of the recording and related materials 
https://www.cdc.gov/nchs/icd/icd10cm_maintenance.htm;
    Procedure code portion of the recording and related materials 
https://www.cms.gov/Medicare/Coding/ICD10/C-and-M-Meeting-Materials.html.
October 1, 2021
    New and revised ICD-10-CM and ICD-10-PCS codes go into effect along 
with MS-DRG changes. Final addendum available on web pages as follows:
    Diagnosis addendum https://www.cdc.gov/nchs/icd/icd10cm.htm;
    Procedure addendum https://www.cms.gov/Medicare/Coding/ICD10/.
October 15, 2021
    Deadline for receipt of public comments on proposed new codes 
discussed at the September 14-15, 2021 ICD-10 Coordination and 
Maintenance Committee Meeting being considered for implementation on 
April 1, 2022.
November 2021
    Any new ICD-10 codes that will be implemented on the following 
April 1 will be announced. Information on any new codes to be 
implemented April 1, 2022 will be posted on the following websites: 
https://www.cdc.gov/nchs/icd/icd10cm.htm, https://www.cms.gov/Medicare/Coding/ICD10/.
November 15, 2021
    Deadline for receipt of public comments on proposed new codes and 
revisions discussed at the September 14-15, 2021 ICD-10 Coordination 
and Maintenance Committee Meeting being considered for implementation 
on October 1, 2022.
December 3, 2021
    Deadline for requestors: Those members of the public requesting 
that topics be discussed at the March XX, 2022 ICD-10 Coordination and 
Maintenance Committee Meeting, must have their requests submitted to 
CMS for procedures and NCHS for diagnoses.
    Requestors should indicate if they are submitting their code 
request for consideration for an October 1, 2022 implementation date, 
or an April 1, 2023 if adopted, implementation date.
    The ICD-10 Coordination and Maintenance Committee will make efforts 
to accommodate the requested implementation date for each request 
submitted, however, the Committee will determine which requests will be 
presented for consideration for an October 1, 2022 implementation date 
or an April 1, 2023 implementation date.
January 2022
    Federal Register notice for the March X-X, 2022 ICD-10 Coordination 
and Maintenance Committee Meeting will be published. This will include 
the tentative agenda.
February 1, 2022
    ICD-10 MS-DRG Grouper software and related materials posted on CMS 
web page at: https://www.cms.gov/

[[Page 44956]]

Medicare/Medicare-Fee-for-Service-Payment/AcuteInpatientPPS/MS-DRG-
Classifications-and-Software.
February 1, 2022
    Any updates to the ICD-10-CM and ICD-10-PCS Coding Guidelines will 
be posted on the following websites: https://www.cdc.gov/nchs/icd/icd10cm.htm https://www.cms.gov/Medicare/Coding/ICD10/.
February 1, 2022
    All ICD-10-CM and ICD-10-PCS code update files (includes April 1 
update and full files from prior October 1) will be posted on the 
following websites: https://www.cdc.gov/nchs/icd/icd10cm.htm https://www.cms.gov/Medicare/Coding/ICD10/.
March 8-9, 2022
    ICD-10 Coordination and Maintenance Committee Meeting.
March 2022
    Recordings and slide presentations of the March 9-10, 2021 ICD-10 
Coordination and Maintenance Committee Meeting will be posted on the 
following web pages:
    Diagnosis code portion of the recording and related materials 
https://www.cdc.gov/nchs/icd/icd10cm_maintenance.htm.
    Procedure code portion of the recording and related materials 
https://www.cms.gov/Medicare/Coding/ICD10/C-and-M-Meeting-Materials.html.
April 1, 2022
    New and revised ICD-10-CM and ICD-10-PCS codes go into effect along 
with MS-DRG changes.
    We note that, as outlined in the sample timeline, by the June 11, 
2021 deadline, requestors were encouraged to indicate in their 
submission of a code request whether they sought consideration for an 
April 1, 2022 implementation date, if adopted, or an October 1, 2022 
implementation date. As discussed earlier in this section, we received 
one procedure code request for consideration of an April 1, 2022 
implementation date for discussion at the September 14-15, 2021 ICD-10 
Coordination and Maintenance Committee meeting. There were no diagnosis 
code requests submitted by that deadline. The process and/or criteria 
to determine which codes would be implemented in April versus October 
would include identifying the number of code requests received for 
consideration of each date, providing the Agenda and meeting materials 
which indicate the implementation date (April or October) being 
considered for each topic, using our established process for presenting 
the code proposal to members of the public participating in the ICD-10 
Coordination and Maintenance Committee meeting process, allowing the 
opportunity for public comments to be submitted following the meeting, 
agency review of the public comments to determine if there is support 
for the code proposal, as well as, support for the proposed 
implementation date.
    We also note that enabling code proposals related to diagnosis code 
topics that are presented in March to be considered for implementation 
the following April would assist in reducing the current 18-month 
timeframe that exists to incorporate new diagnosis codes into the 
classification. We further note that there is additional flexibility 
with regard to repeat diagnosis code proposals that have been updated 
and brought back for consideration to be implemented sooner as well. 
This scenario (repeat proposals) was also suggested by a commenter for 
the agencies to consider as one of the criteria for consideration of an 
April 1 implementation date.
    With respect to coding guideline updates, any updates to the ICD-
10-CM Official Guidelines for Coding and Reporting would depend on the 
circumstances relating to the new code(s), such that, there may be 
instances in which no guideline updates are needed and in other 
instances there may. However, if updates to the guidelines are 
necessary, the four Cooperating Parties for ICD-10 (AHA, AHIMA, CDC, 
and CMS) would evaluate and incorporate the necessary information into 
the appropriate section for all users of the classification 
accordingly. Coding guideline updates in response to April 1 code 
updates effective with discharges on and after April 1 are valid 
beginning on that April 1 date of that fiscal year. These April 1 
coding guideline updates would be in addition to the coding guidelines 
that were effective at the beginning of that same fiscal year. A fiscal 
year for IPPS purposes begins with discharges on and after October 1 
through September 30 of the following year. As displayed in the sample 
timeline, all materials requiring updates would be made publicly 
available by February 1 for an April 1 code implementation, including 
coding guidelines.
    Finally, similar to the current process that is involved for users 
of the classification when incorporating changes associated with the 
annual October 1 code update, we anticipate that other regulatory 
agencies would continue to utilize their existing processes to update 
their payment systems accordingly.
    After consideration of the public comments and feedback received, 
we are adopting an April 1 implementation date, in addition to the 
annual October 1 update, beginning with April 1, 2022. We note that the 
intent of this April 1 implementation date is to allow flexibility in 
the ICD-10 code update process for the reasons previously discussed and 
based on the feedback received by commenters.
    We appreciate the commenters' suggestions on the criteria and/or 
factors that should be considered by the Committee in determining 
whether to consider a code request for an April 1 versus an October 1 
implementation and note that, as discussed during the March 9-10, 2021 
ICD-10 Coordination and Maintenance Committee meeting that we recommend 
a phased in approach with limited code updates. We acknowledge the 
concerns that some commenters expressed with respect to potential 
operational issues and with commercial payers and compliance issues. As 
noted previously, we intend to work with stakeholders and identify how 
we can address issues that may arise in this process. We will continue 
to provide additional information pertaining to the adoption of the 
April 1 implementation date for new codes in connection with the ICD-10 
Coordination and Maintenance Committee meeting process and our annual 
IPPS rulemaking.
    ICD-9-CM addendum and code title information is published on the 
CMS website at: https://www.cms.gov/Medicare/Coding/ICD9ProviderDiagnosticCodes/addendum. ICD-10-CM and ICD-10-PCS addendum 
and code title information is published on the CMS website at: http://www.cms.gov/Medicare/Coding/ICD10/index.html. CMS also sends electronic 
files containing all ICD-10-CM and ICD-10-PCS coding changes to its 
Medicare contractors for use in updating their systems and providing 
education to providers.
    Information on ICD-10-CM diagnosis codes, along with the Official 
ICD-10-CM Coding Guidelines, can be found on the CDC website at: 
https://www.cdc.gov/nchs/icd/icd10cm.htm. Additionally, information on 
new, revised, and deleted ICD-10-CM diagnosis and ICD-10-PCS procedure 
codes is provided to the AHA for publication in the Coding Clinic for 
ICD-10. The AHA also distributes coding update information to 
publishers and software vendors.

[[Page 44957]]

    In the proposed rule we noted that for FY 2021, there are currently 
72,621 ICD-10-CM diagnosis codes and 78,136 ICD-10-PCS procedure codes. 
We also noted that as displayed in Table 6A--New Diagnosis Codes and in 
Table 6B--New Procedure Codes associated with the proposed rule (and 
available via the internet on the CMS website at https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/AcuteInpatientPPS/index/, 
there were 147 new diagnosis codes and 106 new procedure codes that had 
been finalized for FY 2022 at the time of the development of the 
proposed rule. As discussed in section II.D.13 of the preamble of this 
final rule, we are making available Table 6A--New Diagnosis Codes, 
Table 6B--New Procedure Codes, Table 6C--Invalid Diagnosis Codes, Table 
6D--Invalid Procedure Codes Table 6E--Revised Diagnosis Code Titles, 
and Table 6F--Revised Procedure Code Titles via the internet on the CMS 
website at: https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/AcuteInpatientPPS/index.html in association with this final 
rule. As shown in Table 6A--New Diagnosis Codes, there were diagnosis 
codes discussed at the March 9-10, 2021 ICD-10 Coordination and 
Maintenance Committee meeting that were not finalized in time to 
include in the proposed rule. These 12 codes are identified in Table 6A 
with an asterisk and are as follows.
BILLING CODE 4120-01-P
[GRAPHIC] [TIFF OMITTED] TR13AU21.149

The addition of these 12 new diagnosis codes to the 147 diagnosis codes 
that had been finalized at the time of the development of the proposed 
rule result in a total of 159 (147 + 12 = 159) new diagnosis codes for 
FY 2022.
    Similarly, there were procedure codes discussed at the March 9-10, 
2021 ICD-10 Coordination and Maintenance Committee meeting that were 
not finalized in time to include in the proposed rule and are also 
identified with an asterisk, as shown in Table 6B--New Procedure Codes. 
We refer the reader to Table 6B--New Procedure Codes associated with 
this final rule and available via the internet on the CMS website 
at:https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/AcuteInpatientPPS/index.html for the detailed list of these additional 
85 new procedure codes. The addition of these 85 new procedure codes to 
the 106 procedure codes that had been finalized at the time of the 
development of the proposed rule result in a total of 191 (106 + 85 = 
191) new procedure codes for FY 2022.
    We also note, as reflected in Table 6C--Invalid Diagnosis Codes and 
in Table 6D--Invalid Procedure Codes, there are a total of 32 diagnosis 
codes and 107 procedure codes that will become invalid effective 
October 1, 2021. Based on these code updates, effective October 1, 
2021, there are a total of 72,748 ICD-10-CM diagnosis codes and 78,220 
ICD-10-PCS procedure codes for FY 2022 as shown in the following table.
[GRAPHIC] [TIFF OMITTED] TR13AU21.150


[[Page 44958]]


    As stated previously, the public is provided the opportunity to 
comment on any requests for new diagnosis or procedure codes discussed 
at the ICD-10 Coordination and Maintenance Committee meeting. The code 
titles are adopted as part of the ICD-10 Coordination and Maintenance 
Committee process. Thus, although we publish the code titles in the 
IPPS proposed and final rules, they are not subject to comment in the 
proposed or final rules. We will continue to provide the October 
updates in this manner in the IPPS proposed and final rules.
17. Replaced Devices Offered Without Cost or With a Credit
a. Background
    In the FY 2008 IPPS final rule with comment period (72 FR 47246 
through 47251), we discussed the topic of Medicare payment for devices 
that are replaced without cost or where credit for a replaced device is 
furnished to the hospital. We implemented a policy to reduce a 
hospital's IPPS payment for certain MS-DRGs where the implantation of a 
device that subsequently failed or was recalled determined the base MS-
DRG assignment. At that time, we specified that we will reduce a 
hospital's IPPS payment for those MS-DRGs where the hospital received a 
credit for a replaced device equal to 50 percent or more of the cost of 
the device.
    In the FY 2012 IPPS/LTCH PPS final rule (76 FR 51556 through 
51557), we clarified this policy to state that the policy applies if 
the hospital received a credit equal to 50 percent or more of the cost 
of the replacement device and issued instructions to hospitals 
accordingly.
b. Changes for FY 2022
    As discussed in the FY 2022 IPPS/LTCH PPS proposed rule (86 FR 
25195 through 25198) for FY 2022, we proposed to not add any MS-DRGs to 
the policy for replaced devices offered without cost or with a credit. 
We proposed to continue to include the existing MS-DRGs currently 
subject to the policy as displayed in the following table.

[[Page 44959]]

[GRAPHIC] [TIFF OMITTED] TR13AU21.151


[[Page 44960]]


[GRAPHIC] [TIFF OMITTED] TR13AU21.152

BILLING CODE 4120-01-C

[[Page 44961]]

    We did not receive any public comments opposing our proposal to 
continue to include the existing MS-DRGs currently subject to the 
policy. Therefore, we are finalizing the list of MS-DRGs in the table 
included in the proposed rule and in this final rule that will be 
subject to the replaced devices offered without cost or with a credit 
policy effective October 1, 2021.
    The final list of MS-DRGs subject to the IPPS policy for replaced 
devices offered without cost or with a credit will be issued to 
providers in the form of a Change Request (CR).
18. Out of Scope Public Comments Received
    We received public comments on MS-DRG related issues that were 
outside the scope of the proposals included in the FY 2022 IPPS/LTCH 
PPS proposed rule.
    Because we consider these public comments to be outside the scope 
of the proposed rule, we are not addressing them in this final rule. As 
stated in section II.D.1.b. of the preamble of this final rule, we 
encourage individuals with comments about MS-DRG classifications to 
submit these comments no later than November 1, 2021 so that they can 
be considered for possible inclusion in the annual proposed rule. We 
will consider these public comments for possible proposals in future 
rulemaking as part of our annual review process.

E. Recalibration of the FY 2022 MS-DRG Relative Weights

1. Data Sources for Developing the Relative Weights
    In accordance with our final policy in section I.F. of this final 
rule, for the purposes of establishing the FY 2022 MS-DRG relative 
weights, we are finalizing our proposal to use the FY 2019 MedPAR 
claims data, based on claims received by CMS through March 31, 2020, 
and the March 2020 update of the FY 2018 HCRIS file where we ordinarily 
would have used the FY 2020 MedPAR claims data, based on claims 
received by CMS through December 31, 2020, and the December 2020 update 
of the FY 2019 HCRIS file. We refer the reader to section I.F. of this 
final rule for further discussion of our analysis of the best available 
data for purposes of the FY 2022 ratesetting and our related policies.
    Consistent with our established policy, in developing the MS-DRG 
relative weights for FY 2022, we proposed to use two data sources: 
claims data and cost report data. The claims data source is the MedPAR 
file, which includes fully coded diagnostic and procedure data for all 
Medicare inpatient hospital claims. The FY 2019 MedPAR data used in 
this final rule include discharges occurring on October 1, 2018, 
through September 30, 2019, based on claims received by CMS through 
March 31, 2020, from all hospitals subject to the IPPS and short-term, 
acute care hospitals in Maryland (which at that time were under a 
waiver from the IPPS).
    The FY 2019 MedPAR file used in calculating the relative weights 
includes data for approximately 9,216,615 Medicare discharges from IPPS 
providers. Discharges for Medicare beneficiaries enrolled in a Medicare 
Advantage managed care plan are excluded from this analysis. These 
discharges are excluded when the MedPAR ``GHO Paid'' indicator field on 
the claim record is equal to ``1'' or when the MedPAR DRG payment 
field, which represents the total payment for the claim, is equal to 
the MedPAR ``Indirect Medical Education (IME)'' payment field, 
indicating that the claim was an ``IME only'' claim submitted by a 
teaching hospital on behalf of a beneficiary enrolled in a Medicare 
Advantage managed care plan. In addition, the March 31, 2020 update of 
the FY 2019 MedPAR file complies with version 5010 of the X12 HIPAA 
Transaction and Code Set Standards, and includes a variable called 
``claim type.'' Claim type ``60'' indicates that the claim was an 
inpatient claim paid as fee-for-service.
    Claim types ``61,'' ``62,'' ``63,'' and ``64'' relate to encounter 
claims, Medicare Advantage IME claims, and HMO no-pay claims. 
Therefore, the calculation of the relative weights for FY 2022 also 
excludes claims with claim type values not equal to ``60.'' The data 
exclude CAHs, including hospitals that subsequently became CAHs after 
the period from which the data were taken. We note that the FY 2022 
relative weights are based on the ICD-10-CM diagnosis codes and ICD-10-
PCS procedure codes from the FY 2019 MedPAR claims data, grouped 
through the ICD-10 version of the FY 2022 GROUPER (Version 39).
    The second data source used in the cost-based relative weighting 
methodology is the Medicare cost report data files from the HCRIS. 
Normally, we use the HCRIS dataset that is 3 years prior to the IPPS 
fiscal year. However, as discussed earlier in this section, we proposed 
to use the March 31, 2020 update of the FY 2018 HCRIS for calculating 
the FY 2022 cost-based relative weights. Consistent with our historical 
practice, for this FY 2022 final rule, we are providing the version of 
the HCRIS from which we calculated these 19 CCRs on the CMS website at: 
http://www.cms.gov/Medicare/ Medicare-Fee-for- Service-Payment/
AcuteInpatientPPS/index.html. Click on the link on the left side of the 
screen titled ``FY 2022 IPPS Final Rule Home Page'' or ``Acute 
Inpatient Files for Download.'' We note that this file is identical to 
the file used for the FY 2021 IPPS/LTCH PPS final rule. As discussed 
previously and in the proposed rule, we also made available the FY 2019 
HCRIS and the FY 2020 MedPAR file as well as other related information 
and data files for purposes of public comment on our alternative 
approach of using the same FY 2020 data that we would ordinarily use 
for purposes of FY 2022 ratesetting.
    Comment: A few commenters requested that CMS consider whether an 
adjustment needs to be made to the normalization factor since the FY 
2021 and FY 2022 relative weights were both calculated using the same 
set of claims data (FY 2019 MedPAR). Specifically, the commenters were 
concerned about the impact holding real changes in case-mix constant 
(when calculating the relative weights) might have on accuracy of the 
FY 2022 relative weights. A commenter stated that ``by using FY 2019 
utilization in place of FY 2020 data, the base year weights (FY 2021) 
will not reflect any changes in case mix that would occur from using FY 
2020 compared to FY 2019 utilization. Thus, CMS will be making the 
payment year weights (FY 2022) budget neutral to a base year that does 
not reflect any change in real case mix as would normally occur.''
    Response: We believe the commenters may have misinterpreted the 
purpose of the normalization adjustment. The normalization adjustment 
is the first of two steps performed by CMS to ensure that the 
recalibration of the relative weights does not increase nor decrease 
total payments under the IPPS.
    The purpose of the normalization factor is to ensure that changes 
in average case-mix do not impact the final relative weights used for 
payment purposes. For example, if the average cost of cases grouped to 
each MS-DRG remained the same from one year to the next, and all that 
changed was the number of cases grouped to each MS-DRG, the 
normalization factor would ensure that the final relative weights 
calculated in each year were the same. This is appropriate since it 
ensures that when the relative costliness of cases across MS-DRGs is 
unchanged, the relative weights are unchanged as well. Therefore, if 
CMS were to somehow

[[Page 44962]]

develop a method for introducing some level of real-case mix growth 
into the FY 2019 claims, the revised normalization factor would produce 
the same set of final relative weights, since the average cost of 
claims grouped to each MS-DRG would not have changed.
    The result of the normalization adjustment is that the relative 
weights from both years result in the same average case-mix value when 
using the same set of utilization. However, the normalization 
adjustment alone does not completely meet the goal of ensuring that the 
recalibration of the relative weights does not increase nor decrease 
total payments under the IPPS. Due to other factors that impact IPPS 
payments (for example, the wage index), a budget neutrality factor is 
calculated that ensures the normalized relative weights for the current 
year result in the same total payments as the normalized relative 
weights from the previous year. We refer readers to section II.A.4.a of 
the Addendum to this final rule for a complete discussion on the 
calculation of the budget neutrality factor for recalibration of MS-DRG 
relative weights.
    To the extent commenters were implying that CMS should simply 
increase the normalization factor by an estimate of real case mix 
growth without somehow introducing it into the FY 2019 claims, even 
putting aside the methodological issues with such an approach, we note 
that such an increase in the normalization factor would be offset by a 
larger budget neutrality adjustment.
2. Methodology for Calculation of the Relative Weights
a. General
    We calculated the FY 2022 relative weights based on 19 CCRs, as we 
did for FY 2021. The methodology we proposed to use to calculate the FY 
2022 MS-DRG cost-based relative weights based on claims data in the FY 
2019 MedPAR file and data from the FY 2018 Medicare cost reports is as 
follows:
     To the extent possible, all the claims were regrouped 
using the FY 2022 MS-DRG classifications discussed in sections II.B. 
and II.F. of the preamble of this final rule.
     The transplant cases that were used to establish the 
relative weights for heart and heart-lung, liver and/or intestinal, and 
lung transplants (MS-DRGs 001, 002, 005, 006, and 007, respectively) 
were limited to those Medicare-approved transplant centers that have 
cases in the FY 2019 MedPAR file. (Medicare coverage for heart, heart-
lung, liver and/or intestinal, and lung transplants is limited to those 
facilities that have received approval from CMS as transplant centers.)
     Organ acquisition costs for kidney, heart, heart-lung, 
liver, lung, pancreas, and intestinal (or multivisceral organs) 
transplants continue to be paid on a reasonable cost basis. Because 
these acquisition costs are paid separately from the prospective 
payment rate, it is necessary to subtract the acquisition charges from 
the total charges on each transplant bill that showed acquisition 
charges before computing the average cost for each MS-DRG and before 
eliminating statistical outliers.
    Section 108 of the Further Consolidated Appropriations Act, 2020 
provides that, for cost reporting periods beginning on or after October 
1, 2020, costs related to hematopoietic stem cell acquisition for the 
purpose of an allogeneic hematopoietic stem cell transplant shall be 
paid on a reasonable cost basis. We refer the reader to the FY 2021 
IPPS/LTCH PPS final rule for further discussion of the reasonable cost 
basis payment for cost reporting periods beginning on or after October 
1, 2020 (85 FR 58835 to 58842). For FY 2022 and subsequent years, we 
proposed to subtract the hematopoietic stem cell acquisition charges 
from the total charges on each transplant bill that showed 
hematopoietic stem cell acquisition charges before computing the 
average cost for each MS-DRG and before eliminating statistical 
outliers.
     Claims with total charges or total lengths of stay less 
than or equal to zero were deleted. Claims that had an amount in the 
total charge field that differed by more than $30.00 from the sum of 
the routine day charges, intensive care charges, pharmacy charges, 
implantable devices charges, supplies and equipment charges, therapy 
services charges, operating room charges, cardiology charges, 
laboratory charges, radiology charges, other service charges, labor and 
delivery charges, inhalation therapy charges, emergency room charges, 
blood and blood products charges, anesthesia charges, cardiac 
catheterization charges, CT scan charges, and MRI charges were also 
deleted.
     At least 92.8 percent of the providers in the MedPAR file 
had charges for 14 of the 19 cost centers. All claims of providers that 
did not have charges greater than zero for at least 14 of the 19 cost 
centers were deleted. In other words, a provider must have no more than 
five blank cost centers. If a provider did not have charges greater 
than zero in more than five cost centers, the claims for the provider 
were deleted.
     Statistical outliers were eliminated by removing all cases 
that were beyond 3.0 standard deviations from the geometric mean of the 
log distribution of both the total charges per case and the total 
charges per day for each MS-DRG.
     Effective October 1, 2008, because hospital inpatient 
claims include a POA indicator field for each diagnosis present on the 
claim, only for purposes of relative weight-setting, the POA indicator 
field was reset to ``Y'' for ``Yes'' for all claims that otherwise have 
an ``N'' (No) or a ``U'' (documentation insufficient to determine if 
the condition was present at the time of inpatient admission) in the 
POA field.
    Under current payment policy, the presence of specific HAC codes, 
as indicated by the POA field values, can generate a lower payment for 
the claim. Specifically, if the particular condition is present on 
admission (that is, a ``Y'' indicator is associated with the diagnosis 
on the claim), it is not a HAC, and the hospital is paid for the higher 
severity (and, therefore, the higher weighted MS-DRG). If the 
particular condition is not present on admission (that is, an ``N'' 
indicator is associated with the diagnosis on the claim) and there are 
no other complicating conditions, the DRG GROUPER assigns the claim to 
a lower severity (and, therefore, the lower weighted MS-DRG) as a 
penalty for allowing a Medicare inpatient to contract a HAC. While the 
POA reporting meets policy goals of encouraging quality care and 
generates program savings, it presents an issue for the relative 
weight-setting process. Because cases identified as HACs are likely to 
be more complex than similar cases that are not identified as HACs, the 
charges associated with HAC cases are likely to be higher as well. 
Therefore, if the higher charges of these HAC claims are grouped into 
lower severity MS-DRGs prior to the relative weight-setting process, 
the relative weights of these particular MS-DRGs would become 
artificially inflated, potentially skewing the relative weights. In 
addition, we want to protect the integrity of the budget neutrality 
process by ensuring that, in estimating payments, no increase to the 
standardized amount occurs as a result of lower overall payments in a 
previous year that stem from using weights and case-mix that are based 
on lower severity MS-DRG assignments. If this would occur, the 
anticipated cost savings from the HAC policy would be lost.
    To avoid these problems, we reset the POA indicator field to ``Y'' 
only for relative weight-setting purposes for all

[[Page 44963]]

claims that otherwise have an ``N'' or a ``U'' in the POA field. This 
resetting ``forced'' the more costly HAC claims into the higher 
severity MS-DRGs as appropriate, and the relative weights calculated 
for each MS-DRG more closely reflect the true costs of those cases.
    In addition, in the FY 2013 IPPS/LTCH PPS final rule, for FY 2013 
and subsequent fiscal years, we finalized a policy to treat hospitals 
that participate in the Bundled Payments for Care Improvement (BPCI) 
initiative the same as prior fiscal years for the IPPS payment modeling 
and ratesetting process without regard to hospitals' participation 
within these bundled payment models (77 FR 53341 through 53343). 
Specifically, because acute care hospitals participating in the BPCI 
Initiative still receive IPPS payments under section 1886(d) of the 
Act, we include all applicable data from these subsection (d) hospitals 
in our IPPS payment modeling and ratesetting calculations as if the 
hospitals were not participating in those models under the BPCI 
initiative. We refer readers to the FY 2013 IPPS/LTCH PPS final rule 
for a complete discussion on our final policy for the treatment of 
hospitals participating in the BPCI initiative in our ratesetting 
process. For additional information on the BPCI initiative, we refer 
readers to the CMS' Center for Medicare and Medicaid Innovation's 
website at: http://innovation.cms.gov/initiatives/Bundled-Payments/index.html and to section IV.H.4. of the preamble of the FY 2013 IPPS/
LTCH PPS final rule (77 FR 53341 through 53343).
    The participation of hospitals in the BPCI initiative concluded on 
September 30, 2018. The participation of hospitals in the BPCI Advanced 
model started on October 1, 2018. The BPCI Advanced model, tested under 
the authority of section 1115A of the Act, is comprised of a single 
payment and risk track, which bundles payments for multiple services 
beneficiaries receive during a Clinical Episode. Acute care hospitals 
may participate in BPCI Advanced in one of two capacities: As a model 
Participant or as a downstream Episode Initiator. Regardless of the 
capacity in which they participate in the BPCI Advanced model, 
participating acute care hospitals will continue to receive IPPS 
payments under section 1886(d) of the Act. Acute care hospitals that 
are Participants also assume financial and quality performance 
accountability for Clinical Episodes in the form of a reconciliation 
payment. For additional information on the BPCI Advanced model, we 
refer readers to the BPCI Advanced web page on the CMS Center for 
Medicare and Medicaid Innovation's website at: https://innovation.cms.gov/initiatives/bpci-advanced/. Consistent with our 
policy for FY 2021, and consistent with how we have treated hospitals 
that participated in the BPCI Initiative, for FY 2022, we continue to 
believe it is appropriate to include all applicable data from the 
subsection (d) hospitals participating in the BPCI Advanced model in 
our IPPS payment modeling and ratesetting calculations because, as 
noted previously, these hospitals are still receiving IPPS payments 
under section 1886(d) of the Act. Consistent with the FY 2021 IPPS/LTCH 
PPS final rule, we also proposed to include all applicable data from 
subsection (d) hospitals participating in the Comprehensive Care for 
Joint Replacement (CJR) Model in our IPPS payment modeling and 
ratesetting calculations.
    The charges for each of the 19 cost groups for each claim were 
standardized to remove the effects of differences in area wage levels, 
IME and DSH payments, and for hospitals located in Alaska and Hawaii, 
the applicable cost-of-living adjustment. Because hospital charges 
include charges for both operating and capital costs, we standardized 
total charges to remove the effects of differences in geographic 
adjustment factors, cost-of-living adjustments, and DSH payments under 
the capital IPPS as well. Charges were then summed by MS-DRG for each 
of the 19 cost groups so that each MS-DRG had 19 standardized charge 
totals. Statistical outliers were then removed. These charges were then 
adjusted to cost by applying the national average CCRs developed from 
the FY 2018 cost report data, consistent with our FY 2022 ratesetting 
discussed in section II.A.4 of the Addendum of this final rule.
    The 19 cost centers that we used in the relative weight calculation 
are shown in a supplemental data file, Cost Center HCRIS Lines 
Supplemental Data File, posted via the internet on the CMS website for 
this final rule and available at http://www.cms.hhs.gov/Medicare/Medicare-Fee-for-Service-Payment/AcuteInpatientPPS/index.html. The 
supplemental data file shows the lines on the cost report and the 
corresponding revenue codes that we used to create the 19 national cost 
center CCRs. In the proposed rule, we stated that if we receive 
comments about the groupings in this supplemental data file, we may 
consider these comments as we finalize our policy. However, we did not 
receive any comments on the groupings in this table, and therefore, we 
are finalizing the groupings as proposed.
    Consistent with historical practice, we account for rare situations 
of non-monotonicity in a base MS-DRG and its severity levels, where the 
mean cost in the higher severity level is less than the mean cost in 
the lower severity level, in determining the relative weights for the 
different severity levels. If there are initially non-monotonic 
relative weights in the same base DRG and its severity levels, then we 
combine the cases that group to the specific non-monotonic MS-DRGs for 
purposes of relative weight calculations. For example, if there are two 
non-monotonic MS-DRGs, combining the cases across those two MS-DRGs 
results in the same relative weight for both MS-DRGs. The relative 
weight calculated using the combined cases for those severity levels is 
monotonic, effectively removing any non-monotonicity with the base DRG 
and its severity levels. For this FY 2022 final rule, this calculation 
was applied to address non-monotonicity for cases that grouped to MS-
DRG 504 and MS-DRG 505. We note that cases were also combined in 
calculating the relative weights for these two MS-DRGs for FY 2021. In 
the supplemental file titled AOR/BOR File, we include statistics for 
the affected MS-DRGs both separately and with cases combined.
    In the proposed rule, we invited public comments on our proposals 
related to recalibration of the FY 2022 relative weights and the 
changes in relative weights from FY 2021. We did not receive any public 
comments on these proposals. Therefore, we are finalizing our proposed 
policies with respect to the recalibration of the FY 2022 relative 
weights.
b. Relative Weight Calculation for MS-DRG 018
    As discussed in the FY 2021 IPPS/LTCH PPS final rule (85 FR 58599 
through 58600), we created MS-DRG 018 for cases that include procedures 
describing CAR T-cell therapies, which were reported using ICD-10-PCS 
procedure codes XW033C3 or XW043C3. We refer the reader to section 
II.D.2. of this final rule for discussion of the procedure codes for 
CAR T-cell and non-CAR T-cell therapies and other immunotherapies that 
are finalizing for assignment to MS-DRG 018 for FY 2022.
    In the FY 2021 IPPS/LTCH PPS final rule, we finalized our proposals 
to modify our existing relative weight methodology to ensure that the 
relative weight for new MS-DRG 018 appropriately reflects the relative 
resources required for providing CAR T-cell therapy outside of a 
clinical trial, while still accounting for the clinical

[[Page 44964]]

trial cases in the overall average cost for all MS-DRGs, with 
additional refinements in response to comments. For cases that group to 
MS-DRG 018, we finalized to not include claims determined to be 
clinical trial claims that group to new MS-DRG 018 when calculating the 
average cost for new MS-DRG 018 that is used to calculate the relative 
weight for this MS-DRG, with the additional refinements that (a) when 
the CAR T-cell therapy product is purchased in the usual manner, but 
the case involves a clinical trial of a different product, the claim 
will be included when calculating the average cost for new MS-DRG 018 
to the extent such claims can be identified in the historical data, and 
(b) when there is expanded access use of immunotherapy, these cases 
will not be included when calculating the average cost for new MS-DRG 
018 to the extent such claims can be identified in the historical data 
(85 FR 58600). We also finalized our proposal to calculate an 
adjustment to account for the CAR T-cell therapy cases determined to be 
clinical trial cases, as described in the FY 2021 IPPS/LTCH PPS final 
rule, with the additional refinement of including revenue center 891 in 
our calculation of standardized drug charges for MS-DRG 018. Applying 
this finalized methodology, based on the March 2020 update of the FY 
2019 MedPAR file for the FY 2021 IPPS/LTCH PPS final rule, we estimated 
that the average costs of CAR T-cell therapy cases determined to be 
clinical trial cases ($46,062) were 17 percent of the average costs of 
CAR T cell therapy cases determined to be non-clinical trial cases 
($276,042), and therefore, in calculating the national average cost per 
case for purposes of the FY 2021 IPPS/LTCH PPS final rule, each case 
identified as a clinical trial case was adjusted by 0.17. We also noted 
that we were applying this adjustor for cases determined to be CAR T-
cell therapy clinical trial cases for purposes of budget neutrality and 
outlier simulations. We refer the reader to the FY 2021 IPPS/LTCH PPS 
final rule for complete discussion of our finalized modifications to 
the relative weight calculation for MS-DRG 018.
    Since we proposed to use the same FY 2019 MedPAR claims data for FY 
2022 ratesetting that we did for the FY 2021 final rule, we also 
proposed to continue to use the same process to identify clinical trial 
claims in the FY 2019 MedPAR for purposes of calculating the FY 2022 
relative weights. We continue to use the proxy of standardized drug 
charges of less than $373,000, which was the average sales price of 
KYMRIAH and YESCARTA, which are the two CAR T-cell biological products 
in the MedPAR data used for the FY 2021 final rule and this final rule. 
Using the same methodology from the FY 2021 IPPS/LTCH PPS final rule, 
we proposed to apply an adjustment to account for the CAR T cell 
therapy cases identified as clinical trial cases in calculating the 
national average standardized cost per case that is used to calculate 
the relative weights for all MS-DRGs:
    Step 1--Calculate the average cost for cases to be assigned to new 
MS-DRG 018 that contain ICD-10-CM diagnosis code Z00.6 or contain 
standardized drug charges of less than $373,000.
    Step 2--Calculate the average cost for cases to be assigned to new 
MS-DRG 018 that do not contain ICD-10-CM diagnosis code Z00.6 or 
standardized drug charges of at least $373,000.
    Step 3--Calculate an adjustor by dividing the average cost 
calculated in step 1 by the average cost calculated in step 2.
    Step 4--Apply the adjustor calculated in step 3 to the cases 
identified in step 1 as clinical trial cases, then add this adjusted 
case count to the non-clinical trial case count prior to calculating 
the average cost across all MS-DRGs.
    Additionally, we are continuing our finalized methodology for 
calculating this payment adjustment, such that: (a) When the CAR T-cell 
therapy product is purchased in the usual manner, but the case involves 
a clinical trial of a different product, the claim will be included 
when calculating the average cost for cases not determined to be 
clinical trial cases and (b) when there is expanded access use of 
immunotherapy, these cases will be included when calculating the 
average cost for cases determined to be clinical trial cases. However, 
we continue to believe to the best of our knowledge there are no claims 
in the historical data (FY 2019 MedPAR) used in the calculation of the 
adjustment for cases involving a clinical trial of a different product, 
and to the extent the historical data contain claims for cases 
involving expanded access use of immunotherapy we believe those claims 
would have drug charges less than $373,000. Consistent with our 
proposal to use the FY 2019 data for the FY 2022 ratesetting, we also 
proposed to calculate this adjustor based on the March 2020 update of 
the FY 2019 MedPAR file for purposes of establishing the FY 2022 
relative weights. Accordingly, as we did for FY 2021, we proposed to 
adjust the transfer-adjusted case count for MS-DRG 018 by applying the 
proposed adjustor of 17 percent to the applicable clinical trial cases, 
and to use this adjusted case count for MS-DRG 018 in calculating the 
national average cost per case, which is used in the calculation of the 
relative weights. Therefore, in calculating the national average cost 
per case for purposes of the proposed rule, each case identified as a 
clinical trial case was adjusted by 17 percent. As we did for FY 2021, 
we proposed to apply this same adjustor for the applicable cases that 
group to MS-DRG 018 for purposes of budget neutrality and outlier 
simulations.
    As discussed in section I.F. of this final rule, we also solicited 
comments on an alternative approach of using the same FY 2020 data that 
we would ordinarily use for purposes of the FY 2022 rulemaking, which 
we stated we may consider finalizing for FY 2022 based on consideration 
of comments received. We noted that using the methodology as finalized 
in the FY 2021 IPPS/LTCH PPS final rule, we calculated an adjustor of 
0.25 based on this alternative approach of using the FY 2020 MedPAR 
file.
    Comment: The majority of commenters supported CMS' proposal to use 
the same ratesetting methodology for MS-DRG 018 in FY 2022 as it did in 
FY 2021. Commenters stated that the inclusion of cases without product 
acquisition costs would compromise the relative weight calculation. The 
majority of commenters also supported CMS' proposal to apply an 
adjustor to expanded access or clinical trial cases. While the majority 
of commenters generally supported CMS' proposed adjustor of 0.17, 
calculated based on the FY 2019 MedPAR data, some commenters requested 
that we use the calculated adjustment of 0.25 from the FY 2020 MedPAR 
data. Some commenters also requested that CMS raise the $373,000 
threshold or otherwise modify the methodology so that more cases would 
be classified into the expanded access or clinical trial case cohort.
    Response: We appreciate the support and feedback on our proposal to 
use the same ratesetting methodology for MS-DRG 018 in FY 2022 as we 
did in FY 2021, including the application of an adjustor for expanded 
access or clinical trial cases.
    In response to commenters who requested that CMS raise the $373,000 
threshold or otherwise modify the methodology so that more cases would 
be classified into the expanded access or clinical trial case cohort, 
as noted earlier, we are using the FY 2019 MedPAR to approximate the 
relative resource use for each MS-DRG. This is the same data source 
that was used to approximate the relative resource use

[[Page 44965]]

for determining the FY 2021 MS-DRG relative weights. As we discussed in 
the FY 2021 IPPS/LTCH PPS final rule, we believe that given this data 
source, our methodology to divide cases into these cohorts provides 
reasonable estimates on average of the costs of the cases in these 
cohorts. (85 FR 58599) As we are continuing to use the same data source 
that was used for purposes of the FY 2021 MS-DRG relative weights and 
the calculation of the adjustor to the relative weight for MS-DRG 018, 
it continues to be reasonable that in that data source, hospitals would 
not generally have charges of greater than $373,000 in the absence of 
incurring the cost of the CAR T-cell drug. As previously noted, we used 
the proxy of standardized drug charges of less than $373,000, which was 
the average sales price of KYMRIAH and YESCARTA, which are the two CAR 
T-cell biological products in the MedPAR data used for the FY 2021 
final rule and this final rule.
    In response to commenters who requested that we use the calculated 
adjustment of 0.25, we disagree that we should use the adjustment of 
0.25 calculated from the FY 2020 MedPAR data instead of the 0.17 
adjustment calculated from the FY 2019 MedPAR data. Given that under 
the IPPS the relative weight assigned to each MS-DRG reflects the 
relative hospital resources used with respect to discharges classified 
within that group compared to discharges classified within other MS-
DRGs, it would be inappropriate to use the FY 2019 MedPAR to 
approximate the relative resource use for each MS-DRG, including the 
majority of MS-DRG 018 cases, but then a different data source (that 
is, the FY 2020 MedPAR) to determine the relative resources required 
for MS-DRG 018 cases that are expanded access or clinical trial cases 
to calculate the adjustor.
    Comment: Several commenters stated that the MS-DRG relative weight 
for MS-DRG 018 does not result in payment that fully covers the 
hospital resource costs, including the cost of the drug. Some 
commenters indicated that CMS should make structural changes to the 
IPPS, such as incorporating the Average Sales Price of the CAR T-cell 
drug into the IPPS relative weight calculation rather than use our 
usual methodology for determining the MS-DRG relative weight, or we 
should base the Medicare payment itself on the Average Sales Price of 
the CAR T-cell drug. For example, some commenters stated that the price 
of the CAR T-cell drug is expected to increase soon and the IPPS 
payment does not reflect price increases in a timely manner.
    Response: With regard to the comment that the MS-DRG relative 
weight for MS-DRG 018 does not result in payment that fully covers the 
hospital resource costs, we note that the IPPS is a prospective payment 
system and not a cost reimbursement system. The primary objective of 
the IPPS is to create incentives for hospitals to operate efficiently 
and minimize unnecessary costs, while at the same time ensuring that 
payments are sufficient to adequately compensate hospitals for their 
costs in delivering necessary care to Medicare beneficiaries. In 
addition, we share national goals of preserving the Medicare Hospital 
Insurance Trust Fund. Cost reimbursement is not the optimal means of 
achieving these objectives. As indicated earlier, under the IPPS the 
relative weight assigned to each MS-DRG reflects the relative hospital 
resources used with respect to discharges classified within that group 
compared to discharges classified within other MS-DRGs. For the reasons 
described earlier, CMS is using the FY 2019 MedPAR data to determine 
the MS-DRG relative weights for FY 2022, including the relative weight 
for MS-DRG 018.
    We appreciate the commenters' recommendations for structural 
changes to the IPPS, but as we stated in response to similar comments 
in the FY 2021 rulemaking, we believe that is premature to make 
structural changes to the IPPS at this time to pay for CAR T-cell 
therapies. (85 FR 58453). As we gain more experience paying for these 
therapies under the IPPS, we may consider these comments to inform 
future rulemaking.
    Comment: Some commenters requested clarifications or raised 
concerns regarding hospital charging practices for CAR T-cell 
therapies, including the ability of hospitals to set charges for CAR T-
cell drugs consistent with their CCRs. Some commenters requested that 
CMS establish a dedicated CAR T-cell cost center, which they stated 
would allow hospitals to set charges appropriate for CAR T-cell 
therapy.
    Response: As we noted in response to similar comments in the FY 
2021 IPPS final rule, there is nothing that precludes hospitals from 
setting their drug charges consistent with their CCRs (85 FR 58453). We 
also highlight our statements in prior rulemaking regarding our 
existing administrative mechanisms for hospitals to voluntarily 
establish lower charges (85 FR 58874). Specifically, if a hospital is 
planning on voluntarily lowering its charges, it can request a CCR 
change in accordance with 42 CFR 412.84(i)(1) and as also discussed in 
prior rulemaking (84 FR 42630). For example, a hospital could use these 
existing administrative mechanisms to request a CCR closer to 1.0. We 
appreciate the commenters' requests regarding the creation of new cost 
centers and may consider this request in future rulemaking. However, we 
believe that such a step is not necessary at this time given that 
hospitals are not precluded from setting their charges consistent with 
their CCRs and the existing administrative mechanisms for hospitals to 
request CCR changes consistent with lower charges.
    We also note that some commenters requested additional 
clarifications regarding billing instructions for CAR T-cell therapies, 
for example, relating to the use of hospital charges in apportioning 
costs under section 2203 of the Provider Reimbursement Manual. We do 
not believe changes to billing guidance are needed at this time but 
will take these comments into consideration when developing policies 
and program requirements for future years for CAR T-cell therapy 
policy.
    After consideration of the public comments received, we are 
finalizing our proposal regarding the calculation of the relative 
weight for MS-DRG 018.
3. Development of National Average CCRs
    Consistent with our final policy to use the FY 2019 data for the FY 
2022 ratesetting, as discussed earlier in this section, we are 
finalizing our proposal to continue to use the national average CCRs 
that were calculated for the FY 2021 final rule using that same data. 
Specifically, we calculated these national average CCRs as follows:
    Using the FY 2018 cost report data, we removed CAHs, Indian Health 
Service hospitals, all-inclusive rate hospitals, and cost reports that 
represented time periods of less than 1 year (365 days). We included 
hospitals located in Maryland because we include their charges in our 
claims database. Then we created CCRs for each provider for each cost 
center (see the supplemental data file for line items used in the 
calculations) and removed any CCRs that were greater than 10 or less 
than 0.01. We normalized the departmental CCRs by dividing the CCR for 
each department by the total CCR for the hospital for the purpose of 
trimming the data. Then we took the logs of the normalized cost center 
CCRs and removed any cost center CCRs where the log of the cost center 
CCR was greater or less than the mean log plus/minus 3 times the 
standard deviation for the log of that cost center CCR. Once the

[[Page 44966]]

cost report data were trimmed, we calculated a Medicare-specific CCR. 
The Medicare-specific CCR was determined by taking the Medicare charges 
for each line item from Worksheet D-3 and deriving the Medicare-
specific costs by applying the hospital-specific departmental CCRs to 
the Medicare-specific charges for each line item from Worksheet D-3. 
Once each hospital's Medicare-specific costs were established, we 
summed the total Medicare-specific costs and divided by the sum of the 
total Medicare-specific charges to produce national average, charge-
weighted CCRs.
    After we multiplied the total charges for each MS-DRG in each of 
the 19 cost centers by the corresponding national average CCR, we 
summed the 19 ``costs'' across each MS-DRG to produce a total 
standardized cost for the MS-DRG. The average standardized cost for 
each MS-DRG was then computed as the total standardized cost for the 
MS-DRG divided by the transfer-adjusted case count for the MS-DRG. The 
average cost for each MS-DRG was then divided by the national average 
standardized cost per case to determine the relative weight. The FY 
2022 cost-based relative weights were then normalized by an adjustment 
factor of 1.820829 so that the average case weight after recalibration 
was equal to the average case weight before recalibration. The 
normalization adjustment is intended to ensure that recalibration by 
itself neither increases nor decreases total payments under the IPPS, 
as required by section 1886(d)(4)(C)(iii) of the Act.
    The 19 national average CCRs for FY 2022 are as follows:
BILLING CODE 4120-01-P
[GRAPHIC] [TIFF OMITTED] TR13AU21.153

    Since FY 2009, the relative weights have been based on 100 percent 
cost weights based on our MS-DRG grouping system. When we recalibrated 
the DRG weights for previous years, we set a threshold of 10 cases as 
the minimum number of cases required to compute a reasonable weight. We 
used that same case threshold in recalibrating the MS-DRG relative 
weights for FY 2022. Using data from the FY 2019 MedPAR file, there 
were 7 MS-DRGs that contain fewer than 10 cases. For FY 2022, because 
we do not have sufficient MedPAR data to set accurate and stable cost 
relative weights for these low-volume MS-DRGs, we proposed to compute 
relative weights for the low-volume MS-DRGs by adjusting their final FY 
2021 relative weights by the percentage change in the average weight of 
the cases in other MS-DRGs from FY 2021 to FY 2022. The crosswalk table 
is as follows:

[[Page 44967]]

[GRAPHIC] [TIFF OMITTED] TR13AU21.154

BILLING CODE 4120-01-C
    We did not receive any public comments on our proposals and we are 
finalizing our proposals without modification.

F. Add-On Payments for New Services and Technologies for FY 2022

1. Background
    Sections 1886(d)(5)(K) and (L) of the Act establish a process of 
identifying and ensuring adequate payment for new medical services and 
technologies (sometimes collectively referred to in this section as 
``new technologies'') under the IPPS. Section 1886(d)(5)(K)(vi) of the 
Act specifies that a medical service or technology will be considered 
new if it meets criteria established by the Secretary after notice and 
opportunity for public comment. Section 1886(d)(5)(K)(ii)(I) of the Act 
specifies that a new medical service or technology may be considered 
for new technology add-on payment if, based on the estimated costs 
incurred with respect to discharges involving such service or 
technology, the DRG prospective payment rate otherwise applicable to 
such discharges under this subsection is inadequate. We note that, 
beginning with discharges occurring in FY 2008, CMS transitioned from 
CMS-DRGs to MS-DRGs. The regulations at 42 CFR 412.87 implement these 
provisions and 42 CFR 412.87(b) specifies three criteria for a new 
medical service or technology to receive the additional payment: (1) 
The medical service or technology must be new; (2) the medical service 
or technology must be costly such that the DRG rate otherwise 
applicable to discharges involving the medical service or technology is 
determined to be inadequate; and (3) the service or technology must 
demonstrate a substantial clinical improvement over existing services 
or technologies. In addition, certain transformative new devices and 
antimicrobial products may qualify under an alternative inpatient new 
technology add-on payment pathway, as set forth in the regulations at 
Sec.  412.87(c) and (d). We note that section 1886(d)(5)(K)(i) of the 
Act requires that the Secretary establish a mechanism to recognize the 
costs of new medical services and technologies under the payment system 
established under that subsection, which establishes the system for 
paying for the operating costs of inpatient hospital services. The 
system of payment for capital costs is established under section 
1886(g) of the Act. Therefore, as discussed in prior rulemaking (72 FR 
47307 through 47308), we do not include capital costs in the add-on 
payments for a new medical service or technology or make new technology 
add-on payments under the IPPS for capital-related costs. In this rule, 
we highlight some of the major statutory and regulatory provisions 
relevant to the new technology add-on payment criteria, as well as 
other information. For a complete discussion of the new technology add-
on payment criteria, we refer readers to the FY 2012 IPPS/LTCH PPS 
final rule (76 FR 51572 through 51574), FY 2020 IPPS/LTCH PPS final 
rule (84 FR 42288 through 42300) and the FY 2021 IPPS/LTCH PPS final 
rule (85 FR 58736 through 58742).
a. New Technology Add-On Payment Criteria
(1) Newness Criterion
    Under the first criterion, as reflected in Sec.  412.87(b)(2), a 
specific medical service or technology will no longer be considered 
``new'' for purposes of new medical service or technology add-on 
payments after CMS has recalibrated the MS-DRGs, based on available 
data, to reflect the cost of the technology. We note that we do not 
consider a service or technology to be new if it is substantially 
similar to one or more existing technologies. That is, even if a 
medical product receives a new FDA approval or clearance, it may not 
necessarily be considered ``new'' for purposes of new technology add-on 
payments if it is ``substantially similar'' to another medical product 
that was approved or cleared by FDA and has been on the market for more 
than 2 to 3 years. In the FY 2010 IPPS/RY 2010 LTCH PPS final rule (74 
FR 43813 through 43814), we established criteria for evaluating whether 
a new technology is substantially similar to an existing technology, 
specifically: (1) Whether a product uses the same or a similar 
mechanism of action to achieve a therapeutic outcome; (2) whether a 
product is assigned to the same or a different MS-DRG; and (3) whether 
the new use of the technology involves the treatment of the same or 
similar type of disease and the same or similar patient population. If 
a technology meets all three of these criteria, it would be considered 
substantially similar to an existing technology and would not be 
considered ``new'' for purposes of new technology add-on payments. For 
a detailed discussion of the criteria for substantial similarity, we 
refer readers to the FY 2006 IPPS final rule (70 FR 47351 through 
47352) and the FY 2010 IPPS/LTCH PPS final rule (74 FR 43813 through 
43814).
(2) Cost Criterion
    Under the second criterion, Sec.  412.87(b)(3) further provides 
that, to be eligible for the add-on payment for new medical services or 
technologies, the MS-DRG prospective payment rate otherwise applicable 
to discharges involving the new medical service or technology must be 
assessed for adequacy. Under the cost criterion, consistent with the 
formula specified in section 1886(d)(5)(K)(ii)(I) of the Act, to assess 
the adequacy of payment for a new technology paid under the applicable 
MS-DRG prospective

[[Page 44968]]

payment rate, we evaluate whether the charges of the cases involving a 
new medical service or technology will exceed a threshold amount that 
is the lesser of 75 percent of the standardized amount (increased to 
reflect the difference between cost and charges) or 75 percent of one 
standard deviation beyond the geometric mean standardized charge for 
all cases in the MS-DRG to which the new medical service or technology 
is assigned (or the case-weighted average of all relevant MS-DRGs if 
the new medical service or technology occurs in many different MS-
DRGs). The MS-DRG threshold amounts generally used in evaluating new 
technology add-on payment applications for FY 2022 are presented in a 
data file that is available, along with the other data files associated 
with the FY 2021 IPPS/LTCH PPS final rule and correction notice, on the 
CMS website at: https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/AcuteInpatientPPS/index.
    We note that, under the policy finalized in the FY 2021 IPPS/LTCH 
PPS final rule (85 FR 58603 through 58605), beginning with FY 2022, we 
use the proposed threshold values associated with the proposed rule for 
that fiscal year to evaluate the cost criterion for all applications 
for new technology add-on payments and previously approved technologies 
that may continue to receive new technology add-on payments, if those 
technologies would be assigned to a proposed new MS-DRG for that same 
fiscal year.
    As finalized in the FY 2019 IPPS/LTCH PPS final rule (83 FR 41275), 
beginning with FY 2020, we include the thresholds applicable to the 
next fiscal year (previously included in Table 10 of the annual IPPS/
LTCH PPS proposed and final rules) in the data files associated with 
the prior fiscal year. Accordingly, the proposed thresholds for 
applications for new technology add-on payments for FY 2023 were 
presented in a data file that is available on the CMS website, along 
with the other data files associated with the FY 2022 proposed rule, by 
clicking on the FY 2022 IPPS Proposed Rule Home Page at: https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/AcuteInpatientPPS/index. We note, for the reasons discussed in section 
I.F. of the preamble of the proposed rule and this final rule, we 
proposed to use the FY 2019 MedPAR claims data where we ordinarily 
would have used the FY 2020 MedPAR claims data for purposes of proposed 
FY 2022 ratesetting. We refer the reader to section I.F. of the 
preamble of this final rule for further discussion of our analysis of 
the best available data for FY 2022 ratesetting and our related 
proposals, as well as our finalized policy to use the FY 2019 MedPAR 
claims data where we ordinarily would have used the FY 2020 MedPAR 
claims data for purposes of FY 2022 ratesetting. For the FY 2023 
proposed threshold values, consistent with our proposal, we proposed to 
use FY 2019 claims data to evaluate whether the charges of the cases 
involving a new medical service or technology will exceed a threshold 
amount that is the lesser of 75 percent of the proposed FY 2022 
standardized amount (increased to reflect the difference between cost 
and charges) or 75 percent of one standard deviation beyond the 
geometric mean standardized charge (using FY 2019 claims data) for all 
cases in the MS-DRG (using FY 2019 claims data) to which the new 
medical service or technology is assigned (or the case-weighted average 
of all relevant MS-DRGs if the new medical service or technology occurs 
in many different MS-DRGs), rather than the FY 2020 data we would 
otherwise use. As discussed in section I.F. of the preamble of this 
final rule, we also considered, as an alternative to our proposal, the 
use of the same FY 2020 data that we would ordinarily use for purposes 
of FY 2022 ratesetting. We stated that if we were to finalize this 
alternative approach for FY 2022, we would use the FY 2020 claims data 
for purposes of the final thresholds for applications for new 
technology add-on payments for FY 2023 in the FY 2022 IPPS/LTCH PPS 
final rule. We made available the threshold values calculated using the 
FY 2020 claims data at https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/AcuteInpatientPPS.
    As discussed in section I.F. of the preamble of this final rule, we 
are finalizing our proposal to use the FY 2019 MedPAR claims data where 
we ordinarily would have used the FY 2020 MedPAR claims data for 
purposes of FY 2022 ratesetting. Accordingly, consistent with this 
final policy, we are finalizing to use FY 2019 claims data to set the 
thresholds for applications for new technology add-on payments for FY 
2023 in this final rule. The finalized thresholds for applications for 
new technology add-on payments for FY 2023 are presented in a data file 
that is available on the CMS website, along with the other data files 
associated with this FY 2022 final rule, by clicking on the FY 2022 
IPPS Final Rule Home Page at: https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/AcuteInpatientPPS/index.
    In the September 7, 2001 final rule that established the new 
technology add-on payment regulations (66 FR 46917), we discussed that 
applicants should submit a significant sample of data to demonstrate 
that the medical service or technology meets the high-cost threshold. 
Specifically, applicants should submit a sample of sufficient size to 
enable us to undertake an initial validation and analysis of the data. 
We also discussed in the September 7, 2001 final rule (66 FR 46917) the 
issue of whether the Health Insurance Portability and Accountability 
Act (HIPAA) Privacy Rule at 45 CFR parts 160 and 164 applies to claims 
information that providers submit with applications for new medical 
service or technology add-on payments. We refer readers to the FY 2012 
IPPS/LTCH PPS final rule (76 FR 51573) for complete information on this 
issue.
(3) Substantial Clinical Improvement Criterion
    Under the third criterion at Sec.  412.87(b)(1), a medical service 
or technology must represent an advance that substantially improves, 
relative to technologies previously available, the diagnosis or 
treatment of Medicare beneficiaries. In the FY 2020 IPPS/LTCH PPS final 
rule (84 FR 42288 through 42292), we prospectively codified in our 
regulations at Sec.  412.87(b) the following aspects of how we evaluate 
substantial clinical improvement for purposes of new technology add-on 
payments under the IPPS:
     The totality of the circumstances is considered when 
making a determination that a new medical service or technology 
represents an advance that substantially improves, relative to services 
or technologies previously available, the diagnosis or treatment of 
Medicare beneficiaries.
     A determination that a new medical service or technology 
represents an advance that substantially improves, relative to services 
or technologies previously available, the diagnosis or treatment of 
Medicare beneficiaries means--
    ++ The new medical service or technology offers a treatment option 
for a patient population unresponsive to, or ineligible for, currently 
available treatments;
    ++ The new medical service or technology offers the ability to 
diagnose a medical condition in a patient population where that medical 
condition is currently undetectable, or offers the ability to diagnose 
a medical condition earlier in a patient population than allowed by 
currently available methods, and there must also be evidence that use 
of the new medical

[[Page 44969]]

service or technology to make a diagnosis affects the management of the 
patient;
    ++ The use of the new medical service or technology significantly 
improves clinical outcomes relative to services or technologies 
previously available as demonstrated by one or more of the following: A 
reduction in at least one clinically significant adverse event, 
including a reduction in mortality or a clinically significant 
complication; a decreased rate of at least one subsequent diagnostic or 
therapeutic intervention; a decreased number of future hospitalizations 
or physician visits; a more rapid beneficial resolution of the disease 
process treatment including, but not limited to, a reduced length of 
stay or recovery time; an improvement in one or more activities of 
daily living; an improved quality of life; or, a demonstrated greater 
medication adherence or compliance; or
    ++ The totality of the circumstances otherwise demonstrates that 
the new medical service or technology substantially improves, relative 
to technologies previously available, the diagnosis or treatment of 
Medicare beneficiaries.
     Evidence from the following published or unpublished 
information sources from within the United States or elsewhere may be 
sufficient to establish that a new medical service or technology 
represents an advance that substantially improves, relative to services 
or technologies previously available, the diagnosis or treatment of 
Medicare beneficiaries: Clinical trials, peer reviewed journal 
articles; study results; meta-analyses; consensus statements; white 
papers; patient surveys; case studies; reports; systematic literature 
reviews; letters from major healthcare associations; editorials and 
letters to the editor; and public comments. Other appropriate 
information sources may be considered.
     The medical condition diagnosed or treated by the new 
medical service or technology may have a low prevalence among Medicare 
beneficiaries.
     The new medical service or technology may represent an 
advance that substantially improves, relative to services or 
technologies previously available, the diagnosis or treatment of a 
subpopulation of patients with the medical condition diagnosed or 
treated by the new medical service or technology.
    We refer the reader to the FY 2020 IPPS/LTCH PPS final rule for 
additional discussion of the evaluation of substantial clinical 
improvement for purposes of new technology add-on payments under the 
IPPS.
    We note, consistent with the discussion in the FY 2003 IPPS final 
rule (67 FR 50015), that although we are affiliated with the FDA and we 
do not question the FDA's regulatory responsibility for decisions 
related to marketing authorization (for example, approval, clearance, 
etc.), we do not rely upon FDA criteria in our determination of what 
drugs, devices, or technologies qualify for new technology add-on 
payments under Medicare. Our criteria do not depend on the standard of 
safety and efficacy on which the FDA relies but on a demonstration of 
substantial clinical improvement in the Medicare population 
(particularly patients over age 65).
c. Alternative Inpatient New Technology Add-On Payment Pathway
    Beginning with applications for FY 2021 new technology add-on 
payments, under the regulations at Sec.  412.87(c), a medical device 
that is part of FDA's Breakthrough Devices Program may qualify for the 
new technology add-on payment under an alternative pathway. 
Additionally, under the regulations at Sec.  412.87(d) for certain 
antimicrobial products, beginning with FY 2021, a drug that is 
designated by the FDA as a Qualified Infectious Disease Product (QIDP), 
and, beginning with FY 2022, a drug that is approved by the FDA under 
the Limited Population Pathway for Antibacterial and Antifungal Drugs 
(LPAD), may also qualify for the new technology add-on payment under an 
alternative pathway. We refer the reader to the FY 2020 IPPS/LTCH PPS 
final rule (84 FR 42292 through 42297) and the FY 2021 IPPS/LTCH PPS 
final rule (85 FR 58737 through 58739) for a complete discussion on 
this policy. We note that a technology is not required to have the 
specified FDA designation at the time the new technology add-on payment 
application is submitted. CMS will review the application based on the 
information provided by the applicant under the alternative pathway 
specified by the applicant. However, to receive approval for the new 
technology add-on payment under that alternative pathway, the 
technology must have the applicable FDA designation and meet all other 
requirements in the regulations in Sec.  412.87(c) and (d), as 
applicable.
(1) Alternative Pathway for Certain Transformative New Devices
    For applications received for new technology add-on payments for FY 
2021 and subsequent fiscal years, if a medical device is part of FDA's 
Breakthrough Devices Program and received FDA marketing authorization, 
it will be considered new and not substantially similar to an existing 
technology for purposes of the new technology add-on payment under the 
IPPS, and will not need to meet the requirement under Sec.  
412.87(b)(1) that it represent an advance that substantially improves, 
relative to technologies previously available, the diagnosis or 
treatment of Medicare beneficiaries. This policy is codified at Sec.  
412.87(c). Under this alternative pathway, a medical device that has 
received FDA marketing authorization (that is, has been approved or 
cleared by, or had a De Novo classification request granted by, FDA) 
and that is part of FDA's Breakthrough Devices Program will need to 
meet the cost criterion under Sec.  412.87(b)(3), and will be 
considered new as reflected in Sec.  412.87(c)(2). We note, in the FY 
2021 IPPS/LTCH PPS final rule (85 FR 58734 through 58736), we clarified 
our policy that a new medical device under this alternative pathway 
must receive marketing authorization for the indication covered by the 
Breakthrough Devices Program designation. We refer the reader to the FY 
2021 IPPS/LTCH PPS final rule (85 FR 58734 through 58736) for a 
complete discussion regarding this clarification.
(2) Alternative Pathway for Certain Antimicrobial Products
    For applications received for new technology add-on payments for 
certain antimicrobial products, beginning with FY 2021, if a technology 
is designated by FDA as a QIDP and received FDA marketing 
authorization, and, beginning with FY 2022, if a drug is approved under 
FDA's LPAD pathway and used for the indication approved under the LPAD 
pathway, it will be considered new and not substantially similar to an 
existing technology for purposes of new technology add-on payments and 
will not need to meet the requirement that it represent an advance that 
substantially improves, relative to technologies previously available, 
the diagnosis or treatment of Medicare beneficiaries. We codified this 
policy at Sec.  412.87(d). Under this alternative pathway for QIDPs and 
LPADs, a medical product that has received FDA marketing authorization 
and is designated by FDA as a QIDP or approved under the LPAD pathway 
will need to meet the cost criterion under Sec.  412.87(b)(3), and will 
be considered new as reflected in Sec.  412.87(d)(2).
    We refer the reader to the FY 2020 IPPS/LTCH PPS final rule (84 FR 
42292 through 42297) and FY 2021 IPPS/LTCH PPS final rule (85 FR 58737 
through 58739) for a complete discussion on this policy. We note, in 
the FY 2021 IPPS/LTCH PPS final rule (85 FR 58737

[[Page 44970]]

through 58739), we clarified that a new medical product seeking 
approval for the new technology add-on payment under the alternative 
pathway for QIDPs must receive marketing authorization for the 
indication covered by the QIDP designation. We also finalized our 
policy to expand our alternative new technology add-on payment pathway 
for certain antimicrobial products to include products approved under 
the LPAD pathway and used for the indication approved under the LPAD 
pathway.
d. Additional Payment for New Medical Service or Technology
    The new medical service or technology add-on payment policy under 
the IPPS provides additional payments for cases with relatively high 
costs involving eligible new medical services or technologies, while 
preserving some of the incentives inherent under an average-based 
prospective payment system. The payment mechanism is based on the cost 
to hospitals for the new medical service or technology. As noted 
previously, we do not include capital costs in the add-on payments for 
a new medical service or technology or make new technology add-on 
payments under the IPPS for capital-related costs (72 FR 47307 through 
47308).
    For discharges occurring before October 1, 2019, under Sec.  
412.88, if the costs of the discharge (determined by applying operating 
cost-to-charge ratios (CCRs) as described in Sec.  412.84(h)) exceed 
the full DRG payment (including payments for IME and DSH, but excluding 
outlier payments), CMS made an add-on payment equal to the lesser of: 
(1) 50 Percent of the costs of the new medical service or technology; 
or (2) 50 percent of the amount by which the costs of the case exceed 
the standard DRG payment.
    Beginning with discharges on or after October 1, 2019, for the 
reasons discussed in the FY 2020 IPPS/LTCH PPS final rule (84 FR 42297 
through 42300), we finalized an increase in the new technology add-on 
payment percentage, as reflected at Sec.  412.88(a)(2)(ii). 
Specifically, for a new technology other than a medical product 
designated by FDA as a QIDP, beginning with discharges on or after 
October 1, 2019, if the costs of a discharge involving a new technology 
(determined by applying CCRs as described in Sec.  412.84(h)) exceed 
the full DRG payment (including payments for IME and DSH, but excluding 
outlier payments), Medicare will make an add-on payment equal to the 
lesser of: (1) 65 Percent of the costs of the new medical service or 
technology; or (2) 65 percent of the amount by which the costs of the 
case exceed the standard DRG payment. For a new technology that is a 
medical product designated by FDA as a QIDP, beginning with discharges 
on or after October 1, 2019, if the costs of a discharge involving a 
new technology (determined by applying CCRs as described in Sec.  
412.84(h)) exceed the full DRG payment (including payments for IME and 
DSH, but excluding outlier payments), Medicare will make an add-on 
payment equal to the lesser of: (1) 75 Percent of the costs of the new 
medical service or technology; or (2) 75 percent of the amount by which 
the costs of the case exceed the standard DRG payment. For a new 
technology that is a medical product approved under FDA's LPAD pathway, 
beginning with discharges on or after October 1, 2020, if the costs of 
a discharge involving a new technology (determined by applying CCRs as 
described in Sec.  412.84(h)) exceed the full DRG payment (including 
payments for IME and DSH, but excluding outlier payments), Medicare 
will make an add-on payment equal to the lesser of: (1) 75 Percent of 
the costs of the new medical service or technology; or (2) 75 percent 
of the amount by which the costs of the case exceed the standard DRG 
payment. As set forth in Sec.  412.88(b)(2), unless the discharge 
qualifies for an outlier payment, the additional Medicare payment will 
be limited to the full MS-DRG payment plus 65 percent (or 75 percent 
for certain antimicrobial products (QIDPs and LPADs)) of the estimated 
costs of the new technology or medical service.
    We refer the reader to the FY 2020 IPPS/LTCH PPS final rule (84 FR 
42297 through 42300) for complete discussion on the increase in the new 
technology add on payment beginning with discharges on or after October 
1, 2019.
    Section 503(d)(2) of Public Law 108-173 provides that there shall 
be no reduction or adjustment in aggregate payments under the IPPS due 
to add-on payments for new medical services and technologies. 
Therefore, in accordance with section 503(d)(2) of Public Law 108-173, 
add-on payments for new medical services or technologies for FY 2005 
and subsequent years have not been subjected to budget neutrality.
e. Evaluation of Eligibility Criteria for New Medical Service or 
Technology Applications
    In the FY 2009 IPPS final rule (73 FR 48561 through 48563), we 
modified our regulations at Sec.  412.87 to codify our longstanding 
practice of how CMS evaluates the eligibility criteria for new medical 
service or technology add-on payment applications. That is, we first 
determine whether a medical service or technology meets the newness 
criterion, and only if so, do we then make a determination as to 
whether the technology meets the cost threshold and represents a 
substantial clinical improvement over existing medical services or 
technologies. We specified that all applicants for new technology add-
on payments must have FDA approval or clearance by July 1 of the year 
prior to the beginning of the fiscal year for which the application is 
being considered. In the FY 2021 IPPS final rule, to more precisely 
describe the various types of FDA approvals, clearances and 
classifications that we consider under our new technology add-on 
payment policy, we finalized a technical clarification to the 
regulation to indicate that new technologies must receive FDA marketing 
authorization (such as pre-market approval (PMA); 510(k) clearance; the 
granting of a De Novo classification request, or approval of a New Drug 
Application (NDA)) by July 1 of the year prior to the beginning of the 
fiscal year for which the application is being considered. Consistent 
with our longstanding policy, we consider FDA marketing authorization 
as representing that a product has received FDA approval or clearance 
when considering eligibility for the new technology add-on payment 
under Sec.  412.87(e)(2) (85 FR 58742).
    Additionally, in the FY 2021 IPPS final rule (85 FR 58739 through 
58742), we finalized our proposal to provide conditional approval for 
new technology add-on payment for a technology for which an application 
is submitted under the alternative pathway for certain antimicrobial 
products at Sec.  412.87(d) that does not receive FDA marketing 
authorization by the July 1 deadline specified in Sec.  412.87(e)(2), 
provided that the technology otherwise meets the applicable add-on 
payment criteria. Under this policy, cases involving eligible 
antimicrobial products would begin receiving the new technology add-on 
payment sooner, effective for discharges the quarter after the date of 
FDA marketing authorization provided that the technology receives FDA 
marketing authorization by July 1 of the particular fiscal year for 
which the applicant applied for new technology add-on payments.
f. Council on Technology and Innovation (CTI)
    The Council on Technology and Innovation at CMS oversees the 
agency's cross-cutting priority on coordinating coverage, coding and 
payment processes

[[Page 44971]]

for Medicare with respect to new technologies and procedures, including 
new drug therapies, as well as promoting the exchange of information on 
new technologies and medical services between CMS and other entities. 
The CTI, composed of senior CMS staff and clinicians, was established 
under section 942(a) of Public Law 108-173. The Council is co-chaired 
by the Director of the Center for Clinical Standards and Quality (CCSQ) 
and the Director of the Center for Medicare (CM), who is also 
designated as the CTI's Executive Coordinator.
    The specific processes for coverage, coding, and payment are 
implemented by CM, CCSQ, and the local Medicare Administrative 
Contractors (MACs) (in the case of local coverage and payment 
decisions). The CTI supplements, rather than replaces, these processes 
by working to assure that all of these activities reflect the agency-
wide priority to promote high-quality, innovative care. At the same 
time, the CTI also works to streamline, accelerate, and improve 
coordination of these processes to ensure that they remain up to date 
as new issues arise. To achieve its goals, the CTI works to streamline 
and create a more transparent coding and payment process, improve the 
quality of medical decisions, and speed patient access to effective new 
treatments. It is also dedicated to supporting better decisions by 
patients and doctors in using Medicare-covered services through the 
promotion of better evidence development, which is critical for 
improving the quality of care for Medicare beneficiaries.
    To improve the understanding of CMS' processes for coverage, 
coding, and payment and how to access them, the CTI has developed an 
``Innovator's Guide'' to these processes. The intent is to consolidate 
this information, much of which is already available in a variety of 
CMS documents and in various places on the CMS website, in a user 
friendly format. This guide was published in 2010 and is available on 
the CMS website at: https://www.cms.gov/Medicare/Coverage/
CouncilonTechInnov/Downloads/Innovators-Guide-Master-
7[dash]23[dash]15.pdf.
    As we indicated in the FY 2009 IPPS final rule (73 FR 48554), we 
invited any product developers or manufacturers of new medical services 
or technologies to contact the agency early in the process of product 
development if they have questions or concerns about the evidence that 
would be needed later in the development process for the agency's 
coverage decisions for Medicare.
    The CTI aims to provide useful information on its activities and 
initiatives to stakeholders, including Medicare beneficiaries, 
advocates, medical product manufacturers, providers, and health policy 
experts. Stakeholders with further questions about Medicare's coverage, 
coding, and payment processes, or who want further guidance about how 
they can navigate these processes, can contact the CTI at 
[email protected].
g. Application Information for New Medical Services or Technologies
    Applicants for add-on payments for new medical services or 
technologies for FY 2023 must submit a formal request, including a full 
description of the clinical applications of the medical service or 
technology and the results of any clinical evaluations demonstrating 
that the new medical service or technology represents a substantial 
clinical improvement (unless the application is under one of the 
alternative pathways as previously described), along with a significant 
sample of data to demonstrate that the medical service or technology 
meets the high-cost threshold. Complete application information, along 
with final deadlines for submitting a full application, will be posted 
as it becomes available on the CMS website at: https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/AcuteInpatientPPS/newtech.html. To allow interested parties to identify the new medical 
services or technologies under review before the publication of the 
proposed rule for FY 2023, the CMS website also will post the tracking 
forms completed by each applicant. We note that the burden associated 
with this information collection requirement is the time and effort 
required to collect and submit the data in the formal request for add-
on payments for new medical services and technologies to CMS. The 
aforementioned burden is subject to the PRA and approved under OMB 
control number 0938-1347.
    As discussed previously, in the FY 2020 IPPS/LTCH PPS final rule, 
we adopted an alternative inpatient new technology add-on payment 
pathway for certain transformative new devices and for Qualified 
Infectious Disease Products, as set forth in the regulations at Sec.  
412.87(c) and (d). The change in burden associated with these changes 
to the new technology add-on payment application process were discussed 
in a revision of the information collection requirement (ICR) request 
currently approved under OMB control number 0938-1347. In accordance 
with the implementing regulations of the PRA, we detailed the revisions 
of the ICR and published the required 60-day notice on August 15, 2019 
(84 FR 41723) and 30-day notice on December 17, 2019 (84 FR 68936) to 
solicit public comments.
2. Public Input Before Publication of a Notice of Proposed Rulemaking 
on Add-On Payments
    Section 1886(d)(5)(K)(viii) of the Act, as amended by section 
503(b)(2) of Public Law 108-173, provides for a mechanism for public 
input before publication of a notice of proposed rulemaking regarding 
whether a medical service or technology represents a substantial 
clinical improvement or advancement. The process for evaluating new 
medical service and technology applications requires the Secretary to--
     Provide, before publication of a proposed rule, for public 
input regarding whether a new service or technology represents an 
advance in medical technology that substantially improves the diagnosis 
or treatment of Medicare beneficiaries;
     Make public and periodically update a list of the services 
and technologies for which applications for add-on payments are 
pending;
     Accept comments, recommendations, and data from the public 
regarding whether a service or technology represents a substantial 
clinical improvement; and
     Provide, before publication of a proposed rule, for a 
meeting at which organizations representing hospitals, physicians, 
manufacturers, and any other interested party may present comments, 
recommendations, and data regarding whether a new medical service or 
technology represents a substantial clinical improvement to the 
clinical staff of CMS.
    In order to provide an opportunity for public input regarding add-
on payments for new medical services and technologies for FY 2022 prior 
to publication of the FY 2022 IPPS/LTCH PPS proposed rule, we published 
a notice in the Federal Register on October 16, 2020 (85 FR 65815), and 
held a virtual town hall meeting on December 15 and 16, 2020. In the 
announcement notice for the meeting, we stated that the opinions and 
presentations provided during the meeting would assist us in our 
evaluations of applications by allowing public discussion of the 
substantial clinical improvement criterion for the FY 2022 new medical 
service and technology add on payment applications before the 
publication of the FY 2022 IPPS/LTCH PPS proposed rule.

[[Page 44972]]

    Approximately 330 individuals registered to attend the 2-day 
virtual town hall meeting. We posted the recordings of the 2-day 
virtual town hall on the CMS web page at: https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/AcuteInpatientPPS/newtech. We 
considered each applicant's presentation made at the town hall meeting, 
as well as written comments received by the December 28, 2020 deadline, 
in our evaluation of the new technology add-on payment applications for 
FY 2022 in the development of the FY 2022 IPPS/LTCH PPS proposed rule.
    In response to the published notice and the December 15-16, 2020 
New Technology Town Hall meeting, we received written comments 
regarding the applications for FY 2022 new technology add on payments. 
As explained earlier and in the Federal Register notice announcing the 
New Technology Town Hall meeting (85 FR 65815 through 65817), the 
purpose of the meeting was specifically to discuss the substantial 
clinical improvement criterion with regard to pending new technology 
add-on payment applications for FY 2022. Therefore, we did not 
summarize the written comments in the proposed rule that were unrelated 
to the substantial clinical improvement criterion. In section II.H.5. 
of the preamble of the proposed rule, we summarized comments regarding 
individual applications, or, if applicable, indicated that there were 
no comments received in response to the New Technology Town Hall 
meeting notice or New Technology Town Hall meeting, at the end of each 
discussion of the individual applications.
3. ICD-10-PCS Section ``X'' Codes for Certain New Medical Services and 
Technologies
    As discussed in the FY 2016 IPPS/LTCH PPS final rule (80 FR 49434), 
the ICD-10-PCS includes a new section containing the new Section ``X'' 
codes, which began being used with discharges occurring on or after 
October 1, 2015. Decisions regarding changes to ICD-10-PCS Section 
``X'' codes will be handled in the same manner as the decisions for all 
of the other ICD-10-PCS code changes. That is, proposals to create, 
delete, or revise Section ``X'' codes under the ICD-10-PCS structure 
will be referred to the ICD-10 Coordination and Maintenance Committee. 
In addition, several of the new medical services and technologies that 
have been, or may be, approved for new technology add-on payments may 
now, and in the future, be assigned a Section ``X'' code within the 
structure of the ICD-10-PCS. We posted ICD-10-PCS Guidelines on the CMS 
website at: https://www.cms.gov/medicare/icd-10/2021-icd-10-pcs, 
including guidelines for ICD-10-PCS Section ``X'' codes. We encourage 
providers to view the material provided on ICD-10-PCS Section ``X'' 
codes.
4. FY 2022 Status of Technologies Approved for FY 2021 New Technology 
Add-On Payments
    In this section of the final rule, we discuss the proposed FY 2022 
status of 23 technologies approved for FY 2021 new technology add-on 
payments, and our finalized policies, as set forth in the tables that 
follow. In general, we extend new technology add-on payments for an 
additional year only if the 3-year anniversary date of the product's 
entry onto the U.S. market occurs in the latter half of the upcoming 
fiscal year. We refer the reader to section II.F.6.b.(1). of the 
preamble of this final rule for discussion of CONTEPO, which we 
conditionally approved for FY 2021 new technology add-on payments under 
the alternative pathway for certain antimicrobial products, subject to 
the technology receiving FDA marketing authorization by July 1, 2021. 
We note that CONTEPO did not receive FDA marketing authorization by 
July 1, 2021. As discussed in section II.F.6.b.(1). of the preamble of 
this final rule, because the applicant for CONTEPO submitted a new 
application for FY 2022, we are conditionally approving CONTEPO for FY 
2022 new technology add-on payments under the alternative pathway for 
certain antimicrobial products, subject to the technology receiving FDA 
marketing authorization by July 1, 2022.
a. Continuation of New Technology Add-On Payments for FY 2022 for 
Technologies Still Considered to be New
    In the table in section II.F (Proposed Add-On Payments for New 
Services and Technologies for FY 2022) of the proposed rule (86 FR 
25208 through 25211), we presented our proposals to continue the new 
technology add-on payment for FY 2022 for those technologies that were 
approved for the new technology add-on payment for FY 2021 and which 
would still be considered ``new'' for purposes of new technology add-on 
payments for FY 2022.
    Our policy is that a medical service or technology may continue to 
be considered ``new'' for purposes of new technology add-on payments 
within 2 or 3 years after the point at which data begin to become 
available reflecting the inpatient hospital code assigned to the new 
service or technology. Our practice has been to begin and end new 
technology add-on payments on the basis of a fiscal year, and we have 
generally followed a guideline that uses a 6-month window before and 
after the start of the fiscal year to determine whether to extend the 
new technology add-on payment for an additional fiscal year. In 
general, we extend new technology add-on payments for an additional 
year only if the 3-year anniversary date of the product's entry onto 
the U.S. market occurs in the latter half of the fiscal year (70 FR 
47362).
    In the proposed rule, we provided a table listing the technologies 
for which we proposed to continue making new technology add-on payments 
for FY 2022 because they would still be considered new for purposes of 
new technology add-on payments (86 FR 25209). This table also presented 
the newness start date, new technology add-on payment start date, 
relevant final rule citations from prior fiscal years, proposed maximum 
add-on payment amount, and coding assignments. We referred readers to 
the cited final rules in the table for a complete discussion of the new 
technology add-on payment application, coding and payment amount for 
these technologies, including the applicable indications and discussion 
of the newness start date.
    We summarize in this section of this final rule the comments we 
received regarding our proposal to continue making new technology add-
on payments for FY 2022 for the technologies listed in the table in the 
proposed rule because they would still be considered new for purposes 
of new technology add-on payments.
    Comment: Commenters overwhelmingly supported our proposed 
continuation of new technology add-on payments for FY 2022 for those 
technologies that were approved for the new technology add-on payment 
for FY 2021 and which would still be considered ``new'' for purposes of 
new technology add-on payments for FY 2022.
    Response: We appreciate the commenters' support.
    Comment: A commenter, the applicant for Jakafi[supreg], requested 
the maximum new technology add-on payment amount for Jakafi[supreg] be 
updated from $4,096.21 to $6,885.20 to reflect the updated Wholesale 
Acquisition Cost (WAC) for 60 Jakafi tablets using a 14-day anticipated 
duration.
    Response: We appreciate the updated cost information from the 
applicant. Jakafi's current WAC is $14,754.00 per 60 tablets. The 
maximum NTAP, using

[[Page 44973]]

the WAC for 60 Jakafi tablets, determining the per tablet amount, 
multiplying that figure by two (Jakafi taken twice daily), and using a 
14 day anticipated duration, the average cost per case would change to 
$4,475.38 ($14,754.00/60 * 2 * 14) * .65. Based on this updated 
information, the maximum new technology add-on payment for 
Jakafi[supreg] for FY 2022 would be $4,475.38, as reflected in the 
table in this section.
    Comment: The manufacturer for Azedra[supreg] stated that the 
newness period for Azedra[supreg] should start with the first sale 
which would be June 6, 2019 instead of July 30, 2018. Based on this 
date, the commenter stated that the three-year anniversary of that date 
would be June 6, 2022, which would be in the latter half of FY 2022. 
The applicant noted that under longstanding CMS practice and policy, a 
technology generally receives an additional year of new technology add-
on payments if the third anniversary of the product's market entry date 
occurs in the latter half of the relevant fiscal year.
    The commenter added if CMS does not agree that the date of the 
first sale of Azedra[supreg] should be used as the date when the 
product became available on the market, then it believes that an 
appropriate alternative for the start date of Azedra's[supreg] market 
availability is May 21, 2019, as this was the date that the first doses 
of the product were delivered to be used as dosimetry doses for two 
patients who subsequently received their first therapeutic doses of 
Azedra[supreg] in June 2019 and July 2019, respectively. More 
specifically, the commenter explained that its records indicate that, 
prior to May 2019, it received but was not able to fulfill attempted 
orders for Azedra[supreg] due to lack of product availability. 
Accordingly, the records reflect that the first doses of Azedra[supreg] 
became available on the market in May 2019. The commenter confirmed, 
however, that the first orders of Azedra[supreg] that were fulfilled in 
May 2019 were used for dosimetry doses for two patients who, as noted, 
subsequently received their first therapeutic doses of Azedra[supreg] 
in June 2019 and July 2019, respectively. The first therapeutic doses 
of Azedra[supreg] were not available or possible to calculate until 
after the results of the dosimetry dose were obtained.
    Commenters also stated that CMS should finalize its proposal to 
continue Azedra's[supreg] new technology add-on payments for FY 2022 
even if CMS does not finalize its proposal to use the FY 2019 MedPAR 
claims data for the FY 2022 IPPS ratesetting. Commenters emphasized 
that the condition Azedra[supreg] is indicated to treat is exceedingly 
rare and as a result, use of Azedra[supreg] is quite infrequent. A 
commenter believes that the realities with respect to the nature of 
Azedra[supreg], the ultra-orphan condition it treats, and the 
infrequency of its use provide further support for the continuation of 
new technology add-on payments for Azedra[supreg] for FY 2022, 
particularly in light of the unique circumstances in FY 2020 and FY 
2021 related to utilization of hospital services because of the COVID-
19 pandemic and PHE. The commenter believes another year of new 
technology add-on payments for Azedra[supreg] will be critical for 
purposes of additional data collection and further opportunity for 
relevant MS-DRGs to adjust to the availability of this innovative, yet 
very infrequently used, therapy.
    Response: We thank the commenter for their comments and we agree 
that the newness date for Azedra[supreg] should begin on May 21, 2019. 
We believe Azedra[supreg] was available on the market beginning May 21, 
2019 rather than July 30, 2018 as May 21, 2019 was the date that the 
first doses of the product were delivered to be used. Based on the 
information available at the time, we indicated in the proposed rule 
that the newness date for Azedra[supreg] started on July 30, 2018 and 
we included Azedra[supreg] in our table of technologies that we 
proposed a one-year extension of new technology add-on payments for 
those technologies for which the new technology add-on payment would 
otherwise be discontinued. Based on the comment from the manufacturer, 
Azedra[supreg] is still new for FY 2022 and is eligible to continue new 
technology add-on payments for FY 2022 since the 3-year anniversary 
date of the entry of Azedra[supreg] onto the U.S. market (May 21, 2022) 
will occur in the second half of FY 2022. Therefore, we are including 
Azedra[supreg] in the table below for technologies that were approved 
for the new technology add-on payment for FY 2021 and that would still 
be considered ``new'' for purposes of new technology add-on payments 
for FY 2022. Finally, with regard to the comment about the FY 2020 
MedPAR data, we did not finalize use of the FY 2020 MedPAR data for the 
FY 2022 ratesetting and Azedra[supreg] is still new for FY 2022. Also, 
in the FY 2006 IPPS final rule (70 FR 47349), we state that case volume 
is not a relevant consideration for making the determination as to 
whether a product is new. We refer the reader to the FY 2006 IPPS final 
rule for a complete discussion on this.
    After consideration of the public comments we received, we are 
finalizing our proposal to continue new technology add-on payments for 
FY 2022 for the technologies that were approved for the new technology 
add-on payment for FY 2021 and that would still be considered ``new'' 
for purposes of new technology add-on payments for FY 2022, as listed 
in the proposed rule and in the following table in this section of this 
final rule. We note, the table below is the same as it was in the 
proposed rule, but the table in this final rule includes Azedra[supreg] 
and the updated cost information for Jakafi[supreg], as discussed 
previously. The following table also presents the newness start date, 
new technology add-on payment start date, relevant final rule citations 
from prior fiscal years, maximum add-on payment amount, and coding 
assignments. We refer readers to the cited final rules in the following 
table for a complete discussion of the new technology add-on payment 
application, coding and payment amount for these technologies, 
including the applicable indications and discussion of the newness 
start date.
BILLING CODE 4120-01-P

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[GRAPHIC] [TIFF OMITTED] TR13AU21.155


[[Page 44975]]


[GRAPHIC] [TIFF OMITTED] TR13AU21.156

BILLING CODE 4120-01-C
b. Extension of New Technology Add-On Payments
    Section 1886(d)(5)(K)(ii)(II) of the Act provides for the 
collection of data with respect to the costs of a new medical service 
or technology described in subclause (I) for a period of not less than 
2 years and not more than 3 years beginning on the date on which an 
inpatient hospital code is issued with respect to the service or 
technology. As explained in the FY 2005 IPPS final rule (69 FR 49002), 
the intent of section 1886(d)(5)(K) of the Act and regulations under 
Sec.  412.87(b)(2) is to pay for new medical services and technologies 
for the first 2 to 3 years that a product comes on the market, during 
the period when the costs of the new technology are not yet fully 
reflected in the DRG weights. Generally, we use FDA, marketing 
authorization (for example, approval of an NDA) as the indicator of the 
time when a technology begins to become available on the market and 
data reflecting the costs of the technology begin to become available 
for recalibration of the DRGs. The costs of the new medical service or 
technology, once paid for by Medicare for this 2-year to 3-year period, 
are accounted for in the MedPAR data that are used to recalibrate the 
DRG weights on an annual basis. Therefore, we limit the add-on payment 
window for those technologies that have passed this 2-to 3-year 
timeframe.
    As discussed in the FY 2006 IPPS final rule (70 FR 47349) and 
subsequent years, we do not believe that case volume is a relevant 
consideration for making the determination as to whether a product is 
``new.'' Consistent with the statute, a technology no longer qualifies 
as ``new'' once it is more than 2 to 3 years old, irrespective of how 
frequently it has been used in the Medicare population. Therefore, if a 
product is more than 2 to 3 years old, we have historically considered 
its costs to be included in the MS-DRG relative weights whether its use 
in the Medicare

[[Page 44976]]

population has been frequent or infrequent.
    However, in light of the unique circumstances for FY 2022 
ratesetting, for which we proposed to use the FY 2019 MedPAR claims 
data where we ordinarily would have used the FY 2020 MedPAR claims data 
for purposes of developing the FY 2022 relative weights, for the 
reasons discussed in section I.F. of the preamble of the proposed rule 
and this final rule, we stated in the proposed rule that we believe it 
may be appropriate to make a one-time exception to this long-standing 
policy for all technologies approved for new technology add-on payments 
for FY 2021, but for which the add-on payments would otherwise be 
discontinued beginning in FY 2022 because the technologies would no 
longer be considered new.
    As discussed in section I.F. of the preamble of the proposed rule 
and this final rule, ordinarily, the best available MedPAR data for 
ratesetting would be the most recent MedPAR file that contains claims 
from discharges for the fiscal year that is 2 years prior to the fiscal 
year that is the subject of the rulemaking. For FY 2022 ratesetting, 
under ordinary circumstances, the best available data would be the FY 
2020 MedPAR file. As discussed in section I.F. of the preamble of the 
proposed rule and this final rule, the FY 2020 MedPAR claims file 
contains data significantly impacted by the COVID-19 PHE, primarily in 
that the utilization of inpatient services was generally markedly 
different for certain types of services in FY 2020 than would have been 
expected in the absence of the PHE. Accordingly, we questioned whether 
the FY 2020 MedPAR claims file is the best available data to use for 
the FY 2022 ratesetting.
    In our discussion in section I.F. of the preamble of the proposed 
rule and this final rule, we highlighted two factors we considered in 
assessing which data sources would represent the best available data to 
use in the FY 2022 ratesetting. The first factor is whether the FY 2019 
data, which is from before the COVID-19 PHE, or the FY 2020 data, which 
includes the COVID-19 PHE time period, is a better overall 
approximation of the FY 2022 inpatient experience. After analyzing this 
issue, for the reasons discussed in section I.F. of the preamble of the 
proposed rule and this final rule, we stated in the proposed rule that 
we believe for purposes of the proposed rule that FY 2019 data are 
generally a better overall approximation of FY 2022. The second factor 
is to what extent the decision to use the FY 2019 or FY 2020 data 
differentially impacts the FY 2022 IPPS ratesetting. As discussed more 
fully in section I.F. of the preamble of the proposed rule and this 
final rule, after analyzing this issue, we determined that the decision 
does differentially impact the overall FY 2022 IPPS ratesetting. For 
example, we determined that the effect of the FY 2022 MS-DRG relative 
weights is more limited if the FY 2019-based weights are used rather 
than the FY 2020-based weights, should the FY 2022 inpatient experience 
not match the assumption used to calculate the MS-DRG relative weights.
    Based on our analyses, we proposed to use FY 2019 data for the FY 
2022 ratesetting for circumstances where the FY 2020 data is 
significantly impacted by the COVID-19 PHE. We stated in the proposed 
rule that because we believe the FY 2020 MedPAR claims data is 
significantly impacted by the COVID-19 PHE, we were proposing to use 
the FY 2019 MedPAR claims data for purposes where we ordinarily would 
have used the FY 2020 MedPAR claims data, including for purposes of 
developing the FY 2022 relative weights. We referred the reader to 
section I.F. of the preamble of the proposed rule for a further 
discussion on our analysis of the best available data for FY 2022 
ratesetting. We refer the reader to section I.F. of the preamble of 
this final rule for a discussion of our finalized policy on the use the 
FY 2019 data for the FY 2022 ratesetting.
    As discussed previously, in general, we extend new technology add-
on payments for an additional year only if the 3-year anniversary date 
of the product's entry onto the U.S. market occurs in the latter half 
of the upcoming fiscal year. We stated in the proposed rule that 
because we were proposing to use FY 2019 MedPAR data instead of FY 2020 
MedPAR data for the FY 2022 IPPS ratesetting, the costs for a new 
technology for which the 3-year anniversary date of the product's entry 
onto the U.S. market occurs prior to the latter half of the upcoming 
fiscal year (FY 2022) may not be fully reflected in the MedPAR data 
used to recalibrate the MS-DRG relative weights for FY 2022. Therefore, 
in light of our proposal to use FY 2019 data instead of FY 2020 data to 
develop the FY 2022 relative weights, we stated that we believe it 
would be appropriate to allow for a 1-year extension of new technology 
add-on payments for those technologies for which the new technology 
add-on payment would otherwise be discontinued beginning with FY 2022. 
Accordingly, we proposed to use our authority under section 
1886(d)(5)(I) of the Act to provide for a 1-year extension of new 
technology add-on payments for FY 2022 for those technologies listed in 
the table presented in section II.F of the proposed rule (86 FR 25213). 
We noted that if we were to finalize our alternative approach of using 
the same FY 2020 data that we would ordinarily use for purposes of FY 
2022 ratesetting, including development of the FY 2022 relative 
weights, as discussed in section I.F. of the preamble of the proposed 
rule and this final rule, we would also finalize to discontinue the new 
technology add-on payments for these expiring technologies beginning in 
FY 2022, consistent with our historic policies.
    We noted that the table in the proposed rule also presented the 
newness start date, new technology add-on payment start date, relevant 
final rule citations from prior fiscal years, proposed maximum add-on 
payment amount, and coding assignments for these technologies. We 
referred readers to the final rules cited in the table for a complete 
discussion of the new technology add-on payment application, coding and 
payment amount for these technologies, including the applicable 
indications and discussion of the newness start date.
    We invited public comment on our proposal to use our authority 
under section 1886(d)(5)(I) of the Act to provide for a 1-year 
extension of new technology add-on payments for FY 2022 for those 
technologies for which the new technology add-on payment would 
otherwise be discontinued beginning with FY 2022.
    We also noted with regard to ContaCT, which is a technology sold on 
a subscription basis, we continued to welcome comments from the public 
as to the appropriate method to determine a cost per case for 
technologies sold on a subscription basis, including comments on 
whether the cost per case should be estimated based on subscriber 
hospital data as described previously, and if so, whether the cost 
analysis should be updated based on the most recent subscriber data for 
each year for which the technology may be eligible for the new 
technology add-on payment.
    We summarize in this section the comments we received regarding our 
proposal to provide for a 1-year extension of new technology add-on 
payments for FY 2022 for those technologies listed in the table in the 
proposed rule for which the new technology add-on payment would 
otherwise be discontinued beginning with FY 2022.
    Comment: Commenters overwhelmingly supported our proposal to use FY 
2019 data instead of FY 2020

[[Page 44977]]

data to develop the FY 2022 relative weights and allow for a one-year 
extension of new technology add-on payments for those technologies for 
which the new technology add-on payment would otherwise be discontinued 
beginning with FY 2022.
    Response: We appreciate the commenters' support.
    Comment: We received a public comment from the applicants for 
NUZYRA[supreg] and IMFINZI[supreg] supporting our proposal to extend 
new technology add-on payments and requesting an additional extension 
for add-on payments through FY 2023. The applicant for IMFINZI[supreg] 
stated that CMS should evaluate the impact of the COVID 19 PHE on FY 
2021 MedPAR claims data to determine if FY 2019 data should also be 
utilized in lieu of FY 2021 data for FY 2023 rate-setting. The 
applicant for NUZYRA[supreg] asserted that this extension would align 
with CMS' analysis and acknowledgement in the proposed rule that claims 
data from FY 2020 may not be appropriate to use in determining 
prospective hospital payment in the future due to the extenuating 
circumstances surrounding the COVID public health crisis.
    Response: We thank the commenters for their comments. As noted, we 
proposed a one-year extension of new technology add-on payments for 
those technologies for which the new technology add-on payment would 
otherwise be discontinued beginning with FY 2022 because of our 
proposal to use FY 2019 data instead of FY 2020 data to develop the FY 
2022 relative weights. We refer the reader to the discussion in section 
I.F. of the preamble of this final rule for a discussion of our 
finalized policy on the use the FY 2019 data for the FY 2022 
ratesetting.
    Comment: A commenter stated that effective May 5, 2021, the new 
Wholesale Acquisition Cost (WAC) for ELZONRISTM is 
$28,065.44 and requested that CMS update the new technology add-on 
payment amount accordingly.
    Response: We appreciate the updated information from the applicant. 
Based on this updated information and the information regarding dosage 
in the FY 2020 IPPS/LTCH PPS final rule (84 FR 42237), the maximum new 
technology add-on payment for ELZONRISTM for FY 2022 would 
be $144,116.04, as reflected in the table in this section.
    Comment: We received a few comments on our request for comment 
regarding technologies sold on a subscription basis and whether the 
cost per case should be estimated based on subscriber hospital data, 
and if so, whether the cost analysis should be updated based on the 
most recent subscriber data for each year for which the technology may 
be eligible for the new technology add-on payment. Commenters agreed 
that in determining the cost per case for technologies seeking new 
technology add-on payment that utilize a subscription model, we should 
limit our analysis to subscriber hospitals and update the cost analysis 
on an annual basis. A commenter noted that alternative methodologies 
involving estimating the number of patients who would be eligible to 
receive treatment utilizing a technology sold on a subscription basis 
would be likely to result in a payment amount that does not adequately 
reflect the estimated average cost of such service or technology as 
required by the statute. The commenter believes that given the direct 
impact of utilization changes on cost per case when using a 
subscription model, it is reasonable for CMS to annually update the 
payment amount using the most recent subscriber utilization data.
    Response: We thank commenters for their comments and will take the 
comments into consideration in future rulemaking where applicable. CMS 
will continue to consider the issues pertaining to technologies sold on 
a subscription basis relative to the calculation of the cost per unit 
of these technologies including the merits of calculating the cost per 
case across all IPPS hospitals versus limiting the cost per case 
analysis to current users and whether the cost analysis should be 
updated based on the most recent subscriber data for each year for 
which the technology may be eligible for the new technology add-on 
payment, as we gain more experience in this area.
    However, for FY 2022, we believe the cost per case from the ContaCT 
applicant's original cost analysis is still appropriate to be used. 
Specifically, updated data from FY 2020 may be affected by the COVID-19 
PHE as noted in our discussion in section I.A. where we finalize our 
policy to use the FY 2019 MedPAR data instead of the FY 2020 data. The 
applicant estimated that the average cost of ContaCT to the hospital is 
$1,600 based on customer data (85 FR 58630). Based on this information, 
the maximum new technology add-on payment for a case involving the use 
of ContaCT continues to be $1,040 for FY 2022.
    As previously noted, we are finalizing our proposal to use FY 2019 
data instead of FY 2020 data to develop the FY 2022 relative weights, 
as discussed in section I.F of the preamble of this final rule. For the 
reasons discussed previously, in light of this final policy, and after 
consideration of the public comments received, we are finalizing our 
proposal to use our authority under section 1886(d)(5)(I) of the Act to 
allow for a 1-year extension of new technology add-on payments for FY 
2022 for the technologies listed in the proposed rule (except for 
Azedra[supreg] which is discussed above) and in the following table in 
this section of this final rule for which the new technology add-on 
payment would otherwise be discontinued beginning with FY 2022. As we 
discussed previously, because of the unique circumstances associated 
with ratesetting for FY 2022, we believe it is appropriate to make a 
one-time exception to our long-standing policy for all technologies 
approved for new technology add-on payments for FY 2021, but for which 
the add-on payments would otherwise be discontinued beginning in FY 
2022 because the technologies would no longer be considered new.
    The following table lists the technologies for which we are 
finalizing this 1-year extension of new technology add-on payments for 
FY 2022, including the newness start date, new technology add-on 
payment start date, relevant final rule citations from prior fiscal 
years, maximum add-on payment amount, and coding assignments. We refer 
readers to the cited final rules in the following table for a complete 
discussion of the new technology add-on payment application, coding and 
payment amount for these technologies, including the applicable 
indications and discussion of the newness start date.
BILLING CODE 4120-01-P

[[Page 44978]]

[GRAPHIC] [TIFF OMITTED] TR13AU21.157


[[Page 44979]]


[GRAPHIC] [TIFF OMITTED] TR13AU21.158

BILLING CODE 4120-01-C
5. FY 2022 Applications for New Technology Add-On Payments (Traditional 
Pathway)
    We received 26 applications for new technology add-on payments for 
FY 2022. Four applicants withdrew their applications prior to the 
issuance of the FY 2022 IPPS/LTCH PPS proposed rule. Five applicants, 
Iovance Biotherapeutics, Omeros Corporation, Mallinckrodt 
Pharmaceuticals, Janssen Biotech, Inc., and Vericel withdrew their 
applications for lifileucel, narsoplimab, TERLIVAZ (terlipressin), 
ciltacabtagene autoleucel, and Nexobrid respectively, prior to the 
issuance of this FY 2022 IPPS/LTCH PPS final rule. In addition, in 
accordance with the regulations under Sec.  412.87(c), applicants for 
new technology add-on payments must have FDA approval or clearance by 
July 1 of each year prior to the beginning of the fiscal year for which 
the application is being considered. One applicant, Ischemia Care, LLC 
for ISC-REST, did not receive FDA approval for its technology by July 
1, 2021. Therefore, ISC-REST is not eligible for consideration for new 
technology add-on payments for FY 2022. We are not including in this 
final rule the description and discussion of this application which was 
included in the FY 2022 IPPS/LTCH PPS proposed rule.
    We note that we received public comments on the applications for 
technologies that were withdrawn. However, because these technologies 
are ineligible for new technology add-on payments for FY 2022 because 
their applications were withdrawn, we are not summarizing nor 
responding to public comments regarding the new technology criteria for 
these technologies in this final rule. A discussion of the 16 remaining 
applications is presented below.
a. Aidoc Briefcase for PE
    Aidoc Medical Ltd. (Aidoc) applied for new technology add-on 
payments for Aidoc Briefcase for PE (``Briefcase for PE'') for FY 2022. 
According to the applicant, Briefcase for PE is an FDA cleared, 
artificial intelligence (AI)-based solution for triage and notification 
of suspected pulmonary embolism (PE) cases.
    The applicant stated that the device assists hospitals and 
radiologists by flagging and communicating suspected positive findings 
of PE in computed tomography (CT) pulmonary angiography (CTPA) 
examinations, which prompts the radiologist to assess relevant Digital 
Imaging and Communications in Medicine (DICOM) imaging files, allowing 
suspect cases to receive attention sooner than otherwise would have 
occurred, which in turn improves clinical outcomes. According to the 
applicant, patients with PE or suspected PE typically present at 
hospital emergency departments (EDs). The applicant stated that for 
these patients, ED physicians complete a brief evaluation and order 
imaging, which typically includes CTPA. With Briefcase for PE, CTPA 
images are automatically forwarded to the applicant's cloud-based 
engine where they are analyzed by an AI algorithm. The applicant claims 
that when Briefcase for PE detects a suspected PE, the radiologist is 
alerted via the user interface of the Aidoc Worklist Application that 
is installed on the radiologist's desktop. The applicant asserted that 
the notification prompts the radiologist to review the CTPA images and 
communicate with the emergency room team currently caring for the 
patient so that the appropriate clinical action may be taken sooner 
than it would otherwise have occurred in the absence of the tool.
    The applicant stated that acute PE is a severe manifestation of 
venous thromboembolism (VTE) and occurs when a blood clot (thrombus) 
forms in a vein and then dislodges and travels to the pulmonary 
arteries in the lungs. The applicant stated acute symptomatic PE can 
cause death within 1 hour of onset in up to 10 percent of cases\9\ and 
it is

[[Page 44980]]

estimated to be the third largest cause of cardiovascular death after 
coronary artery disease and stroke.10, 11, 12, 13 The 
applicant further noted that acute PE is a life-threatening medical 
emergency that demands urgent intervention and clinical studies have 
demonstrated a strong correlation between time to communication of PE 
findings, treatment, and clinical outcomes.14,15,16 
According to the applicant, in a typical workflow, a patient presenting 
to a hospital with signs or symptoms of PE would move through the 
system as follows: (1) Patient presents with suspected PE to the ED; 
(2) Patient receives contrast-enhanced CTPA imaging; (3) Technologist 
processes and reconstructs the CT images and manually routes them to 
the hospital picture archiving and communication system (PACS); (4) The 
exam enters a first-in-first-out (FIFO) reading queue, where it awaits 
radiological interpretation; (5) Radiologist reads the CT images and 
makes the diagnosis of PE; (6) The radiologist informs the referring 
physician of positive PE either verbally or through the radiologist 
report; (7) ED physician and/or on-call pulmonologist decide on the 
management strategy; (8) If appropriate, the patient proceeds to 
treatment.
---------------------------------------------------------------------------

    \9\ Naess IA, Christiansen SC, Romundstad P, Cannegieter SC, 
Rosendaal FR, Hammerstr[oslash]m J. Incidence and mortality of 
venous thrombosis: a population-based study. J Thromb Haemost. 2007 
Apr;5(4):692-9. doi: 10.1111/j.1538-7836.2007.02450.x. PMID: 
17367492.
    \10\ Giuntini C, Di Ricco G, Marini C, Melillo E, Palla A. 
Pulmonary embolism: Epidemiology. Chest. 1995 Jan;107(1 Suppl):3S-
9S. doi: 10.1378/chest.107.1_supplement.3s. PMID: 7813326.
    \11\ Becattini C, Agnelli G. Risk factors for adverse short-term 
outcome in patients with pulmonary embolism. Thromb Res. 2001 Sep 
15;103(6):V239-44. doi: 10.1016/s0049-3848(01)00291-2. PMID: 
11567661.
    \12\ Goldhaber SZ, Visani L, De Rosa M. Acute pulmonary 
embolism: Clinical outcomes in the International Cooperative 
Pulmonary Embolism Registry (ICOPER). Lancet. 1999 Apr 
24;353(9162):1386-9. doi: 10.1016/s0140-6736(98)07534-5. PMID: 
10227218.
    \13\ Klok FA, Mos IC, Huisman MV. Brain-type natriuretic peptide 
levels in the prediction of adverse outcome in patients with 
pulmonary embolism: A systematic review and meta-analysis. Am J 
Respir Crit Care Med. 2008 Aug 15;178(4):425-30. doi: 10.1164/
rccm.200803-459OC. Epub 2008 Jun 12. PMID: 18556626.
    \14\ Smith SB, Geske JB, Maguire JM, Zane NA, Carter RE, 
Morgenthaler TI. Early anticoagulation is associated with reduced 
mortality for acute pulmonary embolism. Chest. 2010 Jun;137(6):1382-
90. doi: 10.1378/chest.09-0959. Epub 2010 Jan 15. PMID: 20081101; 
PMCID: PMC3021363.
    \15\ Soh S, Kim JM, Park JH, Koh SO, Na S. Delayed 
anticoagulation is associated with poor outcomes in high-risk acute 
pulmonary embolism. J Crit Care. 2016 Apr; 32:21-5. doi: 10.1016/
j.jcrc.2015.11.024. Epub 2015 Dec 8. PMID: 26764578.
    \16\ Wood KE. Major pulmonary embolism: review of a 
pathophysiologic approach to the golden hour of hemodynamically 
significant pulmonary embolism. Chest. 2002 Mar; 121(3):877-905. 
PMID: 11888976.
---------------------------------------------------------------------------

    The applicant asserted that the FIFO workflow is the standard of 
care. The applicant stated that Briefcase for PE allows facilities to 
substantially shorten the period of time between when the patient 
receives CTPA imaging (Step 2) and when the radiologist informs the 
referring physician of positive PE (Step 5). The applicant stated that 
Briefcase for PE streamlines this workflow using AI to analyze CTPA 
images of the chest automatically and notifies the radiologist that a 
suspected PE has been identified, enabling the radiologist to review 
imaging and make diagnostic decisions faster by prioritizing these 
images for review in the queue.
    With respect to the newness criterion, Briefcase for PE received 
FDA 510(k) clearance on April 15, 2019 to market the device under FDA 
510(k) number K190072. The FDA clearance for Briefcase for PE was based 
on substantial equivalence to the legally marketed predicate device, 
Briefcase for Intracranial Hemorrhage (ICH) (FDA 510(k) number 
K180647), as both of these devices use AI algorithms to analyze images 
and highlight cases for further action based on CT images. Briefcase 
for ICH received FDA 510(k) clearance on August 1, 2018. The predicate 
device for Briefcase for ICH is Viz.AI's ContaCT, which received De 
Novo premarket approval in February of 2018. The applicant asserted 
Briefcase for ICH is indicated for use in the analysis of non-enhanced 
head CT images, whereas Briefcase for PE is indicated for use in the 
analysis of non-enhanced CTPA images. The applicant submitted a request 
for approval of a unique ICD-10-PCS procedure code to identify use of 
the technology and was granted approval for the following procedure 
code effective October 1, 2021: XXE3X27 (Measurement of pulmonary 
artery flow, computer-aided triage and notification, new technology 
group 7).
    Under the newness criterion, if a technology meets all three of the 
substantial similarity criteria, it would be considered substantially 
similar to an existing technology and would not be considered ``new'' 
for purposes of new technology add-on payments.
    With respect to the first criterion, whether a product uses the 
same or similar mechanism of action to achieve a therapeutic outcome, 
according to the applicant, Briefcase for PE is the only FDA-cleared 
technology that uses computer-aided triage and notification to rapidly 
detect PE and shorten time to notification of the radiologist. The 
applicant claimed that no other FDA approved or cleared technology uses 
the same mechanism of action for computer-aided triage and 
prioritization of PE.
    With respect to the second criterion, whether a product is assigned 
to the same or a different MS-DRG, the applicant stated it expects that 
patients evaluated for PE or suspected PE using Briefcase for PE will 
be assigned to the same DRGs as patients evaluated for PE or suspected 
PE under the current workflow or standard of care. The applicant 
estimates that under the MS-DRG grouper for FY 2021, Briefcase for PE 
could map to 279 different MS-DRGs, with MS-DRGs 175 (Pulmonary 
embolism with major complication or comorbidity (MCC) or acute cor 
pulmonale) and 176 (Pulmonary embolism without MCC) accounting for 
approximately 45 percent of the estimated cases.
    With respect to the third criterion, whether the new use of 
technology involves the treatment of the same or similar type of 
disease and the same or similar patient population when compared to an 
existing technology, the applicant did not directly respond to the 
criterion but reiterated that no other existing technology is 
comparable to Briefcase for PE and that Briefcase for PE is the only 
FDA-cleared technology that uses computer aided triage and notification 
to rapidly detect PE and shorten time to notification of the 
radiologist.
    We noted the following concerns in the proposed rule (86 FR 25218) 
regarding whether the technology meets the substantial similarity 
criteria and whether it should be considered new. We noted that the 
applicant asserted that Briefcase for ICH, the predicate device for 
Briefcase for PE, is identical in all aspects and differs only with 
respect to the training of the algorithm on PE (that is, non-enhanced 
head CT) and ICH (that is, non-enhanced CTPA) images. We noted that we 
were unclear whether the training of the algorithim on PE and ICH 
images would distinguish the mechanism of action for Briefcase for PE 
from Briefcase for ICH, or its predicate device, ContaCT, and we 
invited comment on whether Briefcase for PE represents a new mechanism 
of action. We noted that although the applicant did not directly state 
whether Briefcase for PE involves the treatment of the same or similar 
type of disease and the same or similar patient population, we believe 
that Briefcase for PE would be used for a different disease and patient 
population than Briefcase for ICH and ContaCT.
    We noted our interest in public comments regarding issues related 
to

[[Page 44981]]

determining newness for technologies that use AI, an algorithm, or 
software, as discussed in the FY 2021 IPPS/LTCH PPS final rule (85 FR 
58628). Specifically, we stated that we are interested in public 
comment on how these technologies, including devices classified as 
radiological computer aided triage and notification software and 
radiological computer-assisted diagnostic software, may be considered 
for the purpose of identifying a unique mechanism of action; how 
updates to AI, an algorithm or software would affect an already 
approved technology or a competing technology; whether software changes 
for an already approved technology could be considered a new mechanism 
of action, and whether an improved algorithm by competing technologies 
would represent a unique mechanism of action if the outcome is the same 
as an already approved AI new technology.
    We invited public comments on whether Briefcase for PE is 
substantially similar to other technologies and whether Briefcase for 
PE meets the newness criterion.
    Comment: The applicant submitted a letter maintaining that 
Briefcase for PE meets the newness criterion. With regard to commercial 
availability, the applicant commented that Briefcase for PE was 
commercially available on a very limited basis for less than six months 
during the FY 2019 time period of the data CMS is proposing to use to 
recalibrate MS-DRG weights and, therefore, that the claims from that 
time period do not reflect the cost of Briefcase for PE.
    With respect to whether Briefcase for PE uses the same or a similar 
mechanism of action when compared to an existing technology, the 
applicant commented that the concern that Briefcase for PE is identical 
in all aspects to its predicate device, Briefcase for ICH, overlooks 
key components of the technology and the anatomy on which it focuses. 
The applicant cited the FDA definition of mechanism of action, which is 
``the means by which a product achieves its intended therapeutic effect 
or action,'' in its assertion that the analysis of CTPA images for 
suspected findings of PE and subsequent computer-assisted triage and 
notification is the new mechanism of action. The applicant also noted 
that the images analyzed by the algorithm are of the pulmonary 
arteries, not of vessels in the brain as with Briefcase for ICH or 
ContaCT. The applicant stated that while AI is a necessary component of 
Briefcase for PE, it is not the mechanism of action per se, and is not 
sufficient to achieve the therapeutic effect alone.
    With regard to the second and third newness criteria, the applicant 
commented that while Briefcase for PE and its predicate technologies 
are all AI-based triage and notification systems, these technologies 
are distinctly different in that the technologies focus on different 
patient populations and would be assigned to different MS-DRGs.
    The applicant also responded to our question as to how AI, an 
algorithm, or software may be viewed as identifying a unique mechanism 
of action. The applicant concurred with other commenters in stating 
that such technologies should be evaluated for newness in the same way 
as CMS evaluates any other medical device applying for new technology 
add-on payment. That is, the commenters stated that human intelligence 
and human processes are not FDA approved or cleared technologies and 
should not be used as a comparator to evaluate whether Briefcase for 
PE, or any technology, meets the definition of newness. A commenter 
also noted that each of the AI technologies that applied for new 
technology add-on payments for FY 2022 are distinctly different in that 
the technologies focus on different patient populations and/or would be 
assigned to different MS-DRGs. This commenter stated, along with the 
applicant, that because there are no other technologies that have been 
approved or cleared by the FDA for the identification, triage and 
notification of suspected findings of PE that have been on the market 
for more than 2 to 3 years, Briefcase for PE meets the newness 
criterion.
    A commenter noted how updates to an AI, an algorithm or software 
would affect an already approved technology or a competing technology. 
This commenter noted a phenomenon known as ``model drift,'' which can 
occur over time due to changes in healthcare workflows, practices, 
populations, and data. The commenter explained that when this occurs, 
the underlying algorithm does not automatically change and adapt to the 
new inputs, but its output predictions can become less accurate over 
time. The commenter further noted that model drift can be detected 
using the same statistical analyses that rigorously tested the 
algorithm's initial training data inputs and output predictions to 
ensure that they are free of statistically significant variances or 
biases. The commenter stated that if the AI/Machine Learning model or 
the algorithms that comprise the model change over time, they ideally 
should be subjected to this extensive statistical testing regimen that 
occurred before its original deployment, and developers should gauge 
the nature and extent of any model drift that occurs and make slight 
modifications if possible that would allow for its continued use in 
clinical care.
    Response: We appreciate the clarification from the applicant with 
respect to whether the product meets the newness criterion. After 
consideration of the comments received and information submitted by the 
applicant as part of its FY 2022 new technology add-on payment 
application, at this time and given our ongoing consideration of 
assessing newness for technology that use AI, an algorithm or software, 
we believe that Briefcase for PE uses a new mechanism of action to 
achieve a therapeutic outcome when compared to existing treatments 
because there are currently no FDA approved or cleared technologies 
that analyze CTPA images for suspected findings of PE and subsequent 
computer-assisted triage and notification. Therefore, we believe that 
Briefcase for PE is not substantially similar to an existing technology 
and meets the newness criterion.
    We also thank the commenters for their input on determining newness 
for technologies that use AI, an algorithm or software, as discussed in 
the proposed rule. We will continue consider how these technologies may 
be used to identify a unique mechanism of action; how updates to AI, an 
algorithm or software would affect an already approved technology or a 
competing technology; whether software changes for an already approved 
technology could be considered a new mechanism of action, and whether 
an improved algorithm by competing technologies would represent a 
unique mechanism of action if the outcome is the same as an already 
approved AI new technology, as we gain more experience in this area.
    With regard to the cost criterion, the applicant presented the 
following analysis. The applicant first identified the principal 
diagnoses associated with the PE-related MS-DRGs 175 (``Pulmonary 
embolism with MCC or acute cor pulmonale'') and 176 (``Pulmonary 
embolism without MCC''). The applicant then searched the FY 2019 
proposed rule MedPAR Limited Data Set (LDS) for claims where the 
principal diagnoses were listed in any position on an inpatient claim. 
The applicant mapped the 2,517 identified claims to the list of unique 
MS-DRGs corresponding to these claims and aggregated the claims by MS-
DRG. Per the applicant, under the MS-DRG grouper for FY 2021, potential 
cases representing patients who may be eligible for treatment using 
Briefcase for

[[Page 44982]]

PE map to 279 MS-DRGs, with MS-DRGs 175 and 176 accounting for 
approximately 45 percent of estimated cases. The applicant also 
provided a table of the top 10 MS-DRGs, which represent approximately 
69 percent of estimated cases.
[GRAPHIC] [TIFF OMITTED] TR13AU21.159

    The applicant standardized the charges and applied the 2-year 
charge inflation factor used to adjust the outlier threshold 
determination, which the applicant stated was 10.22 percent. We note 
that the actual 2-year inflation factor in the FY 2021 IPPS/LTCH PPS 
final rule was 13.2 percent (85 FR 59039), which would have increased 
the inflated charges figure. The applicant did not remove charges for 
prior technology as the applicant maintained that no existing 
technology is comparable to Briefcase for PE. However, the applicant 
removed 31.9 percent of total accommodation charges, which the 
applicant maintained is consistent with their internal study which 
indicated that Briefcase for PE reduced the length of stay for PE-
diagnosed patients.\17\ Per the applicant, the study demonstrated a 
mean length of stay of 8.77 and 5.97 days for pre-AI and post-AI time 
periods, respectively.\18\
---------------------------------------------------------------------------

    \17\ Maya M. et al. Artificial Intelligence Software for 
Flagging Pulmonary Embolism on CTPA Associated with Reduced Length 
of Stay. Abstract draft of an internal study performed by the 
applicant (unpublished).
    \18\ Ibid.
---------------------------------------------------------------------------

    Next, the applicant added charges for the new technology. To 
calculate the charges for the new technology, the applicant multiplied 
the cases involving Briefcase for PE from each of its subscribing 
providers by a Medicare share of 52 percent to obtain the total 
estimated Medicare and non-Medicare cases. The applicant obtained the 
52 percent Medicare share figure from a nationwide sample of inpatient 
claims provided by the Agency for Healthcare Research and Quality 
(AHRQ). Specifically, the applicant searched data from the Healthcare 
Cost and Utilization Project for discharges with the following codes: 
I2699, I2609, I2692, I2602, I2782, T790XXA, T800XXA, T791XXA, I2693, 
I2694, and I2601.\19\ The applicant found 189,575 discharges, of which 
52 percent identified Medicare as the payer. The applicant divided the 
total cost of the technology by the estimated total number of cases for 
each customer to obtain a provider-specific cost per case, which it 
then averaged across all customers to obtain an overall average cost 
per case. Finally, the applicant divided the average cost per case by 
the national average CCR for the CT cost center of 0.034 from the FY 
2021 IPPS/LTCH PPS final rule (85 FR 58601).
---------------------------------------------------------------------------

    \19\ Healthcare Cost and Utilization Project. Free Health Care 
Statistics. https://hcupnet.ahrq.gov/#setup.
---------------------------------------------------------------------------

    The applicant calculated a final inflated average case-weighted 
standardized charge per case of $87,483, which exceeded the average 
case-weighted threshold amount of $71,312. Because the final inflated 
average case-weighted standardized charge per case exceeded the average 
case-weighted threshold amount, the applicant maintained that Briefcase 
for PE meets the cost criterion.
    We stated in the proposed rule (86 FR 25219) that we would like 
more information regarding the methodology by which the applicant 
selected the diagnosis codes associated with MS-DRGs 175 and 176, as 
well as subanalyses that limit the cases to MS-DRGs 175 and 176 and the 
top 10 MS-DRGs, which per the applicant represent 45 percent of 
estimated cases and 69 percent of estimated cases, respectively. 
Additionally, we noted that the applicant appeared to have used a 
single list price of Briefcase for PE per hospital with a cost per 
patient that can vary based on the volume of cases. We questioned 
whether the cost per patient varied based on the utilization of the 
technology by the hospitals. We stated that we were interested in more 
information about the applicant's cost per case calculation, including 
how the applicant selected the codes it used to search for discharges 
from the Healthcare Cost and Utilization Project, as well as the per 
unit cost of Briefcase for PE and how the total cost of the technology 
was calculated for each subscribing provider.
    In the FY 2021 IPPS/LTCH PPS final rule (85 FR 58630), we stated 
our

[[Page 44983]]

understanding that there are unique circumstances to determining a cost 
per case for a technology that utilizes a subscription for its cost. We 
stated our intent to continue to consider the issues relating to the 
calculation of the cost per unit of technologies sold on a subscription 
basis as we gain more experience in this area. In the FY 2022 IPPS/LTCH 
PPS proposed rule, we continued to welcome comments from the public as 
to the appropriate method to determine a cost per case for such 
technologies, including comments on whether the cost per case should be 
estimated based on subscriber hospital data as described previously, 
and if so, whether the cost analysis should be updated based on the 
most recent subscriber data for each year for which the technology may 
be eligible for the new technology add-on payment. We also invited 
public comment on whether Briefcase for PE meets the cost criterion, 
particularly in light of the subscription model, for which the number 
of subscribers and the estimated cost per case based on that subscriber 
data may change over time.
    Comment: The applicant submitted a comment in response to our 
concerns in the proposed rule regarding the methodology for conducting 
the cost analysis for Briefcase for PE. With respect to our inquiry 
regarding the specific MS-DRGs selected for the analysis and the 
reasoning for selecting the identified ICD-10-CM diagnosis codes, the 
applicant explained that because Briefcase for PE is a new technology, 
there is no current utilization available for analysis and that, 
additionally, CT pulmonary angiogram, the imaging procedure that is 
specific to Briefcase for PE, is not reliably reported in the inpatient 
setting using ICD-10-PCS procedure codes. Therefore, to estimate the 
potential utilization of Briefcase for PE among Medicare beneficiaries, 
the applicant stated that it used a multi-step approach that involved 
identifying MS-DRGs specific to pulmonary embolism and determining the 
principal diagnoses associated with those MS-DRGs. The applicant 
determined the principal diagnoses associated with MS-DRG 175 
(``Pulmonary embolism with MCC or acute cor pulmonale'') and MS-DRG 176 
(``Pulmonary embolism without MCC'') and re-examined those diagnosis 
codes used in the initial calculation. The applicant decided to 
eliminate claims with the ICD-10-CM diagnosis of I27.82 (chronic 
pulmonary embolism) as it does not reflect incidental pulmonary 
embolism, the type of suspected positive cases that Briefcase for PE is 
intended to flag. The applicant then searched for all claims where the 
remaining principal diagnoses were listed as a diagnosis in any 
position on the claim, including the admitting diagnosis. Based on this 
methodology, the applicant aggregated the claims by MS-DRG and compiled 
a list of unique MS-DRGs corresponding to these claims. Per the 
applicant, the total claims for those providers who currently use 
Briefcase for PE were then aggregated by these MS-DRGs.
    With respect to our inquiry regarding the applicant's cost per case 
methodology, the applicant clarified that the cost per case for each 
provider was not based on a single list price per hospital, as CMS 
described in the proposed rule, but rather the individual customer's 
specific list price based on the applicant's actual pricing. The 
applicant explained that it calculated the cost per case for each 
provider using the individual list price and total Medicare and non-
Medicare cases, before taking an average of these unique costs per case 
to derive an average cost per case across all users, which the 
applicant then converted to charges.
    In response to concerns CMS previously raised and continues to 
raise concerning variation in the cost per patient for a technology 
with subscription-based pricing, the applicant acknowledged that the 
cost per patient may change as the applicant adds more customers. The 
applicant conducted additional analyses beyond the one submitted in its 
new technology add-on payment application to examine how the cost per 
patient varied when data from all IPPS hospitals are included, versus 
the sample of subscriber hospitals used in its original analysis. 
According to the applicant, these analyses were performed using the 
methodology described in detail in the proposed rule with two 
additional changes: The elimination of ICD-10-CM code I27.82 as noted 
previously and an inflation factor of 13.2 percent instead of 10.22 
percent. The applicant stated that it calculated the cost per patient 
by dividing the total cost of Briefcase for PE per year per hospital by 
the number of total estimated cases for which Briefcase for PE would be 
used at each hospital, and then averaging across all such hospitals. 
The applicant noted that it took a conservative approach and used the 
lowest pricing tier for hospitals that are not current users of the 
technology. After excluding hospitals with fewer than 11 cases, the 
applicant calculated a cost per case across 2,187 general acute care 
hospitals that was higher than the cost per case across subscriber 
hospitals. In updating its analysis, the applicant noted that the final 
inflated average case-weighted standardized charge per case is $104,688 
which exceeded the case-weighted threshold amount of $71,507.
    The applicant conducted two additional analyses for all current 
hospital clients and for all IPPS hospitals. For these analyses, the 
applicant calculated an average cost per case using the methodology 
described previously as well as a case-weighted average cost per case 
where the average was determined by assigning weight to each 
institution in relation to their relative importance and/or 
significance. Per the applicant, the additional analyses use the same 
methodology described previously but limit the cases included. Under 
the first alternative analysis, the applicant limited cases to only 
those in the top 10 MS-DRGs by volume. Under the second alternative 
analysis, the applicant limited cases to only those in the two 
pulmonary embolism MS-DRGs (MS-DRG 175 and 176). Under each scenario, 
the applicant determined that the final inflated case-weighted 
standardized charge per case exceeded the case-weighted threshold.

[[Page 44984]]

[GRAPHIC] [TIFF OMITTED] TR13AU21.160

    Response: We thank the applicant for its input. We note that the 
applicant did not specify how it determined the relative weight and 
importance of institutions when calculating the case-weighted cost per 
case in its supplemental analyses; although it appears to have been 
determined based on each institution's case volume relative to others 
in the sample, we would appreciate a clarification in the future. 
However, we agree with the applicant that the final inflated case-
weighted standardized charge per case exceeded the case-weighted 
threshold under the twelve scenarios presented in its original 
application and in response to our concerns stated in the FY 2022 IPPS/
LTCH PPS proposed rule. Therefore, we agree with the applicant that 
Briefcase for PE meets the cost criterion.
    Comment: The applicant also responded to CMS' request for public 
comment as to the appropriate method to determine a cost per case for 
technologies sold on a subscription basis, including whether the cost 
per case should be estimated based on subscriber hospital data and, if 
so, whether the cost analysis should be updated based on the most 
recent subscriber data for each year for which the technology may be 
eligible for the new technology add-on payment. The applicant concurred 
with other commenters that, in determining the cost per case for 
technologies seeking new technology add-on payment that utilize a 
subscription model, we should limit our analysis to subscriber 
hospitals and update the cost analysis on an annual basis. The 
applicant also concurred that alternative methodologies involving 
estimating the number of patients who would be eligible to receive 
treatment utilizing a technology sold on a subscription basis would be 
likely to result in a payment amount that does not adequately reflect 
the estimated average cost of such service or technology as required by 
Section 1886(d)(5)(K)(ii)(III) of the Act.
    According to the applicant, technologies sold on a subscription 
basis are provided to the customer at a fixed price per period of time, 
resulting in a cost per unit that is directly impacted by the frequency 
that the customer utilizes the technology. The applicant explained that 
customers with low utilization of a subscription-based technology have 
a higher cost per unit than customers with high utilization. The 
applicant also stated that because the overall cost per unit of 
subscription technologies is determined by each customer's ratio of 
price to utilization, an analysis that requires an estimate of cost per 
unit should be limited to subscribers only, as including estimates of 
cost per unit for potential customers that do not currently subscribe 
to the technology may result in a cost-per-case that does not reflect 
the actual costs of current users. The applicant recommends that the 
cost per unit of technologies sold on a subscription basis should be 
based on data from

[[Page 44985]]

current subscribers only and that yearly updates to the cost per unit 
analysis are reasonable to reflect changes in subscribers and thus the 
overall cost per unit.
    The applicant stated that this recommendation is consistent with 
how CMS calculates costs across a variety of payment systems and 
programs, including MS-DRG relative weights and APC relative weights 
where CMS only considers costs from hospitals for cases billed to 
Medicare and does not attempt to estimate what the cost an MS-DRG or 
APC relative weight might be if a broader range of hospitals delivered 
the type of care described by a specific MS-DRG or APC. Similarly, the 
applicant stated that the average sales price methodology used by CMS 
to determine payment for certain separately payable products includes 
only data from actual customer sales. The applicant noted that, 
although the unit price for these separately payable products often 
varies based on utilization, with customers with low utilization paying 
more per unit than customers with higher utilization, CMS does not 
attempt to calculate average sales price by forecasting how future 
customers may alter the current average sales price.
    Response: We appreciate the applicant's comments relating to 
calculation of the cost per unit of technologies sold on a subscription 
basis and will take the comments into consideration in future 
rulemaking where applicable. CMS will continue to consider the issues 
pertaining to technologies sold on a subscription basis relative to the 
calculation of the cost per unit of these technologies including the 
merits of calculating the cost per case across all IPPS hospitals 
versus limiting the cost per case analysis to current users and whether 
the cost analysis should be updated based on the most recent subscriber 
data for each year for which the technology may be eligible for the new 
technology add-on payment, as we gain more experience in this area.
    With regard to the substantial clinical improvement criterion, the 
applicant claimed that Briefcase for PE represents an advance that 
substantially improves the ability to diagnose pulmonary embolism by 
pre-reading images of CTPAs, automatically identifying suspected PE in 
CTPA images, and notifying the radiologist before the radiologist would 
have opened the study in the standard of care, which the applicant 
claims is the FIFO workflow. The applicant also asserted that because 
of a reduction in time-to-exam-open, where Briefcase for PE notifies 
the radiologist to open and read CTPA studies that have a high 
probability of being positive for PE sooner than the radiologist would 
have under the FIFO workflow, the treating physician can initiate 
treatment sooner, which can reduce mortality and reduce length of stay 
related to PE.
    The applicant provided data from an FDA pivotal study in support of 
its assertion that Briefcase for PE reduces time-to-exam-open compared 
to the standard of care and helps in prioritization of diagnosis.\20\ 
For the FDA pivotal study, the applicant conducted a retrospective, 
blinded, multicenter, multinational study of the assessment of 184 
CTPAs from 3 clinical sites (2 U.S. and 1 outside U.S.) using Briefcase 
for PE. The primary endpoint was to evaluate the software's performance 
in identifying pulmonary embolism on an approximately equal number of 
positive and negative cases (images with PE versus without PE), with a 
performance goal of at least 80 percent sensitivity (true positive 
rate) and specificity (true negative rate). Per the applicant, both 
measures exceeded the performance goal, with 90.6 percent sensitivity 
(95 percent CI: 82.2 percent-95.9 percent) and 89.9 percent specificity 
(95 percent CI: 82.2 percent-95.1 percent).
---------------------------------------------------------------------------

    \20\ Aidoc Briefcase for PE--Pivotal Study 1--FDA 510(k)--
K190072. http://www.accessdata.fda.gov/cdrh_docs/pdf19/K190072.pdf.
---------------------------------------------------------------------------

    According to the applicant, the secondary endpoint of the FDA 
pivotal study was to evaluate time-to-notification for true positive PE 
cases compared to the FIFO workflow. The study showed that time-to-
notification with Briefcase for PE is 3.9 minutes (95 percent CI: 3.7-
4.1). The applicant noted that, in contrast, the time-to-exam-open in 
the FIFO workflow was significantly longer at 64.1 minutes (95 percent 
CI 36.6-91.5). The applicant stated the mean difference of 60.2 minutes 
(95 percent CI 32.7-87.6) for these two metrics is statistically 
significant, and assuming the radiologist receives a notification on a 
true positive PE case and acts on it immediately, it can save an 
average of 60.2 minutes (95 percent CI 32.7-87.6) compared to the time-
to exam-open in a FIFO reading queue. Based on this data, the applicant 
concluded Briefcase for PE substantially shortened the time to 
diagnosis for PE cases as compared with the FIFO workflow.
    The applicant further claimed that clinical studies and other real-
world data have demonstrated comparable performance characteristics and 
shown that the integration of the Briefcase for PE software into the 
radiology workflow markedly improves time to notification for PE 
patients across a variety of clinical settings, geographies, and 
facilities. The applicant submitted a retrospective, single-site study 
by Weikert T., et al., which evaluated Briefcase for PE performance on 
1,465 retrospective CTPA examinations from 2017 in an academic center 
outside the US.\21\ The sensitivity and specificity were measured to be 
92.7 percent (95 percent CI: 88.3-95.5 percent) and 95.5 percent (95 
percent CI:94.2- 96.6 percent), respectively. The researchers concluded 
that the system has high diagnostic performance for the automatic 
detection of PE on CTPA exams and as such, speeds up the diagnostic 
workup of critical cases.
---------------------------------------------------------------------------

    \21\ Weikert T, Winkel DJ, Bremerich J, Stieltjes B, Parmar V, 
Sauter AW, Sommer G. Automated detection of pulmonary embolism in CT 
pulmonary angiograms using an AI-powered algorithm. Eur Radiol. 2020 
Jul 3. doi: 10.1007/s00330-020-06998-0. Epub ahead of print. PMID: 
32621243
---------------------------------------------------------------------------

    The applicant stated that unpublished data maintained by Aidoc 
suggest that real-world performance of Briefcase for PE is consistent 
with what was found in the FDA pivotal study.22 23 The 
applicant stated that across 26 sites encompassing a variety of 
geographic locations across the United States, a total of 36,084 CTPA 
examinations were analyzed over a 90-day period (July 13, 2020-October 
11, 2020). Time-to-notification metrics were calculated for all 4,748 
CTPAs analyzed by the software and identified as positive for PE. Time-
to-notification was calculated as the time to get the DICOM exam, de-
identify it, upload it to the cloud, analyze and send a notification 
back to the worklist application. The applicant claimed that the mean 
time-to-notification for PE was 7.0 minutes (median: 6.1/IQR: 4.8). 
According to the applicant, over 85 percent of CTPA examinations 
identified as positive for PE were notified in under 10 minutes. The 
applicant concluded that the study demonstrates the ability of 
Briefcase for PE to provide fast time-to-notification on positive PE 
cases and its generalizability across different centers and patient 
populations.
---------------------------------------------------------------------------

    \22\ Avondo, J. Yalon R., Ashkenasi C. Time-to-notification 
Analysis Across US Facilities with Aidoc Briefcase for PE. Internal 
study performed by the applicant (unpublished).
    \23\ Ibid.
---------------------------------------------------------------------------

    The applicant submitted additional unpublished data from the 26 
sites spread across a variety of geographic locations of the United 
States aggregated over a different 90-day period (September 17, 2020 to 
December 17,

[[Page 44986]]

2020).\24\ Seven sites were excluded from the analysis due to having 
third-party integrations that prevented the ability to capture 
engagement metrics. Two engagement metrics were calculated: The open 
percentage and the time-to-open. The open percentage metric was 
calculated as the percentage of notifications that were presented to 
the radiologist and opened by at least one radiologist. The time-to-
open metric was measured by calculating the time between the arrival of 
the Briefcase for PE notification and the time first opened by a 
radiologist. A total of 2,138 notifications for CTPA examinations found 
to be positive for PE by Briefcase for PE were analyzed. The open 
percentage was found to be 97 percent across all sites (min: 80 
percent, max: 100 percent), and the mean time-to-open was found to be 
2.13 minutes (median: 1.0/interquartile range: 2.0). The data provided 
by the applicant indicated over 90 percent of notifications were found 
to be opened in under 5 minutes. Based on this data, the study 
concluded that radiologists in the US readily engage with notifications 
for positive PE cases provided by Briefcase for PE and do so in a 
timely manner. The study asserted that engagement is an important 
metric to assess radiologist adoption of this technology, which is 
critical to its practical utility in shortening time to diagnosis and 
communication of PE to reduce the time to treatment and improve 
clinical outcomes.
---------------------------------------------------------------------------

    \24\ Avondo, J. Yalon R., Ashkenasi C. Radiologist Engagement 
Analysis Across US Facilities with Aidoc Briefcase for PE. Internal 
study performed by the applicant (unpublished).
---------------------------------------------------------------------------

    The applicant also claimed that Briefcase for PE significantly 
improves clinical outcomes relative to the current standard of care 
using the FIFO workflow because the use of Briefcase for PE reduces 
time to diagnosis and treatment by notifying the radiologist to review 
the image for suspected PE faster in the workflow. The applicant 
claimed early diagnosis and treatment is important in acute PE where 
there exists a ``golden hour,'' during which a timely approach to 
diagnosis and therapy can affect outcomes by reducing mortality and 
reducing length of stay.\25\
---------------------------------------------------------------------------

    \25\ The term ``golden hour'' references a critical period of 
time which may be longer or shorter than a literal hour.
---------------------------------------------------------------------------

    The applicant provided two unpublished internal studies in support 
of the impact of Briefcase for PE on clinical outcomes. The applicant 
stated that in a single-site retrospective study, Maya M., et al. have 
shown a reduction in hospital length of stay for PE patients following 
the use of the Briefcase for PE system, compared to an equivalent time 
period prior to the use of the system.\26\ The applicant stated that 
Maya M., et al. compared mean length of stay for 366 patients with a 
positive PE diagnosis during 10-month periods before and after 
Briefcase for PE was implemented at Cedars-Sinai Medical Center in 
December 2018 (206 patients before the use of Briefcase for PE and 160 
patients after the AI intervention). 3,997 patient encounters that 
underwent CTPA imaging but that were not diagnosed with PE were split 
as 1,926 and 2,071 patient encounters for the pre/post-AI periods based 
on the admission dates. Hip fracture was chosen as a comparison group 
due to acuity, treatment-related factors, and similar length of stay to 
PE. 2,422 patient encounters for patients diagnosed with hip fractures, 
identified by ICD9 code 820 and 821, were split as 1,279 and 1,143 
patient encounters for the pre/post-AI periods based on the admission 
dates. According to the applicant, the pre- and post-implementation had 
similar seasonality and numbers of ``hospital-wide patient encounters'' 
(103,626 vs 104,733 encounters). The applicant noted that for the PE 
diagnosed patients, a mean length of stay of 8.77 and 5.97 days was 
observed for the pre-AI and post-AI time periods, respectively. The 
applicant stated that the mean difference was 2.80 days (p-value 
<0.05). For the group that underwent related PE imaging but was not 
diagnosed with PE, a mean length of stay of 9.28 and 9.70 days was 
observed for the pre-AI and post-AI time periods, respectively (mean 
difference was -0.42 days (p-value <0.05)). For the hip fracture 
diagnosed patients, a mean length of stay of 6.90 and 6.69 days was 
observed for the pre-AI and post-AI time periods, respectively. The 
mean difference was 0.21 days (p-value > 0.05). Additionally, for the 
hospital wide patients, a mean length of stay of 5.78 and 5.96 days was 
observed for the pre-AI and post-AI time periods, respectively. The 
mean difference was -0.18 days (p-value <0.05). According to the 
applicant, Maya et al. concluded that implementation of Briefcase for 
PE for flagging and prioritization of patients with PE resulted in 
significant reduction of length of stay that was not observed in other 
control groups.
---------------------------------------------------------------------------

    \26\ Maya M. et al. Artificial Intelligence Software for 
Flagging Pulmonary Embolism on CTPA Associated with Reduced Length 
of Stay. Abstract draft of an internal study performed by the 
applicant (unpublished).
---------------------------------------------------------------------------

    The applicant also submitted a study by Raskin D., et al. which 
completed an additional retrospective, single-armed, single-site, study 
that indicated improved outcomes in PE patients, compared to a time 
period prior to the use of Briefcase for PE.\27\ In Raskin D., et al., 
data for all patients older than 18 years with a diagnosis of PE on 
CTPA and admitted to the institution's ED was collected for the period 
before the use of the AI software (January 1, 2016-January 1, 2018; 
pre-AI) and afterwards (January 1, 2019-December 6, 2019; post-AI). 
According to the applicant, study variables included demographics, 
clinical data, and imaging data. The applicant stated the primary 
variables for outcomes were 30- and 120-day all-cause mortality. 175 
patients were eligible for the entire analyzed period (123 pre-AI, 52 
Post-AI). The study found that 30- and 120-day all-cause mortality were 
significantly reduced post-AI (8.1 percent vs 7.7 percent, 15.5 percent 
vs 9.6 percent, respectively, p <0.05). According to the applicant, 
Raskin D., et al. concluded that implementation of Briefcase for PE for 
flagging patients with PE resulted in significant reduction of 30- and 
120-day all-cause mortality.
---------------------------------------------------------------------------

    \27\ Daniel Raskin D., MD, Chen Hoffmann C., MD, Gilad Twig G., 
MD Ph.D., Eli Konen E., MD, Gal Yaniv GMD Ph.D. Artificial 
Intelligence Software for Flagging Pulmonary Embolism on CTPA 
Associated with Reduction of Mortality. Abstract draft of an 
internal study performed by the applicant (unpublished).
---------------------------------------------------------------------------

    The applicant submitted five additional clinical studies that do 
not directly involve the use of Briefcase for PE to demonstrate a 
strong correlation between time to communication of PE findings, 
initiation of treatment, and clinical outcomes. The applicants 
submitted a review by Kenneth E. Wood, further establishing a ``golden 
hour'' of PE during which a timely approach to diagnosis and therapy 
can potentially impact outcomes. According to the applicant, Wood 
states that major PE results whenever the combination of embolism size 
and underlying cardiopulmonary status interact to produce hemodynamic 
instability and that most deaths in patients occur within the first few 
hours after presentation, and rapid diagnosis and treatment is 
therefore essential to save patients' lives. One prospective, single-
site study, Kumamaru K., et al. indicates the prevalence of a ``golden 
hour'' for PE diagnosis and treatment and concluded that delay (> 1.5 
hours of CTPA acquisition) in direct communication of acute PE 
diagnosis from radiologists to referring physicians was significantly 
correlated with a higher risk of delayed treatment initiation and death 
within 30 days. Another prospective, single-site study, Kline J., et 
al., concluded that

[[Page 44987]]

patients with a delayed diagnosis had a higher rate of in-hospital 
adverse events (9 percent vs. 30 percent; p = 0.01). An additional 
retrospective, single-site study by Smith S., et al. observed an 
association between early administration of anticoagulation therapy and 
reduced mortality for patients with acute PE. Lastly, a retrospective, 
single-site study asserting a ``golden hour'' by Soh S., et al. was 
submitted by the applicant to demonstrate an association between early 
initiation of anticoagulation therapy and in-hospital mortality in 
high-risk PE patients who needed ICU care. According to the applicant, 
Soh S., et al. concluded that their analysis showed that the cutoff 
point of anticoagulation initiation to achieve improved survival rates 
was 5.2 hours (that is, golden hour). The applicant stated that the 
study observed an association between early anticoagulation and reduced 
mortality for patients with acute PE.
    In reviewing the information submitted by the applicant as part of 
its FY 2022 new technology add-on payment application for Briefcase for 
PE, we noted that the clinical literature provided by the applicant 
only compares the technology to unassisted FIFO workflows and not 
against existing electronic (for example, EHR ``stat'' orders) or 
manual (for example, verbal communication to radiologist) forms of 
prioritization, or other types of existing risk stratification tools or 
features currently available in EHRs. Additionally, we noted that some 
of the studies provided by the applicant that took place over many 
years may not have accounted for confounding variables (for example, 
improvements in care for patients with suspected PE) that may have 
occurred during the study period. Comparing to the FIFO workflow alone 
assumes that no other changes occurred before and after the adoption of 
the system and that the hospitals in question did not implement any 
other changes to their standard operating procedures to stratify 
suspected PE cases over the period of time many of the provided studies 
took place. We also noted that the applicant has not provided data on 
potential outcome concerns associated with this type of clinical 
decision support tool (for example, treatment delays due to false 
negatives, false positives, or multiple workflow prioritization alerts 
presented to the physician at the same time). We invited public comment 
on whether these issues may affect the tool's ability to help diagnose 
a medical condition earlier in a patient population.
    Lastly, we noted that the applicant does not measure the effect of 
its technology on actual treatment outcomes, instead relying on the 
assumption that faster treatment results in better outcomes. Without 
measuring this impact on treatment outcomes, we noted that we were 
uncertain if the technology will lead to substantive clinical outcomes. 
Given that the applicant references a critical ``golden hour'' which 
may be as long as 5.2 hours, the potential time savings resulting from 
the use of Briefcase for PE may be insubstantial in relation to the 
time within which outcomes are affected in the setting of PE.
    We invited public comments on whether Briefcase for PE meets the 
substantial clinical improvement criterion.
    Comment: Several commenters indicated their support for Briefcase 
for PE. Some of these commenters offered their general positive 
clinical experiences as anecdotal support for the product. Other 
commenters offered opinions that the tool reduces bias, improves 
knowledge sharing, reduces treatment time, and improves outcomes with 
patients with pulmonary embolism but did not provide comparison to 
anything other than FIFO workflow. Further, commenters reflected on the 
accuracy of the tool due to its high sensitivity and specificity, and 
others noted that it can help to alleviate situations where radiology 
departments are overwhelmed with orders by helping staff to prioritize 
the workflow.
    Response: We appreciate all of the comments received related to 
Briefcase for PE and have taken them into consideration in making our 
determination.
    Comment: The applicant submitted comments in response to CMS' 
concerns in the FY 2022 IPPS/LTCH PPS proposed rule regarding whether 
Briefcase for PE meets the substantial clinical improvement criterion.
    In response to questions raised at the Town Hall, as referenced in 
the proposed rule (86 FR 25221 through 25222) as to whether the 
shortening of time to notification by Briefcase for PE represents 
substantial clinical improvement, the applicant reiterated data shared 
previously from the FDA Pivotal Study for Aidoc Briefcase for PE.\28\ 
The applicant conducted a blinded, multi-center, multi-national study 
with Briefcase for PE that used the software's performance in 
identifying CTPAs containing pulmonary embolism as the primary 
endpoint, and time to notification for true positive PE cases compared 
to the standard of care as the secondary endpoint. The applicant noted 
a statistically significant mean difference of 60.2 minutes in time-to-
notification between Briefcase for PE and the standard of care. Per the 
applicant, these data indicate that implementation of Briefcase for PE 
saves 60.2 minutes relative to the standard of care clinical workflow. 
The applicant further noted that data collected by the applicant in an 
unpublished study demonstrate that the real-world performance of 
Briefcase for PE is consistent with the results achieved in the 
aforementioned FDA study. Specifically, the applicant noted that across 
4,748 CTPA examinations analyzed by Briefcase over a 90-day period and 
positive for PE, that the mean time-to-notification was seven minutes. 
The applicant also examined how radiologists engage with Briefcase for 
PE, noting that across 2,795 CTPA examinations analyzed by Briefcase 
over a 90-day period and positive for PE, the mean time-to-open as 
measured by calculating the time between when a notification first 
becomes available and the time of open, was 2.13 minutes. In this same 
data, the mean open rate across all customers were found to be 97 
percent, and that over 90 percent of notifications were found to be 
opened in under 5 minutes. The applicant asserted in light of this data 
that by identifying cases of suspected PE and triaging and notifying 
radiologists of such cases, Briefcase for PE substantially shortens the 
time to diagnosis and therefore can impact the time to treat PE cases 
compared to the standard of care.
---------------------------------------------------------------------------

    \28\ Aidoc Briefcase for PE--Pivotal Study 1--FDA 510(k)--
K190072.
---------------------------------------------------------------------------

    Further, the applicant submitted additional clinical evidence from 
Bader et al,\29\ that demonstrates that implementation of Briefcase for 
PE resulted in significant reduction of time to anticoagulation and 
reduction in length of stay in patients diagnosed with PE who were 
administered anticoagulation (intravenous or subcutaneous). In Bader et 
al, the study evaluated patient records prior to and following 
installation of Briefcase for PE, analyzing time to anticoagulation and 
patient length of stay. A total of 118 patients diagnosed with PE-77 
pre-installation and 41 post-installation-were identified. The study 
found a 23.8-minute reduction in mean time to

[[Page 44988]]

anticoagulation following the installation of Briefcase for PE from 
61.74 minutes to 37.92 minutes. The study also found a 1.56 day 
reduction in mean length of stay following the installation of 
Briefcase for PE from 5.71 days to 4.15 days.
---------------------------------------------------------------------------

    \29\ Bader AS. ``Artificial Intelligence software for flagging 
Pulmonary Embolism on CTPA is associated with a reduced Time to 
Anticoagulation and reduced Hospital Length of Stay.'' Unpublished 
manuscript submitted for publication.
---------------------------------------------------------------------------

    In response to our concerns about using FIFO workflow as the 
standard of care against which Briefcase for PE was evaluated, the 
applicant stated that other forms of prioritization such as verbal 
communication or STAT orders have limitations. The applicant stated 
that verbal communication is typically used only in severe cases, which 
are rare and represent less than 5 percent of positive PE cases. The 
applicant also stated that most patients diagnosed with PE have less 
severe clinical signs and symptoms at the time of presentation, making 
verbal communication impossible without the determination of the 
absence or presence of PE using CTPA.\30\ The applicant asserted that 
STAT orders can be overused, citing one article published by Fairview 
Health Services that up 70% of all portable chest x-rays are ordered 
STAT,\31\ and another article citing data from Emory University that up 
to 60% of all brain MRI studies are ordered as STAT and demonstrated 
that the STAT designation had a negative effect on read time.\32\ The 
applicant stated that this overuse of STAT orders would reduce the 
benefit of the prioritization method. The applicant stated that many 
Briefcase for PE customers in fact rely on the product to re-prioritize 
the STAT cases using the additional insight from the AI image-based 
triage and prioritization.
---------------------------------------------------------------------------

    \30\ Kucher N, Rossi E, De Rosa M, and Goldhaber S. Massive 
Pulmonary Embolism. Circ J. 2006;113:577-582.
    \31\ Wesp W. Using STAT Properly. Radiology Management 2006;26-
33. https://www.ahra.org/AM/Downloads/OnlineEd/2005JanFeb2.pdf
    \32\ https://www.radiologybusiness.com/topics/care-delivery/rsna-2017-overuse-stat-designation-slows-mri-workflow-causes-confusion.
---------------------------------------------------------------------------

    In response to our concerns that the applicant had not discussed 
any potential outcome concerns associated with this type of clinical 
decision support tool, the applicant reasserted its position from the 
Town Hall that the device is not intended to diagnose PE, and as a 
triage and notification system, no patient harm results from suspected 
false positive or negative findings because the radiologist would 
review images to make final determinations per the standard of care. 
The applicant cited post-market surveillance data, which show that 
there have been zero reports of adverse effects since FDA clearance, to 
support the notion that Briefcase for PE has not led to significant 
changes in the volume of CTPAs ordered prior to and following 
installation.33 34
---------------------------------------------------------------------------

    \33\ Raskin D, Hoffmann C, Twig G, Konen E, et al. Artificial 
Intelligence Software for Flagging Pulmonary Embolism on CTPA 
Associated with Reduction of Mortality.
    \34\ Maya M et al. Artificial Intelligence Software for Flagging 
Pulmonary Embolism on CTPA Associated with Reduced Length of Stay. 
Cedars Sinai Medical Center, abstract submitted to RSNA 2020.
---------------------------------------------------------------------------

    In response to our concerns on the impact of the use of Briefcase 
for PE on treatment outcomes and whether a reduction in time of 
notification translates into a positive treatment outcome and thus a 
substantial clinical improvement, the applicant submitted data shared 
previously from Raskin et al,\35\ Bader et al.,\36\ Maya et al.,\37\ 
that indicated a reduction on 120-day and 30-day mortality 
respectively; and reductions in length of stay after the introduction 
of Briefcase for PE into the clinical workflow. Specifically, in Raskin 
et al. the retrospective study examined the impact of the use of 
Briefcase for PE on outcomes in PE patients. This study involved a 
retrospective analysis of 1,258 patient medical records for cases 
performed over the two time periods and observed statistically 
significant reductions of 21.8% and 26.6% in 120-day and 30-day 
mortality respectively. Additionally, both Maya et al and Bader et al 
observed statistically significant reductions in length of stay when 
comparing pre and post-implementation of Briefcase for PE and found 
observed reductions of 26.3% and 27.3% in length of stay respectively.
---------------------------------------------------------------------------

    \35\ Raskin D, Hoffmann C, Twig G, Konen E, et al. Artificial 
Intelligence Software for Flagging Pulmonary Embolism on CTPA 
Associated with Reduction of Mortality.
    \36\ Bader AS. ``Artificial Intelligence software for flagging 
Pulmonary Embolism on CTPA is associated with a reduced Time to 
Anticoagulation and reduced Hospital Length of Stay.'' Unpublished 
manuscript submitted for publication.
    \37\ Maya M et al. Artificial Intelligence Software for Flagging 
Pulmonary Embolism on CTPA Associated with Reduced Length of Stay. 
Cedars Sinai Medical Center, abstract submitted to RSNA 2020.
---------------------------------------------------------------------------

    Response: We appreciate the additional data shared by the applicant 
to address our concerns. However, after review of all the data received 
to date, we continue to have concerns regarding the substantial 
clinical improvement criterion as noted in the FY 2022 IPPS/LTCH PPS 
proposed rule. Specifically, it remains unclear if the data provides 
sufficient evidence that use of Briefcase for PE significantly improves 
clinical outcomes for PE patients as compared to currently available 
workflows. While the applicant provided evidence that implementation of 
Briefcase for PE resulted in significant reduction of time to 
anticoagulation and reduction in length of stay in patients diagnosed 
with PE who were administered anticoagulation, we note that the studies 
submitted by the applicant did not directly assess outcomes using the 
technology but rather relied on the assumption that faster treatment 
leads to better outcomes. We also note that studies submitted in 
support of the applicant's substantial clinical improvement claims 
compare the technology to unassisted (FIFO) workflows and do not 
account for existing electronic (for example EHR ``STAT orders'') or 
manual (for example verbal communication to radiologist) forms of 
prioritization. We note the applicant's statement that STAT orders may 
be overused but the evidence provided was from other imaging studies 
and not for CTPA. Additionally, some of the studies provided by the 
applicant took place over separate time periods and may not have 
accounted for improvements in care for patients with suspected PE that 
may have occurred during the study period.
    Therefore, after consideration of the public comments we received 
and based on the information stated previously, we remain unable to 
determine that Briefcase for PE represents a substantial clinical 
improvement over existing therapies, and we are not approving new 
technology add-on payments for the Briefcase for PE for FY 2022.
b. RYBREVANTTM (amivantamab)
    Johnson & Johnson Health Care Systems, Inc. applied for new 
technology add-on payments for RYBREVANTTM (amivantamab) for 
FY 2022. RYBREVANTTM is intended for the treatment of 
metastatic non-small cell lung cancer (NSCLC). The applicant stated 
RYBREVANTTM is a bispecific monoclonal antibody able to 
inhibit the epidermal growth factor receptor (EGFR) and c-MET tyrosine 
kinase signaling pathways known to be involved in the pathogenesis of 
NSCLC. Per the applicant, RYBREVANTTM works by binding EGFR 
and c-MET targets present on the outside of the cell. The applicant 
noted lung cancer is the second most common cancer in the U.S., and 
approximately 85 percent of all lung cancers are NSCLC. The applicant 
stated EGFR mutations are present in 10 to 15 percent of patients with 
NSCLC and are categorized as either common EGFR mutations or atypical 
EGFR mutations. Per the applicant, common EGFR mutations in patients 
with NSCLC can be treated with small molecule, oral tyrosine kinase 
inhibitors that work inside the cell while patients with atypical EGFR

[[Page 44989]]

mutations, such as exon 20 insertion mutations, do not respond well to 
small-molecule, oral EGFR inhibitors or to chemotherapy. The applicant 
stated exon 20 insertion mutations are the most frequently observed 
atypical EGFR mutations affecting 4 to 10 percent of NSCLC patients 
with an EGFR mutation, but there are no FDA approved targeted therapies 
for NSCLC patients with exon 20 insertion mutations.
    With respect to the newness criterion, the applicant stated that, 
in March 2020, RYBREVANTTM (also known as JNJ-61186372) 
received Breakthrough Therapy designation from the FDA for the 
treatment of patients with metastatic NSCLC with EGFR exon 20 insertion 
mutation whose disease has progressed on or after platinum-based 
chemotherapy. RYBREVANTTM was approved by the FDA on May 21, 
2021, for the treatment of adult patients with locally advanced or 
metastatic NSCLC with EGFR exon 20 insertion mutations, as detected by 
an FDA-approved test, whose disease has progressed on or after 
platinum-based chemotherapy. The applicant submitted a request for a 
unique ICD-10-PCS procedure code to identify use of the technology and 
was granted approval for the following procedure codes effective 
October 1, 2021: XW033B7 (Introduction of amivantamab monoclonal 
antibody into peripheral vein, percutaneous approach, new technology 
group 7) and XW043B7 (Introduction of amivantamab monoclonal antibody 
into central vein, percutaneous approach, new technology group 7).
    As previously discussed, if a technology meets all three of the 
substantial similarity criteria under the newness criterion, it would 
be considered substantially similar to an existing technology and would 
not be considered ``new'' for the purpose of new technology add-on 
payments.
    With regard to the first criterion, whether a product uses the same 
or similar mechanism of action to achieve a therapeutic outcome, the 
applicant asserted that the mechanism of action of 
RYBREVANTTM for treating NSCLC is unique as amivantamab is 
anticipated to be the first FDA-approved bispecific antibody therapy 
targeting EGFR and MET mutations simultaneously. The applicant asserted 
that both EGFR and MET are involved in NSCLC pathogenesis, progression, 
and development of resistance to other therapies. According to the 
applicant, the most common first-line treatment for atypical EGFR-
positive patients due to exon 20 insertion mutations is platinum-based 
chemotherapy. Per the applicant, there is no standard of care after 
progression for second-line treatment, and patients receive a variety 
of therapies such as chemotherapy, immunotherapy, and tyrosine kinase 
inhibitors, as well as combinations of these therapies. The applicant 
reiterated that none of these treatments are FDA approved for this 
patient population and that they are associated with limited efficacy 
for these patients.
    With respect to the second criterion, whether a product is assigned 
to the same or a different MS-DRG, the applicant stated that the use of 
amivantamab is not expected to affect the DRG assignment. In their cost 
analysis, as shown below, the applicant identified several MS-DRGs 
relevant to this technology.
BILLING CODE 4120-01-P
[GRAPHIC] [TIFF OMITTED] TR13AU21.161

    With respect to the third criterion, whether the new use of the 
technology involves the treatment of the same or a similar type of 
disease and the same or similar patient population, the applicant 
stated that RYBREVANTTM treats a distinct patient population 
with metastatic NSCLC: Metastatic NSCLC with exon 20 insertion 
mutations whose disease has progressed on or after platinum-based 
chemotherapy. Per the applicant, there were no FDA-approved therapies 
at the time of the proposed rule for this patient population, and the 
most commonly used therapies are associated with limited efficacy.
    In summary, the applicant asserted that RYBREVANTTM 
should be considered new and not substantially similar to an existing 
technology because the mechanism of action of RYBREVANTTM 
for treating NSCLC is unique and it treats a distinct patient 
population.
    We invited public comments on whether RYBREVANTTM is 
substantially similar to other currently available therapies and/or 
technologies and whether this technology meets the newness criterion.
    Comment: The applicant submitted a comment reiterating that 
RYBREVANTTM meets the newness criterion because it does not 
meet two of the substantial similarity criteria. The applicant stated 
that it does not meet the first criterion because 
RYBREVANTTM's mechanism of action for treating NSCLC is 
unique in that it is the first FDA-approved bispecific antibody therapy 
targeting EGFR and MET mutations simultaneously, and it does not meet 
the third criterion since it treats a distinct patient population with 
metastatic NSCLC with exon 20 insertion mutations for which there is no 
other FDA-approved therapy.
    Response: We thank the applicant for their comment. Based on this 
comment and on information submitted by the applicant as part of its FY 
2022 new technology add-on payment application for 
RYBREVANTTM, as discussed in the proposed rule (86 FR 25222 
through 25227) and previously summarized, we believe that 
RYBREVANTTM has a unique mechanism of action due to treating 
NSCLC via bispecific antibody therapy targeting EGFR and MET mutations 
simultaneously. We also agree that RYBREVANTTM treats a new 
patient population, as there are no other FDA-approved therapies for 
patients

[[Page 44990]]

with metastatic NSCLC with exon 20 insertion mutations. Therefore, we 
believe RYBREVANTTM is not substantially similar to existing 
treatment options and meets the newness criterion. We consider the 
beginning of the newness period to commence when RYBREVANTTM 
was approved by FDA for the indication of treatment of advanced or 
metastatic NSCLC with EGFR Exon 20 insertion mutations, on May 21, 
2021.
    With regard to the cost criterion, the applicant provided the 
following analysis to demonstrate that the technology meets the cost 
criterion. The applicant searched the FY 2019 Medicare Provider 
Analysis and Review (MedPAR) final rule file for cases based on the 
presence of one of the following ICD-10-CM diagnosis codes for lung 
cancer:
[GRAPHIC] [TIFF OMITTED] TR13AU21.162


[[Page 44991]]


    We note that the applicant also provided the following ICD-10-PCS 
procedure codes, which the applicant stated could be used to identify 
cases involving RYBREVANTTM in the absence of a unique ICD-
10-PCS code.
[GRAPHIC] [TIFF OMITTED] TR13AU21.164

    To further refine the cases used in the analysis, the applicant 
used the following methodology. Per the applicant, clinical data 
suggests 80 to 85 percent of lung cancer patients are NSCLC 
patients.\38\ The applicant stated that, of those patients, 10-15 
percent are EGFR-mutations patients,39 40 and of those, at 
least 9 percent have atypical EGFR mutations like exon 20 ins.\41\ The 
applicant selected 0.93% (82.5% * 12.5% * 9%) of the cases identified 
based on the lung cancer diagnosis codes listed previously. The 
applicant stated this is the target population for 
RYBREVANTTM, which the applicant used for the cost analysis.
---------------------------------------------------------------------------

    \38\ ``What is Lung Cancer?'' American Cancer Society. 1 October 
2019: https://www.cancer.org/content/cancer/en/cancer/lung-cancer/about/what-is.html.
    \39\ Wee, P., & Wang, Z. (2017). Epidermal growth factor 
receptor cell proliferation signaling pathways. Cancers, 9(5), 52.
    \40\ Pao, W., & Girard, N. (2011). New driver mutations in non-
small-cell lung cancer. The Lancet Oncology, 12(2), 175-180.
    \41\ Arcila, M. E., Nafa, K., Chaft, J. E., Rekhtman, N., Lau, 
C., Reva, B. A., and Ladanyi, M. (2013). EGFR exon 20 insertion 
mutations in lung adenocarcinomas: prevalence, molecular 
heterogeneity, and clinicopathologic characteristics. Molecular 
Cancer Therapeutics, 12(2), 220-229.
---------------------------------------------------------------------------

    The applicant then accounted for the circumstances where 
RYBREVANTTM would be administered during an inpatient stay. 
The applicant stated that RYBREVANTTM will typically be 
administered in the outpatient setting, and that it assumed that 
RYBREVANTTM would be administered during an inpatient stay, 
possibly for care unrelated to a patient's cancer treatment, when that 
stay coincided with the 2-week cycle during which a patient receiving 
RYBREVANTTM would undergo an infusion in the outpatient 
setting were it not for their inpatient admission. The applicant stated 
that, because it is very important that patients receive continuity of 
cancer care, it assumed that some patients would receive their 
RYBREVANTTM infusion during their hospital stay. To account 
for this scenario, the applicant calculated the average length of stay 
for all of the cases in its patient population, which it asserted was 
about 5.862 days. The applicant then divided the average length of stay 
for all of the cases by 14, as per the applicant RYBREVANTTM 
is administered on 28-day cycle, with a weekly administration for the 
first cycle, and an administration every 2 weeks thereafter.
    The applicant stated that current clinical guidelines are expected 
to give medical professionals discretion to administer 
RYBREVANTTM during the hospitalization or pause the 
treatment cycle. To account for physician discretion, the applicant 
included only 50 percent of these cases in the final cost analysis.
    The applicant identified 349 cases mapping to the following MS-
DRGs. The applicant has not made a request for RYBREVANTTM 
to map to a new or different MS-DRG for FY 2022.
[GRAPHIC] [TIFF OMITTED] TR13AU21.165


[[Page 44992]]


BILLING CODE 4120-01-C
    The applicant assumed patients receiving RYBREVANTTM 
would receive one dose of the drug during their inpatient stay. Because 
RYBREVANTTM would be administered in addition to any other 
drugs the patient was receiving during their inpatient admission, the 
applicant did not remove costs associated with any previous technology. 
The applicant then standardized the charges using the FY 2019 IPPS/LTCH 
PPS final rule Impact file. Then the applicant applied the 2-year 
inflation factor of 13.2 percent (1.13218) from the FY 2021 IPPS/LTCH 
PPS final rule (85 FR 59039). The applicant then added charges for 
RYBREVANTTM, which the applicant determined using the 
inverse of the FY 2021 IPPS/LTCH PPS final rule pharmacy national 
average cost to charge ratio (CCR) of 0.187 (85 FR 58601).
    Because the applicant calculated a final inflated average case-
weighted standardized charge per case of $108,159, which exceeds the 
case weighted threshold of $64,736, the applicant maintained the 
technology meets the cost criterion.
    Based on the information provided by the applicant, we stated in 
the proposed rule that we had several concerns with regard to whether 
the technology meets the cost criterion. In its cost analysis, the 
applicant combined 234 cases from multiple MS-DRGs into one group with 
a case-weight of 67 percent of cases. We stated that we do not believe 
this is appropriate for the cost analysis. As reflected in Sec.  
412.87(b)(3), where cases eligible for a particular technology may be 
assigned to multiple MS-DRGs, in performing the cost analysis, the 
applicant should compare the charges of the cases to a threshold amount 
that is the lesser of 75 percent of the standardized amount or 75 
percent of one standard deviation beyond the case-weighted average of 
all MS-DRGs to which the cases map. In the event that a single MS-DRG 
has fewer than 11 cases, the applicant should impute a minimum case 
number of 11 rather than the actual value. In this way, the appropriate 
threshold and case weighted threshold value can be calculated.
    In its analysis, the applicant appeared to take a sample of a 
larger case population based on clinical data. We stated that it was 
unclear whether the applicant was taking a simple random sample or a 
targeted sample of cases. We noted that, if the applicant obtained a 
random sample, this sample may not be any more representative of the 
larger population of cases identified by the lung cancer diagnosis 
codes listed previously. If the applicant instead non-randomly sampled 
cases from the larger population, we stated that we would like to 
understand the process used by the applicant to identify this targeted 
sample. We requested information under either approach on how a 
sampling of cases from the greater population is more representative of 
potential RYBREVANTTM patients.
    We invited public comments on whether RYBREVANTTM meets 
the cost criterion.
    Comment: The applicant provided clarifications to their analysis. 
With respect to the concern that the applicant combined cases from 
multiple MS-DRGs into one group with a case weight of 67 percent, the 
applicant was in agreement that it is not appropriate to combine cases 
that fall below the 11-case blinding threshold. The applicant stated 
that, in response to CMS' concern, they provided two versions of the 
table--one in the application pdf file with MS-DRGs that had fewer than 
11 cases grouped into an ``all other'' category--and the full Excel 
file showing the complete list of DRGs, even if they had fewer than 11 
cases.
    With respect to CMS' request for information on how a random 
sampling of cases from the greater population is more representative of 
potential RYBREVANTTM patients, the applicant first 
reiterated the assumptions behind its original cost analysis. The 
applicant pointed to clinical data from the American Cancer Society 
suggesting 80 to 85 percent of lung cancer patients are NSCLC patients, 
and that of those patients, 10-15 percent are EGFR-mutations, and of 
those, at least 9 percent are atypical EGFR mutations like exon 20 
insertions which per the applicant is the target patient population for 
RYBREVANTTM. The applicant also stated its assumption that, 
although RYBREVANTTM will typically be administered in the 
outpatient setting, there would be situations in which the patient 
would be admitted to the hospital for care that is possibly unrelated 
to their cancer treatment, and that this inpatient stay would coincide 
with the day that they would normally receive RYBREVANTTM as 
part of their ongoing cancer treatment. Per the applicant, 
RYBREVANTTM's dosing regimen would mean that many 
beneficiaries' inpatient stays would not coincide with the 
RYBREVANTTM treatment scenario, and that to account for this 
scenario, the applicant calculated the average length of stay for all 
of the cases in its patient population and divided the average length 
of stay for all of the cases by 14, after which the applicant 
multiplied this new factor by the number of cases in the sample to 
reduce the sample to those cases where the RYBREVANTTM 
treatment day would occur during the hospitalization. The applicant 
then reiterated the clinical guidelines that give physicians discretion 
to administer RYBREVANTTM during the hospitalization or a 
pause in the treatment cycle, and stated that to account for this 
discretion, it included only half of these cases in its cost analysis. 
Per the applicant, these calculations are intended to acknowledge that 
while there are many patients with lung cancer diagnoses receiving 
different types of treatment in the hospital, there are only a small 
number of beneficiaries who have ESCLC and are receiving 
RYBREVANTTM that happen to be in the hospital on the day 
when they are normally scheduled to receive RYBREVANTTM 
whose physician would like to continue treatment during the 
hospitalization.
    The applicant then addressed CMS' concerns by presenting a revised 
analysis including only the cases with the lowest total charges at each 
of its filtering points, rather than selecting a random sample. The 
applicant explained that the cases with the lowest total charges are 
the least likely to meet the cost criterion threshold, and so selecting 
those cases represented the most conservative option in selecting a 
sample. The applicant first reran the analysis selecting 0.93 percent 
of cases with the lowest total charges to account for the portion of 
lung cancer patients who have NSCLC and atypical EGFR mutations. The 
applicant further filtered the cases to account for the patients who 
would receive RYBREVANTTM in the hospital based on timing 
and physician discretion, resulting in a sample of 91 cases which the 
applicant reiterated had the lowest total charges. The applicant then 
added charges for RYBREVANTTM based on the drug's WAC, 
resulting in a final inflated case-weighted standardized charge per 
case that exceeded the case weighted threshold, and the applicant 
maintained that RYBREVANTTM meets the cost criterion.
    Response: We thank the applicant for its comments addressing our 
concerns regarding the cost criterion. We appreciate the explanation of 
the sampling methodology behind the applicant's original analysis as 
well as its revised analysis representing the most conservative 
approach using cases with the lowest total charges that are least 
likely to meet the cost criterion. We agree that the applicant's 
approach

[[Page 44993]]

to sampling is reasonable and representative of potential 
RYBREVANTTM patients and that RYBREVANTTM meets 
the cost criterion.
    With respect to the substantial clinical improvement criterion, the 
applicant asserted that RYBREVANTTM represents a substantial 
clinical improvement over existing technologies. The applicant asserted 
several claims of substantial clinical improvement for 
RYBREVANTTM: (1) RYBREVANTTM is anticipated to be 
the first therapy to treat the metastatic NSCLC with exon 20 insertion 
mutations for patients whose disease has progressed on or after 
platinum-based chemotherapy; (2) the objective response rate (ORR) was 
higher than what would be expected with chemotherapy or immunotherapy; 
(3) a clinical benefit rate higher than what would be expected with 
chemotherapy or immunotherapy; (4) a duration of response higher than 
what would be expected with chemotherapy or immunotherapy; (5) the 
median progression free survival was higher than what would be expected 
with chemotherapy or immunotherapy; and (6) the incidence and severity 
of diarrhea was lower than what would be expected with any oral EGFR 
inhibitor.
    The applicant stated that patients with NSCLC and EGFR exon 20 
insertion mutations have a form of disease that is generally 
insensitive to available EGFR TKI treatments and, as a result, carries 
a worse prognosis compared to patients with more common EGFR 
mutations.\42\ Per the applicant, the current standard of care for the 
initial treatment of exon 20 insertion metastatic NSCLC is platinum-
based chemotherapy; \43\ and, after a patient with EGFR exon 20 
insertion metastatic NSCLC disease progresses on or during platinum-
based chemotherapy, there is no standard of care. The applicant stated 
there are currently no FDA-approved targeted therapies for patients 
with lung cancer who have EGFR exon 20 insertion mutations.\44\ The 
applicant cited an analysis of the Flatiron Health database, which 
includes electronic health data records from over 265 cancer clinics 
representing over 2 million active US cancer patients, that found 
prescribers use a wide variety of treatment strategies, all of which 
have an unclear role in the second-line treatment of exon 20 insertion 
mutated metastatic NSCLC or are known to be ineffective and/or have 
potential tolerability issues.\45\ Specifically, the analysis showed 
that in the second-line treatment of exon 20 insertion metastatic 
NSCLC, approximately 33 percent of patients received single-agent 
immunotherapy, 14.1 percent received an EGFR-targeting oral agent, 5.9 
percent received chemoimmunotherapy combination, 5.9 percent received 
chemotherapy with a VEGF inhibitor, 5.9 percent received a clinical 
study drug, and the remainder received a variety of single-agent 
chemotherapies or other regimens. The applicant stated this re-iterates 
the lack of an accepted standard of care for the second-line treatment 
of exon 20 insertion metastatic NSCLC and thus underscores the unmet 
need of these patients. The applicant stated in their application that 
based on the Breakthrough Therapy designation for 
RYBREVANTTM, it was anticipated that 
RYBREVANTTM's first expected approval would be for the 
second-line treatment of exon 20 insertion metastatic NSCLC.
---------------------------------------------------------------------------

    \42\ Vyse, S., and Huang, P. H. (2019). Targeting EGFR exon 20 
insertion mutations in non-small cell lung cancer. Signal 
Transduction and Targeted Therapy, 4(1), 1-10.
    \43\ Chantharasamee, J., Poungvarin, N., Danchaivijitr, P., and 
Techawatanawanna, S. (2019). Clinical outcome of treatment of 
metastatic non-small cell lung cancer in patients harboring uncommon 
EGFR mutation. BMC Cancer, 19(1), 701.
    \44\ Yasuda, H., Kobayashi, S., and Costa, D. B. (2012). EGFR 
exon 20 insertion mutations in non-small-cell lung cancer: 
preclinical data and clinical implications. The Lancet Oncology, 
13(1), e23-e31.
    \45\ Flatiron Health database, Second Line Treatment Regimens in 
Advanced NSCLC (January 2015-October 2019).
---------------------------------------------------------------------------

    The applicant provided three references to support a finding of 
substantial clinical improvement for RYBREVANTTM as well as 
some supplementary information in the application itself. The first 
reference was a conference presentation given at the 2019 Annual 
Meeting of the Society for Clinical Oncology titled ``JNJ-61186372 
(JNJ-372), an EGFR-cMet bispecific antibody, in EGFR-driven advanced 
non-small cell lung cancer (NSCLC)'' by Haura et al. The second was a 
poster presented at the 2020 Annual Meeting of the American Society for 
Clinical Oncology titled ``Amivantamab (JNJ-61186372), an anti-EGFR-MET 
bispecific antibody, in patients with EGFR Exon 20 insertion 
(Exon20ins)-mutated non-small cell lung cancer (NSCLC)'' by Park et al. 
The third was a conference presentation given in January 2021 at the 
World Conference on Lung Cancer titled ``Amivantamab in Post-platinum 
EGFR Exon 20 Insertion Mutant Non-small Cell Lung Cancer'' by Sabari et 
al.
    These three references all describe the ongoing Phase 1 trial 
titled ``A Phase 1, First-in-Human, Open-Label, Dose Escalation Study 
of JNJ-61186372, a Human Bispecific EGFR and cMet Antibody, in Subjects 
With Advanced Non-Small Cell Lung Cancer'' (https://clinicaltrials.gov/ct2/show/NCT02609776). This open label, multicenter, first-in-human 
study, also known as ``CHRYSALIS,'' consists of two parts.\46\ Part 1 
was a dose escalation study used to establish the recommended Phase 2 
dosing regimen.\47\ Part 2 was a dose expansion study to assess safety 
and efficacy at the recommended Phase 2 dosing regimen.\48\ The primary 
efficacy endpoint was the overall response rate per Response Evaluation 
Criteria in Solid Tumors v1.1.\49\ Key secondary endpoints included 
clinical benefit rate (CBR), duration of response (DOR), progression-
free survival (PFS), and overall survival (OS).\50\
---------------------------------------------------------------------------

    \46\ https://clinicaltrials.gov/ct2/show/study/NCT02609776 
https://clinicaltrials.gov/ct2/show/study/NCT02609776.
    \47\ Sabari JK, Shu CA, Park K, et al. Amivantamab in post-
platinum EGFR exon 20 insertion mutant non-small cell lung cancer. 
Oral presentation presented at: International Association for the 
Study of Lung Cancer (IASLC) 2020 World Conference on Lung Cancer 
Singapore (WCLC 2020); January 28-31, 2021; Worldwide Virtual Event.
    \48\ Ibid.
    \49\ Ibid.
    \50\ Ibid.
---------------------------------------------------------------------------

    Key eligibility criteria for the post-platinum population of 
patients enrolled in the study included: Metastatic/unresectable NSCLC, 
EGFR exon 20 insertion mutation, and progression on platinum-based 
chemotherapy.\51\ Patients received the recommended Phase 2 dose of 
1050 mg (1400 mg for patients >=80 kg) amivantamab intravenously once 
weekly for the first cycle and biweekly thereafter.\52\ The safety 
population (N=114) included all post-platinum exon 20 ins patients who 
received amivantamab at the recommended Phase 2 dose, and the response-
evaluable population (n=81) included post-platinum exon 20 ins patients 
who had at least three disease assessments or had discontinued, 
progressed, or died prior to the third post-baseline assessment at the 
time of clinical cut-off.\53\
---------------------------------------------------------------------------

    \51\ Ibid.
    \52\ Ibid.
    \53\ Ibid.
---------------------------------------------------------------------------

    In the efficacy population, the median age was 62.\54\ In addition, 
59 percent of the patients were female, 49 percent of the patients were 
Asian, and 47 percent had a history of smoking.\55\ Median time from 
initial diagnosis was 17 months

[[Page 44994]]

with a range of 1-130 months.\56\ All patients, by definition, had a 
prior history of platinum-based chemotherapy while 46 percent had prior 
immuno-oncology therapy and 25 percent had a history of EGFR TKI 
treatment.\57\
---------------------------------------------------------------------------

    \54\ Ibid.
    \55\ Ibid.
    \56\ Ibid.
    \57\ Ibid.
---------------------------------------------------------------------------

    In the safety population, 98 percent of patients experienced a 
treatment-related adverse event.\58\ Of these, 16 percent were Grade 3 
or higher, 9 percent were serious, 4 percent led to discontinuation, 13 
percent led to dose reduction, and 21 percent led to dose 
interruption.\59\ Of note, 2 percent discontinued due to rash and 10 
percent had treatment-related diarrhea with 8.5 percent at grade 1-2 
and 3.5 percent at grade 3.\60\
---------------------------------------------------------------------------

    \58\ Ibid.
    \59\ Ibid.
    \60\ Ibid.
---------------------------------------------------------------------------

    The applicant stated that preliminary safety results from the 
CHRYSALIS trial presented at the 2020 ASCO meeting appear to 
demonstrate that amivantamab has a manageable safety profile, with 60% 
of adverse events at grade 1 to 2.\61\ Per the applicant, this appears 
to be an improvement relative to the types and frequency of adverse 
events reported for platinum based chemotherapies overall in advanced 
NSCLC, with over half of patients reporting adverse events of grade 3 
to 5, such as neutropenia, nausea, and vomiting.\62\ The applicant 
noted the best tolerated EGFR-targeting oral agent osimertinib was 
associated with a rate of discontinuation due to adverse events of 13 
percent in the phase 3 FLAURA study.\63\ In addition, the applicant 
noted osimertinib was associated with a rate of any grade diarrhea of 
58 percent with 2 percent of patients having grade 3 or higher in this 
study.\64\ In the same phase 3 FLAURA study, the applicant noted the 
comparator arm (gefitinib or erlotinib) was associated with a 57 
percent incidence of any grade diarrhea with 2 percent of patients 
experiencing grade 3 or higher.
---------------------------------------------------------------------------

    \61\ 2020 ASCO Annual Meeting: Park, K, et al. J Clin Oncol 
38:2020 (suppl; abstr 9512).
    \62\ Schiller, JH et al. (2002). Comparison of four chemotherapy 
regimens for advanced non-small-cell lung cancer. New England 
Journal of Medicine, 346(2), 92-98.
    \63\ Ibid.
    \64\ Ibid.
---------------------------------------------------------------------------

    Regarding efficacy, in the Sabari et al reference, a blinded 
independent central review found an ORR in the efficacy population of 
40 percent (95 percent CI 29-51) and a median DOR of 11.1 months (95 
percent CI 6.9-not reached).\65\ Patients experienced a complete 
response in 4 percent of cases, partial response in 36 percent of 
cases, stable disease in 48 percent of cases, progressive disease in 10 
percent of cases, and one percent of patients was not evaluable.\66\ 
Finally, the CBR (defined as complete response, partial response, or 
stable disease for at least two disease assessments) was 74 percent (95 
percent CI 63-83).\67\ The median patient follow-up in this most recent 
analysis was 9.7 months (range 1.1-29.3). Of note, 47 percent of 
patients remained on treatment at time of data cutoff and 63 percent 
had responses of at least six months.\68\ The median PFS was 8.3 months 
(95 percent CI 6.5-10.9), and the median overall survival was 22.8 
months (95 percent CI 14.6-not reached).\69\
---------------------------------------------------------------------------

    \65\ Sabari JK, Shu CA, Park K, et al. Amivantamab in post-
platinum EGFR exon 20 insertion mutant non-small cell lung cancer. 
Oral presentation presented at: International Association for the 
Study of Lung Cancer (IASLC) 2020 World Conference on Lung Cancer 
Singapore (WCLC 2020); January 28-31, 2021; Worldwide Virtual Event.
    \66\ Ibid.
    \67\ Ibid.
    \68\ Ibid.
    \69\ Ibid.
---------------------------------------------------------------------------

    The applicant stated that, while direct comparison between 
therapies cannot be definitively made in the absence of comparative 
trials, amivantamab results appear promising and numerically better 
than those expected with current therapies (chemotherapy, 
immunotherapy, chemoimmunotherapy combination, or oral EGFR tyrosine 
kinase inhibitors) based on available data. The applicant stated 
platinum-based chemotherapy has been associated with a median 
progression free survival of 5.1 to 6.0 months in patients with exon 20 
T790m mutations--the most common mutation observed following resistance 
to small molecule TKI inhibitors commonly used in advanced EGFR 
mutation positive NSCLC.\70\ The applicant stated that oral EGFR 
tyrosine kinase inhibitors (for example, erlotinib, gefitinib, 
afatinib, dacomitinib, osimertinib) and immunotherapies are also used 
to treat patients with exon 20 insertion metastatic NSCLC but generally 
have limited efficacy as exon 20 insertion mutations have been 
associated with resistance to EGFR tyrosine kinase inhibitors.\71\ The 
applicant stated most immunotherapy and chemoimmunotherapy studies have 
excluded patients with EGFR mutation because single-agent 
immunotherapies have very limited efficacy in patients with EGFR-
mutated NSCLC.
---------------------------------------------------------------------------

    \70\ Yoshida, T., Kuroda, H., Oya, Y., Shimizu, J., Horio, Y., 
Sakao, Y., et al. . . . and Yatabe, Y. (2017). Clinical outcomes of 
platinum-based chemotherapy according to T790M mutation status in 
EGFR-positive non-small cell lung cancer patients after initial 
EGFR-TKI failure. Lung Cancer, 109, 89-91.
    \71\ Vyse, S., & Huang, P.H. (2019). Targeting EGFR exon 20 
insertion mutations in non-small cell lung cancer. Signal 
Transduction and Targeted Therapy, 4(1), 1-10.
---------------------------------------------------------------------------

    The applicant provided the following table 1, which outlines median 
progression free survival (mPFS) and response rate (ORR) data among 
patients with exon 20 insertion mutation for amivantamab and some of 
the currently existing therapies. The applicant noted this table is 
intended to provide general information about individual therapies and 
is not intended for making direct comparisons between therapies as 
differences between study populations, follow-up time, prior 
treatments, and other factors may exist.
[GRAPHIC] [TIFF OMITTED] TR13AU21.166


[[Page 44995]]


    Finally, the applicant cited an analysis presented at the 2020 
American Society of Clinical Oncology (ASCO) Annual Meeting, which 
found patients experienced a median ORR of 13% and PFS of 3.5 months 
when receiving a wide variety of different therapies, including 
immunotherapies, chemoimmunotherapies, EGFR-targeting TKIs, and other 
chemotherapy regimens as second-line treatment.\72\
---------------------------------------------------------------------------

    \72\ Park, K. (2020, May). Amivantamab (JNJ-61186372), an anti-
EGFR-MET bispecific antibody, in patients with EGFR Exon 20 
insertion (Exon20ins)-mutated non-small cell lung cancer (NSCLC). 
Poster presented at the 2020 Annual Meeting of the American Society 
of Clinical Oncology.
---------------------------------------------------------------------------

    In the proposed rule, after review of the information provided by 
the applicant, we noted the following concerns regarding whether the 
technology meets the substantial clinical improvement criterion. We 
stated that at the time, results provided by the applicant were based 
on an ongoing Phase 1 trial. We were concerned that these are 
potentially partial results, from which end conclusions may not be 
drawn, and also about the potential for overestimating treatment 
effects when trials stop early or report interim results. We further 
noted that the only study cited by the applicant to establish 
substantial clinical improvement is a single-armed study assessing the 
safety and efficacy of RYBREVANTTM in the target population. 
As noted by the applicant, no formal comparisons to other therapies 
were made. Without the ability to control for factors such as study 
design, patient characteristics, etc., we noted that we may be unable 
to determine whether any differences seen are the result of 
RYBREVANTTM's potentially superior efficacy or confounding 
variables. We also noted that the single-arm study design results in an 
inability to distinguish between the effect of RYBREVANTTM 
treatment, a placebo effect, and the effect of natural course of the 
disease.
    We invited public comments on whether RYBREVANTTM meets 
the substantial clinical improvement criterion.
    Comment: The applicant submitted a comment regarding substantial 
clinical improvement. With regard to the concern that results provided 
by the applicant are based on an ongoing Phase 1 trial from which end 
conclusions may not be drawn, the applicant stated that these results 
supported the accelerated approval granted to RYBREVANTTM by 
the US FDA on May 21, 2021.73 74 75 The applicant also 
reiterated that RYBREVANTTM received Priority Review and 
Breakthrough Therapy designation, and explained that these designations 
are significant because they are only granted to applications for drugs 
that would be significant improvements in the safety or effectiveness 
of the treatment, diagnosis or prevention of serious conditions when 
compared to standard applications (in the case of Priority Review) or 
drugs that are intended to treat a serious condition and whose 
preliminary clinical evidence demonstrated substantial improvement over 
available therapy on clinically significant endpoints (in the case of 
Breakthrough Therapy). Per the applicant, the study that supported 
approval, CHRYSALIS (NCT02609776), is an ongoing, phase 1 multi-cohort, 
multi-center study that has not been stopped prematurely. The applicant 
noted that although enrollment has been closed for the study, patients 
continue to be followed for efficacy and safety for final data that 
will be provided to FDA when available. The applicant also noted that 
RYBREVANTTM received FDA approval based on overall response 
rate (ORR) and duration of response (DoR) which were assessed and 
confirmed by blinded independent central review (BICR) in CHRYSALIS. 
The applicant emphasized that there were no currently approved 
therapies for the target patient population with high unmet medical 
needs.76 77
---------------------------------------------------------------------------

    \73\ PR Newswire. FDA approves first targeted therapy for subset 
of non-small cell lung cancer; https://www.prnewswire.com/news-releases/fda-approves-first-targeted-therapy-for-subset-of-non-small-cell-lung-cancer-301296998.html. May 21, 2021. Accessed June 
1, 2021.
    \74\ Janssen Announces U.S. FDA Breakthrough Therapy Designation 
Granted for JNJ-6372 for the Treatment of Non-Small Cell Lung 
Cancer. https://www.jnj.com/janssen-announces-u-s-fda-breakthrough-therapy-designationgranted-for-jnj-6372-for-the-treatment-of-non-small-cell-lung-cancer. May 21, 2021. Accessed June 01, 2021.
    \75\ RYBREVANT (amivantamab-vmjw) [Prescribing Information]. 
Horsham, PA: Janssen Biotech, Inc.; https://www.janssenlabels.com/package-insert/product-monograph/prescribing-information/RYBREVANT-pi.pdf.
    \76\ Ibid. PR Newswire
    \77\ Ibid. Janssen Announces US FDA Breakthrough Therapy 
Designation Granted.
---------------------------------------------------------------------------

    The applicant also acknowledged that continued approval for this 
indication may be contingent upon verification and description of 
clinical benefit in the confirmatory trials (RYBREVANTTM 
Prescribing Information). Per the applicant, the confirmatory phase 3 
trial, which is currently enrolling, is a study of 
RYBREVANTTM in combination with platinum-based chemotherapy, 
compared to platinum-based chemotherapy alone in participants with 
advanced or metastatic NSCLC characterized by EGFR Exon 20 
insertions.\78\
---------------------------------------------------------------------------

    \78\ Janssen Research & Development, LLC. A study of combination 
amivantamab and carboplatin-pemetrexed therapy, compared with 
carboplatin-pemetrexed, in participants with advanced or metastatic 
NSCLC characterized by EGFR Exon 20 insertions. In: 
ClinicalTrials.gov [internet]. Bethesda (MD): National Library of 
Medicine (US). 2000- [cited 2021 June 01]. Available from: https://clinicaltrials.gov/ct2/show/NCT04538664. NLM Identifier: 
NCT04538664.
---------------------------------------------------------------------------

    With respect to the concern that CHRYSALIS is a single-armed study 
assessing the safety and efficacy of RYBREVANTTM in the 
target patient population, the applicant stated that because there is 
no standard of care (SOC) therapy and no randomized, comparative (head-
to-head) studies published in patients with NSCLC and EGFR exon 20 
insertion mutations, no formal comparisons to existing treatments can 
be made. The applicant stated that external controls can add valuable 
context in interpreting RYBREVANTTM efficacy and 
appreciating unmet needs with current real-world therapies, the most 
common of which are single-agent chemotherapies, immuno-oncology 
therapies, and EGFR tyrosine kinase inhibitors (TKIs). Per the 
applicant, an external control arm was constructed using three real 
world datasets from US companies. The datasets were de-duplicated and 
adjusted using propensity score weighting for differences in age, brain 
metastases, ECOG PS, and prior lines of therapy. The applicant stated 
that patients receiving RYBREVANTTM had longer OS and PFS 
than patients treated with real world therapies in the post-platinum-
based chemotherapy setting based on a recent analysis. Specifically, 
the overall response rate (ORR) was 40 percent among 
RYBREVANTTM-treated patients, 13 to 18 percent among 
external controls, and 16 percent for the pooled real-world dataset. 
The applicant also noted that RYBREVANTTM-treated patients 
had a 53 percent risk reduction in progression, a 60 percent risk 
reduction in commencement of next therapy, and a 51 percent risk 
reduction in death compared to external controls. Per the applicant, 
poor performance of the external controls reflects the ineffectiveness 
of currently available real world treatments and highlights the urgent 
need to find more targeted treatments for the patient population.\79\
---------------------------------------------------------------------------

    \79\ Minchom AR, et al. Amivantamab compared with real world 
therapies in patients with NSCLC with EGFR Exon 20 insertion 
mutations who have progressed after platinum doublet chemotherapy. 
Poster presented at: 2021 American Society of Clinical Oncology 
(ASCO) Annual Meeting; June 4-8, 2021; Virtual. Abstract 9052.

---------------------------------------------------------------------------

[[Page 44996]]

    In response to our concern that the single-arm CHRYSALIS study 
results in an inability to distinguish between the effect of 
RYBREVANTTM treatment, a placebo effect, and the effect of 
natural course of the disease, the applicant provided a poster of 
results to distinguish between the effects of RYBREVANTTM 
treatment. The applicant stated that the poster revealed that most Exon 
20 insertion mutations in NSCLC have been associated with insensitivity 
or resistance to currently available small-molecule TKIs and are 
associated with poor prognosis (93% increased risk of progression or 
death with EGFR Exon20ins compared to common EGFR mutations); 
therefore, this represents an area of high unmet medical 
need.80 81 82 83 The applicant stated that the 5-year 
relative survival rate for patients with lung and bronchus cancer is 
20.5%, with rates varying by stage from 59% with localized disease to 
6% with metastatic disease.\84\ In addition, the 5-year relative 
survival rate for patients with NSCLC is 24.9%, with rates varying by 
stage from 63% to 7% for localized and metastatic disease, 
respectively.\85\ The applicant further stated that a retrospective 
cohort study of real-world data from the Flatiron Health Database (1 
January 2011 through 21 May 2020) found that patients with metastatic 
NSCLC harboring exon 20 insertion mutations have an estimated 5-year 
survival of 8% compared to 19% for patients with common EGFR 
mutations.\86\ For these reasons, the applicant asserts that 
RYBREVANTTM demonstrates substantial clinical improvement 
for this population of patients.
---------------------------------------------------------------------------

    \72\ Arcila ME, et al. ECGR exon 20 insertion mutations in lung 
adrenocarcinomas: Prevalence, molecular heterogeneity, and 
clincopathologic characteristics. Mol Cancer Ther. 2013;12(2):220-
229.
    \81\ Yasuda H, et al. Structural, biochemical and clinical 
characterization of epidermal growth factor receptor (EGFR) exon 20 
insertion mutations in lung cancer. Sci Transl Med. 
2013;5(216):216ra177
    \82\ Yun J, et al. Antitumor activity of amivantamab (JNJ-
61186372), an EGFR-cMet bispecific antibody, in diverse models of 
EGFR Exon 20 insertion-driven NSCLC. Cancer Discov. 2020;10(8):1194-
1209.
    \83\ Girard N, et al. Comparative clinical outcomes for patients 
with NSCLC harboring EGFR exon 20 insertion mutations and common 
EGFR mutations. Oral presentation presented at: International 
Association for the Study of Lung Cancer (IASLC) 2020 World 
Conference on Lung Cancer Singapore (WCLC 2020); January 28-31, 
2021; Worldwide Virtual Event.
    \84\ National Cancer Institute Surveillance, Epidemiology, and 
End Results Program (NCI SEER). Cancer stat facts: lung and bronchus 
cancer. 2020a. Available at: https://seer.cancer.gov/statfacts/html/lungb.html. Accessed June 01, 2021.
    \85\ National Cancer Institute Surveillance, Epidemiology, and 
End Results Program (NCI SEER). Cancer statistics review, 1975-2017; 
Table 15.14. April 15, 2020b. Available at: https://seer.cancer.gov/csr/1975_2017/. Accessed June 01, 2021.
    \86\ Ibid. Girard.
---------------------------------------------------------------------------

    Response: We appreciate the additional information provided by the 
applicant in response to our concerns regarding substantial clinical 
improvement. After reviewing the information submitted by the applicant 
addressing our concerns raised in the proposed rule, we agree with the 
applicant that RYBREVANTTM represents a substantial clinical 
improvement over existing technologies because, based on the 
information provided by the applicant, the technology offers a 
treatment option for patients with metastatic NSCLC with exon 20 
insertion mutations whose disease has progressed on or after platinum-
based chemotherapy, for which it is the first and only FDA approved 
treatment.
    After consideration of the public comments we received, we have 
determined that RYBREVANTTM meets all of the criteria for 
approval for new technology add-on payments. Therefore, we are 
approving new technology add-on payments for RYBREVANTTM for 
FY 2022. Cases involving the use of RYBREVANTTM that are 
eligible for new technology add-on payments will be identified by ICD-
10- PCS procedure codes XW033B7 (Introduction of amivantamab monoclonal 
antibody into peripheral vein, percutaneous approach, new technology 
group 7) or XW043B7 (Introduction of amivantamab monoclonal antibody 
into central vein, percutaneous approach, new technology group 7).
    RYBREVANTTM is administered in 26 treatments annually 
and is estimated that the annual cost of the product will be $180,000 
per patient. In its application, the applicant stated that 
RYBREVANTTM is administered on a 28-day cycle. It is 
administered weekly for the first cycle, and every 2 weeks thereafter. 
The dose is 1050 mg (3 vials) for patients who weigh less than 80 kg 
and 1400 mg (4 vials) for patients who weigh 80 kg or more. Per the 
applicant, the WAC of RYBREVANTTM is $2,986.43 for a 350mL 
vial. According to the applicant, 70% of patients with exon 20 
mutations weigh less than or equal to 80 Kg, while 30% exceed 80 kg. 
Therefore, the average cost per patient for RYBREVANTTM is 
$9,855.22 ($2,986.43 per vial * 3 vials * 0.70) + ($2,986.43 per vial * 
4 vials * 0.30). Under Sec.  412.88(a)(2), we limit new technology add-
on payments to the lesser of 65 percent of the costs of the new medical 
service or technology, or 65 percent of the amount by which the costs 
of the case exceed the MS-DRG payment. As a result, the maximum new 
technology add-on payment for a case involving the use of 
RYBREVANTTM is $6,405.89 for FY 2022.
c. BREYANZI[supreg] (lisocabtagene maraleucel)
    Juno Therapeutics, a Bristol-Myers Squibb Company, submitted an 
application for new technology add-on payment for FY 2022 for 
BREYANZI[supreg]. BREYANZI[supreg] is a CD19-directed, autologous 
chimeric antigen receptor (CAR) T-cell immunotherapy that is comprised 
of individually formulated CD8 (killer) and CD4 (helper) CAR T-cells 
indicated for the treatment of adult patients with relapsed or 
refractory (r/r) large B-cell lymphoma after at least two prior 
therapies. We note that Juno Therapeutics previously submitted an 
application for new technology add-on payments for BREYANZI[supreg] for 
FY 2021, as summarized in the FY 2021 IPPS/LTCH PPS proposed rule, 
under the name lisocabtagene maraleucel (85 FR 32647-32652).
    According to the National Comprehensive Cancer Network, Diffuse 
Large B-cell lymphoma (DLBCL) is the most common type of Non-Hodgkin's 
Lymphoma (NHL) in the U.S. and worldwide, accounting for nearly 30% of 
newly diagnosed cases of B-cell NHL in U.S.\87\ DLBCL is characterized 
by spreading of B-cells through the body that have either arrived de 
novo or by the transformation from indolent lymphoma.
---------------------------------------------------------------------------

    \87\ Ferlay J, Colombet M, Soerjomataram, et al., Estimating the 
global cancer incidence and mortality in 2018: GLOBOCAN sources and 
methods, Int J Cancer. 144: 1941-1953 (Ferlay, 2019); NCCN Clinical 
Practice Guidelines in Oncology (NCCN Guidelines[supreg]) for B-Cell 
Lymphomas V. 5.2019. (copyright) National Comprehensive Cancer 
Network, Inc. 2019 (NCCN, 2019).
---------------------------------------------------------------------------

    According to the applicant, the standard-of-care, first-line 
immune-chemotherapy for DLBCL includes regimens such as 
cyclophosphamide, doxorubicin, vincristine, and prednisone plus 
rituximab (R-CHOP).\88\ These regimens result in long-lasting remission 
in more than 50% of patients.\89\ However, approximately 10% to 15% of 
patients will have primary refractory disease (that is, nonresponse or 
relapse within 3 months of first-line therapy), and an additional 20% 
to 25% will relapse following an initial response to therapy.\90\ 
Patients with relapses of aggressive B-cell lymphomas are believed to 
have a poor

[[Page 44997]]

prognosis because of potential treatment resistance and rapid tumor 
growth, with only about 30% to 40% responding to salvage chemotherapy 
(for example, R-ICE, DHAP, or Gem-ox) followed by high-dose therapy and 
autologous stem cell transplantation for patients demonstrating 
chemotherapy-sensitive disease.91 92 Among patients eligible 
to undergo autologous stem cell transplantation (ASCT), only 50% will 
achieve a remission adequate to proceed to ASCT, and approximately 50% 
will relapse after transplantation.\93\ The applicant also noted that 
transplant eligibility is also restricted based on age and tolerance to 
high dose chemotherapy and thus excludes a moderate subset of patients 
with r/r DLBCL.
---------------------------------------------------------------------------

    \88\ Coiffier, BBertrand et al., Long-term outcome of patients 
in the LNH-98.5 trial, the first randomized study comparing 
rituximab-CHOP to standard CHOP chemotherapy in DLBCL patients: A 
study by Group d'Etudes des Lymphomes de l'Adulte, blood 2010 116: 
2040-2045. (Coiffier, 2010).
    \89\ Ibid.
    \90\ Ibid.
    \91\ Crump M, Neelapu SS, Farooq U, et al., Outcomes in 
refractory diffuse large B-cell lymphoma: Results from the 
international SCHOLAR-1 study, Blood. 2017; 130(16): 1800-1808 
(Crump, 2017).
    \92\ Cunningham D, Hawkes EA, Jack A, et al. Rituximab plus 
cyclophosphamide, doxorubicin, vincristine, and prednisolone in 
patients with newly diagnosed diffuse large B-cell non-Hodgkin 
lymphoma: A phase 3 comparison of dose intensification with 14-day 
versus 21-day cycles Lancet. 2013; 381: 1817-1826 (Cunningham, 
2013).
    \93\ Ibid.
---------------------------------------------------------------------------

    Additionally, the applicant explained that the available therapies 
for 3L+ large B-cell lymphoma include the following:
     CD19-directed genetically modified autologous CAR T-cell 
immunotherapy axicabtagene ciloleucel (YESCARTA[supreg]), approved in 
October 2017 for the treatment of adult patients with r/r large B-cell 
lymphoma after two or more lines of systemic therapy, including DLBCL 
not otherwise specified, primary mediastinal large B-cell lymphoma, 
high grade B-cell lymphoma, and DLBCL arising from follicular lymphoma 
(FL).\94\
---------------------------------------------------------------------------

    \94\ YESCARTA[supreg]'s approval was based on a single arm study 
(ZUMA-1) demonstrating an IRC-assessed ORR of 72%, CR of 51%, and an 
estimated median DOR of 9.2 months in 101 subjects included in the 
modified intent-to-treat (mITT population).
---------------------------------------------------------------------------

     CAR T-cell therapy tisagenlecluecel (KYMRIAH[supreg]), 
approved in May 2018, for the treatment of adult patients with r/r 
large B-cell lymphoma after two or more lines of systemic therapy, 
including DLBCL not otherwise specified, high grade B-cell lymphoma, 
and DLBCL arising from FL.\95\
---------------------------------------------------------------------------

    \95\ KYMRIAH[supreg]'s approval was based on a single-arm study 
(JULIET) demonstrating an ORR of 50% and a CR rate of 32% in 68 
efficacy-evaluable subjects. A median DOR was not reached with a 
median follow-up of 9.4 months.
---------------------------------------------------------------------------

     Programmed death receptor-1 (PD-1)-blocking antibody 
(KEYTRUDA[supreg]), approved in 2018, for the treatment of adult and 
pediatric patients with refractory primary mediastinal B-cell lymphoma 
(PMBCL), or who have relapsed after two or more prior lines of 
therapy.\96\
---------------------------------------------------------------------------

    \96\ KEYTRUDA is not recommended for treatment of patients with 
PMBCL who require urgent cytoreductive therapy. Keytruda USPI 
(2019).
---------------------------------------------------------------------------

     CD79b-directed antibody-drug conjugate polatuzumab vedotin 
(POLIVY[supreg]), in combination with bendamustine and rituximab, 
approved in 2019, for the treatment of adult patients with r/r DLBCL, 
not otherwise specified, after at least two prior therapies.
    According to the applicant, despite the availability of these 
therapies, r/r large B-cell lymphoma remains a major cause of morbidity 
and mortality due to the aggressive disease course. The applicant noted 
that the safety profiles of these therapies exclude many r/r large B-
cell lymphoma patients from being able to undergo treatment with these 
therapies.\97\
---------------------------------------------------------------------------

    \97\ Smith SD, Reddy P, Sokolova A, et al., Eligibility for CAR 
T-cell therapy: An analysis of selection criteria and survival 
outcomes in chemorefractory DLBCL, Am. J. Hematol. 2019; E119: 1-4 
(Smith, 2019).
---------------------------------------------------------------------------

    With respect to the newness criterion, the applicant submitted a 
BLA for BREYANZI[supreg] in October 2019, and was approved by FDA on 
February 5, 2021. BREYANZI[supreg] was granted Breakthrough Therapy 
Designation (BTD) on December 15, 2016 and Regenerative Medicine 
Advanced Therapy (RMAT) designation on October 20, 2017, for the 
treatment of patients with r/r aggressive large B-cell NHL, including 
DLBCL, not otherwise specified (DLBCL NOS; de novo or transformed from 
indolent lymphoma), primary mediastinal B-cell lymphoma (PMBCL), or 
follicular lymphoma Grade 3B (FL3B)). BREYANZI[supreg] is a CD19-
directed genetically modified autologous T cell immunotherapy indicated 
for the treatment of adult patients with relapsed or refractory large 
B-cell lymphoma after two or more lines of systemic therapy, including 
diffuse large B-cell lymphoma (DLBCL) not otherwise specified 
(including DLBCL arising from indolent lymphoma), high-grade B-cell 
lymphoma, primary mediastinal large B-cell lymphoma, and follicular 
lymphoma grade 3B. BREYANZI[supreg] is not indicated for the treatment 
of patients with primary central nervous system lymphoma. We note that 
effective October 1, 2021 the following ICD-10-PCS codes may be used to 
uniquely describe procedures involving the infusion of 
BREYANZI[supreg]: XW033N7 (Introduction of lisocabtagene maraleucel 
immunotherapy into peripheral vein, percutaneous approach, new 
technology group 7) and XW043N7 (Introduction of lisocabtagene 
maraleucel immunotherapy into central vein, percutaneous approach, new 
technology group 7). The applicant also submitted a request for a new 
HCPCS code, which will uniquely describe procedures involving the use 
of BREYANZI[supreg]. The applicant noted in their application that 
BREYANZI[supreg] would likely map to the same MS-DRG as other CAR T-
cell therapies, MS-DRG 018 (Chimeric Antigen Receptor (CAR) T-cell 
Immunotherapy).
    As previously discussed, if a technology meets all three of the 
substantial similarity criteria, it would be considered substantially 
similar to an existing technology and would not be considered ``new'' 
for purposes of new technology add-on payments.
    With regard to the first criterion, whether a product uses the same 
or a similar mechanism of action to achieve a therapeutic outcome, the 
applicant described two ways in which it believes the mechanism of 
action for BREYANZI[supreg] differs from previously approved therapies 
for DLBCL. First, the applicant described the therapy as being 
comprised of individually formulated cryopreserved patient-specific 
helper (CD4) and killer (CD8) CAR T-cells in suspension that are 
administered as a defined composition of CAR-positive viable T-cells 
(from individually formulated CD8 and CD4 components). The applicant 
stated that the therapy involves a different mechanism of action from 
other CAR-T cell therapies because the CD4 and CD8 T-cells are purified 
and cultured separately to maintain compositional control of each cell 
type. Furthermore, during culture, each cell type is separately 
modified to have the CAR on the cell surface, expanded and quantified, 
and frozen in two separate cell suspensions. The applicant then 
described how BREYANZI[supreg] is infused with the same target dose of 
CD4 and CD8 CAR T-cells for every patient. The applicant asserted that 
because BREYANZI[supreg] controls the same dosage for both CD4 and CD8, 
it differs from other CAR T-cell therapies for DLBCL and could 
potentially provide for higher safety and efficacy; the applicant 
stated that CAR T-cell therapies that do not control for CD8 CAR T-cell 
dosage have demonstrated higher rates of severe and life-threatening 
toxicities, such as cytokine release syndrome (CRS) and neurotoxicity 
(NT).
    The second feature the applicant described as distinguishing 
BREYANZI[supreg]'s mechanism of action from existing CD19-directed CAR 
T-cell therapies was the presence of an EGFRt cell surface tag. The 
applicant explained

[[Page 44998]]

that the EGFRt cell surface tag could hypothetically be targeted for 
CAR T-cell clearance by separately administering cetuximab, a 
monoclonal antibody. According to the applicant, if the patient was 
separately administered cetuximab, the presence of the EGFRt cell 
surface tag within BREYANZI[supreg] would allow cetuximab to bind to 
the CAR T-cells and clear the cells from the patient. The applicant 
highlighted studies that showed that persistent functional CD19-
directed CAR T-cells in patients caused sustained depletion of a 
patient's normal B-cells that expressed CD19, resulting in 
hypogammaglobulinemia and an increased risk of life-threatening or 
chronic infections.\98\ The applicant further explained that such 
prolonged low levels of normal B-cells could place a patient at risk of 
life-threatening or chronic infections. According to the applicant, the 
ability to deplete CAR T-cells, via the administration of cetuximab, 
when a patient achieves a long-term remission could hypothetically 
allow recovery of normal B-cells and potentially reduce the risk of 
life-threatening or chronic infections. The applicant noted that 
experiments in a laboratory setting showed that targeting EGFRt with 
the monoclonal antibody cetuximab eliminated CAR T-cells expressing the 
EGFRt marker, which resulted in long-term reversal of B-cell aplasia in 
mice.\99\ However, the applicant noted that this mechanism of CAR T-
cell clearance, via administration of cetuximab and EGFRt cell surface 
tags/markers, has not been tested in humans, including patients treated 
with BREYANZI[supreg].
---------------------------------------------------------------------------

    \98\ Kalos M, Levine BL, Porter DL, et al., T Cells with 
Chimeric Antigen Receptors Have Potent Antitumor Effects and Can 
Establish Memory in Patients with Advanced Leukemia, Sci Transl Med. 
2011; 3(95): 1-21 (Kalos, 2011).
    \99\ Paszkiewicz PJ, Frable SP, Srivastava S, et al., Targeted 
antibody-mediated depletion of murine CD19 CAR T cells permanently 
reverses B cell aplasia, J Clin Invest. 2016; 126(11): 4262-4272 
(Paszkiewicz, 2016).
---------------------------------------------------------------------------

    With respect to the second criterion, whether a product is assigned 
to the same or a different MS-DRG, the applicant acknowledged that the 
ICD-10-PCS procedure codes used to uniquely identify procedures 
involving the administration of BREYANZI[supreg] XW033N7 (Introduction 
of lisocabtagene maraleucel immunotherapy into peripheral vein, 
percutaneous approach, new technology group 7) and XW043N7 
(Introduction of lisocabtagene maraleucel immunotherapy into central 
vein, percutaneous approach, new technology group 7) are assigned to 
MS-DRG 018 (Chimeric Antigen Receptor (CAR) T-cell Immunotherapy). The 
applicant has not made a request for the technology to map to a new or 
different MS-DRG for FY 2022.
    With respect to the third criterion, whether the new use of the 
technology involves the treatment of the same or similar type of 
disease and the same or similar patient population, according to the 
applicant, BREYANZI[supreg] fills an unmet need in the treatment of 
large B-cell lymphoma because BREYANZI[supreg] would be indicated as a 
third-line treatment option for patients with r/r DLBCL, who cannot be 
treated with existing CAR T-cell therapies. The applicant asserted that 
BREYANZI[supreg] would be able to treat these patients that present 
with uncommon subtypes of DLBCL including, PMBCL, FL3B, and DLBCL 
transformed from indolent lymphoma from other follicular lymphoma, 
elderly patients (>=65 years old), patients with secondary CNS 
involvement by lymphoma, and those with moderate renal or cardiac 
comorbidities. The applicant asserted that these patient populations 
were excluded from registrational trials for YESCARTA[supreg] and 
KYMRIAH[supreg], and therefore represent an unmet patient need.
    Regarding newness, we stated in the proposed rule that we were 
concerned whether a differing production and/or dosage represented a 
different mechanism of action as compared to previously FDA-approved 
CAR T-cell therapies. We were also concerned about whether the 
existence of an EGFRt cell surface tag equates to a new mechanism of 
action given that in order to activate this cell surface tag, an 
additional medication, cetuximab, which targets the CAR T-cells for 
clearance, would be needed. We also expressed concern that, based on 
our understanding, the presence of the EGFRt cell surface tag is a 
potential way to treat an adverse event of the BREYANZI[supreg] therapy 
and is not critical to the way the drug treats the underlying disease. 
We noted that the applicant referenced that while this EGFRt cell 
surface tag is included within the BREYANZI[supreg] compound, it 
remains dormant without activation by cetuximab. Finally, the applicant 
noted that BREYANZI[supreg] has been shown safe and effective for 
patient populations excluded from registrational trials for 
YESCARTA[supreg] and KYMRIAH[supreg], including patients with uncommon 
subtypes of large B-cell lymphoma, including PMBCL, FL3B, and DLBCL 
transformed from indolent lymphoma other than FL, elderly patients 
(>=65 years old), patients with secondary CNS involvement by lymphoma 
and those with moderate renal or cardiac comorbidities.\100\ We noted 
that the FDA label for YESCARTA[supreg] and KYMRIAH[supreg] does not 
appear to specifically exclude these patient populations or NHL 
subtypes. As such, it was unclear whether BREYANZI[supreg] would in 
fact treat a patient population different from other CAR T-cell 
therapies that treat patients with DLBCL.
---------------------------------------------------------------------------

    \100\ Lisocabtagene maraleucel Biologics License Application 
(BLA).
---------------------------------------------------------------------------

    We invited public comments on whether BREYANZI[supreg] is 
substantially similar to other technologies and whether 
BREYANZI[supreg] meets the newness criterion.
    Comment: A commenter, the manufacturer of a competitor CAR T-cell 
product to BREYANZI[supreg], stated that despite small differences in 
production and dosage, they agree with CMS that BREYANZI[supreg]'s 
mechanism of action does not represent a different mechanism of action 
as compared to KYMRIAH[supreg] and YESCARTA[supreg]. The commenter next 
provided the FDA-approved prescribing information for BREYANZI[supreg], 
KYMRIAH[supreg], and YESCARTA[supreg] which they asserted describe the 
same or similar mechanism of action for these technologies. The 
commenter added BREYANZI[supreg], KYMRIAH[supreg], and YESCARTA[supreg] 
are all CD19-directed genetically modified autologous T-cell 
immunotherapies that bind to CD19-expressing cancer cells and normal B 
cells. The commenter next stated that according to the applicant, 
BREYANZI[supreg]'s mechanism of action can be distinguished from 
existing CD19-directed CAR T-cell therapies given the presence of an 
EGFRt cell surface tag. According to the commenter, the applicant noted 
that EGFRt cell surface tag could ``hypothetically'' be targeted for 
CAR T-cell clearance by separately administering cetuximab, a 
monoclonal antibody. The commenter asserted that nevertheless, there is 
only preclinical murine data to support the claim that the presence of 
an EGFRt cell surface tag for BREYANZI[supreg] improves safety or 
efficacy. Therefore, the commenter asserted that the claim about the 
mechanism of action made by the applicant is merely hypothetical and 
should not be the basis to evaluate a claim for newness under the new 
technology add-on payment criteria. Lastly, the commenter stated that 
according to the applicant, BREYANZI[supreg] controls the same dosage 
for both CD4 and CD8, which ``could potentially provide for higher 
safety and efficacy'' than previously FDA-approved CAR T-

[[Page 44999]]

cell therapies. In response, the commenter described an analysis of how 
different product attributes of KYMRIAH[supreg], including CD4:CD8 
ratio, affect efficacy and safety, in which the investigators found 
that the CD4:CD8 ratio had no significant impact on response rate, CRS, 
or neurotoxicity.\101\ The commenter added that in the phase 2 trial 
for YESCARTA[supreg], investigators also found that response rates did 
not appear to be influenced by product characteristics, including the 
CD4:CD8 ratio.\102\
---------------------------------------------------------------------------

    \101\ Backanova V, Tam CS, Borchmann P, et al. Impact of 
Tisagenlecleucel Chimeric Antigen Receptor (CAR)-T Cell Therapy 
Product Attributes on Clinical Outcomes in Adults with Relapsed or 
Refractory Diffuse Large B-Cell Lymphoma (r/r DLBCL). Oral 
presentation presented at: 61st ASH Annual Meeting; December 7-10, 
2019; Orlando, FL; Abstract 242.
    \102\ Neelapu SS, Locke FL, Bartlett NL, et al. Axicabtagene 
Ciloleucel CAR T-Cell Therapy in Refractory Large B-Cell Lymphoma. N 
Engl J Med. 2017;377(26):2531-2544. doi:10.1056/NEJMoa1707447.
---------------------------------------------------------------------------

    Next, the commenter asserted BREYANZI[supreg] treats the same or 
similar type of disease and patient populations as KYMRIAH[supreg] and 
YESCARTA[supreg]. The commenter stated its disagreement that 
BREYANZI[supreg] presents a new treatment option for patients with r/r 
DLBCL that cannot be treated with existing FDA-approved CAR T-cell 
therapies. The commenter stated there is large overlap in the eligible 
patient populations for all three therapies as the patient populations 
or NHL subtypes are not excluded from the FDA label of the existing 
FDA-approved CAR T-cell therapies.
    Response: We appreciate the information provided by the commenter 
and have taken this comment into consideration in our determination of 
the newness criterion.
    Comment: In response to CMS' concerns in the proposed rule, a 
commenter stated their agreement and support that BREYANZI[supreg] 
needs additional data to show that it meets the newness criterion to 
support an approval for new technology add-on payment. The commenter 
stated specifically that they do not believe BREYANZI[supreg] is 
significantly different from the current two FDA approved CAR T-cell 
products YESCARTA[supreg] and KYMRIAH[supreg] for the treatment of 
Diffuse Large B-cell lymphoma (DLBCL). The commenter added that there 
have not been any head-to-head clinical trials performed to support the 
request from the manufacturer of BREYANZI[supreg].
    A few commenters encouraged CMS to consider assigning new 
technology add-on payments for new CAR T-cell therapies including 
lisocabtagene maraleucel to ensure patient access.
    Response: We appreciate the information submitted by the commenters 
and have taken this into consideration in our final determination of 
new technology add-on payment status.
    Comment: In response to CMS' concerns in the proposed rule, the 
applicant submitted a comment. The applicant stated that 
BREYANZI[supreg] does not use the same or similar mechanism of action 
to achieve a therapeutic outcome. The applicant asserted that in terms 
of the CAR construct and design, the therapy is impacted by differences 
in length of the transmembrane/hinge region, domain type, and 
costimulatory/activation domains. According to the applicant, new data 
demonstrates that the length of the transmembrane/hinge region, along 
with the domain type (CD28, CD8, etc.) in combination with the 
costimulatory/activation domains (CD28, 4-1BB, etc.), can affect 
cytokine production, proliferation, and T-cell memory generation, which 
are critical to the activity of CAR T-cell therapy.\103\ According to 
the applicant, BREYANZI[supreg] utilizes a different mechanism of 
action from other CAR T-cell therapies, including KYMRIAH[supreg] and 
YESCARTA[supreg], which are also indicated to treat certain patient 
populations with DLBCL. The applicant added that BREYANZI[supreg] has a 
unique mechanism of action because it is comprised of two individually 
formulated cryopreserved patient-specific helper (CD4) and killer (CD8) 
CAR T-cells in suspensions administered as a defined composition of 
CAR-positive viable T-cells in a 1:1 ratio (CD4/CD8) as compared to 
KYMRIAH[supreg] and YESCARTA[supreg] which are comprised of varying 
CD4/CD8 CAR T-cell ratios and are manufactured as mixed populations. 
The applicant further asserted that BREYANZI[supreg] also has the 
unique attribute of incorporating an EGFRt cell surface tag that could 
potentially be used in combination with cetuximab to eliminate the 
genetically altered T-cells through antibody dependent cell-mediated 
cytotoxicity should the patient experience a catastrophic adverse 
event, as compared to KYMRIAH[supreg] and YESCARTA, neither of which 
has this same EGFRt cell surface tag.
---------------------------------------------------------------------------

    \103\ Brudno JN, Lam N, Vanasse, D, et al. Safety and 
feasibility of anti-CD19 CAR T cells with fully human binding 
domains in patients with B-cell lymphoma, Nature Medicine. 2020; 
26:270-280; Ying Z, Huang XF, Xiang X, et al. A safe and potent 
anti-CD19 CAR T cell therapy, Nature Medicine. 2019; 25:947-953.
---------------------------------------------------------------------------

    The applicant stated that BREYANZI[supreg] does not involve the 
treatment of the same or similar type of disease or same or similar 
patient population as other technologies. The applicant asserted 
BREYANZI[supreg] has been shown to be safe and effective for patient 
populations excluded from registrational trials for YESCARTA[supreg] 
and KYMRIAH[supreg], including patients with uncommon subtypes of large 
B-cell lymphoma, including refractory primary mediastinal B-cell 
lymphoma (PMBCL), FL3B, and DLBCL transformed from indolent lymphoma 
other than follicular lymphoma (FL), elderly patients (>=65 years old), 
patients with secondary central nervous system (CNS) involvement by 
lymphoma and those with moderate renal or cardiac comorbidities. The 
applicant added the FDA labels for YESCARTA[supreg] and KYMRIAH[supreg] 
may not exclude all these B cell lymphoma subtypes; however, clinical 
studies for YESCARTA[supreg] and KYMRIAH[supreg] failed to include 
patients transformed from indolent lymphomas (for example, chronic 
lymphocytic leukemia (CLL) and marginal zone lymphoma (MZL)) and 
patients with FL3b. Additionally, according to the applicant, clinical 
studies for YESCARTA[supreg] and KYMRIAH[supreg] did not allow 
enrollment of patients with prior allogeneic hematopoietic stem cell 
transplant (HSCT) or with secondary CNS disease, reduced renal 
function, and other specific comorbidities. The applicant asserted its 
belief that it would be unlikely for a clinician to prescribe 
KYMRIAH[supreg] or YESCARTA[supreg] for patients that were expressly 
excluded from the clinical trials for those therapies and even more 
unlikely for a commercial payor to reimburse for the use of 
KYMRIAH[supreg] or YESCARTA[supreg] in a patient population that was 
excluded from the clinical trials. Lastly, the applicant asserted 
patients with FL3b are excluded from Medicare coverage for 
KYMRIAH[supreg] and YESCARTA[supreg] under National Coverage 
Determination (NCD) 110.24 (Chimeric Antigen Receptor (CAR) T cell 
Therapy), but are covered for BREYANZI[supreg].\104\
---------------------------------------------------------------------------

    \104\ CMS Manual System, Pub 100-04 Medicare Claims Processing 
Manual, Transmittal 10796, Change Request 12177 (May 20, 2021), 
available at https://www.cms.gov/files/document/r10796cp.pdf.
---------------------------------------------------------------------------

    Response: We appreciate the information submitted by the commenters 
in response to whether BREYANZI[supreg] meets the newness criterion. In 
regard to the first criterion, whether a technology uses the same or 
similar mechanism of action to achieve a therapeutic outcome, we do not 
believe there is a clear differentiation between the mechanism of 
action of BREYANZI[supreg] and currently available

[[Page 45000]]

CAR T-cell therapies, namely KYMRIAH[supreg] and YESCARTA[supreg]. 
While the applicant highlights differences, such as the length of the 
transmembrane/hinge region, domain type, costimulatory/activation 
domains and CD4/CD8 ratios, we do not believe these meaningfully 
differentiate the mechanism of action of BREYANZI[supreg] from other 
CD-19 directed CAR T-cell therapies, which are all genetically modified 
autologous T-cell immunotherapies that bind to CD-19 expressing cancer 
cells. We refer the reader to the FY 2019 IPPS/LTCH PPS final rule (83 
FR 41287 through 41291) for a further discussion of this issue, where 
we determined that KYMRIAH[supreg] and YESCARTA[supreg] were 
substantially similar to one another based on similar concerns. We 
agree with the first commenter that the differences in production and 
dosage between BREYANZI[supreg], YESCARTA[supreg], and KYMRIAH[supreg] 
do not represent a different mechanism of action. We also agree with 
the first commenter that the EGFRt surface tag characteristic of 
BREYANZI[supreg] has not been shown to be a meaningful difference due 
to the experimental nature from which these results are derived.
    In regard to the second criterion, whether a product is assigned to 
the same or a different MS-DRG, as noted in the proposed rule, the 
procedure codes used to describe the administration of BREYANZI[supreg] 
are assigned to MS-DRG 018 with other CAR T-cell therapies.
    In regard to the third criterion, whether a technology treats the 
same or similar type of disease and patient populations, CMS notes 
there is substantial overlap between the patient populations treated by 
BREYANZI[supreg], YESCARTA[supreg], and KYMRIAH[supreg]. Based on B-
cell lymphoma classifications and FDA indications for adult patients 
with relapsed or refractory (r/r) large B-cell lymphoma after two or 
more lines of systemic therapy, there appear to be only limited 
clinical differences between BREYANZI[supreg] and the two prior 
therapies. Specifically, based on coverage determinations by CMS, we 
believe that while YESCARTA[supreg] and KYMRIAH[supreg] treat DBLCL 
transformed from follicular lymphoma, BREYANZI[supreg] can also treat 
follicular lymphoma grade 3b that does not coexist with DLBCL.
    Based on the information received to date, we believe that 
BREYANZI[supreg] is generally intended to treat the same or similar 
disease in the same or similar patient population as existing CAR T-
cell technologies using the same mechanism of action as previously 
approved CAR T-cell therapies, that of engineered autologous cellular 
immunotherapy comprised of CAR T-cells that recognizes CD-19 expressing 
cancer cells, and mapping to the same MS-DRGs. However, because 
BREYANZI[supreg] can also be used to treat follicular lymphoma grade 3b 
that does not coexist with DLBCL, we believe that this represents a new 
indication for BREYANZI[supreg]. Therefore, based on the information 
stated previously, BREYANZI[supreg] is substantially similar to 
YESCARTA[supreg] and KYMRIAH[supreg] with regard to the other forms of 
large B-cell lymphoma listed on the indication and is therefore not new 
for these indications. However, BREYANZI[supreg] is considered new and 
not substantially similar to YESCARTA[supreg] and KYMRIAH[supreg] for 
the specific subpopulation of cases without DLBCL but with follicular 
lymphoma grade 3b.
    With regard to the cost criterion, the applicant searched the FY 
2019 MedPAR correction notice (December 1, 2020) data file to identify 
potential cases representing patients who may be eligible for treatment 
using BREYANZI[supreg]. The applicant identified claims that reported 
an ICD-10-CM diagnosis code of: C83.30 (DLBCL, unspecified site); 
C83.31 (DLBCL, lymph nodes of head, face and neck); C83.32 (DLBCL, 
intrathoracic lymph nodes); C83.33 (DLBCL, intra-abdominal lymph 
nodes); C83.34 (DLBCL, lymph nodes of axilla and upper limb); C83.35 
(DLBCL, lymph nodes of inquinal region and lower limb); C83.36 (DLBCL, 
intrapelvic lymph nodes); C83.37 (DLBCL, spleen); or C83.38 (DLBCL, 
lymph nodes of multiple sites) in one of the first five diagnosis code 
positions on the claim. The applicant excluded claims if they had one 
or more diagnoses from the list below because these conditions would 
preclude use of BREYANZI[supreg].
BILLING CODE 4120-01-P

[[Page 45001]]

[GRAPHIC] [TIFF OMITTED] TR13AU21.167


[[Page 45002]]


[GRAPHIC] [TIFF OMITTED] TR13AU21.168


[[Page 45003]]


[GRAPHIC] [TIFF OMITTED] TR13AU21.169

BILLING CODE 4120-01-C
    However, the applicant noted that the aforementioned C83.XX ICD-10-
CM codes do not differentiate r/r patients from the broader DLBCL 
population. A clinical literature search completed by the applicant 
found that the r/r population makes up one-fourth of the DLBCL 
population, but since r/r patients typically have higher inpatient 
costs the applicant selected 19.36 percent of the cases with the 
highest total charges for their cost analysis. Applying the previously 
mentioned parameters, the applicant found a total of 991 cases mapped 
to 12 MS-DRGs.
    The applicant stated that the use of BREYANZI[supreg]'s therapy 
would replace chemotherapy or other drug therapies, including other CAR 
T-cell therapies. Because of this, the applicant stated they removed 
all charges in the drug cost center since it was not possible to 
differentiate between different drugs on inpatient claims. The 
standardized charges per case were then calculated using the 2019 IPPS/
LTCH PPS final rule Impact file and the 2-year inflation factor of 13.2 
percent (1.3218) was applied. Finally, to determine the charges for 
BREYANZI[supreg], the applicant used the inverse of a simulated 
alternative cost-to-charge ratio (CCR) specifically for CAR T-cell 
therapies to account for CAR T-cell therapies' higher costs compared to 
other drugs. To determine this alternative CCR for CAR T-cell 
therapies, the applicant referred to the FY 2021 IPPS final rule AOR/
BOR file and calculated an alternative markup percentage by dividing 
the AOR drug charges within MS-DRG 018 by the number of cases to 
determine a per case drug charge. The applicant then divided the drug 
charges per case by $373,000, the acquisition cost of YESCARTA[supreg] 
and KYMRIAH[supreg], the CAR T-cell products used in those claims, to 
arrive at a CCR of 0.295. The applicant noted that the cost of 
BREYANZI[supreg] had not yet been determined at the time of 
application. However, for the purposes of its cost analysis, the 
applicant assumed the per-patient cost to the hospital will be 
$373,000. Based on the FY 2021 IPPS/LTCH PPS final rule correction 
notice data file thresholds for FY 2022, the applicant calculated a 
final inflated average case-weighted standardized charge per case of 
$1,377,616 which exceeded the MS-DRG 018 average case-weighted 
threshold of $1,251,127 by $126,489. Therefore, the applicant stated 
that BREYANZI[supreg] met the cost criterion.
    In the proposed rule, we stated that as noted in previous 
discussions, the submitted costs for CAR T-cell therapies vary widely 
due to differences in provider billing and charging practices for this 
therapy. Therefore, with regard to the use of this data for purposes of 
calculating a CAR T-cell CCR, we were uncertain how representative this 
data is for use in the applicant's cost analyses given this potential 
for variability.
    We also stated that we continued to be interested in public 
comments regarding the eligibility of CAR T-cell technologies for new 
technology add-on payments when assigned to MS-DRG 018. As we have 
noted in prior rulemaking with regard to the CAR T-cell therapies (83 
FR 41172 and 85 FR 58603 through 58608), if a new MS-DRG were to be 
created, then consistent with section 1886(d)(5)(K)(ix) of the Act, 
there may no longer be a need for a new technology add-on payment under 
section 1886(d)(5)(K)(ii)(III) of the Act. We welcomed comment on this 
issue.
    We invited public comment on whether BREYANZI[supreg] meets the 
cost criterion.
    Comment: MedPAC's comments addressed the cost criterion in general 
as it relates to CAR T-cell therapies. In particular, MedPAC stated 
that CMS should provide a more detailed discussion of the NTAP cost 
criterion and whether under the current methodology a new CAR-T product 
priced similarly to existing CAR-T products can meet the cost 
criterion. MedPAC noted that at least one of the new CAR-T products may 
meet the NTAP cost criterion with a manufacturer price of $373,000, but 
that, with a price of $373,000, the new product's price would be 
similar to the prices of existing CAR-T products that are paid under 
the existing Chimeric Antigen Receptor (CAR) T-cell Immunotherapy MS-
DRG (MS-DRG 018). MedPAC further noted that the possibility that a new 
CAR-T product with a price similar to existing CAR-T products might 
meet the cost criterion and qualify for additional payments (over and 
above what is paid for cases using other, similarly priced CAR-T 
products) seems inconsistent with the intent of current NTAP policy and 
the new CAR-T MS-DRG.
    In addition, MedPAC stated that the discussion of each NTAP 
applicant's cost calculations in the proposed rule is not granular 
enough to discern the different factors that may contribute to this 
potential outcome, and urged CMS to provide a more detailed discussion 
of this issue.
    MedPAC also stated that the current cost criterion provides an 
incentive for manufacturers and hospitals to increase their prices and 
charges and noted that the Commission may examine ways to improve how 
Medicare pays for new products to better balance manufacturer 
incentives to innovate with value and affordability for beneficiaries 
and taxpayers.
    Response: We appreciate the comment from MEDPAC on this particular 
issue related to CAR T-cell and the cost criterion. As we stated in 
section II.F.1.a.(2) of the preamble of this final rule, the cost 
criterion is evaluated consistently with the formula specified in 
section 1886(d)(5)(K)(ii)(I) of the Act. Specifically, the charges of 
the cases involving a new medical service or technology are compared 
to, and must exceed, a threshold amount which is the lesser of 75 
percent of the standardized amount or 75 percent of one standard 
deviation beyond the geometric mean standardized charge for all cases 
in the MS-DRG to which the new medical service or technology is 
assigned.
    The cost criterion is based on the average charge per case 
including the cost of the technology which must exceed the threshold 
rather than just comparing the given price of a technology to the price 
of other similar technologies. If a technology meets all of the new 
technology add-on payment criteria then it will be eligible for the

[[Page 45004]]

add-on payment. We refer the commenter to the spreadsheet we provide 
with the application (on the CMS website at https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/AcuteInpatientPPS/newtech) 
which details step-by-step calculations applicants provide with regard 
to the cost criterion. We believe the step-by-step calculation, which 
we summarized previously, meets the statutory criteria and is granular 
with sufficient detail to determine if the average charge per case 
exceeds the threshold.
    With regard to MedPAC's concern that the cost criterion may provide 
an incentive for manufacturers and hospitals to increase their prices 
and charges, we welcome further comments from the public and MedPAC 
with regard to how to examine ways to improve how Medicare pays for new 
products to better balance manufacturer incentives to innovate with 
value and affordability for beneficiaries and taxpayers.
    Comment: Commenters strongly opposed that CAR T-cell therapies 
would be ineligible for new technology add on payments consistent with 
section 1886(d)(5)(K)(ix) of the Act. The commenters voiced the need 
for new technology add on payments CAR T-cell therapies as they believe 
they are underpaid and meet all the criteria (including the cost 
criterion) to be eligible for new technology add on payments.
    Response: We thank the commenters for their comments. In this final 
rule we have evaluated all CAR T-cell applications based on the 
traditional pathway criterion newness, cost, and substantial clinical 
improvement criterion. We will take the comments into consideration for 
future rulemaking.
    Comment: In response to CMS' concerns, the applicant stated in its 
comment that CAR T-cell therapies that meet the cost and other criteria 
for new technology add-on payment status should continue to be eligible 
for new technology add-on payment status notwithstanding the creation 
of MS-DRG 018. The applicant stated that there is still a need for new 
technology add-on payment status for new CAR T-cell therapies, like 
BREYANZI[supreg], to ensure patient access. Further, the applicant 
stated that while the payment amount for MS-DRG 018 is certainly more 
aligned with CAR T-cell therapy costs generally, BREYANZI[supreg] 
exceeds the cost threshold for MS-DRG 018, meaning that the 
reimbursement rate for MS-DRG 018 is not adequate for BREYANZI[supreg]. 
The applicant asserted that per CMS, this is precisely the type of 
scenario that the new technology add-on payment is intended to address.
    In response to CMS' concerns regarding the cost criterion and the 
variability of provider billing and charging practices for CAR T-cell 
therapies, the applicant stated it considered the variability of CAR T-
cell charging practices when developing its cost analyses and presented 
options that were intended to address this variability by using more 
conservative assumptions than have typically been the case for other 
new technology add-on payment applications. The applicant stated that 
most new technology add-on payment applications use the national 
average CCR for the cost center for which the new technology belongs to 
inflate the acquisition cost for the new technology to charges. The 
applicant added that in the case of a drug or biological, this would 
mean that the inverse of the national average CCR for drugs would be 
used to convert the WAC of BREYANZI[supreg] to charges. The applicant 
stated that using the drug CCR in the prescribed manner would result in 
charges that would potentially overstate actual hospital charging 
practices for CAR T-cell therapies. Furthermore, the applicant noted 
that numerous studies on charge compression have shown that hospital 
charging practices tend to result in higher markup percentages for 
lower cost drugs and lower markup percentages for higher cost drugs. 
The applicant added that given that the WAC for BREYANZI[supreg] is 
well above the average of drugs overall, it was concerned that using 
the inverse of the national average drug CCR might overstate what 
hospitals would typically charge for BREYANZI[supreg] on inpatient 
claims. Therefore, the applicant calculated a CAR T-cell specific CCR 
based solely on the total drug charges for CAR T-cell claims.
    The applicant stated that to calculate the CAR T-cell CCR, it took 
the total drugs charges for cases in MS-DRG 018 from the FY 2021 IPPS 
Final Rule After Outliers Removed/Before Outliers Removed (AOR/BOR) 
file ($183,433,947.58). Next the applicant divided that amount by the 
number of cases (145) to determine an average drug charge per case 
($1,265,061.70). Next it divided that amount by $373,000, the 
acquisition cost of YESCARTA[supreg] and KYMRIAH[supreg]. This value 
represents the average mark-up percentage hospitals used to convert the 
cost of CAR T-cell therapies to charges on claims in FY 2019. The 
applicant converted this mark-up percentage to a CCR by dividing 1 by 
the percentage (1/3.39 = 0.295).
    Ultimately, the applicant stated it recognizes CMS' concern that 
hospitals vary in their CAR T-cell charging practices but states that 
its method for calculating a CAR T-cell specific CCR is meant to 
address this exact concern. The applicant asserted that by focusing 
solely on CAR T-cell claims, it is able to capture the range of 
charging practices in hospitals that used a CAR T-cell therapy in a 
non-clinical trial case in 2019. Furthermore, the applicant stated that 
in addition to addressing the concerns about variability in hospital 
charging practices, the CAR T-cell CCR is also a more conservative 
assumption to use in the cost threshold analysis because it inflates 
CAR T-cell costs to charges at a lower percentage (339%) than if the 
inverse of the national average drug CCR is used (535%).
    Response: In regard to whether CAR T-cell therapies would be 
ineligible for new technology add on payments consistent with section 
1886(d)(5)(K)(ix) of the Act, in this final rule we have evaluated all 
CAR T-cell applications based on the traditional pathway criteria of 
newness, cost, and substantial clinical improvement.
    We appreciate the information provided by the applicant in their 
comment in regard to their calculation of a CAR T-cell CCR. As we 
stated in section E.2.b. of this rule, we continue to believe that it 
is premature to make structural changes to the IPPS at this time to pay 
for CAR T-cell therapies (78 FR 58453). As we gain more experience 
paying for these therapies under the IPPS, we may consider these 
comments to inform future rulemaking. However, we appreciate the 
thoughtfulness used by the applicant to provide as clear as possible a 
description of CAR T-cell therapy cost calculations. We appreciate the 
usage of multiple cost analyses, such as varying the CCR used to 
inflate cost to charges, which potentially allowed for a more 
conservative markup. After consideration of the public comments we 
received and based on the information included in the applicant's new 
technology add-on payment application, we believe that BREYANZI[supreg] 
meets the cost criterion.
    With respect to the substantial clinical improvement criterion, the 
applicant asserted that BREYANZI[supreg] represents a substantial 
clinical improvement over existing technologies because: (1) The 
totality of the circumstances regarding BREYANZI[supreg]'s clinical 
efficacy, safety, and data make clear that BREYANZI[supreg] 
substantially improves, relative to services or technologies previously 
available, the treatment of Medicare beneficiaries with R/R NHL; (2) 
BREYANZI[supreg] offers a

[[Page 45005]]

treatment option for a patient population unresponsive to, or 
ineligible for, currently available treatments; (3) BREYANZI[supreg] 
has, overall, an improved safety profile compared to YESCARTA and 
KYMRIAH; (4) BREYANZI[supreg] has a comparable or superior 
effectiveness compared to existing therapies; and (5) 
BREYANZI[supreg]'s patient population in its registrational study more 
accurately reflects real-world NHL patients compared to the studies of 
currently available CAR T-cell therapies.
    The applicant asserts that the totality of the clinical efficacy 
and safety data from the TRANSCEND NHL 001 trial, which is a 
prospective, single arm, multicenter study of BREYANZI[supreg] in 
patients with r/r aggressive B-cell NHL, and the supportive safety data 
from the BREYANZI[supreg] clinical studies included in their Biologics 
License Application (BLA) submission demonstrate that BREYANZI[supreg] 
has equal or better efficacy and a better safety profile in a broad R/R 
patient population that better approximates the real world large B-cell 
lymphoma patient population--a population that the applicant asserted 
includes NHL subtypes not studied or approved for treatment with 
current approved or conditionally approved agents.
    The applicant shared the results of the Phase I TRANSCEND NHL 001 
trial, which was a prospective, single arm, multicenter study of 
BREYANZI[supreg] in patients with relapsed/refractory aggressive B-cell 
NHL. The applicant noted that TRANSCEND NHL 001 included subjects with 
the average age of 63 years with 111 subjects (41%) over 65 years of 
age and 27 (10%) subjects older than 75 years of age. These patients 
also failed previous therapies. Of the total number of subjects studied 
(efficacy: n=256; safety: n=269), 137 subjects (51%) had DLBCL, 60 
(22%) had DLBCL transformed from FL, 18 (7%) had DLBCL transformed 
other indolent lymphomas, 36 patients (13%) had high grade lymphoma, 15 
(6%) had PMBCL and 3 (1%) had FL3B.\105\ Additionally, the applicant 
explained that TRANSCEND NHL 001 was more inclusive, compared to the 
registrational trials for KYMRIAH[supreg] and YESCARTA[supreg], of 
Medicare aged patients with comorbidities and NHL disease subtypes seen 
in the real world presentation of the disease. To support this, the 
applicant referenced that within this study, between 40% to 50% of 
subjects studied had cardiac ejection fraction, 3% had secondary CNS 
lymphoma, 51 patients (19%) had a creatinine clearance between 30-60 
mL/min and 39 patients (14.6%) had grade >=3 cytopenias. Furthermore, 
the applicant noted that 51 patients (19%) had decreased renal function 
and 13 patients (4.9%) had decreased cardiac function. The applicant 
stated that the TRANSCEND NHL 001 study showcased that the patient 
population treated during the study better reflected the real world 
large B-cell lymphoma patient population, a population that the 
applicant asserted included NHL subtypes not studied or approved for 
treatment with currently approved or conditionally approved agents, 
while providing similar safety and efficacy. The applicant contended 
that these high-unmet need large B-cell lymphoma subsets included 
patients with DLBCL transformed from rare indolent lymphomas other than 
FL, patients with FL3B, patients 65 years of age and older, as well as 
patients with moderate comorbidities of renal and cardiac 
insufficiency.
---------------------------------------------------------------------------

    \105\ Ibid.
---------------------------------------------------------------------------

    The applicant further explained that BREYANZI[supreg] provided 
improved effectiveness as compared to existing therapies. Patients with 
aggressive large B-cell NHL who have failed at least 2 prior therapies 
or SCT are treated with combinations of agents or monotherapy based on 
institutional preferences, but there is no standard of care for salvage 
therapies beyond first treatment therapy.\106\ The applicant noted that 
commonly used salvage therapies (non-CAR T-cell therapies) for 
relapsed, large B-cell lymphoma demonstrated objective response rates 
(ORRs) in the range of 12% to 46% and complete response (CR) rates of 
6% to 38%. Among the patients who did achieve a response, the median 
duration of response (DOR) ranges from approximately 6 to 17 months and 
median overall survival was generally less than 12 
months.107 108 109 110 111 112 113 Comparatively, TRANSCEND 
NHL 001, which provided subjects with BREYANZI[supreg], met its primary 
endpoint of Independent Review Committee (IRC)-assessed ORR in adult 
patients with r/r large lymphoma after at least 2 prior therapies, as 
reported by the applicant. In the 256 efficacy evaluable patients, the 
ORR was 73% (95% confidence interval (CI]): 67.0% to 78.3%), and the CR 
rate was 53% (95% CI: 46.6% to 59.2%). With a median follow-up of 10.8 
months, the median DOR per IRC assessment was 13.3 months and the 
median DOR for CR was not reached. By comparison, the applicant 
summarized that YESCARTA[supreg], as demonstrated in the Phase I-II 
ZUMA-1 study (see the FY 2019 IPPS/LTCH PPS final rule 83 FR 41295 for 
a description of this study), had an ORR of 72.0% (95% confidence 
interval (CI: 62.0% to 81.0%). Also, according to the applicant, 
KYMRIAH[supreg], as demonstrated by the Phase II JULIET study (see the 
FY 2019 IPPS/LTCH PPS final rule 83 FR 41293 for a description of this 
study), had an ORR of 50.0% (95% confidence interval (CI: 38.0% to 
62.0%). The applicant contended that the results for BREYANZI[supreg] 
(ORR of 73% (95% confidence interval (CI]): 67.0% to 78.3%), and the CR 
rate of 53% (95% CI: 46.6% to 59.2%)) were observed across all 
subgroups tested, including elderly subjects, those with high burden 
disease or high baseline inflammatory biomarkers, those requiring anti-
lymphoma therapy for disease control, as well as rare patient 
populations with a high unmet medical need (for example, PMBCL, DLBCL 
transformed from indolent lymphoma other than FL, and FL3B). The 
applicant contended that this data supports that BREYANZI[supreg] 
demonstrates comparable or superior effectiveness compared to existing 
therapies for patients with r/r large B-cell NHL.114 115
---------------------------------------------------------------------------

    \106\ National Comprehensive CancerNetwork Treatment of Cancer: 
Guidelines, 2019. NCCN, 2019.
    \107\ Czuczman MS, Davies A, Linton KM, et al., A Phase 2/3 
Multicenter, Randomized Study Comparing the Efficacy and Safety of 
Lenalidomide Versus Investigator's Choice in Relapsed/Refractory 
DLBCL, Blood. 2014; 124: 628 (Czuczman, 2014).
    \108\ Jacobsen ED, Sharman JP, Oki Y, et al., Brentuximab 
vedotin demonstrates objective responses in a phase 2 study of 
relapsed/refractory DLBCL with variable CD30 expression, Blood. 
2015; 125(9): 1394-1402 (Jacobsen, 2015).
    \109\ Nagle SJ, Woo K, Schuster SJ, et al., Outcomes of patients 
with relapsed/refractory diffuse large B-cell lymphoma with 
progression of lymphoma after autologous stem cell transplantation 
in the rituximab era, Am. J. Hematol. 2013; 88: 890-894 (Nagle, 
2013).
    \110\ Pettengell R, Coiffier B, Narayanan G, et al., Pixantrone 
dimaleate versus other chemotherapeutic agents as a single-agent 
salvage treatment in patients with relapsed or refractory aggressive 
non-Hodgkin lymphoma: A phase 3, multicenter, open-label, randomised 
trial, Lancet Oncol. 2012; 13: 696-706 (Pettengell, 2012).
    \111\ Rigacci L, Puccini B, Cortelazzo S, et al., Bendamustine 
with or without rituximab for the treatment of heavily pretreated 
non-Hodgkin's lymphoma patients, Ann Hematol. 2012; 91: 1013-1022 
(Rigacci, 2012).
    \112\ Van Den Neste E, Schmitz N, Mounier N, et al., Outcome of 
patients with relapsed diffuse large B-cell lymphoma who fail 
second-line salvage regimens in the International CORAL study, Bone 
Marrow Transplantation. 2016; 51: 51-57 (Van Den Neste, 2016).
    \113\ Wang M, Fowler N, Wagner-Bartak N, et al., Oral 
lenalidomide with rituximab in relapsed or refractory diffuse large 
cell, follicular and transformed lymphoma: A phase II clinical 
trial, Leukemia. 2013; 27: 1902-1909 (Wang, 2013).
    \114\ YESCARTA[supreg] United States Prescribing Information 
USPI (2019).
    \115\ KYMRIAH[supreg] United States Prescribing Information USPI 
(2018).

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[[Page 45006]]

    Furthermore, the applicant stated that BREYANZI[supreg] had an 
improved safety profile in comparison to YESCARTA[supreg] and 
KYMRIAH[supreg]. The applicant stated that both of these FDA-approved 
CAR T-cell therapies had higher rates of toxicity as compared to 
BREYANZI[supreg]. In the TRANSCEND NHL 001 registrational study 
(n=268), 42% and 2% of subjects developed all-grade and Grade >3 CRS, 
respectively, and 30% and 10% developed all-grade and Grade >3 NT. The 
applicant compared these results to the results of the JULIET study has 
found in KYMRIAH's[supreg] prescribing information and summarized that 
KYMRIAH[supreg] had higher rates of all-grade and Grade >3 CRS (74% and 
23%, respectively) and all-grade and Grade >3 NT (58% and 18%, 
respectively). The applicant provided the same comparison of the 
toxicity results of BREYANZI[supreg] to the results showcased in the 
ZUMA-1 study featuring YESCARTA[supreg] as found in YESCARTA[supreg]'s 
prescribing information and summarized that YESCARTA[supreg] had higher 
rates of all-grade and Grade >3 CRS (94% and 13%, respectively) and 
all-grade and Grade >3 NT (87% and 31%, 
respectively).116 117
---------------------------------------------------------------------------

    \116\ YESCARTA[supreg] USPI (2019).
    \117\ KYMRIAH[supreg] USPI (2018).
---------------------------------------------------------------------------

    In the proposed rule, after reviewing the information submitted by 
the applicant as part of its FY 2022 new technology add-on payment 
application, we were concerned that there were no published studies 
directly comparing BREYANZI[supreg] and the two currently available CAR 
T-cell therapies for r/r DLBCL, YESCARTA[supreg] and KYMRIAH[supreg]. 
Additionally, we were concerned with the lack of long-term data 
supporting the effectiveness and efficacy of BREYANZI[supreg] and 
whether the lack of long-term data may limit the generalizability of 
the findings from the TRANSCEND NHL 001 study to the general Medicare 
population. While there have been no direct comparison studies of 
BREYANZI[supreg], YESCARTA[supreg] and KYMRIAH[supreg], the applicant 
did provide a comparison of the ORR, CR, PR and DOR across all three 
CAR T-cell therapies. While we noted that BREYANZI[supreg] does appear 
to provide an improved ORR, CR, PR, and DOR compared to the other FDA-
approved CAR T-cell therapies based on the data presented by the 
applicant, we further noted that these differences appear to be small 
in magnitude, between 1-2% for the ORR, CR, and PR. Without a direct 
comparison of outcomes between these therapies, we were concerned as to 
whether these differences translate to clinically meaningful 
differences or improvements. We stated that BREYANZI[supreg] appeared 
to demonstrate similar patient outcomes to that of YESCARTA[supreg] and 
we questioned whether the TRANSCEND NHL 001 study is evidence that 
BREYANZI[supreg] is a more effective therapy to treat DLBCL over 
existing CAR T-cell therapies. Additionally, as previously discussed, 
the applicant noted that BREYANZI[supreg] has been shown safe and 
effective for patient populations excluded from registrational trials 
for YESCARTA[supreg] and KYMRIAH[supreg]. However, we stated it was 
unclear whether this suggests that BREYANZI[supreg] is a treatment 
option for patients who cannot be treated with these existing CART-cell 
therapies, given that the FDA label for YESCARTA[supreg] and 
KYMRIAH[supreg] appears to not specifically exclude these patient 
populations. Finally, we were concerned that the use of the EGFRt cell 
surface tag was not activated in patients receiving BREYANZI[supreg] to 
study the impact of clearing these CAR T-cells after remission and that 
this feature has not yet been tested on humans or in conjunction with 
patients treated with BREYANZI[supreg]. We expressed concern regarding 
the safety and efficacy of this feature given its lack of testing.
    We invited public comments on whether BREYANZI[supreg] meets the 
substantial clinical improvement criterion.
    Comment: In support to CMS' concerns about substantial clinical 
improvement, a commenter, the manufacturer of a competitor CAR T-cell 
product, submitted a comment. First, the commenter stated 
BREYANZI[supreg] is not a new treatment option for patients that can be 
treated by KYMRIAH[supreg] or YESCARTA[supreg]. The commenter stated 
that as part of the substantial clinical improvement criterion, the 
applicant argued that given that BREYANZI[supreg] has been shown to be 
safe and effective for patient populations excluded from registrational 
trials for KYMRIAH[supreg] and YESCARTA[supreg], then it follows that 
BREYANZI[supreg] is a new treatment option for patients who cannot be 
treated with these therapies. The commenter was in agreement with CMS 
that these patient populations are not excluded from the FDA label of 
the existing FDA-approved CAR T-cell therapies, and thus 
BREYANZI[supreg] does not represent a new treatment option for these 
NHL subtypes.
    Next, the commenter stated BREYANZI[supreg] does not demonstrate 
improved effectiveness over KYMRIAH[supreg] and YESCARTA[supreg]. The 
commenter stated that the applicant claimed that BREYANZI[supreg] 
demonstrated improved effectiveness as compared to existing therapies, 
when comparing the TRANSCEND data to that of KYMRIAH[supreg]'s JULIET 
trial and YESCARTA[supreg]'s ZUMA-1 trial. The commenter stated that it 
is not appropriate to claim clinically meaningful differences including 
improved effectiveness by comparing outcomes across different studies, 
as opposed to performing a head-to-head study, as these differences may 
be attributable to study populations and study design.
    Lastly, the commenter stated that BREYANZI[supreg] does not 
demonstrate an improved safety profile over KYMRIAH[supreg] and 
YESCARTA[supreg]. The commenter stated that the applicant claimed that 
BREYANZI[supreg] demonstrates an improved safety profile in comparison 
to KYMRIAH[supreg] and YESCARTA[supreg]. As well as contending that it 
is inappropriate to claim clinically meaningful differences across 
different studies, the commenter stated that the safety profile between 
KYMRIAH[supreg] and BREYANZI[supreg] cannot be compared. However, 
according to the commenter, even using the applicant's own method of 
analysis by comparing safety data across different studies, the 
incidence of serious adverse reactions was in fact comparable across 
BREYANZI[supreg]'s TRANSCEND trial and YESCARTA[supreg]'s ZUMA-1 trial. 
The commenter added that the incidence of any grade neurologic events 
was actually lower in KYMRIAH[supreg]'s JULIET trial than in 
BREYANZI[supreg]'s TRANSCEND trial with a comparable incidence rate of 
grade \3/4\ neurologic events. Furthermore, the commenter stated there 
may also appear to be a lower incidence of Grade >3 CRS with 
BREYANZI[supreg] than with KYMRIAH[supreg] when looking solely at the 
pivotal trial data; however, this is likely due to differences in 
adverse event management across BREYANZI[supreg]'s TRANSCEND trial and 
KYMRIAH[supreg]'s JULIET trial. Lastly, the commenter stated 
KYMRIAH[supreg]'s safety data from the Center for International Blood 
and Marrow Transplant Research (CIBMTR)'s Cellular Therapy (CT) 
registry study \118\ illustrates comparable

[[Page 45007]]

safety to the TRANSCEND trial in true real-world conditions. The 
commenter stated of the 155 patients with NHL evaluated in the CIBMTR 
CT registry study, the rate of grade 3 or higher CRS and neurotoxicity 
occurred in 4.5% and 5.1% of patients respectively.\119\ The commenter 
concluded that even if safety data is compared across the different 
trials--which it stated is problematic--BREYANZI[supreg] is in fact not 
a safer therapy to treat DLBCL over existing FDA-approved CAR T-cell 
therapies.
---------------------------------------------------------------------------

    \118\ CIBMTR is a research collaboration between the National 
Marrow Donor Program[supreg] (NMDP)/Be The Match[supreg] and the 
Medical College of Wisconsin (MCW). The CIBMTR[supreg] CT registry 
study was a requirement from FDA's approval of Kymriah[supreg] and 
required Novartis to conduct a postmarketing, prospective, 
multicenter observational study to assess the long-term safety and 
the risk of all secondary malignancies occurring after treatment 
with tisagenlecleucel.
    \119\ Pasquini MC, Hu ZH, Curran K, et al. Real-world evidence 
of tisagenlecleucel for pediatric acute lymphoblastic leukemia and 
non-Hodgkin lymphoma. Blood Adv. 2020;4(21):5414-5424.
---------------------------------------------------------------------------

    Response: We appreciate the additional information submitted by the 
commenter and have taken this comment into consideration in determining 
whether BREYANZI[supreg] meets the substantial clinical improvement 
criterion.
    Comment: The applicant submitted a comment in response to CMS' 
concerns on substantial clinical improvement. The applicant stated that 
BREYANZI[supreg] is a substantial clinical improvement over existing 
technologies because: (1) The totality of the circumstances regarding 
BREYANZI[supreg]'s clinical efficacy, safety, and data make clear that 
BREYANZI[supreg] substantially improves, relative to services or 
technologies previously available, the treatment of Medicare 
beneficiaries with relapsed/refractory (R/R) NHL; (2) BREYANZI[supreg] 
fills an unmet need among patients with R/R NHL; (3) BREYANZI[supreg] 
has, overall, an improved safety profile compared to YESCARTA[supreg] 
and KYMRIAH[supreg]; (4) BREYANZI[supreg] has a comparable or superior 
effectiveness compared to existing therapies; and (5) 
BREYANZI[supreg]'s patient population in its registrational study more 
accurately reflects real-world NHL patients compared to the studies of 
currently available CAR T-cell therapies.
    According to the applicant, first, CMS questions the lack of long-
term data supporting the effectiveness and efficacy of BREYANZI[supreg] 
and whether the lack of long-term data may limit the generalizability 
of the findings from the TRANSCEND NHL 001 study to the general 
Medicare population.\120\ The applicant stated they believe this 
concern is unwarranted because the duration of data is unrelated to the 
generalizability of data to the Medicare population, the TRANSCEND NHL 
001 trial was specifically designed to include a patient population 
that is representative of real-world Medicare beneficiaries with NHL, 
including comorbidities, and BREYANZI[supreg], like the other CAR T-
cell therapies, is a new technology, none of which have long-term data.
---------------------------------------------------------------------------

    \120\ 86 FR at 25233.
---------------------------------------------------------------------------

    Next the applicant stated that CMS raises questions regarding the 
lack of published studies directly comparing BREYANZI[supreg] with 
YESCARTA[supreg] and KYMRIAH[supreg].\121\ The applicant stated they 
appreciate what they stated was CMS' recognition that BREYANZI[supreg] 
demonstrates improved clinical outcomes compared to KYMRIAH[supreg] and 
YESCARTA[supreg], which supports that BREYANZI[supreg] is a substantial 
clinical improvement over prior technologies. The applicant asserted 
that a head-to-head comparison of the therapies is not required for 
purposes of new technology add-on payment status. The applicant further 
asserted that BREYANZI[supreg] is clearly superior to both products 
from a safety perspective with any grade and grade \3/4\ CRS rate of 
42% and 2% respectively,\122\ compared to 94% and 13% for 
YESCARTA[supreg] \123\ and 57% and 17% for KYMRIAH[supreg].\124\ The 
applicant stated BREYANZI[supreg] showed equivalent efficacy and 
improved safety compared to YESCARTA[supreg], and improved efficacy 
with similar safety compared with KYMRIAH[supreg]. Thus, according to 
the applicant, the very nature of these differences demonstrates that 
BREYANZI[supreg] is in fact a substantial clinical improvement.
---------------------------------------------------------------------------

    \121\ 86 FR at 25233.
    \122\ Abramson JS, Palomba ML, Gordon LI, et al. Lisocabtagene 
maraleucel for patients with relapsed or refractory large B-cell 
lymphomas (TRANSCEND NHL001): a multicentre seamless design study. 
Lancet. 2020; 396(10254): 839-852 (Abramson, 2020).
    \123\ Yescarta[supreg] U.S. Prescribing Information (2020).
    \124\ Kymriah[supreg] U.S. Prescribing Information (2018).
---------------------------------------------------------------------------

    Next the applicant stated that CMS asks whether the TRANSCEND NHL 
001 study is evidence that BREYANZI[supreg] is a more effective therapy 
to treat DLBCL over existing CAR T-cell therapies or whether 
BREYANZI[supreg] has similar patient outcomes to YESCARTA[supreg].\125\ 
The applicant contends that BREYANZI[supreg] is an equally effective 
and safer CAR T-cell therapy than YESCARTA[supreg] since the TRANSCEND 
NHL 001 study population represents a more accurate real-world 
population and is more inclusive of patients across multiple large B-
cell lymphoma subtypes as well as patients with comorbidities than was 
represented in the registrational trial for YESCARTA[supreg]. The 
applicant asserted that three retrospective studies suggest that 
restrictive eligibility criteria employed in the YESCARTA[supreg] ZUMA-
1 study made for an overall study population with a more favorable 
prognosis and better outcomes with standard and CAR T-cell 
therapy.126 127 128 According to the applicant, these three 
studies each demonstrated that patients who did not meet key 
eligibility criteria for ZUMA-1 were found to have a substantially 
shorter survival compared to those enrolled to ZUMA-1. According to the 
applicant, the TRANSCEND NHL 001 study included these patients. The 
applicant further asserted that BREYANZI[supreg] results should be more 
equivalent to real-world patients based on the fact that the enrolled 
population that was at high risk for worse outcomes compared to the 
population studied for YESCARTA[supreg] in ZUMA-1. Yet, despite that, 
according to the applicant, BREYANZI[supreg] showed equivalent efficacy 
and improved safety compared to YESCARTA[supreg]. The applicant stated 
that one can only speculate as to what the efficacy would have been for 
BREYANZI[supreg] had the patient population in TRANSCEND NHL 001 been 
limited in the same manner as the patient population for ZUMA-1.
---------------------------------------------------------------------------

    \125\ 86 FR at 25233.
    \126\ Smith SD, Reddy P, Sokolova A, et al., Eligibility for CAR 
T cell therapy: An analysis of selection criteria and survival 
outcomes in chemorefractory DLBCL, Am J Hematol. 2019; 94(4): E116-
E117.
    \127\ Nastoupil LJ, Jain MD, Spiegel JY, et al., Axicabtagene 
Ciloleucel (Axi-cel) CD19 Chimeric Antigen Receptor (CAR) T cell 
Therapy for Relapsed/Refractory Large B-Cell Lymphoma: Real World 
Experience, Blood. 2018; 132:91.
    \128\ Jacobson CA, Hunter B., Armand P, et al., Axicabtagene 
Ciloleucel in the Real World: Outcomes and Predictors of Response, 
Resistance and Toxicity, Blood. 2018; 132: 92.
---------------------------------------------------------------------------

    Lastly, the applicant stated that they believe it is important to 
underscore that the potential use of the EGFRt cell surface tag is a 
method of last resort to alleviate any severe toxicities that may 
become life threatening to a patient. The applicant added that given 
the overall safety profile of BREYANZI[supreg], it is expected that the 
potential use of the EGFRt cell surface tag would be extremely rare. 
The applicant asserted that the existence of the EGFRt cell surface tag 
at least provides a potential option for patients who are at serious 
risk of death due to a rare adverse event; according to the applicant, 
the lack of this option for patients treated with YESCARTA[supreg] and 
KYMRIAH[supreg] means that there are limited options to mitigate 
serious incidents.
    Response: We thank the commenters for the additional information in 
response to our substantial clinical improvement concerns. We note that 
in their comment, the applicant stated that CMS recognized that 
BREYANZI[supreg] demonstrates improved clinical outcomes compared to 
KYMRIAH[supreg] and

[[Page 45008]]

YESCARTA[supreg], which supports that BREYANZI[supreg] is a substantial 
clinical improvement over prior technologies. We believe the applicant 
may have misunderstood what was stated in the proposed rule. Rather, we 
stated in the proposed rule that some data may show improvement but the 
differences were small and may not translate to clinically meaningful 
differences or improvements (86 FR 25233). We did not claim that 
BREYANZI[supreg] was a substantial clinical improvement. We further 
stated that we were not certain that the benefits were meaningful and 
due to differences in treatment, rather than other factors such as 
sample characteristics or study design. While the applicant asserts 
that BREYANZI[supreg] represents a substantial clinical improvement 
over YESCARTA[supreg] and KYMRIAH[supreg], we continue to have concerns 
with regard to whether BREYANZI[supreg] demonstrates an improved safety 
profile compared to existing treatments as discussed by a commenter. 
Furthermore, as noted previously in this section, we believe 
BREYANZI[supreg] is generally substantially similar to YESCARTA[supreg] 
and KYMRIAH[supreg] and not new. Moreover, the applicant did not 
provide data for the specific subpopulation of patients without DLBCL 
and with follicular lymphoma grade 3b, for which we consider 
Breyanzi[supreg] new. Upon further review of the TRANSCEND NHL 001 
study, three patients had FL3b at baseline.\129\ While the authors 
report that two patients with FL3b who received Breyanzi[supreg] 
remained in complete response after 1 year, we are not certain that 
these results can be generalizable to the greater FL3b patient 
population. We accept all information submitted by applicants and 
consider it in our determination of substantial clinical improvement. 
However, we believe a sample size of two or three patients is a very 
small sample from which to generalize about a larger population to then 
make a determination of substantial clinical improvement.
---------------------------------------------------------------------------

    \129\ Abramson JS, Palomba ML, Gordon LI, et al., Lisocabtagene 
maraleucel for patients with relapsed or refractory large B-cell 
lymphomas (TRANSCEND NHL 001): a multicenter seamless design study. 
Lancet. 2020; 396(10254):839-852.
---------------------------------------------------------------------------

    While we believe head to head studies are ideal for demonstration 
of superiority and to determine a difference in treatment effects, we 
accept all information submitted by applicants, as stated previously. 
However, we believe that we are consistent in requiring that the 
applicant provide data designed to test differences in treatment 
effects to allow us to distinguish the effect of a particular treatment 
from the effects of study design, sample characteristics, etc.
    We agree with the applicant that the generalizability of a study 
may not be directly related to whether a study is long-term and we 
appreciate the TRANSCEND NHL 001 was designed to include a patient 
population that is representative of real-world Medicare beneficiaries 
with NHL. However, we note that long-term data supports the 
effectiveness and efficacy of a technology, and without long-term data, 
it is difficult to determine if benefits seen are durable.
    We also note the applicant commented that there is a potential use 
of the EGFRt cell surface tag to alleviate severe toxicities in 
patients. We appreciate that this may be a potential use, however as a 
commenter stated, this is only supported by preclinical murine models. 
Without clinical trial data, we remain concerned that we are unable to 
verify the applicant's claims of a potential for positive clinical 
outcomes related to claims made about the EGFRt cell surface tag.
    Therefore, for the reasons discussed previously, particularly the 
insufficiency of data evaluating the population for which Breyanzi is 
considered new, we are unable to determine whether Breyanzi[supreg] 
represents a substantial clinical improvement for the specific 
subpopulation for which it would be eligible for new technology add-on 
payments. Also, as noted previously, BREYANZI[supreg] is considered not 
new and substantially similar to YESCARTA[supreg] and KYMRIAH[supreg] 
with regard to the other forms of large B-cell lymphoma listed on the 
indication and is therefore not new for these indications. Therefore, 
we are not approving new technology add-on payments for Breyanzi for FY 
2022.
d. COSELATM (trilaciclib)
    G1 Therapeutics submitted an application for new technology add-on 
payments for Trilaciclib for FY 2022. COSELATM (trilaciclib) 
is indicated to decrease the incidence of chemotherapy-induced 
myelosuppression in adult patients when administered prior to a 
platinum/etoposide-containing regimen or topotecan-containing regimen 
for extensive-stage small cell lung cancer (ES-SCLC).\130\
---------------------------------------------------------------------------

    \130\ G1 Therapeutics Inc., Rev. 2/2021, COSELA prescribing 
information: https://www.g1therapeutics.com/cosela/pi/
#:~:text=COSELA%20is%20indicated%20to%20decrease,cancer%20(ES%2DSCLC)
.&text=The%20recommended%20dose%20of%20COSELA%20is%20240%20mg%2Fm2%20
per%20dose.
---------------------------------------------------------------------------

    According to the applicant, COSELATM is a first-in-class 
myelopreservation therapy that has the potential to mitigate 
chemotherapy-induced myelosuppression (CIM). COSELATM is a 
selective, transient inhibitor of cyclin dependent kinases 4 and 6 
(CDK4/6) with potential antineoplastic and chemoprotective activities. 
CDK4 and CDK6 are key regulators of the G1 cell-cycle checkpoint and 
play important roles in cell proliferation and associated biological 
processes. One of the most common pathways dysregulated in cancer is 
the cyclin D-cyclin-dependent kinase four or six (CDK4/6)-
retinoblastoma (RB) pathway. COSELATM arrests hematopoietic 
stem and progenitor (HSPCs) bone marrow cells in the G1 phase of the 
cell cycle during chemotherapy exposure, protecting them from 
chemotherapy-induced damage.
    According to the applicant, the defining characteristic of cancer 
is uncontrolled cellular proliferation, a phenomenon that requires 
tumor cells to avoid or disable normal, physiologic cell-cycle 
regulation. While there are both CDK 4/6 independent and dependent 
cells, HSPCs and immune cells are CDK 4/6 dependent whereas SCLC cells 
are CDK 4/6 independent. According to the applicant, the transient 
arrest of HSPCs and lymphocytes by COSELATM during the 
administration of chemotherapy is thought to have a number of 
beneficial effects, including a reduction in chemotherapy-induced 
myelosuppression and preservation of immune function, as well as an 
enhanced immune response.131 132 133 Specifically, SCLC 
cells replicate independently of CDK 4/6 and therefore these cells are 
damaged by chemotherapy. Because HSPCs and

[[Page 45009]]

lymphocytes are CDK 4/6 dependent, COSELATM's mechanism of 
action is believed to preserve these cells by temporarily arresting 
their proliferation during chemotherapy. In this way, 
COSELATM reduces chemotherapy-induced myelosuppression in 
patients with extensive-stage small-cell lung cancer (ES-SCLC).\134\ 
The applicant also asserted that in preclinical models, CDK4/6 
inhibition by COSELATM also alters the tumor immune 
microenvironment through transient inhibition of the immune cells known 
as lymphocytes that are also dependent on CDK4/6 activity for 
proliferation.\135\
---------------------------------------------------------------------------

    \131\ Daniel D, Kuchava V, Bondarenko I, et al. Trilaciclib (T) 
decreases myelosuppression in extensive-stage small cell lung cancer 
(ES-SCLC) patients receiving first-line chemotherapy plus 
atezolizumab. Ann Oncol. 2019;30:v713, Abstract 1742PD: https://www.g1741therapeutics.com/file.cfm/1734/docs/tr-G1741_ESMO2019_Daniel.pdf.
    \132\ Weiss JM, Csoszi T, Maglakelidze M, et al. 
Myelopreservation with the CDK4/6 inhibitor trilaciclib in patients 
with small-cell lung cancer receiving first-line chemotherapy: a 
phase Ib/randomized phase II trial. Ann Oncol. 2019;30(10):1613-
1621.
    \133\ Hart LL, Andric ZG, Hussein MA, et al. Effect of 
trilaciclib, a CDK 4/6 inhibitor, on myelosuppression in patients 
with previously treated extensive-stage small cell lung cancer 
receiving topotecan. J Clin Oncol. 2019;37(15_suppl): Abstract 8505: 
https://www.g8501therapeutics.com/file.cfm/8534/docs/tr-G8501T8528-8503%8520ASCO%202019%202020Oral%202020Presentation%20060119-20060111.pdf.
    \134\ Donjerkovic D, Scott DW. Regulation of the G1 phase of the 
mammalian cell cycle. Cell Res. 2000;10(1):1-16.
    \135\ Lai AY, Sorrentino JA, Dragnev KH, et al. CDK\4/6\ 
inhibition enhances antitumor efficacy of chemotherapy and immune 
checkpoint inhibitor combinations in preclinical models and enhances 
T-cell activation in patients with SCLC receiving chemotherapy. J 
Immunother Cancer. 2020;0:e000847. doi:10.1136/jitc-2020-000847.
---------------------------------------------------------------------------

    According to the applicant, chemotherapy remains the cornerstone of 
treatment for extensive stage small cell lung cancer (ES-SCLC). The 
applicant asserted that almost all of the ~18,600 ES-SCLC patients 
diagnosed each year are treated with platinum/etoposide-containing or 
topotecan-containing chemotherapy regimens. Chemotherapy drugs target 
cells at different phases of the cell cycle. According to the 
applicant, systemic chemotherapy, alone or in combination with immune 
checkpoint inhibitors, is the standard of care for patients with 
advanced SCLC. Additionally, per the applicant, rescue interventions, 
including growth factors and blood transfusions, are commonly routine 
therapies for SCLC. The applicant also indicated that granulocyte 
colony-stimulating factors (G-CSFs) only address neutropenia, while 
erythropoiesis stimulating agent (ESAs) and red blood cell (RBC) 
transfusions only address anemia, and there is no available treatment 
that broadly mitigates myelosuppressive effects and their corresponding 
impact on patient well-being before chemotherapy damage occurs.
    COSELATM received FDA's New Drug Application approval on 
February 12, 2021. COSELATM is for intravenous use only. The 
recommended dose of COSELATM is 240 mg/m2 as a 30-minute 
intravenous infusion completed within four hours prior to the start of 
chemotherapy on each day chemotherapy is administered.\136\ The 
applicant also stated that in 2019, COSELATM was granted 
Breakthrough Therapy Designation for the mitigation of clinically 
significant chemotherapy-induced myelosuppression in adult patients 
with SCLC. The applicant submitted a request for a new ICD-10-PCS code 
and was granted approval for the following codes to uniquely identify 
COSELATM effective October 1, 2021: XW03377 (Introduction of 
trilaciclib into peripheral vein, percutaneous approach, new technology 
group 7) and XW04377 (Introduction of trilaciclib into central vein, 
percutaneous approach, new technology group 7).
---------------------------------------------------------------------------

    \136\ G1 Therapeutics Inc., Rev. 2/2021, COSELA prescribing 
information: https://www.g1therapeutics.com/cosela/pi/
#:~:text=COSELA%20is%20indicated%20to%20decrease,cancer%20(ES%2DSCLC)
.&text=The%20recommended%20dose%20of%20COSELA%20is%20240%20mg%2Fm2%20
per%20dose.
---------------------------------------------------------------------------

    As previously discussed, if a technology meets all three of the 
substantial similarity criteria, it would be considered substantially 
similar to an existing technology and, therefore, would not be 
considered ``new'' for purposes of new technology add-on payments.
    With respect to the first criterion, whether a product uses the 
same or a similar mechanism of action to achieve a therapeutic outcome, 
the applicant asserted that COSELATM, also referred to as 
G1T28, has a unique mechanism of action as a small molecule, 
competitive inhibitor of CDK4/6, with potential antineoplastic and 
chemoprotective activities. The applicant stated that upon 
administration, COSELATM binds to and inhibits the activity 
of CDK4/6, thereby blocking the phosphorylation of the retinoblastoma 
protein (Rb) in early G1. This prevents G1/S phase transition, causing 
cell cycle arrest in the G1 phase and induced apoptosis, which inhibits 
the proliferation of CDK4/6-overexpressing tumor cells. In patients 
with CDK4/6-independent tumor cells, G1T28 may protect against multi-
lineage chemotherapy-induced myelosuppression (CIM) by transiently and 
reversibly inducing G1 cell cycle arrest in hematopoietic stem and 
progenitor cells (HSPCs) and preventing transition to the S phase. Per 
the applicant, this protects all hematopoietic lineages, including red 
blood cells, platelets, neutrophils and lymphocytes, from the DNA-
damaging effects of certain chemotherapeutics and preserves the 
function of the bone marrow and the immune system.
    The applicant stated that the cell cycle consists of four distinct 
phases, Gap 1 phase (G1), S phase, Gap 2 (G2) 
post-synthesis phase, and the M phase.\137\ Regulation of this process 
is maintained by a series of highly conserved proteins referred to as 
cyclins, and their catalytic binding partners, CDKs. The CDKs are a 
family of enzymes that control several cellular processes in mammalian 
cells, including the modulation of the cell cycle via binding to 
cyclins A-E, which results in the activation of transcription factors 
that regulate the cellular transition from G1 (growth phase) to S (DNA 
replication) and G2 (growth phase) to M (mitosis).\138\
---------------------------------------------------------------------------

    \137\ Ferrarotto R, Anderson I, Medgyasszay B, et al. 
Trilaciclib reduces the need for growth factors and red blood cell 
transfusions to manage chemotherapy-induced myelosuppression. Poster 
presented at: IASLC: 2020 North America Conference on Lung Cancer; 
October 16-17, 2020; Virtual congress.
    \138\ Asghar U, Witkiewicz AK, Turner NC, Knudsen ES. The 
history and future of targeting cyclin-dependent kinases in cancer 
therapy. Nat Rev Drug Discov. 2015;14(2):130-146.
---------------------------------------------------------------------------

    According to the applicant, the G1-to-S checkpoint is a critical 
restriction point in the process of cell division. Cells are maintained 
in a quiescent state until the proper signal is achieved for reentry 
into the cell cycle. Throughout G1, expression of the D-type cyclins 
(D1, D2, D3) increases until active complexes with CDK4/6 are formed. 
Active CDK4/6 complexes partially phosphorylate RB, which allows 
partial depression of the transcription factor E2F. This induces 
additional transcript production of cyclin E1, which binds CDK2 to form 
active complexes that result in the hyperphosphorylation of RB and 
drives the cells through late G1 into S phase. Inhibition of cyclin D-
CDK4/6 by the tumor suppressor CDKN2A leads to a G1 arrest and cell-
cycle progression is halted.\139\
---------------------------------------------------------------------------

    \139\ Donjerkovic D, Scott DW. Regulation of the G1 phase of the 
mammalian cell cycle. Cell Res. 2000;10(1):1-16.
---------------------------------------------------------------------------

    With respect to the second criterion, whether a product is assigned 
to the same or a different MS-DRG, the applicant asserted that 
COSELATM will be assigned the same MS-DRG as existing 
technologies. The applicant did not explicitly state to which MS-DRG(s) 
COSELATM would be assigned, but included MS-DRGs 180 
(Respiratory Neoplasms with MCC), 181 (Respiratory Neoplasms with CC), 
and 182 (Respiratory Neoplasms without CC/MCC) in its cost analysis.
    With respect to the third criterion, whether the new use of the 
technology involves the treatment of the same or similar type of 
disease and the same or similar patient population when compared to an 
existing technology, the applicant stated that COSELATM is 
the only proactive (preventive) multilineage

[[Page 45010]]

(erythrocytes, leukocytes, and thrombocytes, neutrophils and 
lymphocytes) therapy given as a 30-minute infusion administered prior 
to chemotherapy on each day of chemotherapy. Due to its mechanism of 
action, COSELATM's benefit is coupled to its administration 
schedule (that is, COSELATM must be administered prior to 
chemotherapy to ensure G1 arrest of HSPCs when those cells are exposed 
to cytotoxic chemotherapy). According to the applicant, this 
therapeutic paradigm contrasts with standard available treatment 
options and interventions that are administered after chemotherapy to 
reactively reduce or treat chemotherapy side effects. The applicant 
asserted that typical supportive care rescue interventions such as 
growth factors (G-CSFs, ESAs) and red blood cell (RBC) transfusions are 
used after chemotherapy causes damage to stem cells. Current supportive 
care therapies are used reactively to treat single cell lineage 
specific (leukocytes and erythrocytes) complications,\140\ such as 
neutropenia and anemia. Additionally, the applicant indicated that 
growth factor and RBC transfusion use are known to carry a number of 
risks and cause complications and adverse events.
---------------------------------------------------------------------------

    \140\ National Comprehensive Cancer Network. NCCN Clinical 
Practice Guidelines in Oncology. Hematopoietic Growth Factors. 
Version 1.2020. 27 January. 2020.
---------------------------------------------------------------------------

    In the FY 2022 IPPS/LTCH PPS proposed rule (86 FR 25240), we noted 
that the information provided by the applicant in response to whether 
COSELATM treats the same or similar type of disease or the 
same or similar patient population, appeared to only speak to the first 
criterion and whether COSELATM has a mechanism of action 
that is different than existing technologies; however, we stated we 
believe COSELATM appears to treat the same patient 
population and disease as existing therapies.
    We invited public comments on whether COSELATM is 
substantially similar to an existing technology and whether it meets 
the newness criterion.
    Comment: The applicant submitted a comment reiterating that 
COSELATM meets the newness criterion because it is the first 
and only FDA-approved therapy to provide myeloprotective efficacy. The 
applicant stated that existing treatments are single lineage rescue 
interventions and that COSELATM is the only available 
treatment that broadly mitigates multilineage myelosuppressive effects 
and their corresponding impact on patient well-being before 
chemotherapy damage occurs. The applicant further explained that 
existing therapies, such as growth factors (granulocyte colony 
stimulating factor (G-CSF), erythropoiesis-stimulating agents (ESAs) 
and red blood cell (RBC) transfusions) do not treat chemotherapy-
induced myelosuppression but that they treat the side effects of 
chemotherapy-induced myelosuppression, such as single cell lineage 
specific complications like neutropenia and anemia after chemotherapy 
damage has occurred. The applicant also stated that existing therapies 
are designed to work in different ways and treat different conditions 
than COSELATM.
    The applicant also stated that COSELATM does not treat 
the same or similar patient population as existing therapies but that 
it treats adult patients diagnosed with ES-SCLC prior to a platinum/
etoposide-containing regimen or topotecan-containing regimen whereas 
the patient population treated by other therapies (for example, G-CSF, 
ESAs, and RBC transfusions) is patients with side effects associated 
with chemotherapy-induced myelosuppression. The applicant stated that 
COSELATM treats a patient population that is not currently 
served by growth factors. The applicant concluded by reiterating that 
COSELATM does not use the same mechanism of action, does not 
treat the same condition or disease, and does not treat the same 
patient population as existing therapies.
    Response: We thank the applicant for its comment and the additional 
information submitted in regard to the newness criterion. Based on our 
review, we agree that COSELATM has a unique mechanism of 
action to decrease the incidence of chemotherapy-induced 
myelosuppression in adult patients by preventing it when administered 
prior to a platinum/etoposide-containing regimen or topotecan-
containing regimen for ES-SCLC. Though the applicant states that 
COSELATM treats a new patient population since it treats 
patients before they encounter side effects from chemotherapy-induced 
myelosuppression, we disagree that patients with such side effects 
would be considered a distinct patient population because 
COSELATM also treats adult patients with ES-SCLC.
    Based on information submitted by the applicant in its comment and 
as part of its FY 2022 new technology add-on payment application for 
COSELATM, as discussed in the proposed rule (86 FR 25239) 
and previously summarized, we believe that COSELATM has a 
unique mechanism of action. Therefore, COSELATM is not 
substantially similar to existing treatment options and meets the 
newness criterion. We consider the beginning of the newness period to 
commence when COSELATM was approved by FDA to decrease the 
incidence of chemotherapy-induced myelosuppression in adult patients 
when administered prior to a platinum/etoposide-containing regimen or 
topotecan-containing regimen for extensive-stage small cell lung cancer 
(ES-SCLC), on February 12, 2021.
    With respect to the cost criterion, the applicant conducted the 
following analysis to demonstrate that COSELATM meets the 
cost criterion. In identifying the cost of COSELATM, the 
applicant stated that dosing is based on body surface area, 240 mg/m\2\ 
with an average of two vials (300mg each) per patient per dose. To 
identify cases that may be eligible for the use of COSELATM, 
the applicant searched the FY 2019 MedPAR LDS file for claims reporting 
an ICD-10-PCS code of category C34 through C34.92 (Malignant neoplasm 
related to the bronchus, lobe, or lung) as noted in the following 
table.
BILLING CODE 4120-01-P

[[Page 45011]]

[GRAPHIC] [TIFF OMITTED] TR13AU21.170


[[Page 45012]]


[GRAPHIC] [TIFF OMITTED] TR13AU21.171

    According to the applicant, based on the advice of clinical 
experts, it limited case selection criteria to claims that included one 
of MS-DRGs 180, 181, or 182. The applicant then randomly selected 15% 
of the claims from the sample to account for the fact that SCLC 
comprises 15% of lung cancer cases.\141\ Based on the FY 2019 MedPAR 
LDS file, the applicant identified 3,500 cases. The applicant noted 
that 2,346 cases mapped to MS-DRG 180; 1,085 cases mapped to MS-DRG 
181; and 69 cases mapped to MS-DRG 182.
---------------------------------------------------------------------------

    \141\ Govindan R, et al. J Clin Oncol. 2006;24:4539-44. Byers 
LA, Rudin CM. Cancer. 2015;121:664-72.
---------------------------------------------------------------------------

    Using these 3,500 cases, the applicant then calculated the 
unstandardized average charges per case for each MS-DRG. Because the 
use of COSELATM results in approximately half of patients no 
longer needing drugs used to counter the effects of chemotherapy during 
the inpatient stay, the applicant removed 50% of the drug charges for 
the technology being replaced.
    The applicant then standardized the charges using the 2019 IPPS/
LTCH PPS final rule impact file and inflated the charges by 1.13218 or 
13.2 percent, the same inflation factor used by CMS to update the 
outlier threshold in the FY 2021 IPPS/LTCH PPS final rule. The 
applicant then added the charges for COSELATM by converting 
the costs to a charge by dividing the cost by the national average 
cost-to-charge ratio of 0.187 for pharmacy from the FY 2021 IPPS/LTCH 
PPS final rule.
    Using the data file thresholds associated with the FY 2021 IPPS/
LTCH PPS final rule correction notice, the average case-weighted 
threshold amount was $57,031. In the applicant's analysis, the final 
inflated average case-weighted standardized charge per case was 
$95,701. Because the final inflated average case-weighted standardized 
charge per case exceeds the average case-weighted threshold amount, the 
applicant maintained that the technology meets the cost criterion.
    With respect to the cost criterion, we noted in the proposed rule 
that in listing the codes it used to identify cases that may be 
eligible for the use of COSELATM, the applicant provided 
several ICD-10 codes that lack four digits and thus, are considered 
invalid. We stated that we would be interested in understanding the 
basis for the applicant's choice of codes. We also noted that in its 
analysis, the applicant randomly selected 15% of the claims from the 
sample to account for the fact that SCLC comprises 15% of lung cancer 
cases. In so doing, we stated that the applicant was making the 
assumption that SCLC cases are randomly distributed amongst all cases 
from which the applicant sampled. By randomly sampling the population, 
the applicant was selecting a subsample that is ideally similar to the 
population with less variance. We stated that it may be the case that 
SCLC cases are systematically different from other cases in the 
population. If this is true, then a random sample may not be 
appropriate. Accordingly, we questioned the appropriateness of the 
sampling used and whether it accurately represents cases that would use 
the technology.
    Finally, with respect to pricing, we stated that it appeared that 
the applicant's final inflated average case-weighted standardized 
charge per case reflected pricing prior to the availability of more 
current total wholesale acquisition cost. We therefore requested that 
the applicant update its cost analysis to reflect the final inflated 
average case weighted standardized charge per case based on this more 
current information. We invited public comment on whether 
COSELATM meets the cost criterion.
    Comment: The applicant submitted a comment in response to these 
concerns. First, with respect to the ICD-10 codes included in the 
application lacking four digits, the applicant stated that the codes 
used in the cost criterion analysis included both the two to three-
digit code family names and all the four-digit codes that fall within 
the code families. The applicant clarified that in querying the claims 
data, only the codes with four digits resulted in usable claims for the 
analysis. The applicant clarified that the codes used to identify the 
claims for the cost criterion analysis were limited to the following 
four-digit ICD-10-CM codes:

[[Page 45013]]

[GRAPHIC] [TIFF OMITTED] TR13AU21.172

BILLING CODE 4120-01-C
    Second, with respect to whether the applicant's sampling accurately 
represents cases in which the technology would be used, the applicant 
indicated that it relied on a random sample of lung cancer cases 
derived by selecting 15 percent of the claims from the sample to 
account for the fact that SCLC comprises 15 percent of lung cancer 
cases, since there was a lack of evidence suggesting a more specified 
sample should be used instead. The applicant further stated that in 
further examining the claims data, the current ICD-10-CM codes do not 
provide the level of detail and granularity to correctly identify the 
SCLC population from the larger lung cancer population. The applicant 
also stated that without a precise mechanism to differentiate the 15 
percent of cases that would be eligible for COSELATM from 
the 85 percent of cases where use of COSELATM would not be 
clinically appropriate, it made the best assumption based on the 
information available, acknowledging that the random sample collected 
may not be perfectly representative of the target SCLC population but, 
absent additional information to otherwise identify the population, a 
random sample was the most appropriate assumption. The applicant stated 
that it ran an additional, more conservative analysis using the 15 
percent of lung cancer cases with the lowest total charges recognizing 
that that sample would be the least likely to meet the cost threshold, 
and that COSELATM still met the cost criterion. The 
applicant concluded in noting that there is no clinical information to 
suggest that this sample is more representative of the 
COSELATM-eligible population than the random sample used in 
the original analysis.
    Finally, with respect to pricing, the applicant submitted an 
updated cost analysis based on newly available total wholesale 
acquisition cost (WAC) of COSELATM of $1,417 per vial. The 
applicant stated that an average hospitalization would include one

[[Page 45014]]

cycle, which is comprised of three doses. The applicant further noted 
that each dose includes two vials and therefore, on average, an 
inpatient hospitalization would involve six vials of 
COSELATM for a total cost of $8,502 per hospitalization. The 
applicant also stated that in relying on the conservative analysis 
using 15 percent of lung cancer cases with the lowest charges, there is 
a final inflated case weighted standardized charge per case of $58,314, 
which exceeds the case weighted threshold of $54,566. The applicant 
also stated that it assumed hospitals will use the inverse of the 
national average cost to charge ratio for pharmacy to markup charges 
and therefore assumed that charges for COSELATM would be 
$45,465. The applicant concluded by stating that COSELATM 
meets the cost criterion because the final inflated case weighted 
standardized charge per case of $58,314 exceeds the case weighted 
threshold of $54,566.
    Response: We appreciate the applicant's clarification that only the 
codes with four digits resulted in usable claims for the cost analysis. 
We also appreciate the additional information from the applicant 
regarding its use of a random sample for purposes of its initial 
analysis, as well as its supplemental cost analysis using the 15 
percent of lung cancer cases with the lowest total charges. Based on 
the information submitted by the applicant as part of its FY 2022 new 
technology add-on payment application for COSELATM, as 
discussed in the proposed rule (86 FR 25240 through 25242) and 
previously summarized, and the updated analysis provided in the 
applicant's public comment, we agree that the final inflated average 
case-weighted standardized charge per case exceeded the average case-
weighted threshold amount. Therefore,COSELATM meets the cost 
criterion.
    With respect to the substantial clinical improvement criterion, the 
applicant asserted that trilaciclib represents a substantial clinical 
improvement over existing technologies because it offers a treatment 
option for patients unresponsive to or ineligible for currently 
available treatments and improves clinical outcomes for a patient 
population as compared to currently available treatments. The applicant 
stated that chemotherapy-induced myelosuppression (CIM) is typically 
managed with treatment dose delays and reductions due to the slow 
recovery of bone marrow after a course of chemotherapy.\142\ The 
applicant also stated that CIM is managed with rescue interventions 
including hematopoietic growth factors (G-CSFs and ESAs) and by RBC and 
platelet transfusions.143 144 Per the applicant, despite the 
availability and use of these treatment options, CIM continues to be of 
clinical significance and remains a central concern in the delivery of 
chemotherapy.145 146 The applicant further stated that 
myelosuppression results in dose reductions, dose delays, and/or dose 
discontinuations, affecting the dose intensity and intended antitumor 
efficacy of chemotherapy.\147\ Per the applicant, the supportive care 
interventions for treatment of myelosuppression are suboptimal and are 
often administered reactively, do not protect the bone marrow from 
chemotherapy-induced cytotoxic effects, are specific to single 
hematopoietic lineages, and impart their own risks for adverse 
reactions.\148\ The applicant concluded by stating that new approaches 
that proactively prevent chemotherapy-induced damage and its associated 
consequences, whilst not decreasing the efficacy of chemotherapy, are 
urgently needed to improve care of patients with ES-SCLC.\149\
---------------------------------------------------------------------------

    \142\ Crawford J, Dale DC, Lyman GH. Chemotherapy-induced 
neutropenia: Risks, consequences, and new directions for its 
management. Cancer. 2004;100(2):228.
    \143\ Kurtin S. Myeloid Toxicity of Cancer Treatment. J Adv 
Pract Oncol 2012;3:209-24.
    \144\ Asghar U, Witkiewicz AK, Turner NC, Knudsen ES. The 
history and future of targeting cyclin-dependent kinases in cancer 
therapy. Nat Rev Drug Discov. 2015;14(2):130-46.
    \145\ Crawford J, Dale DC, Lyman GH. Chemotherapy-induced 
neutropenia: Risks, consequences, and new directions for its 
management. Cancer. 2004;100(2):228.
    \146\ Lyman GH. Chemotherapy dose intensity and quality cancer 
care. Oncology (Williston Park). 2006;20(14 Suppl 9):16-25.
    \147\ Smith RE. Trends in recommendations for myelosuppressive 
chemotherapy for the treatment of solid tumors. J Natl Compr Canc 
Netw. 2006;4(7):649-58.
    \148\ Bisi JE, Sorrentino JA, Roberts PJ, Tavares FX, Strum JC. 
Preclinical characterization of G1T28: A novel CDK4/6 inhibitor for 
reduction of chemotherapy-induced myelosuppression. Mol Cancer Ther. 
2016;15(5):783-93.
    \149\ Nurgali K, Jagoe T, Raquel Abalo R. Editorial: Adverse 
Effects of Cancer Chemotherapy: Anything New to Improve Tolerance 
and Reduce Sequelae? Front Pharmacol. 2018;9:245.
---------------------------------------------------------------------------

    In regard to the claim that the use of COSELATM 
significantly improves clinical outcomes for a patient population as 
compared to currently available treatments, the applicant stated that 
the administration of COSELATM prior to chemotherapy in 
patients with SCLC prevented chemotherapy-induced neutropenia, reduced 
chemotherapy-induced anemia, reduced CIM or sepsis-related 
hospitalizations, and has the potential to improve the management and 
quality of life of patients receiving myelosuppressive chemotherapy as 
compared to placebo.\150\
---------------------------------------------------------------------------

    \150\ Ferrarotto R, Anderson I, Medgyasszay B, et al. 
Trilaciclib reduces the need for growth factors and red blood cell 
transfusions to manage chemotherapy-induced myelosuppression. Poster 
presented at: IASLC: 2020 North America Conference on Lung Cancer; 
October 16-17, 2020; Virtual congress.
---------------------------------------------------------------------------

    The applicant presented eight claims in support of the assertion 
that COSELATM represents substantial clinical improvement 
over existing technologies in the mitigation of clinically significant 
chemotherapy-induced myelosupression in adult patients with SCLC.
    In its first and second claims, the applicant asserted that 
COSELATM reduces the mean duration of severe G4 neutropenia 
in cycle 1 of chemotherapy and reduces the proportion of patients 
experiencing severe G4 neutropenia in comparison to placebo. The 
applicant submitted three sources in support of these claims. First, 
the applicant submitted a poster presentation from Daniel, et. al., 
describing a global, randomized, double-blind, placebo-controlled, 
multicenter, phase 2 study that assessed the potential of 
COSELATM to reduce the incidence and consequences of 
chemotherapy-induced myelosuppression in patients with newly diagnosed 
ES-SCLC treated with etoposide, carboplatin, and atezolizumab. One 
hundred seven eligible patients were randomized to receive 
COSELATM (n=53) or placebo (n=54). The primary endpoints 
were mean duration of severe neutropenia (SN) in cycle 1 and percent of 
patients with grade 4 SN. Results summarized mean duration of SN in 
cycle 1 as 0 days with trilaciclib and 4 days with placebo, and percent 
of patients with grade 4 SN as 1.9% vs 49.1%, respectively.\151\
---------------------------------------------------------------------------

    \151\ Daniel D, Kuchava V, Bondarenko I et al. Trilaciclib 
Decreases Myelosuppression in Extensive-Stage Small Cell Lung Cancer 
(ES-SCLC) Patients Receiving First-Line Chemotherapy Plus 
Atezolizumab [Poster Presentation]. European Society of Medical 
Oncology (ESMO). October, 2019; Barcelona, Spain.
---------------------------------------------------------------------------

    Second, the applicant submitted an article by Weiss, et. al., 
summarizing a phase II randomized, double-blind placebo-controlled 
study of the safety, efficacy and pharmacokinetics (PK) of 
COSELATM in combination with etoposide/carboplatin (E/P) 
therapy for treatment-naive extensive-stage small-cell lung cancer 
patients. Thirty-nine patients were included in the COSELATM 
group versus 38 in the

[[Page 45015]]

placebo group. The applicant stated that treatment with 
COSELATM resulted in a reduced mean duration of severe G4 
neutropenia in cycle 1 (0 days versus 3 days in placebo) and reduced 
proportion of patients experiencing severe G4 neutropenia for 
COSELATM (5% versus 43%).\152\
---------------------------------------------------------------------------

    \152\ Weiss JM, Csoszi T, Maglakelidze M et al. 
Myelopreservation with the CDK4/6 inhibitor Trilaciclib in Patients 
with Small-Cell Lung Cancer Receiving First-Line Chemotherapy: A 
Phase Ib/Randomized Phase II Trial. Ann Oncol. 2019;30(10):1613-
1621.
---------------------------------------------------------------------------

    Third, the applicant submitted a presentation from Hart, et. al., 
describing a randomized, double-blind, placebo-controlled, phase 2 
study to compare the results of 32 patients receiving 
COSELATM versus 28 receiving placebo in patients being 
treated with topotecan for previously treated ES-SCLC. Primary 
endpoints were mean duration of SN in cycle 1 and the percentage of 
patients with SN. Results demonstrated that the mean duration of severe 
G4 neutropenia in cycle 1 was reported at 2 days for 
COSELATM versus eight days for placebo. The proportion of 
patients experiencing severe G4 neutropenia was reported at 41% for 
COSELATM versus 76% for placebo.\153\
---------------------------------------------------------------------------

    \153\ Hart LL, Andric ZG, Hussein MA et al. Effect of 
Trilaciclib, a CDK4/6 Inhibitor, on Myelosuppression in Patients 
with Previously Treated Extensive-Stage Small Cell Lung Cancer [Oral 
Presentation]. Presented at: American Society of Clinical Oncology 
(ASCO). June 2019; Chicago, US.
---------------------------------------------------------------------------

    In the third claim, the applicant asserted that COSELATM 
reduces the proportion of patients experiencing febrile neutropenia 
treatment emergent adverse events (TEAE) in comparison to placebo. In 
the fourth claim, the applicant asserted that COSELATM 
decreases the rate of therapeutic intervention with G-CSF in comparison 
to placebo, noting that growth factors are known to carry a number of 
risks, cause complications and adverse events. In the fifth claim, the 
applicant asserted that COSELATM reduces the proportion of 
patients experiencing grade 3/4 anemia in comparison to placebo. In the 
sixth claim, the applicant asserted that COSELATM decreases 
the rate of therapeutic intervention with red blood cell transfusions 
in comparison to placebo. To support these claims, the applicant 
submitted a 2020 poster presentation from Weiss, et. al., describing a 
pooled analysis across three RCTs that compared the proportion of ES-
SCLC patients experiencing febrile neutropenia between 
COSELATM and placebo. The COSELATM group included 
122 patients and the placebo group included 118 patients. The 
presentation reflected the following results: The proportion of 
patients experiencing febrile neutropenia for COSELATM was 
3% versus placebo at 9%; the rate of therapeutic intervention with G-
CSF for COSELATM at 29% versus 56% for placebo; the 
proportion of patients experiencing grade 3/4 anemia for 
COSELATM at 20% versus 32% for placebo; and the rate of 
therapeutic intervention with red blood cell transfusions for 
COSELATM at 15% versus 26% for placebo.\154\
---------------------------------------------------------------------------

    \154\ Weiss J, Goldschmidt J, Andric Z et al. Myelopreservation 
and Reduced Use of Supportive Care with Trilaciclib in Patients with 
Small Cell Lung Cancer [Poster Presentation]. Presented at: American 
Society of Clinical Oncology (ASCO). May 2020.
---------------------------------------------------------------------------

    In the seventh claim, the applicant asserted that 
COSELATM delays time to deterioration in symptoms and 
functioning domains of patient-reported quality of life measures on 
Functional Assessment of Cancer Therapy (FACT) scores. The applicant 
submitted a 2019 presentation from Weiss, et. al., describing a pooled 
analysis across three RCTs. The applicant stated that 
COSELATM delays time to confirmed deterioration in a variety 
of symptoms and functioning domains compared to placebo, for example: 
Median of 4.7 months delay to deterioration for fatigue; median of 3.5 
months delay for anemia; and median of 4 months delay for functional 
well-being.\155\
---------------------------------------------------------------------------

    \155\ Weiss J, Skaltsa K, Gwaltney C, et al: Results from three 
phase 2 randomized, double-blind, placebo-controlled small cell lung 
cancer trials. 2019 Multinational Association of Supportive Care in 
Cancer/International Society of Oral Oncology International 
Symposium on Supportive Care in Cancer. Abstract eP723. Presented 
June 21, 2019.
---------------------------------------------------------------------------

    In the eighth claim, the applicant asserted that 
COSELATM decreases the number of hospitalizations due to 
myelosuppression or sepsis. The applicant submitted a conference agenda 
referring to an oral presentation by Ferrarotto, et. al., at the North 
America Conference on Lung Cancer, October 16, 2020. The applicant 
stated that hospitalizations due to myelosuppression or sepsis occurred 
in significantly fewer patients and significantly less often among 
patients receiving COSELATM prior to chemotherapy versus 
placebo though we were unable to locate support for this claim in the 
conference agenda submitted with the application.\156\
---------------------------------------------------------------------------

    \156\ Ferrarotto R, Anderson I, Medgyasszay B, et al. 
Trilaciclib reduces the need for growth factors and red blood cell 
transfusions to manage chemotherapy-induced myelosuppression. [Oral 
Presentation]. Presented at: North America Conference on Lung 
Cancer, October 2020. https://naclc2020.iaslc.org/program-at-a-glance/.
---------------------------------------------------------------------------

    With respect to the substantial clinical improvement criterion, we 
noted several concerns in the proposed rule (86 FR 25243 through 
25244). First, the data submitted by the applicant included one 
published peer reviewed article from Weiss, et. al.,\157\ abstracts 
from Daniel, et. al.,\158\ and Hart, et. al.,\159\ and references to 
trials exploring broader cohorts of small cell lung cancer, breast 
cancer and colon cancer patients. In addition, as summarized 
previously, we noted that most of the studies submitted by the 
applicant had sample sizes fewer than 100 participants which may limit 
generalizability of the studies. With respect to the Weiss, et. al., 
study, we noted that COSELATM was compared with placebo at a 
significance level of two-sided [alpha] = 0.2 which is much lower than 
the typical cutoff of 0.05 and may have increased the risk of false 
positives and interfered with the ability to draw conclusions that are 
based on statistical methods. We also noted the lack of any statistical 
correction for multiple comparisons. We noted that in sources provided 
by the applicant, mean duration of severe neutropenia was assessed in 
day increments.160 161 162 163 However, it was

[[Page 45016]]

not clear that zero days would indicate that those patients experienced 
no severe neutropenia. Specifically, we questioned whether mean hours 
in severe neutropenia was evaluated or whether, in addition to the 
groupings by days, one day or less would be an appropriate value for 
inclusion. Finally, while the applicant referred to decreases in the 
number of hospitalizations, we noted that the source provided was 
limited to a conference agenda that only linked to an abstract 
pertaining to reductions in utilization of supportive care 
interventions but did not reflect hospitalization rates.\164\
---------------------------------------------------------------------------

    \157\ Weiss JM, Csoszi T, Maglakelidze M, et al. 
Myelopreservation with the CDK4/6 inhibitor trilaciclib in patients 
with small-cell lung cancer receiving first-line chemotherapy: A 
phase Ib/randomized phase II trial. Ann Oncol. 2019;30(10):1613-
1621.
    \158\ Daniel D, Kuchava V, Bondarenko I, et al. Trilaciclib (T) 
decreases myelosuppression in extensive-stage small cell lung cancer 
(ES-SCLC) patients receiving first-line chemotherapy plus 
atezolizumab. Ann Oncol. 2019;30:v713, Abstract 1742PD.https://www.g1741therapeutics.com/file.cfm/1734/docs/tr-G1741_ESMO2019_Daniel.pdf.
    \159\ Hart LL, Andric ZG, Hussein MA, et al. Effect of 
trilaciclib, a CDK \4/6\ inhibitor, on myelosuppression in patients 
with previously treated extensive-stage small cell lung cancer 
receiving topotecan. J Clin Oncol. 2019;37(15_suppl): Abstract 8505: 
https://www.g8501therapeutics.com/file.cfm/8534/docs/tr-G8501T8528-8503%8520ASCO%202019%202020Oral%202020Presentation%20060119-20060111.pdf.
    \160\ Weiss JM, Csoszi T, Maglakelidze M, et al. 
Myelopreservation with the CDK4/6 inhibitor trilaciclib in patients 
with small-cell lung cancer receiving first-line chemotherapy: A 
phase Ib/randomized phase II trial. Ann Oncol. 2019;30(10):1613-
1621.
    \161\ Daniel D, Kuchava V, Bondarenko I, et al. Trilaciclib (T) 
decreases myelosuppression in extensive-stage small cell lung cancer 
(ES-SCLC) patients receiving first-line chemotherapy plus 
atezolizumab. Ann Oncol. 2019;30:v713, Abstract 1742PD: https://www.g1741therapeutics.com/file.cfm/1734/docs/tr-G1741_ESMO2019_Daniel.pdf.
    \162\ Hart LL, Andric ZG, Hussein MA et al. Effect of 
Trilaciclib, a CDK4/6 Inhibitor, on Myelosuppression in Patients 
with Previously Treated Extensive-Stage Small Cell Lung Cancer [Oral 
Presentation]. Presented at: American Society of Clinical Oncology 
(ASCO). June 2019; Chicago, US.
    \163\ Weiss J, Goldschmidt J, Andric Z et al. Myelopreservation 
and Reduced Use of Supportive Care with Trilaciclib in Patients with 
Small Cell Lung Cancer [Poster Presentation]. Presented at: American 
Society of Clinical Oncology (ASCO). May 2020.
    \164\ Ferrarotto R, Anderson I, Medgyasszay B, et al. 
Trilaciclib reduces the need for growth factors and red blood cell 
transfusions to manage chemotherapy-induced myelosuppression. [Oral 
Presentation]. Presented at: North America Conference on Lung 
Cancer, October 2020. https://naclc2020.iaslc.org/program-at-a-glance/.
---------------------------------------------------------------------------

    We invited public comments as to whether COSELATM met 
the substantial clinical improvement criterion.
    Comment: The applicant submitted comments stating that 
COSELATM satisfies the substantial clinical improvement 
criterion. Specifically, the applicant reiterated that 
COSELATM plus the standard of care demonstrated substantial 
clinical improvement over placebo plus the standard of care in 
decreasing the incidence of chemotherapy-induced myelosuppression in 
adult patients when administered prior to a platinum/etoposide-
containing regimen or topotecan-containing regimen for ES-SCLC. The 
applicant also stated that compared with placebo, COSELATM 
consistently reduced the incidence and duration of chemotherapy-induced 
neutropenia, as measured by both the duration and occurrence of severe 
neutropenia. The applicant also stated that COSELATM 
consistently reduced chemotherapy-induced anemia compared with placebo, 
reflected by the reduced occurrence of RBC transfusions on or after 
week 5, and a reduction in ESA use. Per the applicant, fewer patients 
on COSELATM were hospitalized due to chemotherapy induced 
myelosuppression or sepsis and that by reducing the incidence of 
chemotherapy-induced myelosuppression and reducing the need for 
associated supportive care and hospitalizations, COSELATM 
has the potential to improve the management and quality of life of 
patients receiving myelosuppressive chemotherapy for the treatment of 
ES-SCLC and is therefore a substantial clinical improvement over prior 
therapies.
    In response to CMS' concerns with respect to the limited published 
studies and small sample sizes of the studies, the applicant noted that 
the Daniel et. al. study publication is now available and is considered 
its pivotal study.\165\
---------------------------------------------------------------------------

    \165\ Daniel D, et al. Trilaciclib prior to chemotherapy and 
atezolizumab in patients with newly diagnosed extensive165stage 
small cell lung cancer: A multicentre, randomised, double-blind, 
placebo-controlled Phase II trial. International Journal of Cancer. 
2020: 148(10); 2557-70.
---------------------------------------------------------------------------

    The applicant further noted that within the pivotal study, the 
planned sample size of this study was 106 (~53 per group) and was 
calculated to support the evaluation of COSELATM prior to 
carboplatin, etoposide and atezolizumab (E/P/A) placebo prior to E/P/A 
on each of the primary endpoints, with at least 90 percent power at a 
two-sided significance level of 0.025 (Bonferroni split of overall 2-
sided [alpha] = .05 between the two primary endpoints).\166\
---------------------------------------------------------------------------

    \166\ Ibid.
---------------------------------------------------------------------------

    The applicant further stated that the pivotal study assumed 
treatment effects on duration of severe neutropenia (DSN) in C1 and 
occurrence of severe neutropenia (SN) were a between-group mean 
difference of 2 days (standard deviation 2.5), and an absolute 
reduction of 34 percent (assuming a placebo event rate of 45 percent), 
respectively. The applicant stated that within the pivotal study, the 
sample size was adjusted for the possibility that 5 percent of patients 
would not have any post-baseline absolute neutrophil count 
assessments.\167\
---------------------------------------------------------------------------

    \167\ Daniel D, et al. Trilaciclib prior to chemotherapy and 
atezolizumab in patients with newly diagnosed extensive167stage 
small cell lung cancer: A multicentre, randomised, double-blind, 
placebo-controlled Phase II trial. International Journal of Cancer. 
2020: 148(10); 2557-70.
---------------------------------------------------------------------------

    Next, in response to our concern regarding the low significance 
level cutoff of the Weiss et. al.\168\ study, the applicant clarified 
that they viewed this study as exploratory whereas the Daniel et 
al.\169\ study was the applicant's pivotal study. The applicant further 
noted that the pivotal study relied on the typical cutoff for alpha, 
meaning that it did not rely on significance levels as low as [alpha] = 
0.2 and thus asserted that there is less concern regarding false 
positive results or the ability to draw conclusions based on 
statistical methods.
---------------------------------------------------------------------------

    \168\ Weiss JM, Csoszi T, Maglakelidze M, et al. 
Myelopreservation with the CDK4/6 inhibitor trilaciclib in patients 
with small-cell lung cancer receiving first-line chemotherapy: a 
phase Ib/randomized phase II trial. Ann Oncol. 2019;30(10):1613-
1621.
    \169\ Daniel D, et al. Trilaciclib prior to chemotherapy and 
atezolizumab in patients with newly diagnosed extensive169stage 
small cell lung cancer: A multicentre, randomised, double-blind, 
placebo-controlled Phase II trial. International Journal of Cancer. 
2020: 148(10); 2557-70.
---------------------------------------------------------------------------

    In response to our concern related to assessing the mean duration 
of severe neutropenia in day increments as opposed to smaller time 
increments, the applicant clarified that in the pivotal study, zero 
days indicates that in the COSELATM arm, there was a mean 
duration of zero days of severe neutropenia in cycle 1. The mean 
duration of severe neutropenia in cycle 1 was zero days (standard 
deviation 1.0) for COSELATM vs 4 days (standard deviation 
4.7) for placebo (p < 0.0001). The applicant also stated that a total 
of 1 patient (1.9%) on the COSELATM arm experienced severe 
neutropenia in any cycle, whereas a total of 26 patients (49.1%) on the 
placebo arm experienced severe neutropenia in any cycle (p < 
0.0001).\170\
---------------------------------------------------------------------------

    \170\ Ibid.
---------------------------------------------------------------------------

    Response: We thank the applicant for its comment and clarifications 
regarding the substantial clinical improvement analysis. After 
consideration of the public comments received, we believe that 
COSELATM demonstrates a substantial clinical improvement 
over existing technologies in decreasing the incidence of chemotherapy-
induced myelosuppression in adult patients when administered prior to a 
platinum/etoposide-containing regimen or topotecan-containing regimen 
for ES-SCLC. We appreciate the applicant's clarification that days of 
severe neutropenia were evaluated by the mean number of days and not 
partial days and agree with the applicant that COSELATM 
demonstrated superior outcomes as compared to placebo given the 
significant reduction in severe neutropenia and therefore believe 
COSELATM offers a therapeutic option that can decrease the 
occurrence and duration of neutropenia. We also believe that COSELA's 
potential to improve quality of life by preventing the side effects of 
chemotherapy, as opposed to treating them once they occur, is 
clinically important. We note that we remain unable to confirm the 
assertion that COSELATM decreases hospitalization rates as 
we did not receive a source to support it.
    After consideration of the public comments we received and the 
information included in the applicant's new technology add-on payment 
application, we have determined that COSELATM meets all of 
the criteria for approval of the new technology add-on payment for the 
reasons stated previously. Therefore, we are approving

[[Page 45017]]

new technology add-on payments for COSELATM for FY 2022. 
Cases involving the use of COSELATM that are eligible for 
new technology add-on payments will be identified by ICD-10- PCS 
procedure codes XW03377 (Introduction of trilaciclib into peripheral 
vein, percutaneous approach, new technology group 7) or XW04377 
(Introduction of trilaciclib into central vein, percutaneous approach, 
new technology group 7).
    In submitting its public comment, the applicant identified the cost 
of COSELATM as $8,502 per hospitalization. Under Sec.  
412.88(a)(2), we limit new technology add-on payments to the lesser of 
65 percent of the average cost of the technology, or 65 percent of the 
costs in excess of the MS-DRG payment for the case. As a result, the 
maximum new technology add-on payment for a case involving the use of 
COSELATM is $5,526.30 for FY 2022.
e. Ellipsys[supreg] Vascular Access System
    Avenu Medical, Inc. submitted an application for new technology 
add-on payments for the Ellipsys[supreg] Vascular Access System 
(``Ellipsys'') for FY 2022. Ellipsys is a device that enables 
percutaneous creation of an arteriovenous fistula (AVF), which is used 
to access the bloodstream for hemodialysis for the treatment of end-
stage renal disease (ESRD). According to the applicant, to create the 
fistula, a physician inserts a crossing needle through the perforating 
vein and into the proximal radial artery in the forearm. A specialized 
catheter is then used to bring the artery and vein together. The two 
vessels are ``welded'' together with thermal resistance energy, 
creating an anastomosis. According to the applicant, the only means of 
creating an AVF was through open surgery before the approval of 
Ellipsys, and percutaneous AVF (pAVF) offers a number of advantages 
over surgical AVF (sAVF).
    With respect to the newness criterion, the applicant for Ellipsys 
received 510(k) clearance from the FDA on August 9, 2019, with an 
indication for the creation of a proximal radial artery to perforating 
vein anastomosis via a retrograde venous access approach in patients 
with a minimum vessel diameter of 2.0mm and less than 1.5mm of 
separation between the artery and vein at the fistula creation site who 
have chronic kidney disease requiring dialysis.\171\ The subject of 
this 510(k) clearance was an update to the Instructions for Use (IFU) 
to allow an additional procedural step for balloon dilation of the 
anastomosis junction at the radial artery and adjacent outflow vein of 
the AVF immediately after creation with the Ellipsys catheter. Per the 
applicant, the device was immediately available on the market. The 
applicant further stated that the device was originally approved under 
a De Novo clearance on June 22, 2018. Ellipsys also received two 
additional 510(k) clearances dated January 25, 2019 (minor change in 
the packaging of components) and October 5, 2018 (minor technological 
differences in the power control unit and minor enhancements to the 
catheter design) but the applicant states they are not regarded as 
material for this application. The FDA has classified Ellipsys as a 
Class II device under the generic name percutaneous catheter for 
creation of an arteriovenous fistula for hemodialysis access. The 
applicant stated that currently, two ICD-10-PCS codes identify 
procedures using Ellipsys: 031B3ZF (Bypass right radial artery to lower 
arm vein, percutaneous approach); and 031C3ZF (Bypass left radial 
artery to lower arm vein, percutaneous approach). However, since these 
codes also identify the WavelinQTM EndoAVF System 
(``WavelinQ''), another percutaneous fistula device, Avenu Medical 
submitted a code request for a unique ICD-10-PCS code to distinctly 
identify Ellipsys beginning in FY 2022 and was granted approval for the 
following procedure codes, effective October 1, 2021: X2KB317 (Bypass 
right radial artery using thermal resistance energy, percutaneous 
approach, new technology group 7) and X2KC317 (Bypass left radial 
artery using thermal resistance energy, percutaneous approach, new 
technology group 7). The applicant stated this technology was first 
assigned HCPCS code C9754 on January 1, 2019, which was then replaced 
by HCPCS code G2170 on July 1, 2020. Per the applicant, WavelinQ was 
assigned HCPCS codes (C9755 replaced by G2171) with the same timing, 
and the codes for the 2 pAVF technologies are differentiated by the use 
of thermal resistance energy for Ellipsys and the use of radiofrequency 
energy for WavelinQ.
---------------------------------------------------------------------------

    \171\ U.S. Food and Drug Administration (FDA). Center for 
Devices and Radiological Health. 510(k) Summary No. K1191114. 2019. 
Retrieved from: https://www.accessdata.fda.gov/cdrh_docs/pdf19/K191114.pdf.
---------------------------------------------------------------------------

    The applicant stated that hemodialysis access for the treatment of 
ESRD can be provided by catheter, graft, or AVF, of which AVF is 
generally preferred for patients whose vascular anatomy and condition 
permit it. Per the applicant, the only method for creating an AVF was 
through an open surgical approach until the introduction of Ellipsys 
and WavelinQ, two devices that use a percutaneous approach.
    As discussed earlier, if a technology meets all three of the 
substantial similarity criteria, it would be considered substantially 
similar to an existing technology and would not be considered ``new'' 
for purposes of new technology add-on payments.
    With regard to the first criterion, whether a product uses the same 
or similar mechanism of action to achieve a therapeutic outcome, the 
applicant asserted that Ellipsys uses a new mechanism of action 
compared to its initial clearance. Per the applicant, the current 
device included an additional step in the IFU, creating a different 
procedure profile and a different mechanism of action. The applicant 
states that the addition of this step, a balloon angioplasty performed 
within the same operative session as the creation of the pAVF, instead 
of days or weeks later, typically contributes to decreased time to 
maturation, improved initial flow, and helps avoid early thrombosis of 
the newly-created access, in addition to decreasing the number of 
secondary procedures required for maturation and maintenance. According 
to the applicant, the explicit inclusion of the step in the IFU, where 
it was not previously explicitly included, represents a new mechanism 
of action.
    With respect to the second criterion, whether a product is assigned 
to the same or different MS-DRG, the applicant generally stated that 
Ellipsys is assigned to the same MS-DRGs as existing technologies. 
According to information provided by the applicant, these MS-DRGs 
appear to be MS-DRGs 264, 356, 357, 358, 628, 629, 630, 673, 674, 675, 
907, 908, 909, 981, 982, and 983.
    With respect to the third criterion, whether the new use of the 
technology involves the treatment of the same or similar type of 
disease and the same or similar patient population, the applicant 
generally stated that Ellipsys will be used to treat the same or 
similar type of disease and the same or similar patient population as 
the current standard-of-care treatments.
    In summary, the applicant believed that Ellipsys is not 
substantially similar to other currently available therapies and/or 
technologies because it uses a new mechanism of action and that 
therefore, the technology meets the ``newness'' criterion. However, in 
the proposed rule, we stated that we believe that the mechanism of 
action for Ellipsys may be the same or similar to the original version 
of the Ellipsys

[[Page 45018]]

system, which received FDA approval on June 22, 2018. We stated that 
though the current IFU includes an additional procedure as part of the 
index procedure, it is not clear that this step of balloon angioplasty 
done concurrently changes the mechanism of action of the Ellipsys 
system. Per the FDA's 510(k) summary, compared to the predicate device, 
there were no changes to the device or the manner in which it creates a 
percutaneous anastomosis, and other than the additional procedural step 
of balloon dilation, all characteristics remain unchanged.\172\ In 
addition, we noted that clinicians were not precluded from performing 
this step before the change in the IFU, and in fact, balloon dilation 
was already performed during the index procedure in some cases.\173\ 
Though the applicant maintained that performing this additional step in 
all cases, as opposed to some, leads to superior clinical outcomes, we 
stated that it was unclear whether this has any bearing on newness for 
this technology or if it represents a change in the mechanism of action 
of this device. We noted that if the current device is substantially 
similar to the original version of Ellipsys, we believe the newness 
period for this technology would begin on June 22, 2018 with the De 
Novo approval date and, therefore, because the 3-year anniversary date 
of the technology's entry onto the U.S. market (June 22, 2021) would 
occur in FY 2021, the technology would no longer be considered new and 
would not be eligible for new technology add-on payments for FY 2022. 
We welcomed public comments on whether the change in the Ellipsys IFU 
represents a change to the device's mechanism of action.
---------------------------------------------------------------------------

    \172\ U.S. Food and Drug Administration (FDA). Center for 
Devices and Radiological Health. 510(k) Summary No. K1191114. 2019. 
Retrieved from: https://www.accessdata.fda.gov/cdrh_docs/pdf19/K191114.pdf.
    \173\ Hull JE, Jennings W, et al., ``The Pivotal Multicenter 
Trial of Ultrasound-Guided Percutaneous Arteriovenous Fistula 
Creation for Hemodialysis Access,'' Journal of Vascular and 
Interventional Radiology 2018; 29: 149-158.
---------------------------------------------------------------------------

    We also noted that differences in mechanism of action between 
Ellipsys and WavelinQ were not included. We noted that CMS stated in 
the FY 2021 IPPS/LTCH PPS final rule (85 FR 58702) that WavelinQ uses a 
unique mechanism of action that differed from that of other 
commercially available devices.
    We invited public comments on whether Ellipsys is substantially 
similar to other currently available therapies and/or technologies and 
whether this technology meets the newness criterion.
    Comment: We received a comment from a competitor stating that they 
believe that the mechanism of action for Ellipsys has not changed, and 
is the same as the original version approved on June 22, 2018. Per the 
commenter, it is still the use of thermal resistance energy that 
creates the fistula, as no changes were made to the predicate device 
for the 510(k) clearance, and though balloon angioplasty could 
potentially assist with maturation, it does not support the actual 
fistula creation. Therefore, the commenter believes the underlying 
mechanism of action is unchanged. The commenter further stated that 
since Ellipsys meets the other two criteria, as it is assigned to same 
MS-DRGs and treats the same disease and patient population as the 
earlier version of Ellipsys, and has a newness date of June 22, 2018 
due to substantial similarity with the earlier version, Ellipsys should 
not be considered new and would not be eligible for new technology add-
on payments for FY 2022.
    Response: We appreciate the information provided by the commenter 
and have taken this comment into consideration in our determination of 
the newness criterion, which is described later in this section.
    Comment: The applicant submitted a public comment in response to 
the concerns that CMS presented in the FY 2022 IPPS/LTCH PPS proposed 
rule regarding the newness criterion. In response to the concern that 
the mechanism of action of Ellipsys is unchanged from the De Novo 
version, the applicant stated that the additional step of immediate 
balloon angioplasty creates a different procedural profile, which makes 
a material difference not only in the procedure but in outcomes. The 
applicant described improvements in brachial artery flow volume in the 
post-market maturation study by Hull et al. described previously, which 
used the additional step of balloon angioplasty immediately after 
anastomosis creation, demonstrating a positive impact on patient care 
by avoiding complications that may limit use of the fistula. Per the 
applicant, the study demonstrated a decrease in early thrombosis, 
decreased time to two-needle cannulation, and decreased secondary 
procedures as compared to the pivotal trial where balloon angioplasty 
was done in only a small portion of cases. The applicant further stated 
that where the use of the prior version of Ellipsys might be considered 
to have one aspect of fistula creation, the current version might be 
considered to have two aspects: Fistula creation and balloon dilation. 
The applicant believes that CMS should focus on the actions involved in 
considering differences in the mechanism of action. Per the applicant, 
the hardware configuration of the device may be the same, but the 
clinical pattern of use has changed, and the action it accomplishes is 
different as well.
    In response to the note that the application did not address 
differences in mechanism of action between Ellipsys and 
WavelinQTM EndoAVF System, the applicant reiterated 
differences between the two pAVF systems described in the FY 2021 IPPS/
LTCH PPS final rule (85 FR 58702), where CMS recognized that WavelinQ 
uses a unique mechanism of action, and stated that CMS should carry 
that logic through and similarly determine that Ellipsys uses a new 
mechanism of action as well.
    Response: We appreciate the information provided by the applicant 
regarding the newness criterion. We agree that Ellipsys and WavelinQ 
have two unique mechanisms of action. In regard to the mechanism of 
action of the current version of Ellipsys as compared to the previous 
version, we continue to have concerns as stated in the proposed rule 
and as described by a commenter. As stated in the FY 2005 IPPS final 
rule (69 FR 49002), the intent of section 1886(d)(5)(K) of the Act and 
regulations under Sec.  412.87(b)(2) is to pay for new medical services 
and technologies for the first 2 to 3 years that a product comes on the 
market, during the period when the costs of the new technology are not 
yet fully reflected in the DRG weights. We note that even if a medical 
product receives a new FDA approval or clearance, it may not 
necessarily be considered ``new'' for purposes of new technology add-on 
payments if it is ``substantially similar'' to another medical product 
that was approved or cleared by FDA and has been on the market for more 
than 2 to 3 years. Although the applicant maintains that the change in 
the Ellipsys IFU represents a new mechanism of action, we believe that 
regardless of whether the procedural steps have changed, the manner in 
which the device functions is unchanged from the De Novo version and 
therefore does not represent a new mechanism of action. That is, both 
the current and De Novo versions of the Ellipsys System use thermal 
resistance energy to create a percutaneous fistula in the same location 
using the same catheter. As per the commenter and the FDA 510(k) 
clearance, no changes have been made to the device or the manner in 
which it creates a percutaneous anastomosis for the clearance of the 
current version. We agree with the commenter that though the additional

[[Page 45019]]

step of balloon angioplasty may assist with maturation, it does not 
change the method by which the fistula is created.
    Futhermore, we agree with the applicant and commenter that the two 
versions of the technology are intended to treat the same or similar 
disease in the same or similar patient population--patients with ESRD 
requiring hemodialysis access and eligible for a percutaneous fistula, 
and cases involving the technologies would be assigned to the same MS-
DRGs. Because the current version of Ellipsys meets all three of the 
substantial similarity criteria, we believe the current version of 
Ellipsys is substantially similar to the original version. Therefore, 
we consider the beginning of the newness period for the device to begin 
on June 22, 2018, which is the date that the original version of the 
Ellipsys system received FDA approval. Because the 3-year anniversary 
date of the entry of Ellipsys onto the U.S. market (June 22, 2021) will 
occur in FY 2021, the device does not meet the newness criterion and it 
is not eligible for new technology add-on payments for FY 2022. We note 
that we received public comments with regard to the cost and 
substantial clinical improvement criteria for this technology, but 
because we have determined that the technology does not meet the 
newness criterion and therefore is not eligible for approval for new 
technology add-on payments for FY 2022, we are not summarizing comments 
received or making a determination on those criteria in this final 
rule.
f. ENSPRYNGTM (satralizumab-mwge)
    Genentech, Inc. submitted an application for new technology add-on 
payments for the ENSPRYNGTM (satralizumab-mwge) injection 
for FY 2022. According to the applicant, ENSPRYNG\TM\ is indicated by 
the FDA for the treatment of neuromyelitis optica spectrum disorder 
(NMOSD) in adult patients who are anti-aquaporin-4 (AQP4) antibody 
positive. ENSPRYNG\TM\ is the first subcutaneous, first self-
administered, and third FDA-approved drug for the treatment of this 
severe chronic autoimmune disease of the central nervous system.\174\ 
The applicant stated, due to the severity of relapses, relapse 
prevention is a key disease management priority. Patients who relapse 
are often admitted to the hospital for acute treatment. According to 
the applicant, with every relapse, patients are at risk of becoming 
blind or paralyzed, and thus it is critical to minimize the risk of 
future relapses by initiating maintenance treatment with a therapy such 
as ENSPRYNG\TM\ in a timely manner while the patient is still admitted. 
Therefore, according to the applicant, ENSPRYNG\TM\ should be approved 
for new technology add-on payments in order to maximize the likelihood 
that this especially sick patient population can start the treatment 
they need while in the inpatient setting.
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    \174\ ENSPRYNG (satralizumab) [prescribing information]. South 
San Francisco, CA: Genentech USA, Inc.; 2020. SOLIRIS (eculizumab) 
[prescribing information]. Boston, MA: Alexion Pharmaceuticals, 
Inc.; 2019. UPLIZNA (inebilizumab) [prescribing information]. 
Gaithersburg, MD: Viela Bio, Inc.; 2020.
---------------------------------------------------------------------------

    According to the applicant, NMOSD is a rare, inflammatory, 
potentially life-threatening autoimmune central nervous system (CNS) 
disorder characterized primarily by severe, unpredictable relapses of 
optic neuritis and/or acute longitudinally extensive transverse 
myelitis (LETM).\175\ The applicant asserted that NMOSD has an 
estimated prevalence of 0.1-10 per 100,000 individuals, affecting 
nearly 15,000 individuals in the United States.\176\ NMOSD occurs in 
children \177\ and adults \178\ of all races \179\ and 
disproportionately affects African and Asian females aged 30 to 40 
years.\180\ According to the applicant, the (bilateral) optic neuritis 
and/or LETM that are characteristic of NMOSD result from inflammation 
of the optic nerve, spinal cord,\181\ and brainstem,\182\ but other 
regions of the CNS may be affected as well. The vast majority of 
patients (80%-90%) experience repeated relapses, and disability 
accumulates with each relapse.\183\ Around 60% of patients relapse 
within one year of diagnosis, and 90% relapse within 3 years.\184\ 
Compared with patients who experience an isolated attack, patients with 
relapsing disease have greater disease-related clinical burden, and 
upward of 83% of patients do not fully recover after subsequent 
relapses.\185\
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    \175\ Jarius S, Ruprecht K, Wildemann B, et al. Contrasting 
disease patterns in seropositive and seronegative neuromyelitis 
optica: A multicentre study of 175 patients. J. Neuroinflammation 
2012;9(1) doi:10.1186/1742-2094-9-14.
    \176\ Flanagan EP, Cabre P, Weinshenker BG, et al. Epidemiology 
of Aquaporin-4 Autoimmunity And Neuromyelitis Optica Spectrum. Ann 
Neurol. 2016;79(5):775-783. doi:10.1002/ana.24617.
    \177\ Siegel Rare Neuroimmune Association. Neuromyelitis Optica 
Spectrum Disorder (NMOSD). https://wearesrna.org/living-with-myelitis/disease-information/neuromyelitis-optica-spectrum-disorder/diagnosis/#nmosd. Accessed August 19, 2020.
    \178\ Etemadifar M, Nasr Z, Khalili B, Taherioun M, Vosoughi R. 
Epidemiology of Neuromyelitis Optica in the World: A Systematic 
Review and Meta-analysis. Mult Scler Int. 2015;2015:174720. 
doi:10.1155/2015/174720.
    \179\ Simon KC, Schmidt H, Loud S, Ascherio A. Risk Factors For 
Multiple Sclerosis, Neuromyelitis Optica And Transverse Myelitis. 
Mult Scler. 2015;21(6):703-709. doi:10.1177/1352458514551780.
    \180\ Wingerchuk DM, Lennon VA, Lucchinetti CF, et al. The 
spectrum of neuromyelitis optica. Lancet Neurol. 2007;6(9)805-815. 
doi:10.1016/s1474-4422(07)70216-8.
    \181\ Siegel Rare Neuroimmune Association. Neuromyelitis Optica 
Spectrum Disorder (NMOSD). https://wearesrna.org/living-with-myelitis/disease-information/neuromyelitis-optica-spectrum-disorder/diagnosis/#nmosd. Accessed August 19, 2020.
    \182\ National Organization for Rare Disorders (NORD[supreg]). 
Neuromyelitis Optica Spectrum Disorder. https://rarediseases.org/rare-diseases/neuromyelitis-optica/. Accessed August 19, 2020.
    \183\ Wingerchuk DM. Diagnosis and Treatment of Neuromyelitis 
Optica. Neurologist 2007;13(1)2-11. doi:10.1097/
01.nrl.0000250927.21903.f8.
    \184\ Wingerchuk DM, Lennon VA, Lucchinetti CF, et al. The 
spectrum of neuromyelitis optica. Lancet Neurol. 2007;6(9)805-815. 
doi:10.1016/s1474-4422(07)70216-8.
    \185\ Jarius S, Ruprecht K, Wildemann B, et al. Contrasting 
disease patterns in seropositive and seronegative neuromyelitis 
optica: A multicentre study of 175 patients. J. Neuroinflammation 
2012;9(1) doi:10.1186/1742-2094-9-14.
---------------------------------------------------------------------------

    According to the applicant, the negative impact of NMOSD on patient 
quality of life (QoL) is predominantly a result of physical disability, 
pain, vision impairment, and bowel and bladder dysfunction.\186\ 
Disease-induced disability and symptoms have a considerable impact on 
patients' ability to work and thrive in social activities and personal 
relationships.\187\ The applicant added that the loss of motor and 
sensory function leads to approximately 50% of patients requiring a 
wheelchair \188\ and 62% of patients becoming functionally blind \189\ 
within 5 years of diagnosis.\190\ Therefore, according to the 
applicant, it is critical that treatments that consistently and 
effectively reduce the risk of relapse are initiated rapidly in 
patients diagnosed with NMOSD.
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    \186\ Beekman J, Keisler A, Pedraza O, et al. Neuromyelitis 
optica spectrum disorder. Neurol.--Neuroimmunol. Neuroinflammation 
2019;6(4)e580. doi:10.1212/nxi.0000000000000580.
    \187\ Ibid.
    \188\ Kessler RA, Mealy MA, Levy M. Treatment of Neuromyelitis 
Optica Spectrum Disorder: Acute, Preventive, and Symptomatic. Curr. 
Treat. Options Neurol. 2015;18(1) doi:10.1007/s11940-015-0387-9.
    \189\ Wingerchuk DM, Hogancamp WF, O'Brien PC, et al. The 
clinical course of neuromyelitis optica (Devic's syndrome). 
Neurology 2012;53(5)1107-1107. doi:10.1212/wnl.53.5.1107.
    \190\ Wingerchuk DM, Weinshenker BG. Neuromyelitis optica: 
Clinical predictors of a relapsing course and survival. Neurology 
2012;60(5)848-853. doi:10.1212/01.wnl.0000049912.02954.2c.
---------------------------------------------------------------------------

    With respect to the newness criterion, ENSPRYNG\TM\ received FDA 
BLA approval on August 14, 2020. The applicant added that ENSPRYNG\TM\ 
was

[[Page 45020]]

granted Fast Track designation \191\ and Breakthrough Therapy 
designation \192\ by the FDA. The applicant stated that ENSPRYNG\TM\ 
was not commercially available until August 24, 2020 because the 
applicant had to wait for final approval for printing and labeling as 
well as customs and importation. The recommended loading dosage of 
ENSPRYNG\TM\ for the first three administrations is 120 mg by 
subcutaneous injection at Weeks 0, 2, and 4, followed by a maintenance 
dosage of 120 mg every four weeks. The applicant submitted a request 
for an ICD-10-PCS code to uniquely identify the administration of 
ENSPRYNG\TM\ beginning FY 2022 and was granted approval for the 
following code effective October 1, 2021: XW01397 (Introduction of 
satralizumab-mwge into subcutaneous tissue, percutaneous approach, new 
technology Group 7).
---------------------------------------------------------------------------

    \191\ US Department of Health and Human Services. FDA Approves 
Treatment for Rare Disease Affecting Optic Nerves, Spinal Cord. 
https://www.fda.gov/news-events/press-announcements/fda-approves-treatment-rare-disease-affecting-optic-nerves-spinal-cord. Accessed 
September 10, 2020.
    \192\ Genentech, USA Inc. FDA Approves Genentech's Enspryng for 
Neuromyelitis Optica Spectrum Disorder. https://www.gene.com/media/press-releases/14873/2020-08-14/fda-approves-genentechs-enspryng-for-neu. Accessed September 10, 2020.
---------------------------------------------------------------------------

    As discussed earlier, if a technology meets all three of the 
substantial similarity criteria, it would be considered substantially 
similar to an existing technology and would not be considered ``new'' 
for purposes of new technology add-on payments. The applicant stated 
that there are limited treatment guidelines available for NMOSD with 
the most recent US guidelines published in 2012. These US NMOSD 
treatment guidelines exclusively recommend off-label drugs: 
Azathioprine, with or without prednisone; mycophenolate mofetil, with 
or without prednisone; rituximab; or prednisone alone.\193\ The 
applicant stated that there are presently two other FDA-approved 
therapies for patients with AQP4-IgG positive NMOSD: SOLIRIS[supreg] 
(eculizumab),\194\ which was approved in 2019, and UPLIZNA[supreg] 
(inebilizumab-cdon), which was approved in 2020.\195\
---------------------------------------------------------------------------

    \193\ Kimbrough DJ, Fujihara K, Jacob A, et al. Treatment of 
Neuromyelitis Optica: Review And Recommendations. Mult Scler Relat 
Disord. 2012;1(4):180-187. doi:10.1016/j.msard.2012.06.002.
    \194\ SOLIRIS (eculizumab) [prescribing information]. Boston, 
MA: Alexion Pharmaceuticals, Inc.; 2019.
    \195\ UPLIZNA (inebilizumab) [prescribing information]. 
Gaithersburg, MD: Viela Bio, Inc.; 2020.
---------------------------------------------------------------------------

    With regard to the first criterion, whether a product uses the same 
or similar mechanism of action to achieve a therapeutic outcome, the 
application stated that ENSPRYNG\TM\ is an interleukin-6 (IL-6) 
receptor antagonist indicated for the treatment of NMOSD in adult 
patients who are AQP4-IgG positive.\196\ According to the applicant, 
ENSPRYNG\TM\ targets soluble and membrane-bound IL-6 receptors to 
inhibit IL-6 signaling and subsequently disrupt downstream inflammatory 
effects that contribute to the pathophysiology of NMOSD; \197\ 
ENSPRYNG\TM\ dissociates from the IL-6 receptor at an acidic pH within 
endosomes and is recycled to circulation, prolonging the plasma half-
life of the drug.\198\
---------------------------------------------------------------------------

    \196\ ENSPRYNG (satralizumab) [prescribing information]. South 
San Francisco, CA: Genentech USA, Inc.; 2020.
    \197\ Yamamura T, Kleiter I, Fujihara K, et al. Trial of 
Satralizumab in Neuromyelitis Optica Spectrum Disorder. N. Engl. J. 
Med. 2019;381(22)2114-2124. doi:10.1056/nejmoa1901747.
    \198\ Igawa T, Ishii S, Tachibana T, et al. Antibody Recycling 
By Engineered Ph-Dependent Antigen Binding Improves The Duration of 
Antigen Neutralization. Nat Biotechnol. 2010;28(11):1203-1207. 
doi:10.1038/nbt.1691. Heo Y. Satralizumab: First Approval. Drugs 
2020;80(14)1477-1482. doi:10.1007/s40265-020-01380-2.
---------------------------------------------------------------------------

    The applicant next identified other drugs used to treat NMOSD and 
their corresponding mechanisms of action. According to the applicant, 
these current treatments include: SOLIRIS[supreg], for which a precise 
mechanism of action is unknown but is presumed to involve inhibition of 
AQP4-IgG-induced terminal complement C5b-9 deposition; \199\ 
UPLIZNA[supreg], for which a precise mechanism of action is unknown but 
is presumed to involve binding to CD19, a surface antigen present on 
pre-B and mature B cells; \200\ azathioprine, for which a precise 
mechanism of action is unknown; \201\ Rituxan, which targets CD20 
antigen on B cells and leads to profound B cell depletion, principally 
over an antibody-dependent cell cytotoxicity mechanism; \202\ 
mycophenolate mofetil, which is an immunosuppressive and an inhibitor 
of inosine monophosphate dehydrogenase and therefore of the guanosine 
nucleotide synthesis pathway upon which T and B cells depend; \203\ and 
prednisone, which is a synthetic adrenocortical steroid drug with 
predominately corticosteroid properties.\204\ The applicant concluded 
that none of these current drugs are characterized by their binding and 
blocking of soluble and membrane-bound IL-6 receptors to inhibit IL-6 
signaling. Therefore, the applicant believes ENSPRYNG\TM\ has a unique 
and distinct mechanism of action.
---------------------------------------------------------------------------

    \199\ SOLIRIS (eculizumab) [prescribing information]. Boston, 
MA: Alexion Pharmaceuticals, Inc.; 2019.
    \200\ UPLIZNA (inebilizumab) [prescribing information]. 
Gaithersburg, MD: Viela Bio, Inc.; 2020.
    \201\ IMURAN (azathioprine) [prescribing information]. Roswell, 
GA: Sebela Pharmaceuticals Inc.; 2018.
    \202\ RITUXAN (rituximab) [prescribing information]. South San 
Francisco, CA: Genentech, Inc.; 2019.
    \203\ Allison AC, Eugui EM. Mycophenolate Mofetil And Its 
Mechanisms of Action. Immunopharmacology 2000;47(2-3)85-118. 
doi:10.1016/s0162-3109(00)00188-0.
    \204\ RAYOS (prednisone) [prescribing information]. Lake Forest, 
IL: Horizon Therapeutics USA, Inc.; 2019.
---------------------------------------------------------------------------

    With respect to the second criterion, whether a product is assigned 
to the same or different MS-DRG, the applicant acknowledged that 
ENSPRYNG\TM\ may be assigned to the same MS-DRG when compared to 
existing technology. Per the applicant, cases representing patients who 
may be eligible for treatment with ENSPRYNG\TM\ map to MS-DRGs 058, 
059, and 060.
    With respect to the third criterion, whether the new use of the 
technology involves the treatment of the same or similar type of 
disease and the same or similar patient population, the applicant 
stated that the use of ENSPRYNG\TM\ may not involve the treatment of 
the same or similar patient population when compared with an existing 
technology because: (1) Current technologies such as SOLIRIS[supreg] 
may be contraindicated in patients with unresolved serious Neisseria 
meningitidis infections; and (2) SOLIRIS[supreg] and UPLIZNA[supreg] 
are administered as IV infusions which not all patients may be willing 
to receive.
    In summary, the applicant asserted ENSPRYNG\TM\ meets the newness 
criterion because it is the only treatment for NMOSD that works 
specifically by suppressing IL-6 signaling, and because it may not 
involve the treatment of the same or similar patient population as 
existing technology.
    In the proposed rule (86 FR 25253), we noted that the applicant 
stated that the use of ENSPRYNG\TM\ may not involve treatment of the 
same or similar patient population when compared to SOLIRIS[supreg] 
with regard to the treatment of patients with unresolved serious 
Neisseria meningitidis infection and with regard to the treatment of 
patients unwilling to receive an IV infusion. However, we questioned if 
UPLIZNA[supreg] may also be a treatment option for patients with 
meningococcal disease. We further questioned whether patients who are 
unwilling to receive an IV infusion would constitute a new patient

[[Page 45021]]

population for NMOSD. We invited public comment on whether ENSPRYNG\TM\ 
involves the treatment of the same or similar patient population when 
compared to existing technologies.
    We invited public comments on whether ENSPRYNG\TM\ is substantially 
similar to other technologies and whether ENSPRYNG\TM\ meets the 
newness criterion.
    Comment: We received a public comment regarding the newness 
criterion. The commenter stated that ENSPRYNG\TM\ is not substantially 
similar to UPLIZNA[supreg]. The commenter explained that 
UPLIZNA[supreg] and ENSPRYNG\TM\ have different mechanisms of action. 
The commenter stated that while ENSPRYNG\TM\'s mechanism of action 
involves the binding and blocking of soluble and membrane-bound IL-6 
receptors to inhibit IL-6 signaling, UPLIZNA[supreg]'s mechanism of 
action involves binding to CD19, a cell surface antigen present on pre-
B and mature B lymphocytes, and results in antibody-dependent, cell-
mediated B cell depletion. The commenter also explained that 
UPLIZNA[supreg] and ENSPRYNG\TM\ are not substantially similar because 
UPLIZNA[supreg] is the only NMOSD treatment that is administered twice 
per year, after two initial start-up doses. The commenter stated that 
the maintenance dose schedule of twice per year, following the initial 
start-up doses, presents an important benefit for NMOSD patients 
wishing to receive treatment once every six months and for patients who 
do not wish to or are unable to self-administer injections. Finally, 
the commenter responded to CMS' request for information on whether 
UPLIZNA[supreg] is a treatment option for NMOSD patients with 
meningococcal disease. The commenter stated that UPLIZNA[supreg] is not 
contraindicated in patients with unresolved serious Neisseria 
meningitidis infections and clarified that this was not a serious 
adverse event reported during the Phase 3 clinical trials. The 
commenter concluded that based on the different mechanisms of action, 
routes of administration, and recommended dosing schedules for 
maintenance treatment, UPLIZNA[supreg] and ENSPRYNG\TM\ are not 
substantially similar.
    The applicant also submitted a comment addressing concerns raised 
by CMS in the proposed rule regarding whether ENSPRYNG\TM\ meets the 
newness criterion. In response to our concerns that UPLIZNA[supreg] may 
also be a treatment option for patients with meningococcal disease, the 
applicant stated that UPLIZNA[supreg] may or may not be an option for 
NMOSD patients with meningococcal disease. However, the applicant 
pointed out that although UPLIZNA[supreg] is not specifically 
contraindicated in patients with meningococcal disease, its prescribing 
information warns prescribers about PML, which has been observed in 
patients treated with other B-cell-depleting antibodies and other 
therapies that affect immune competence, like UPLIZNA[supreg]. In 
response to our concerns regarding whether patients who are unwilling 
to receive an IV infusion constitute a new patient population for 
NMOSD, the applicant stated that ENSPRYNG\TM\ is the only FDA-approved 
option for NMOSD patients that are unwilling or unable to receive 
infusions, perhaps due to difficulties associated with their venous 
access.
    Response: We appreciate the commenters' input. Based on the 
comments received and the information submitted as part of the FY 2022 
new technology add-on payment application for ENSPRYNG\TM\, as 
discussed in the proposed rule (86 FR 25070 through 25790) and in this 
final rule, we concur with the comments received that ENSPRYNG\TM\ has 
a unique mechanism of action when compared to existing technologies 
because the other technologies are not characterized by their binding 
and blocking of soluble and membrane-bound IL-6 receptors to inhibit 
IL-6 signaling, as ENSPRYNGTM's mechanism of action does 
and, therefore, we believe that ENSPRYNGTM is not 
substantially similar to existing treatment options. However, we note 
that we disagree with the applicant that ENSPRYNGTM does not 
involve the treatment of the same or similar patient population as 
existing technologies for two reasons. As the first commenter stated, 
UPLIZNA[supreg], another treatment for NMOSD, is not contraindicated in 
patients with unresolved serious Neisseria meningitidis infections, and 
therefore, may also be a treatment option for patients with 
meningococcal disease. In addition, the applicant noted that existing 
technologies are administered via IV infusion, which not all patients 
may be willing or able to receive. We do not agree that patients who 
are unwilling to receive an IV infusion constitute a new patient 
population for NMOSD. Additionally, although IV infusion may be 
difficult to administer for some patients, we are not aware of cases 
where it is impossible.
    Therefore, we believe ENSPRYNG\TM\ is not substantially similar to 
existing treatment options and meets the newness criterion. We consider 
the beginning of the newness period to commence when ENSPRYNG\TM\ 
became commercially available, on August 24, 2020.
    With regard to the cost criterion, the applicant provided two cost 
analyses, with the first being an update of the analysis used in FY 
2021 by the applicant for SOLIRIS[supreg], which is also indicated for 
NMOSD, and the second which is specific to ENSPRYNG[supreg].
    Under the first analysis, the applicant searched the FY 2019 MedPAR 
database for cases reporting ICD-10-CM code G36.0 in the primary and/or 
admitting position, which resulted in 583 cases. The applicant imputed 
one case where an MS-DRG had a case volume lower than 11, resulting in 
556 cases mapping to 30 MS-DRGs. The applicant stated that it 
restricted the analysis to MS-DRGs 058, 059, and 060, which accounted 
for 92.1% of all cases identified. The applicant also excluded cases 
that were not included in the FY 2021 Proposed Rule Impact File from 
this analysis, resulting in a final case count of 466 cases mapping to 
three MS-DRGs. Using a CCR of 0.343 (national other services average 
CCR), the applicant then removed all charges in the drug cost center, 
all charges in the blood cost center, and an additional $12,000 of cost 
for plasma exchange procedural costs for cases with non-zero charges in 
the blood cost center, for charges for related and prior technologies. 
The applicant applied an inflation factor of 13.1%, which per the 
applicant is the outlier charge inflation factor used in the FY 2021 
IPPS/LTCH PPS final rule, to update the standardized charges from FY 
2019 to FY 2021. We note that the applicant appears to have used the FY 
2021 IPPS/LTCH PPS proposed rule inflation factor rather than the 2-
year inflation factor from the FY 2021 IPPS/LTCH PPS final rule of 13.2 
percent (85 FR 59038), which would have increased the inflated charges. 
Finally, the applicant added charges for the technology by multiplying 
the cost of ENSPRYNG\TM\, based on an average of 1.22 doses per 
patient, by the inverse of the national average drug CCR of 0.187 from 
the FY 2021 IPPS/LTCH PPS final rule (85 FR 58601). The applicant 
calculated a final inflated average case-weighted standardized charge 
per case of $150,154, which exceeds the case-weighted threshold of 
$47,813.
    For the second analysis, the applicant used the same sample of 
cases (466) from the first analysis, as identified in the FY 2019 
MedPAR database with the ICD-10-CM code G36.0 and with the same sample 
restrictions. In this analysis, the applicant did not remove

[[Page 45022]]

charges for related or prior technologies because, per the applicant, 
ENSPRYNG\TM\ is anticipated to neither replace plasma exchange nor be 
used as a monotherapy in all patients. The applicant standardized and 
inflated the charges, as well as added charges for ENSPRYNG\TM\ using 
the same methodology as the first analysis, described previously. The 
applicant calculated a final inflated average case-weighted 
standardized charge per case of $175,021, which exceeded the case-
weighted threshold of $47,813. The applicant asserted that ENSPRYNG\TM\ 
meets the cost criterion based on these analyses.
    Based on the information provided by the applicant, we stated that 
it was uncertain to us why the national other services average CCR was 
used to inflate costs to charges in the first analysis when the 
applicant indicated that it removed charges from the drugs cost center 
and blood cost center. We sought public comment on whether this or 
another CCR, such as a CCR for drugs or blood and blood products, would 
be more appropriate. Furthermore, in the event that a MS-DRG has fewer 
than 11 cases, we stated that the applicant should impute a minimum 
case number of 11.
    We invited public comments on whether ENSPRYNG\TM\ meets the cost 
criterion, including whether the use of another CCR would substantially 
alter the results of the applicant's analysis.
    Comment: The applicant submitted a comment addressing the concerns 
raised by CMS in the proposed rule regarding whether ENSPRYNG\TM\ meets 
the cost criterion. The applicant reiterated that CMS was provided with 
two cost analyses in its original application: An updated version of 
the analysis used in FY 2021 by the new technology add-on payment 
applicant for SOLIRIS[supreg] and a second analysis that was the 
applicant's original work and aligned more closely with how 
ENSPRYNG\TM\ would be used. The applicant first noted the following 
updates to both analyses per CMS' feedback: (1) Imputing a minimum case 
number of 11 and (2) using the 2-year inflation factor from the FY 2021 
IPPS/LTCH PPS final rule of 13.2 percent. The applicant then addressed 
CMS' concern regarding the appropriateness of the CCR used to inflate 
cost to charges in these analyses. With respect to the first analysis, 
the applicant indicated that CMS accepted the use of the ``other 
services'' national average cost-to-charge ratio for SOLIRIS[supreg] 
and that its use in the first scenario is therefore appropriate. The 
applicant noted that while a different CCR (such as the CCR for drugs 
or blood and blood products, as suggested by CMS) might be more 
appropriate, it provided CMS with the first analysis for contextual 
purposes only and did not want to comment on the validity of the cost 
analysis for SOLIRIS[supreg]. With respect to the second analysis, the 
applicant maintained that since ENSPRYNGTM is not 
anticipated to replace plasma exchange or be used as a monotherapy in 
all patients, there are no charges to remove. Per the applicant, the 
issue of which CCR is more appropriate to use when removing charges is 
therefore moot, and did not apply to the second analysis.
    After following the methodology described previously with the 
exception of the imputed case value of 11 and updated inflation factor, 
the applicant presented the results of the revised cost analyses by MS-
DRG.
[GRAPHIC] [TIFF OMITTED] TR13AU21.173


[[Page 45023]]


[GRAPHIC] [TIFF OMITTED] TR13AU21.174

    The applicant stated that, under both revised analyses, the average 
case-weighted standardized charge per case exceeded the revised case-
weighted threshold and therefore ENSPRYNG\TM\ meets the cost criterion.
    Response: We thank the applicant for submitting its comments 
addressing the concerns we raised in the FY 2022 IPPS/LTCH PPS proposed 
rule (86 FR 25070 through 25104), including with respect to the use of 
the ``other services'' CCR, and its submission of a revised cost 
analysis. Based on the information provided by the applicant, because 
the final inflated average case-weighted standardized charge per case 
exceeded the case-weighted threshold of amount in both scenarios, we 
agree with the applicant that ENSPRYNG\TM\ meets the cost criterion.
    With regard to the substantial clinical improvement criterion, the 
applicant asserted that ENSPRYNG\TM\ represents a substantial clinical 
improvement in the following ways: (1) It significantly improves 
clinical outcomes relative to services or technologies previously 
available for the treatment of NMOSD in adult patients who are AQP4-IgG 
positive; (2) these improvements are not accompanied by serious safety 
concerns; (3) ENSPRYNG\TM\ is the only FDA-approved treatment for NMOSD 
that is subcutaneously administered; \205\ and (4) the totality of 
circumstances demonstrates ENSPRYNG\TM\, relative to technologies 
previously available, substantially improves the treatment of Medicare 
beneficiaries. The applicant submitted two recent studies to support 
their claims of substantial clinical improvement over existing 
technologies.
---------------------------------------------------------------------------

    \205\ ENSPRYNG (satralizumab) [prescribing information]. South 
San Francisco, CA: Genentech USA, Inc.; 2020.
---------------------------------------------------------------------------

    The SAkuraStar (NCT02073279) \206\ study was a Phase 3, double-
blind, placebo-controlled, parallel-group trial at 44 investigational 
sites in 13 countries to assess the safety and efficacy of ENSPRYNG\TM\ 
monotherapy in patients with NMOSD. 95 (57%) of 168 screened 
participants aged 18-74 years with AQP4-IgG positive or negative NMOSD 
met the inclusion criteria and were randomly assigned (2:1) to 
treatment with ENSPRYNG\TM\ 120mg (n = 63) or visually matched placebo 
(n = 32). Inclusion criteria included participants who had experienced 
at least one documented NMOSD attack or relapse in the previous 12 
months and had a score of 6.5 or less on the Expanded Disability Status 
Scale, while exclusion criteria included clinical relapse 30 days or 
fewer before baseline. The primary endpoint was time to the first 
protocol-defined relapse, based on the intention-to-treat (ITT) 
population (AQP4-IgG positive and negative) (n=95), and analyzed with 
stratification for two randomization factors (previous therapy for 
prevention of attacks and nature of the most recent attack). Treatment 
in both arms was given subcutaneously at weeks 0, 2, 4, and every 4 
weeks thereafter. The double-blind phase was due to last until 44 
protocol-defined relapses occurred or 1.5 years after random assignment 
of the last patient enrolled, whichever occurred first. Participants 
could enter an open-label phase after the occurrence of a protocol-
defined relapse or at the end of the double-blind phase. Protocol-
defined relapses occurred in 19 (30%) patients receiving satralizumab 
and 16 (50%) receiving placebo (hazard ratio 0.45, 95% CI 0.23-0.89; p 
= 0.018). 473.9 adverse events per 100 patient-years occurred in the 
satralizumab group and 495.2 per 100 patient-years in the placebo 
group. The authors noted that the incidence of serious adverse events 
and adverse events leading to withdrawal was similar between groups.
---------------------------------------------------------------------------

    \206\ Traboulsee A, Greenberg BM, Bennett JL, et al. Safety And 
Efficacy of Satralizumab Monotherapy In Neuromyelitis Optica 
Spectrum Disorder: A Randomised, Double-Blind, Multicentre, Placebo-
Controlled Phase 3 Trial. Lancet Neurol. 2020;19(5):402-412. 
doi:10.1016/S1474-4422(20)30078-8.
---------------------------------------------------------------------------

    According to the applicant, this study demonstrated that the time 
to the first relapse was significantly longer in ENSPRYNG\TM\ treated 
patients compared with patients who received a placebo (risk reduction, 
55%; hazard ratio, 0.45 (95% CI 0.23, 0.89); p = 0.0184). In the AQP4-
IgG positive population, there was a 74% risk reduction and a hazard 
ratio of 0.26 (95% CI 0.11, 0.63; p = 0.0014). The results in the 
subgroup of AQP4-IgG negative patients were not statistically 
significant.207 208 The annualized relapse

[[Page 45024]]

rate for AQP4-IgG positive patients was 0.1 (95% CI, 0.05-0.2) in the 
ENSPRYNG\TM\ group and 0.5 (95% CI, 0.3-0.9) in the placebo group.\209\ 
The proportion of relapse-free AQP4-IgG positive patients at week 96 
was 77% in the ENSPRYNG\TM\ group and 41% in the placebo group.\210\ 
According to the applicant, the study concluded that ENSPRYNG\TM\ 
monotherapy reduced the rate of NMOSD relapse compared with placebo in 
the overall trial population and had a favorable safety profile.
---------------------------------------------------------------------------

    \207\ ENSPRYNG (satralizumab) [prescribing information]. South 
San Francisco, CA: Genentech USA, Inc.; 2020.
    Traboulsee A, et al. Efficacy of satralizumab monotherapy in 
prespecified subgroups of SAkuraStar, a phase 3 study in patients 
with neuromyelitis optica spectrum disorder. Oral Presentation at: 
Annual Americas Committee for Treatment and Research in Multiple 
Sclerosis (ACTRIMS) Forum; West Palm Beach, FL, USA; February 27-29, 
2020.
    \208\ ENSPRYNG (satralizumab) [prescribing information]. South 
San Francisco, CA: Genentech USA, Inc.; 2020.
    Traboulsee A, et al. Efficacy of satralizumab monotherapy in 
prespecified subgroups of SAkuraStar, a phase 3 study in patients 
with neuromyelitis optica spectrum disorder. Oral Presentation at: 
Annual Americas Committee for Treatment and Research in Multiple 
Sclerosis (ACTRIMS) Forum; West Palm Beach, FL, USA; February 27-29, 
2020.
    \209\ Traboulsee A, et al. Efficacy of satralizumab monotherapy 
in prespecified subgroups of SAkuraStar, a phase 3 study in patients 
with neuromyelitis optica spectrum disorder. Oral Presentation at: 
Annual Americas Committee for Treatment and Research in Multiple 
Sclerosis (ACTRIMS) Forum; West Palm Beach, FL, USA; February 27-29, 
2020.
    \210\ Traboulsee A, Greenberg BM, Bennett JL, et al. Safety And 
Efficacy of Satralizumab Monotherapy In Neuromyelitis Optica 
Spectrum Disorder: A Randomised, Double-Blind, Multicentre, Placebo-
Controlled Phase 3 Trial. Lancet Neurol. 2020;19(5):402-412. 
doi:10.1016/S1474-4422(20)30078-8.
---------------------------------------------------------------------------

    In the second Phase 3, randomized, double-blind, placebo-controlled 
study submitted by the applicant, the SAkuraSky (NCT02028884) \211\ 
trial, 83 patients with NMOSD who were seropositive or seronegative for 
AQP4-IgG were randomly assigned (1:1) to receive either 120 mg of 
satralizumab (n=41) or placebo (n=42) administered subcutaneously at 
weeks 0, 2, and 4 and every 4 weeks thereafter, in addition to stable 
IST. The primary end point was the first protocol-defined relapse in a 
time-to-event analysis. Key secondary end points were the change from 
baseline to week 24 in the visual-analogue scale (VAS) pain score 
(range, 0 to 100, with higher scores indicating more pain) and the 
Functional Assessment of Chronic Illness Therapy-Fatigue (FACIT-F) 
score (range, 0 to 52, with lower scores indicating more fatigue). 
Safety was also assessed.
---------------------------------------------------------------------------

    \211\ U.S. Department of Health and Human Services. Active Study 
[verbar] Neuromyelitis Optica Spectrum Disorder. https://clinicaltrials.gov/ct2/results?cond=&term=NCT02028884&cntry=&state=&city=&dist=. Accessed 
August 14, 2020.
---------------------------------------------------------------------------

    The results of the SAkuraSky trial demonstrated that the median 
treatment duration with satralizumab in the double-blind period was 
107.4 weeks. Relapse occurred in 8 patients (20%) receiving 
satralizumab and in 18 (43%) receiving placebo (hazard ratio, 0.38; 95% 
confidence interval [CI], 0.16 to 0.88). Multiple imputations for 
censored data (including patients who discontinued the trial, received 
rescue therapy, had a change in baseline treatment, or were continuing 
in the trial at the data-cutoff date) resulted in hazard ratios ranging 
from 0.34 to 0.44 (with corresponding P values of 0.01 to 0.04). Among 
the 55 AQP4-IgG-seropositive patients, relapse occurred in 11% of those 
in the satralizumab group and in 43% of those in the placebo group 
(hazard ratio, 0.21; 95% CI, 0.06 to 0.75); among 28 AQP4-IgG-
seronegative patients, relapse occurred in 36% and 43%, respectively 
(hazard ratio, 0.66; 95% CI, 0.20 to 2.24). The between-group 
difference in the change in the mean VAS pain score was 4.08 (95% CI, -
8.44 to 16.61); the between-group difference in the change in the mean 
FACIT-F score was -3.10 (95% CI, -8.38 to 2.18). The rates of serious 
adverse events and infections did not differ between groups.
    In support of the applicant's claim that ENSPRYNG\TM\ significantly 
improves clinical outcomes relative to services or technologies 
previously available for the treatment of NMOSD in adult patients who 
are AQP4-IgG positive, the applicant stated that patients treated with 
ENSPRYNG\TM\ plus IST exhibited a significantly longer time to first 
relapse when compared to placebo. This also included a risk reduction 
of 62% in patients treated with ENSPRYNG\TM\ plus IST when compared 
with patients who received a placebo plus IST and a 79% risk reduction 
in the AQP4-IgG positive population. Results in the AQP4-IgG negative 
patient subgroup were not statistically significant.\212\ The 
proportion of relapse free AQP4-IgG positive patients at week 96 was 
92% in ENSPRYNG\TM\ plus IST group and 53% in the placebo plus IST 
group.\213\
---------------------------------------------------------------------------

    \212\ ENSPRYNG (satralizumab) [prescribing information]. South 
San Francisco, CA: Genentech USA, Inc.; 2020.
    \213\ Yamamura T, Kleiter I, Fujihara K, et al. Trial of 
Satralizumab in Neuromyelitis Optica Spectrum Disorder. N. Engl. J. 
Med. 2019;381(22)2114-2124. doi:10.1056/nejmoa1901747.
---------------------------------------------------------------------------

    According to the applicant's second claim, substantial improvements 
in clinical efficacy are not accompanied by serious concerns. In the 
SAkuraSky trial, 90% of patients in the ENSPRYNG\TM\ plus IST group had 
at least one adverse event compared to 95% in the placebo plus IST 
group.\214\ The safety profile of ENSPRYNG\TM\ in the OST period was 
consistent with the double-blind period. There were no deaths or 
anaphylactic reactions, rates of AEs and serious AEs did not increase 
with longer exposure to ENSPRYNG\TM\; and the most frequently reported 
AEs in the OST period were consistent with the double-blind 
period.\215\
---------------------------------------------------------------------------

    \214\ Yamamura T, Kleiter I, Fujihara K, et al. Trial of 
Satralizumab in Neuromyelitis Optica Spectrum Disorder. N. Engl. J. 
Med. 2019;381(22)2114-2124. doi:10.1056/nejmoa1901747.
    \215\ Greenberg B, Seze JD, Fox E. et al. Safety of satralizumab 
in neuromyelitis optica spectrum disorder (NMOSD): Results from the 
open-label extension periods of SAkuraSky and SAkuraStar 
Presentation at: Americas Committee for treatment and research in 
Multiple Sclerosis (ACTRIMS); September 2020; Virtual
---------------------------------------------------------------------------

    The applicant's third claim concerns the flexibility provided to 
patients by the option to self-administer ENSPRYNG\TM\. According to 
the applicant, ENSPRYNG\TM\ is the only FDA-approved treatment for 
NMOSD that is administered subcutaneously.\216\ Once treatment is 
initiated during inpatient hospital admission, upon discharge and 
having received adequate training on how to perform the injection, an 
adult patient/caregiver may administer all subsequent doses of 
ENSPRYNG\TM\ at home if the treating physician determines that it is 
appropriate and the adult patient/caregiver can perform the injection 
technique. According to the applicant, self-administration provides the 
patient the option to continue the therapy initiated in the hospital 
while in the convenience of their own home, with reduced disruption to 
daily life. The applicant stated that additionally, the option to self-
administer provides flexibility to patients, as they can bring their 
medication with them while traveling without having to worry if there 
is an infusion site nearby. The applicant claims this may potentially 
reduce the rate of hospital readmissions.
---------------------------------------------------------------------------

    \216\ ENSPRYNG (satralizumab) [prescribing information]. South 
San Francisco, CA: Genentech USA, Inc.; 2020.
---------------------------------------------------------------------------

    In their fourth claim, the applicant stated the totality of 
circumstances otherwise demonstrate that ENSPRYNG\TM\, relative to 
technologies previously available, substantially improves the treatment 
of Medicare beneficiaries. The applicant asserted that a cross trial 
comparison between ENSPRYNG\TM\ and SOLIRIS[supreg] (approved for new 
technology add-on payment in FY 2021) cannot be made due to differences 
in trial design and study population. However, the applicant noted the 
following distinctions between ENSPRYNG\TM\ and SOLIRIS[supreg] and 
their clinical trials. Per the applicant, the first distinction is that 
in the registrational study for SOLIRIS[supreg], a higher proportion of 
patients receiving SOLIRIS[supreg] than those receiving a placebo 
discontinued their participation in the clinical trial (17% vs 
6%).\217\

[[Page 45025]]

During the double-blind period of SAkuraSky trial, however, a total of 
three patients (7%) in the ENSPRYNG\TM\ group and 10 patients (24%) in 
the placebo group discontinued the trial agent.\218\ The applicant 
stated that discontinuation of SOLIRIS[supreg] may be associated with 
relapse and hospitalization. The second distinction made by the 
applicant is that the prescribing information for ENSPRYNG\TM\ \219\ 
does not bear a black-box warning, in contrast to that of 
SOLIRIS[supreg].\220\ The third distinction is that patients must be 
vaccinated against Neisseria meningitidis before receiving 
SOLIRIS[supreg] \221\ and no such requirement applies to 
ENSPRYNGTM.\222\ The fourth and final distinction made by 
the applicant highlights duration of treatment. In the SAkuraSky trial, 
the mean period of treatment in the double-blind period was 94.1  72.6 weeks in the ENSPRYNGTM group and 66.0  61.4 weeks in the placebo group.\223\ However, the median trial 
durations were shorter in the SOLIRIS[supreg] trial, at 90.93 and 43.14 
weeks (minimum-maximum, 6.4-211.1 and 8.0-208.6) for the 
SOLIRIS[supreg] and placebo groups, respectively.\224\
---------------------------------------------------------------------------

    \217\ Pittock SJ, Berthele A, Fujihara K, et al. Eculizumab in 
Aquaporin-4-Positive Neuromyelitis Optica Spectrum Disorder. N. 
Engl. J. Med. 2019;381(7)614-625. doi:10.1056/nejmoa1900866.
    \218\ Yamamura T, Kleiter I, Fujihara K, et al. Trial of 
Satralizumab in Neuromyelitis Optica Spectrum Disorder. N. Engl. J. 
Med. 2019;381(22)2114-2124. doi:10.1056/nejmoa1901747.
    \219\ ENSPRYNG (satralizumab) [prescribing information]. South 
San Francisco, CA: Genentech USA, Inc.; 2020.
    \220\ SOLIRIS (eculizumab) [prescribing information]. Boston, 
MA: Alexion Pharmaceuticals, Inc.; 2019.
    \221\ SOLIRIS (eculizumab) [prescribing information]. Boston, 
MA: Alexion Pharmaceuticals, Inc.; 2019.
    \222\ ENSPRYNG (satralizumab) [prescribing information]. South 
San Francisco, CA: Genentech USA, Inc.; 2020.
    \223\ Yamamura T, Kleiter I, Fujihara K, et al. Trial of 
Satralizumab in Neuromyelitis Optica Spectrum Disorder. N. Engl. J. 
Med. 2019;381(22)2114-2124. doi:10.1056/nejmoa1901747.
    \224\ Pittock SJ, Berthele A, Fujihara K, et al. Eculizumab in 
Aquaporin-4-Positive Neuromyelitis Optica Spectrum Disorder. N. 
Engl. J. Med. 2019;381(7)614-625. doi:10.1056/nejmoa1900866.
---------------------------------------------------------------------------

    In connection with the applicant's fourth claim to support 
substantial clinical improvement, the applicant stated that both the 
SAkuraStar \225\ and SAkuraSky \226\ clinical trials included 
comparator arms. In SAkuraStar, an exclusion criterion was IST use, 
whereas in SAkuraSky, patients were permitted to continue baseline 
treatment with a stable dose of the IST agents in addition to the trial 
drug. This allowed the efficacy of ENSPRYNGTM to be assessed 
both in patients who were receiving one of the IST agents for their 
NMOSD and in the others who were receiving nothing at all. The 
applicant stated that in contrast, SOLIRIS[supreg] was tested only in a 
single Phase 3 clinical trial where the primary end point was the first 
adjudicated relapse in the population of patients taking stable-dose 
IST and either SOLIRIS[supreg] or placebo; the efficacy of 
SOLIRIS[supreg] monotherapy was a sub analysis,\227\ and 
UPLIZNA[supreg] was tested only in a single Phase 3 clinical trial as a 
monotherapy with only a 28-week randomized, controlled period.\228\ 
According to the applicant, ENSPRYNGTM has received approval 
by regulatory authorities in Japan,\229\ Canada, and Switzerland \230\ 
for the treatment of both adults and adolescents (12-17 years of age) 
with NMOSD. The applicant asserted that patients in the 
ENSPRYNGTM clinical trials likely are representative of 
Medicare patients despite their mean ages (45.3 years for the 
ENSPRYNGTM arm of SAkuraStar \231\ and 40.8 years for the 
ENSPRYNGTM arm of SAkuraSky \232\) being less than 65, as 
NMOSD is so severe that patients may qualify for disability accompanied 
by Medicare benefits regardless of their age.\233\ The applicant 
explained that a severe onset attack causing increased disability is 
reported to occur in 45% of patients with NMOSD \234\ and that 52.4% of 
US-based NMOSD patients report severe problems with mobility,\235\ 
which is consistent with definitions of disability used by the Social 
Security Administration (SSA).\236\ Per the applicant, SSA maintains a 
list of impairments considered severe enough to prevent gainful 
activity. Though NMOSD is not listed, multiple sclerosis (MS) is,\237\ 
and the two conditions are frequently confused due to similarities 
between clinical presentations.\238\ According to the applicant, the 
SSA is open to allowing people to qualify for disability by showing 
their condition is as severe as one that is on the list.\239\
---------------------------------------------------------------------------

    \225\ Traboulsee A, Greenberg BM, Bennett JL, et al. Safety And 
Efficacy of Satralizumab Monotherapy In Neuromyelitis Optica 
Spectrum Disorder: A Randomised, Double-Blind, Multicentre, Placebo-
Controlled Phase 3 Trial. Lancet Neurol. 2020;19(5):402-412. 
doi:10.1016/S1474-4422(20)30078-8.
    \226\ Yamamura T, Kleiter I, Fujihara K, et al. Trial of 
Satralizumab in Neuromyelitis Optica Spectrum Disorder. N. Engl. J. 
Med. 2019; 381(22)2114-2124. doi:10.1056/nejmoa1901747.
    \227\ Pittock SJ, Berthele A, Fujihara K, et al. Eculizumab in 
Aquaporin-4-Positive Neuromyelitis Optica Spectrum Disorder. N. 
Engl. J. Med. 2019;381(7)614-625. doi:10.1056/nejmoa1900866.
    \228\ Cree BAC, Bennett JL, Kim HJ, et al. Inebilizumab for the 
treatment of neuromyelitis optica spectrum disorder (N-MOmentum): a 
double-blind, randomised placebo-controlled phase \2/3\ trial. 
Lancet 2019;394(10206)1352-1363. doi:10.1016/s0140-6736(19)31817-3.
    \229\ F. Hoffmann-La Roche Ltd. Roche's ENSPRYNG (satralizumab) 
Approved In Japan For Adults And Children With Neuromyelitis Optica 
Spectrum Disorder. https://www.roche.com/media/releases/med-cor-2020-06-29.htm. Accessed August 14, 2020.
    \230\ Heo Y. Satralizumab: First Approval. Drugs 
2020;80(14)1477-1482. doi:10.1007/s40265-020-01380-2.
    \231\ Traboulsee A, Greenberg BM, Bennett JL, et al. Safety And 
Efficacy of Satralizumab Monotherapy In Neuromyelitis Optica 
Spectrum Disorder: A Randomised, Double-Blind, Multicentre, Placebo-
Controlled Phase 3 Trial. Lancet Neurol. 2020;19(5):402-412. 
doi:10.1016/S1474-4422(20)30078-8.
    \232\ Yamamura T, Kleiter I, Fujihara K, et al. Trial of 
Satralizumab in Neuromyelitis Optica Spectrum Disorder. N. Engl. J. 
Med. 2019;381(22)2114-2124. doi:10.1056/nejmoa1901747.
    \233\ Social Security Administration. Medicare Information. 
https://www.ssa.gov/disabilityresearch/wi/medicare.htm. Accessed 
September 10, 2020.
    \234\ Kim S, Mealy MA, Levy M, et al. Racial differences in 
neuromyelitis optica spectrum disorder. Neurology 2018;91(22)e2089-
e2099. doi:10.1212/wnl.0000000000006574.
    \235\ Mealy MA, Boscoe A, Caro J, et al. Assessment of Patients 
with Neuromyelitis Optica Spectrum Disorder Using the EQ-5D. Int. J. 
MS Care 2018; 21(3)129-134. doi:10.7224/1537-2073.2017-076.
    \236\ Social Security Administration. How You Qualify. https://www.ssa.gov/benefits/disability/qualify.html. Accessed October 2, 
2020.
    \237\ Social Security Administration. Disability Evaluation 
Under Social Security. https://www.ssa.gov/disability/professionals/bluebook/11.00-Neurological-Adult.htm#11_09. Accessed September 10, 
2020.
    \238\ Etemadifar M, Nasr Z, Khalili B, Taherioun M, Vosoughi R. 
Epidemiology of Neuromyelitis Optica In The World: A Systematic 
Review And Meta-Analysis. Mult Scler Int. 2015;2015:174720. 
doi:10.1155/2015/174720.
    \239\ Social Security Administration. How You Qualify. https://www.ssa.gov/benefits/disability/qualify.html. Accessed October 2, 
2020.
---------------------------------------------------------------------------

    After reviewing the information submitted by the applicant as part 
of its FY 2022 new technology add-on payment application for 
ENSPRYNGTM, we noted that while the applicant provided data 
comparing ENSPRYNGTM to placebo with or without IST, the 
applicant did not provide data to demonstrate improved outcomes over 
existing FDA approved treatments for NMOSD. While the applicant stated 
reasons why a comparison could not be made, we stated that additional 
information would help inform our assessment of whether 
ENSPRYNGTM demonstrates a significant clinical improvement 
over existing technologies for outcomes such as time to first relapse 
and annual relapse rate. In addition, we stated that while we 
understand that there may be potential benefits related to the self-
administrative delivery of ENSPRYNGTM, we questioned if the 
benefits are related only to the outpatient administration of the 
medication and whether they would demonstrate improved clinical 
outcomes that represent a substantial clinical improvement in the 
inpatient setting. We invited public comments on

[[Page 45026]]

whether ENSPRYNGTM meets the substantial clinical 
improvement criterion.
    Comment: We received several comments in support of the new 
technology add-on payment application for ENSPRYNG\TM\ urging the 
approval of this application to ensure that Medicare beneficiaries with 
NMOSD will have timely access to appropriate treatment in the inpatient 
setting for this devastating, rare, autoimmune disease. The commenters 
highlighted the risk of relapse associated with NMOSD, and the current 
practice of using ongoing treatment with medications that suppress the 
immune system to prevent relapse from happening. The commenters 
explained that approval of the new technology add-on payment for 
ENSPRYNG\TM\ would minimize the risk of future relapses and potential 
hospital readmissions by allowing patients to start on a safe and 
effective maintenance treatment while admitted in the inpatient 
setting. The commenters referenced the SAkuraStar and SAkuraSky 
studies, summarized here and in the FY 2022 IPPS/LTCH PPS proposed rule 
(86 FR 25254 through 25256), as evidence that ENSPRYNG\TM\ is a safe 
and effective treatment for NMOSD.
    Response: We thank the commenters for sharing their perspective on 
the new technology add-on payment application for ENSPRYNG\TM\ and have 
taken these comments into consideration in our determination of 
substantial clinical improvement, which is discussed later in this 
section.
    Comment: The applicant submitted a comment in response to the 
concerns raised by CMS in the proposed rule regarding whether 
ENSPRYNG\TM\ meets the substantial clinical improvement criterion (86 
FR 25256). With regard to our concern that the applicant did not submit 
data to demonstrate improved outcomes over existing FDA approved 
treatments for NMOSD, the applicant commented that off-label (including 
IST) therapies are the most appropriate comparator for CMS to use when 
evaluating whether or not ENSPRYNG\TM\ is a substantial clinical 
improvement because neither SOLIRIS[supreg] nor UPLIZNA[supreg] are 
generally available to inpatient Medicare beneficiaries. The applicant 
explained that because SOLIRIS[supreg] and UPLIZNA[supreg] did not have 
claims in the Statistical Analytical File for CY 2020, the drugs were 
unavailable in the inpatient setting, and therefore ENSPRYNG\TM\ should 
not be compared against them for evidence of substantial clinical 
improvement.
    The applicant also commented that ENSPRYNG\TM\ represents a 
substantial clinical improvement over existing technologies because it 
is the only FDA-approved treatment for at least two subsets of NMOSD 
patients who are ineligible for SOLIRIS[supreg] and UPLIZNA[supreg]: 
Patients who are not currently vaccinated against Neisseria 
meningitidis and patients at a higher risk of PML. The applicant stated 
that ENSPRYNG\TM\ is the only FDA-approved treatment for NMOSD that 
specifically addresses important components of NMOSD pathophysiology 
without eliminating targeted components of the immune system. The 
applicant explained that SOLIRIS[supreg] is contraindicated in patients 
who are not currently vaccinated against Neisseria meningitidis. 
Although the vaccination reduces the risk of meningococcal infection, 
the applicant explained that the SOLIRIS[supreg] label states that 
``life-threatening and fatal meningococcal infections have occurred in 
patients treated with SOLIRIS[supreg].'' The applicant also argued that 
UPLIZNA[supreg]'s mechanism of action in targeting B cells may impact 
cellular reconstitution and long-term humoral memory, which cause 
potential safety risks including hypogammaglobulinemia and enhanced 
risk of infections like PML, a viral infection of the brain caused by 
the JC virus.\240\ The applicant cited two technologies that CMS 
approved for new technology add-on payment technologies, GORE[supreg] 
TAG[supreg] (70 FR 47356 through 47359) and CardioWest \TM\ Temporary 
Total Artificial Heart System (73 FR 48555 through 48557), as further 
support that offering treatment options for patients otherwise 
ineligible for currently available treatments constitutes substantial 
clinical improvement.
---------------------------------------------------------------------------

    \240\ Papadopoulos, MC et al. Treatment of neuromyelitis optica: 
state-of-the-art and emerging therapies. Nat Rev Neurol 2014;10:493-
506.
---------------------------------------------------------------------------

    The applicant also commented in response to our concerns in the FY 
2022 IPPS/LTCH PPS proposed rule (86 FR 25256) regarding whether the 
benefits of ENSPRYNG\TM\ are related only to the outpatient 
administration of the medication and our concern on whether those 
benefits would demonstrate improved clinical outcomes that represent a 
substantial clinical improvement in the inpatient setting. The 
applicant commented that the benefits associated with the self-
administration of ENSPRYNG\TM\ are realized in both the inpatient and 
outpatient settings, and therefore demonstrate improved clinical 
outcomes in the inpatient setting. First, the applicant stated that the 
benefits associated with the self-administration of ENSPRYNG\TM\ in the 
outpatient setting directly confer benefits in the inpatient setting. 
As an example, the applicant stated that self-administration of 
ENSPRYNG\TM\ in the outpatient setting allows patients flexibility to 
bring their medication with them when they travel without ensuring an 
infusion site is near their destination. The applicant also explained 
that due to the severity of NMOSD and its propensity to cause patients 
experiencing a relapse to be hospitalized, and the clinically-proven 
ability of ENSPRYNG\TM\ to reduce the incidence of relapse compared to 
off-label IST treatments, its outpatient use may reduce 
hospitalizations. Second, the applicant stated that ENSPRYNG\TM\ is the 
only FDA-approved option in the inpatient setting for patients that are 
unwilling or unable (perhaps due to difficulties associated with their 
venous access) to receive IV infusions. Third, the applicant pointed 
out that CMS has approved several technologies for the new technology 
add-on payment that are used in both the inpatient and outpatient 
settings, including DIFICIDTM (77 FR 53358), STELARA[supreg] 
(82 FR 38129), CABLIVI[supreg] (84 FR 42208), BALVERSATM (84 
FR 42242), ERLEADATM (84 FR 42247), XOSPATA[supreg] (84 FR 
42260), XENLETA (85 FR 58732), TECENTRIQ[supreg] (85 FR 58684), and 
IMFINZI[supreg] (85 FR 58684).
    The applicant commented that CMS's past approval decisions on new 
technology add-on payments and commentary support the approval of 
ENSPRYNG\TM\'s application and stated that CMS appears to be taking a 
new policy position regarding how an applicant demonstrates substantial 
clinical improvement. The applicant states that at least one new 
technology add-on payment applicant, SPRAVATO[supreg], has been 
approved for new technology add-on payment based on that technology's 
assertions of improved safety versus other existing treatment options. 
The applicant also cited six technologies approved for new technology 
add-on payment that the applicant believes did not submit studies in a 
manner conducive to a demonstration of improved outcomes over existing 
FDA-approved treatments or studies with any improved outcomes at all: 
GIAPREZATM (83 FR 41342), IMFINZI[supreg] (85 FR 58684), 
ZEMDRITM (83 FR 41334), BALVERSATM (84 FR 42242), 
JAKAFITM (84 FR 422732), and BLINCYTOTM (80 FR 
49451).
    Response: We thank the applicant for its comment in response to our 
concerns and providing additional information for us to consider. After 
further review, we continue to have concerns as to

[[Page 45027]]

whether ENSPRYNG\TM\ meets the substantial clinical improvement 
criterion to be approved for new technology add-on payments. 
Specifically, the applicant did not provide data to demonstrate 
improved outcomes over existing FDA approved treatments for NMOSD. The 
applicant commented that the lack of utilization, as evidenced by the 
absence of claims for SOLIRIS[supreg] and UPLIZNA[supreg] in the CY 
2020 SAF, suggests that the drugs are unavailable in the inpatient 
setting, and are therefore not the appropriate comparators for 
ENSPRYNG\TM\. We disagree. Both SOLIRIS[supreg] and UPLIZNA[supreg] are 
covered by Medicare, on the market, and, are therefore available for 
Medicare beneficiaries in the inpatient setting. It appears that the 
applicant is speculating with regard to the availability of the 
existing technologies. Therefore, whether there were Medicare claims in 
the CY 2020 SAF for SOLIRIS[supreg] and UPLIZNA[supreg] is not relevant 
to whether these drugs are an appropriate comparator for the purposes 
of substantial clinical improvement. We further disagree with the 
applicant that the lack of claims in the CY 2020 SAF data calls into 
question the degree of clinical improvement with which they are 
associated. We note that SOLIRIS[supreg] demonstrated substantial 
clinical improvement in their FY 2021 new technology application based 
on clinical data. We make substantial clinical improvement 
determinations based on the criteria at Sec.  412.87(b), and not based 
on the utilization of a technology within the claims data. In addition, 
while the applicant states that the manufacturer for SPRAVATO asserted 
without providing supporting data that electroconvulsive therapy (ECT) 
had limited availability and nevertherless was awarded new technology 
add-on payments without providing a comparison to that comparator (84 
FR 42247 through 42256), we note that we concluded that ECT was not an 
appropriate comparator because of poor side effects and the clinical 
challenges and difficulties arising from treatment with ECT which 
contributed to the limited availability. In this case, we believe that 
SOLIRIS[supreg] and UPLIZNA[supreg] do not have limited availability, 
for the reasons noted previously.
    While the commenter is correct that CMS has determined that prior 
technologies, including GORE TAG[supreg] (70 FR 47356 through 47359) 
and CardioWest \TM\ (73 FR 48555 through 48557), represented a 
substantial clinical improvement because they offer a treatment option 
for patients otherwise ineligible for currently available treatments, 
we cannot conclude based on the information provided that ENSPRYNG\TM\ 
offers a treatment option for a patient population unresponsive to, or 
ineligible for, currently available treatments. We disagree with the 
applicant's assertion that individuals who are not currently vaccinated 
against Neisseria meningitidis and patients at a higher risk of PML 
constitute individual patient populations that are unresponsive to, or 
ineligible for, currently available treatments. First, vaccinations 
against Neisseria meningitidis are safe and effective, recommended by 
the CDC,\241\ and are required for SOLIRIS[supreg] treatment. 
Individuals that are not vaccinated against Neisseria meningitidis are 
not considered a separate patient population because eligibility can be 
easily attained via a widely available vaccine and are also able to 
receive treatment with UPLIZNA[supreg] which does not require a vaccine 
as noted previously in this section. Second, a patient that is at a 
higher risk of PML is not ineligible for UPLIZNA[supreg], as the 
applicant stated, because patients at risk are not contraindicated from 
using UPLIZNA[supreg], and therefore we conclude that having a higher 
risk of developing PML does not create a population of patients that 
are ineligible for UPLIZNA[supreg]. As described earlier in this 
section, we also disagree that patients unwilling or unable to receive 
an IV infusion constitute a new population. We note that patients with 
acute NMOSD in the inpatient setting will require IV access for 
treatment (that is, for IV corticosteroids, plasmapheresis, and/or 
IST), so we believe that inpatients with NMOSD would not be unwilling 
or unable to receive further IV therapies. For these reasons, unlike 
GORE TAG[supreg] and CardioWestTM which demonstrated 
treatment of patients with an unmet need, ENSPRYNG[supreg] does not 
meet this criterion. Please refer to (70 FR 47356 through 47359) and 
(73 FR 48555 through 48557) for a full discussion of how these 
determinations were made.
---------------------------------------------------------------------------

    \241\ CDC, ``Meningococcal: Who Needs to Be Vaccinated?'' 
https://www.cdc.gov/vaccines/vpd/mening/hcp/who-vaccinate-hcp.html, 
last updated: July 26, 2019.
---------------------------------------------------------------------------

    With regard to the applicant's assertion that the self-
administration of ENSPRYNG[supreg] realizes benefits in the inpatient 
and outpatient settings, we agree that subcutaneous drugs offer 
additional flexibility over infusions. The applicant claims that this 
flexibility may potentially reduce the rate of hospital readmissions, 
but the applicant did not provide any data to support a reduction of 
hospitalizations or other outcomes related to the form of drug 
administration as compared to existing treatments. The applicant listed 
examples of outcomes that can support a determination of substantial 
clinical improvement from the regulation text at Sec.  412.87 such as 
an improvement in quality of life and greater medication adherence or 
compliance, stating that these are not restricted to demonstration of 
benefits in the inpatient setting; however, the applicant did not 
demonstrate that ENSPRYNG[supreg] confers these benefits. While we have 
granted new technology add-on payments to technologies that are given 
in both the inpatient and outpatient settings, we note that these 
technologies demonstrated substantial clinical improvement by 
demonstrating outcomes superior to the standard of care. Please see a 
full discussion of how these determinations were made at 77 FR 53350 
through 53358, 82 FR 38125 through 38129, 84 FR 42201 through 42208, 84 
FR 42237 through 42242, 84 FR 42242 through 42247, 84 FR 42256 through 
42260, and 85 FR 58672 through 58684.
    Finally, we disagree that we are taking a new policy position with 
regard to how an applicant demonstrates substantial clinical 
improvement. With all applications, from the time the application is 
submitted until the final rule, we make a concerted effort to gather 
all of the information necessary to make an informed decision with 
regard to substantial clinical improvement. We rigorously review each 
application with our medical officers and clinical staff to determine 
whether a technology represents a substantial clinical improvement over 
existing technologies. We provide concerns in the proposed rule for 
each technology to ensure transparency with regard to our review, and 
applicants have the opportunity to address these concerns prior to the 
final rule in the comment period. With regard to the applicant's 
reference to other new technology add-on payment applications that were 
previously approved to demonstrate why ENSPRYNG\TM\ should be approved, 
we note that every application is evaluated on its own data and merits 
to determine whether it meets the new technology add-on payment 
criterion for substantial clinical improvement. In listing examples of 
various previously approved technologies, it appeared that the 
applicant did not consider the differences between applications, as 
well as the variations in currently

[[Page 45028]]

available technologies an applicant is compared against for purposes of 
showing substantial clinical improvement. For example, the applicant 
cited IMFINZI[supreg] as an example of a new technology add-on payment 
approval that, per the applicant, did not submit studies in a manner 
conducive to a demonstration of improved outcomes over existing FDA-
approved treatments or studies with any improved outcomes at all. 
IMFINZI[supreg] was approved for FY 2021 new technology add-on payment 
after CMS concluded that it met the criteria, including demonstrating a 
substantial clinical improvement over existing technologies by being 
one of the first two treatments (the second being TECENTRIQ[supreg], of 
which the applicant is also the manufacturer) to show improved overall 
survival in the treatment of patients with extensive-stage small cell 
lung cancer (ES-SCLC) in more than 20 years (85 FR 58672 through 
58684). CMS reached this conclusion after reviewing data submitted by 
both IMFINZI[supreg] and TECENTRIQ[supreg] in their applications and 
during the comment period, including data that showed a sustained 
overall survival (OS) benefit in combination with SOC chemotherapy as 
compared to SOC chemotherapy+placebo. CMS did not require the two new 
treatments to demonstrate superiority over each other as they were 
determined to be substantially similar. Per our policy, because the 
applications were submitted for review in the same year, and because we 
believed they were substantially similar to each other, we considered 
both sets of clinical data in making a determination, and we did not 
believe that it would be possible to choose one set of data over 
another set of data in an objective manner. Accordingly, CMS disagrees 
with the applicant's claim that CMS approved IMFINZI[supreg] without a 
finding of substantial clinical improvement over existing technologies.
    After review of the information submitted by the applicant as part 
of its FY 2022 new technology add-on payment application for 
ENSPRYNG\TM\ and consideration of the comments received, for the 
reasons discussed in the proposed rule and in this final rule, we are 
unable to determine that ENSPRYNG\TM\ meets the substantial clinical 
improvement criterion, and therefore we are not approving new 
technology add-on payments for ENSPRYNG\TM\ for FY 2022.
g. ABECMA[supreg] (idecabtagene vicleucel)
    Celgene Corporation, a wholly owned subsidiary of Bristol-Myers 
Squibb (BMS), submitted an application for new technology add-on 
payment for ABECMA[supreg] for FY 2022. ABECMA[supreg] is a B-cell 
maturation antigen (BCMA)-directed genetically modified autologous 
chimeric antigen receptor (CAR) T-cell immunotherapy for the treatment 
of adult patients with relapsed or refractory (RR) multiple myeloma 
(MM) (RRMM) who have received at least four prior therapies including 
an immunomodulatory agent (IMiD), a proteasome inhibitor (PI), and an 
anti-CD38 antibody (for example, triple-class-exposed). ABECMA[supreg] 
is expected to be a 5th line plus (5L+) treatment.
    Multiple myeloma (MM) is typically characterized by the neoplastic 
proliferation of plasma cells producing a monoclonal immunoglobulin. 
The plasma cells proliferate in the bone marrow and can result in 
extensive skeletal destruction with osteolytic lesions, osteopenia, 
and/or pathologic fractures. The diagnosis of MM is often suspected 
because of one (or more) of the following clinical presentations:

 Bone pain with lytic lesions discovered on routine skeletal 
films or other imaging modalities
 An increased total serum protein concentration and/or the 
presence of a monoclonal protein in the urine or serum
 Systemic signs or symptoms suggestive of malignancy, such as 
unexplained anemia
 Hypercalcemia, which is either symptomatic or discovered 
incidentally
 Acute renal failure with a bland urinalysis or rarely 
nephrotic syndrome due to concurrent immunoglobulin light chain (AL) 
amyloidosis

    It is important to distinguish MM both from other causes of these 
clinical presentations and from other plasma cell dyscrasias for the 
purposes of prognosis and treatment.\242\ Data from the US 
Surveillance, Epidemiology, and End Results (SEER) registry estimate 
32,000 new cases of MM and 13,000 deaths from MM annually in the US. 
This correlates with an annual incidence of approximately 7 per 100,000 
men and women per year. MM is largely a disease of older adults. The 
median age at diagnosis is 65 to 74 years. MM is also slightly more 
frequent in men than in women (approximately 1.4:1). MM is associated 
with substantial morbidity and mortality \243\ and approximately 25% of 
patients have a median survival of 2 years or less.\244\
---------------------------------------------------------------------------

    \242\ Laubauch, J.P. (2021). Multiple myeloma: Clinical 
features, laboratory manifestations, and diagnosis. UptoDate. 
Available from https://www.uptodate.com/contents/multiple-myeloma-
clinical-features-laboratory-manifestations-and-
diagnosis?search=multiple%20myeloma&source=search_result&selectedTitl
e=1~150&usage_type=default&display_rank=1.
    \243\ R?owan AJ, Allen C, Barac A, et al. Global Burden of 
Multiple Myeloma: A Systematic Analysis for the Global Burden of 
Disease Study 2016. JAMA Oncol. 2018;4(9):1221-1227. doi:10.1001/
jamaoncol.2018.2128.
    \244\ Biran, N., Jagannath, S., Risk Stratification in Multiple 
Myeloma, Part 1: Characterization of High-Risk Disease 2013. 
Clinical Adv in Hematology & Oncology 11(8); 489-503.
---------------------------------------------------------------------------

    With respect to the newness criterion, ABECMA[supreg] received FDA 
approval on March 26, 2021, and is indicated for the treatment of adult 
patients with relapsed or refractory multiple myeloma after four or 
more prior lines of therapy, including an immunomodulatory agent, a 
proteasome inhibitor, and an anti-CD38 monoclonal antibody. A single 
dose of ABECMA[supreg] contains a cell suspension of 300 to 460 x 106 
CAR T-cells.
    The applicant submitted a request for unique ICD-10-PCS codes that 
describe the administration of ABECMA[supreg] at the September 2020 
Coordination and Maintenance Committee meeting. The following codes 
were approved to describe procedures involving the administration of 
ABECMA[supreg]: XW033K7 (Introduction of idecabtagene vicleucel 
immunotherapy into peripheral vein, percutaneous approach, new 
technology group 7) and XW043K7 (Introduction of idecabtagene vicleucel 
immunotherapy into central vein, percutaneous approach, new technology 
group 7). These codes will be effective starting October 1, 2021.
    As previously stated, if a technology meets all three of the 
substantial similarity criteria as previously described, it would be 
considered substantially similar to an existing technology and 
therefore would not be considered ``new'' for purposes of new 
technology add-on payments.
    With respect to whether a product uses the same or a similar 
mechanism of action when compared to an existing technology to achieve 
a therapeutic outcome, the applicant asserted that ABECMA[supreg] does 
not use the same or similar mechanism of action as other therapies 
approved to treat 4L+ RRMM or CAR T-cell therapies approved to treat 
different diseases. According to the applicant, with regard to its 
mechanism of action, ABECMA[supreg] is a chimeric antigen receptor 
(CAR)-positive T cell therapy targeting B-cell maturation antigen 
(BCMA), which is expressed on the surface of normal and malignant 
plasma cells. The CAR construct includes an anti-BCMA scFv-targeting 
domain for antigen specificity, a transmembrane domain, a CD3-zeta T

[[Page 45029]]

cell activation domain, and a 4-1BB costimulatory domain. Antigen-
specific activation of ABECMA[supreg] results in CAR-positive T cell 
proliferation, cytokine secretion, and subsequent cytolytic killing of 
BCMA-expressing cells.
    According to the applicant, with respect to the non-CAR T-cell 
therapies to treat 4L+ RRMM, specifically Xpovio[supreg], Blenrep, and 
chemotherapy, ABECMA[supreg]'s mechanism of action is different because 
it is a CAR T-cell therapy. The applicant stated that the mechanism of 
action for Xpovio[supreg] is reversible inhibition of nuclear export of 
tumor suppressor proteins (TSPs), growth regulators, and mRNAs of 
oncogenic proteins by blocking exportin 1 (XPO1). XPO1 inhibition by 
Xpovio[supreg] leads to accumulation of TSPs in the nucleus, reductions 
in several oncoproteins, such as c[hyphen]myc (a ``master regulator'' 
which controls many aspects of cellular growth regulation and cellular 
metabolism) and cyclin D1, cell cycle arrest, and apoptosis of cancer 
cells. The applicant stated that Blenrep's mechanism of action is cell 
destruction via microtubule inhibition, where the microtubule inhibitor 
is conjugated to a BCMA-specific antibody (antibody-drug conjugate). 
The applicant further stated that the mechanism of action for 
chemotherapy regimens generally is disruption of normal processes 
required for cell survival, such as deoxyribonucleic acid (DNA) 
replication and protein synthesis or degradation.
    With respect to the mechanism of action of other currently FDA 
approved CAR T-cell therapies, according to the applicant, there are no 
other FDA approved CAR T-cell therapies that are indicated for 
treatment of RRMM with the same or similar mechanism of action as 
ABECMA[supreg]. The applicant stated that CAR T-cell therapies employ a 
unique mechanism of action which modifies the patient's own T-cell to 
express a chimeric antigen receptor (CAR) that programs T-cells to 
destroy cells that express a specific target. In the case of 
ABECMA[supreg], this target is BCMA, which is a protein that is highly 
expressed on the surface of MM cells making it an ideal target for the 
treatment of MM. The applicant asserted that the key feature that 
distinguishes ABECMA[supreg] from CD-19 directed CAR T-cell therapies 
is the BCMA targeting domain. According to the applicant, 
ABECMA[supreg]'s BCMA targeting domain means that ABECMA[supreg] has a 
completely different mechanism of action from other currently FDA 
approved CAR T-cell therapies. In its application, the applicant 
asserted that since there are currently no FDA approved anti-BCMA CAR 
T-cell therapies, if approved, ABECMA[supreg] is the first CAR T-cell 
therapy approved for the treatment of RRMM and the only approved CAR T-
cell therapy with a BCMA targeting domain which makes it unique as 
compared to other currently approved FDA therapies used to treat RRMM.
    With regard to whether a product is assigned to the same DRG when 
compared to an existing technology, the applicant stated that it 
expects that cases involving the administration ABECMA[supreg] will be 
assigned to the same MS-DRG, MS-DRG 018 (Chimeric Antigen Receptor 
(CAR) T-cell Immunotherapy), as other CAR T-cell therapies.
    With regard to whether the new use of the technology involves the 
treatment of the same or similar type of disease and the same or 
similar patient population when compared to an existing technology, the 
applicant asserted that, if FDA approved, ABECMA[supreg] will be the 
first and only anti-BCMA CAR T-cell therapy available to treat RRMM. 
The applicant further asserted that ABECMA[supreg] would be indicated 
for a broader population than other currently FDA-approved available 
therapies, specifically multiple myeloma patients having received four 
prior therapies.
    In summary, according to the applicant, because ABECMA[supreg] has 
a unique mechanism of action when compared to other currently FDA 
approved treatments for RRMM, and does not involve the treatment of the 
same or similar type of disease (RRMM) or the same or similar patient 
population (triple-class-exposed adult patients with RRMM), the 
technology is not substantially similar to an existing technology and 
therefore meets the newness criterion. However, we questioned whether 
ABECMA[supreg]'s mechanism of action may be similar to that of 
ciltacabtagene autoleucel, another CAR T-cell therapy for which an 
application for new technology add-on payments was submitted for FY 
2022 as discussed in the proposed rule. Both ABECMA[supreg] and 
ciltacabtagene autoleucel seem to be intended for similar patient 
populations; multiple myeloma patients with three or more prior 
therapies, and would involve the treatment of the same conditions; 
adult patients with relapsed or refractory multiple myeloma.
    We indicated that we were interested in information on how these 
two technologies may differ from each other with respect to the 
substantial similarity criteria and newness criterion, to inform our 
analysis of whether ABECMA[supreg] and ciltacabtagne autoleucel, if 
approved by July 1, 2021, are substantially similar to each other and 
therefore should be considered as a single application for purposes of 
new technology add-on payments.
    We invited public comments on whether ABECMA[supreg] is 
substantially similar to an existing technology and whether it meets 
the newness criterion.
    Comment: A few commenters encouraged CMS to consider assigning new 
technology add-on payments for new CAR T-cell therapies including 
idecabtagene vicleucel to ensure patient access.
    Another commenter disagreed with CMS that ABECMA[supreg] would not 
be considered ``new'' for purposes of new technology add-on payment. 
The commenter supported that this product is different from the 
currently approved products treating patients with multiple myeloma and 
therefore supported that ABECMA[supreg] receive new technology add-on 
payment status.
    Response: We appreciate the input from the commenters and the 
information they have highlighted, and we have taken these comments 
into consideration in our final decision, which is discussed later in 
this section.
    Comment: In response to CMS' concerns for the substantial 
similarity criterion, the applicant submitted a comment. The applicant 
asserted that ABECMA[supreg] is currently the only FDA approved CAR T-
cell therapy for the treatment of adult patients with RRMM after four 
or more prior lines of therapy and the only CAR T-cell therapy approved 
for the treatment of multiple myeloma. The applicant stated that unlike 
other therapies approved to treat 5L+ RRMM, ABECMA[supreg] modifies the 
patient's own T-cell to express a CAR that programs T-cells to kill 
cells that express a specific target, the BCMA. According to the 
applicant, all other approved CAR T-cell therapies today target the 
CD19 cell surface protein and are approved for the treatment of 
specific types of Non-Hodgkins Lymphoma (NHL).\245\ The applicant 
asserted that ABECMA[supreg] does not involve the treatment of the same 
or similar type of disease or the same or similar patient population 
when compared to existing technology because ABECMA[supreg] is the only 
CAR T-cell therapy available for the treatment of patients with RRMM. 
The applicant stated that the other treatments used in this space 
utilize different technologies, including small molecule inhibitors of

[[Page 45030]]

cellular processes (XPOVIO[supreg]) or antibody drug conjugates 
(BLENREP).\246\
---------------------------------------------------------------------------

    \245\ Nair, R. and J. Westin, CAR T cells. Adv Exp Med Biol, 
2020. 1244: p. 215-233.
    \246\ Chari, A., et al., Oral Selinexor-Dexamethasone for 
Triple-Class Refractory Multiple Myeloma. N Engl J Med, 2019. 
381(8): p. 727-738; Lonial, S., et al., Belantamab mafodotin for 
relapsed or refractory multiple myeloma (DREAMM-2): A two-arm, 
randomised, open-label, phase 2 study. Lancet Oncol, 2020. 21(2): p. 
207-221.
---------------------------------------------------------------------------

    In regard to CMS' concern whether ABECMA[supreg] and ciltacabtagne 
autoleucel are similar, the applicant commented that ciltacabtagene 
autoleucel is not yet FDA approved and is unlikely to be FDA approved 
by July 1, 2021, as its FDA Prescription Drug User Fee Act target 
action date has been set for November 29, 2021.\247\ The applicant 
stated that CMS should evaluate ABECMA[supreg]'s new technology add-on 
payment application on its own and should grant new technology add-on 
payment status effective October 1, 2021, in order to ensure Medicare 
beneficiary access.
---------------------------------------------------------------------------

    \247\ ``U.S. Food and Drug Administration Grants BCMA CAR-T 
Cilta-cel Priority Review for the Treatment for Relapsed/Refractory 
Multiple Myeloma.'' Legend Biotech Corporation, May 26, 2021. Press 
release.
---------------------------------------------------------------------------

    Response: After consideration of the public comments we received 
and information submitted by the applicant in its application, we agree 
with the applicant that ABECMA[supreg] is not used to treat the same or 
similar type of disease (for the treatment of adult patients with 
relapsed or refractory multiple myeloma after four or more prior lines 
of therapy including an immunomodulatory agent, a proteasome inhibitor, 
and an anti-CD38 monoclonal antibody) or a similar patient population 
as currently available treatment options, and that ABECMA[supreg] does 
not use the same or similar mechanism of action as other technologies 
used for the treatment of the indication stated previously. 
Furthermore, as previously noted, the applicant for ciltacabtagene 
autoleucel withdrew its application prior to the issuance of this FY 
2022 IPPS/LTCH PPS final rule, and we further note that the technology 
as not yet been FDA approved as of the time of the development of this 
final rule. We believe that the ABECMA[supreg] has a new mechanism of 
action as it is the only CAR T-cell therapy available for the treatment 
of adult patients with relapsed or refractory multiple myeloma after 
four or more prior lines of therapy including an immunomodulatory 
agent, a proteasome inhibitor, and an anti-CD38 monoclonal antibody 
and, therefore, we believe that ABECMA[supreg] is not substantially 
similar to existing technologies and meets the newness criterion. We 
consider the beginning of the newness period to commence on the first 
date ABECMA[supreg] received FDA approval, March 26, 2021.
    With regard to the cost criterion, the applicant searched the FY 
2019 MedPAR correction notice (December 1, 2020) file to identify 
potential cases representing patients who may be eligible for treatment 
using ABECMA[supreg]. In its analysis, the applicant identified a 
primary cohort to assess whether this therapy met the cost criterion. 
The following ICD-10-CM diagnosis codes were used to identify claims 
involving multiple myeloma procedures.
[GRAPHIC] [TIFF OMITTED] TR13AU21.175

    The applicant chose to limit its analysis to MS-DRG 016 (Autologous 
Bone Marrow Transplant W CC/MCC or T-Cell Immunotherapy, MS-DRG 840 
(Lymphoma & Non-Acute Leukemia W MCC) and MS-DRG 841 (Lymphoma & Non-
Acute Leukemia W CC). The claim search conducted by the applicant 
resulted in 1,955 claims mapped to MS-DRG 016, MS-DRG 840 and MS-DRG 
841 using the FY 2019 MedPAR. The applicant determined an average 
unstandardized case weighted charge per case of $1,237,393. The 
applicant used the MS-DRG-018 New Technology Threshold for FY 2022 from 
the FY 2021 IPPS/LTCH PPS final rule.
    The applicant removed all charges in the drug cost center for the 
prior technology because, according to the applicant, it is not 
possible to differentiate between different drugs on inpatient claims. 
The applicant added that this is likely an overestimate of the charges 
that would be replaced by the use of ABECMA[supreg]. The applicant then 
standardized the charges using the FY 2019 final rule impact file. 
Next, the applicant applied the 2-year inflation factor used in the FY 
2021 IPPS/LTCH PPS final rule to calculate outlier threshold charges 
(1.13218). To calculate the charges for the new technology, the 
applicant used a national average CCR for the CAR T-cell therapies of 
0.295. To determine this alternative CCR for CAR T-cell therapies, the 
applicant referred to the FY 2021 IPPS/LTCH PPS final rule AOR/BOR file 
and calculated an alternative markup percentage by dividing the AOR 
drug charges within DRG 018 by the number of cases to determine a per 
case drug charge. The applicant then divided the drug charges per case 
by $373,000, the acquisition cost of YESCARTA and KYMRIAH. The 
applicant calculated a final inflated average case-weighted 
standardized charge per case of $1,329,540, which exceeded the average 
case-weighted threshold amount of $1,251,127 by $78,413. The applicant 
stated that because the final inflated average case-weighted 
standardized charge per case exceeded the average case-weighted 
threshold amount, the therapy meets the cost criterion.
    As noted in previous discussions, the submitted costs for CAR T-
cell therapies vary widely due to differences in provider billing and 
charging practices for this therapy. Therefore, with regard to the use 
of this data for purposes of calculating a CAR T-cell CCR, we stated in 
the proposed rule that we were uncertain how representative this data 
is for use in the applicant's cost analyses given the potential for 
variability.
    We stated that we continued to be interested in public comments 
regarding the eligibility of CAR T-cell technologies for new technology 
add-on payments when assigned to MS-DRG 018. As we have noted in prior 
rulemaking with regard to the CAR T-cell therapies (83 FR 41172 and 85 
FR 58603 through 58608), if a new MS-DRG were to be created, then 
consistent with section 1886(d)(5)(K)(ix) of the Act,

[[Page 45031]]

there may no longer be a need for a new technology add-on payment under 
section 1886(d)(5)(K)(ii)(III) of the Act.
    We invited public comment on whether ABECMA[supreg] meets the cost 
criterion.
    Comment: We received a comment from MEDPAC which addressed the cost 
criterion in general as it relates to CAR T-cell therapies. Please 
refer to the response in the BREYANZI[supreg] application in section 
II.F.X.c. of the preamble of this final rule for detailed discussion of 
this issue.
    Comment: We received multiple comments in response to our concern 
for CAR T-cell therapy, the MS-DRG 018 assignment, and new technology 
add-on payment eligibility.
    Response: For a complete discussion of these comments and our 
response, please see the BREYANZI[supreg] application in section 
II.F.X.c. of the preamble of this final rule.
    Comment: A few commenters suggested that CMS should establish a new 
technology add-on payment pathway specific to gene therapies similar to 
that of the QIDP and breakthrough device designation. These commenters 
suggested that these new pathways will provide streamlined 
opportunities for novel therapies to receive new technology add-on 
payment under the IPPS. Some commenters stated that CMS should create a 
category such as Regenerative Medicine Advanced Therapy (RMAT) 
designation to meet the newness and substantial clinical improvement 
new technology add-on payment criteria.
    Response: We did not propose to add a new pathway to the new 
technology add-on payment evaluation process. We believe this comment 
is outside the scope of this rule.
    Comment: In response to CMS' concerns, the applicant submitted 
similar comments to those submitted by the applicant for 
BREYANZI[supreg]. As discussed previously, the applicant stated in its 
comment that CAR T-cell therapies that meet the cost and other criteria 
for new technology add-on payment status should continue to be eligible 
for new technology add-on payment status notwithstanding the creation 
of MS-DRG 018. The applicant stated that there is still a need for new 
technology add-on payment status for new CAR T-cell therapies, like 
ABECMA[supreg], to ensure patient access. Further, the applicant stated 
while the payment amount for MS-DRG 018 is certainly more aligned with 
CAR T-cell therapy costs generally, ABECMA[supreg] exceeds the cost 
threshold for MS-DRG 018, meaning that the reimbursement rate for MS-
DRG 018 is not adequate for ABECMA[supreg]. The applicant asserted that 
per CMS, this is precisely the type of scenario that the new technology 
add-on payment is intended to address.
    In responses to CMS' concerns regarding the cost criterion and the 
variability of provider billing and charging practices for CAR T-cell 
therapies (86 FR 25258), the applicant stated they considered the 
variability of CAR T-cell charging practices when developing its cost 
analyses and presented options that were intended to address this 
variability by using more conservative assumptions than have typically 
been the case for other new technology add-on payment applications. The 
applicant stated that most new technology add-on payment applications 
use the national average CCR for the cost center for which the new 
technology belongs is used to inflate the acquisition cost for the new 
technology to charges. The applicant added that in the case of a drug 
or biological, this would mean that the inverse of the national average 
CCR for drugs would be used to convert the WAC of ABECMA[supreg] to 
charges. The applicant stated that using the pharmacy CCR in the 
prescribed manner would result in charges that would potentially 
overstate actual hospital charging practices for CAR T-cell therapies. 
Furthermore, the applicant noted that numerous studies on charge 
compression have shown that hospital charging practices tend to result 
in higher markup percentages for lower cost drugs and lower markup 
percentages for higher cost drugs. The applicant added that given that 
the WAC for ABECMA[supreg] is well above the average of drugs overall, 
they were concerned that using the inverse of the national average drug 
CCR might overstate what hospitals would typically charge for 
ABECMA[supreg] on inpatient claims. Therefore, the applicant calculated 
a CAR T-cell specific CCR based solely on the total drug charges for 
CAR T-cell claims.
    The applicant stated that to calculate the CAR T-cell CCR, they 
took the total drugs charges for cases in MS-DRG 018 from the FY 2021 
IPPS/LTCH PPS final rule After Outliers Removed/Before Outliers Removed 
(AOR/BOR) file ($183,433,947.58). Next, the applicant divided that 
amount by the number of cases (145) to determine an average drug charge 
per case ($1,265,061.70). The applicant then divided that amount by 
$373,000, the acquisition cost of YESCARTA[supreg] and KYMRIAH[supreg]. 
This value represents the average mark-up percentage hospitals used to 
convert the cost of CAR T-cell therapy to charges on claims in FY 2019. 
The applicant converted this mark-up percentage to a CCR by dividing 1 
by the percentage (1/3.39 = 0.295).
    Ultimately, the applicant stated that it recognizes CMS's concern 
that hospitals vary in their CAR T-cell charging practices but states 
their method for calculating a CAR T-cell specific CCR is meant to 
address this exact concern. The applicant asserted that by focusing 
solely on CAR T-cell claims, they are able to capture the range of 
charging practices in hospitals that used a CAR T-cell therapy in a 
non-clinical trial case in 2019. Furthermore, the applicant stated that 
in addition to addressing the concerns about variability in hospital 
charging practices, the CAR T-cell CCR is also a more conservative 
assumption to use in the cost threshold analysis because it inflates 
CAR T-cell costs to charges at a lower percentage (339%) than if the 
inverse of the national average drug CCR is used (535%).
    Response: We appreciate the information provided by the applicant 
in their comment in regard to their calculation of a CAR T-cell CCR. As 
we stated in section E.2.b. of this rule, we continue to believe that 
it is premature to make structural changes to the IPPS at this time to 
pay for CAR T-cell therapies (78 FR 58453). As we gain more experience 
paying for these therapies under the IPPS, we may consider these 
comments to inform future rulemaking. However, we appreciate the 
thoughtfulness used by the applicant to provide as clear as possible a 
description of CAR T-cell therapy cost calculations. We appreciate the 
usage of multiple cost analyses, such as varying the CCR used to 
inflate cost to charges, which potentially allowed for a more 
conservative markup.
    After consideration of the public comments we received and based on 
the information included in the applicant's new technology add-on 
payment application, we believe that the ABECMA[supreg] system meets 
the cost criterion.
    With regard to the substantial clinical improvement criterion, the 
applicant asserted that it believes that ABECMA[supreg] represents a 
substantial clinical improvement over existing technologies because: 
(1) The totality of the circumstances regarding ABECMA[supreg]'s 
clinical efficacy, safety, and data make clear that ABECMA[supreg] 
substantially improves, relative to services or technologies currently 
available, the treatment of Medicare beneficiaries with RRMM; (2) 
ABECMA[supreg] has superior effectiveness compared to existing 
therapies; (3) ABECMA[supreg] fills an unmet need as demonstrated by 
the patient population in its registrational study,

[[Page 45032]]

which is reflective of real-world RRMM patients and 4) ABECMA[supreg] 
improves quality of life for patients with RRMM.
    In support of its assertion that the totality of the circumstances 
regarding ABECMA[supreg]'s clinical efficacy, safety, and data make 
clear that ABECMA[supreg] substantially improves, relative to services 
or technologies currently available, the treatment of Medicare 
beneficiaries with RRMM, the applicant cited results from the KarMMA 
study, a single-arm, open-label, phase 2 trial of ABECMA[supreg]. The 
primary outcome measure for the KarMMA study was overall response rate 
(ORR). Secondary endpoints were; complete response rate (CRR) (key 
secondary; null hypothesis <=10%), safety, duration of response (DOR), 
progression-free survival (PFS), overall survival (OS), 
pharmacokinetics (PK), minimum residual disease (MRD), quality of life 
(QOL) and health economics and outcomes research (HEOR). The study 
enrolled 140 patients and 128 received treatment. Patients were treated 
at target dose between 150 and 450 x 10\6\ CAR T-cells. Treated 
patients had received three or more prior lines of therapy including an 
immunomodulatory drug (IMiD), a proteasome inhibitor (PI), and an anti-
CD38 antibody. All patients were refractory to the last regimen (94% 
were refractory to anti-CD38 and 84% were refractory to triple 
therapy). Efficacy results showed an ORR of 50% for patients (n=4) 
receiving the target ABECMA[supreg] dose of 150 x 10\6\; 68.6% for 
patients (n=70) receiving the target dose of 300 x 10\6\; 81.5% for 
patients (n=54) receiving the target dose of 450 x 10\6\. The overall 
ORR for all patients (n=128) who received ABECMA[supreg] was 73.4%.
    The applicant asserts that in the KarMMA study, patients who 
received ABECMA[supreg] achieved numerically superior response rates, 
duration of response, and overall survival compared with outcomes seen 
for alternative therapies (belantamab-mafodotin and selinexor) in other 
trials.248 249 250 251 252 253 Response rates, according to 
the applicant, were also high even in patients refractory to five 
therapies (defined as 2 IMiD agents, 2 PIs, and 1 anti-CD38 antibody), 
reflecting the novel mechanism of action, according to the applicant. 
The applicant asserts that compared with anti-CD-19 CAR T-cell 
therapies, the adverse event profile revealed low rates of grade 3+ CRS 
(5%) and neurotoxicity (NT) (3%).\254\ According to the applicant, 
these safety results confirm that ABECMA[supreg] has the potential to 
offer a meaningful benefit to Medicare beneficiaries. The applicant 
also asserts that ABECMA[supreg] has been demonstrated to be effective 
and with a manageable safety profile for patients with a high-unmet 
need (older age, aggressive disease). The applicant asserts that the 
results from the pivotal KarMMa study confirm the clinical benefit of 
ABECMA[supreg] in a heavily pre-treated RRMM patient population.
---------------------------------------------------------------------------

    \248\ Munshi NC, Anderson, Jr LD, Shah N, et al. Idecabtagene 
vicleucel (ide-cel; bb2121), a BCMA-targeted CAR T-cell therapy, in 
patients with relapsed and refractory multiple myeloma (RRMM): 
Initial KarMMa results. J Clin Oncol. 2020;38(15_suppl):8503-8503. 
doi:10.1200/JCO.2020.38.15_suppl.8503.
    \249\ Rodriguez-Otero P, Weisel K, Davies F, et al. Matching-
adjusted indirect comparisons of efficacy outcomes for idecabtagene 
vicleucel from the KARMMA study vs selinexor plus dexamethasone 
(STORM part 2) and belantamab mafodotin (DREAMM-2). In: European 
Hematology Association. ; 2020.
    \250\ Jagannath S, Lin Y, Goldschmidt H, et al. KarMMa-RW: A 
study of real-world treatment patterns in heavily pretreated 
patients with relapsed and refractory multiple myeloma (RRMM) and 
comparison of outcomes to KarMMa. J Clin Oncol. 
2020;38(15_suppl):8525-8525. doi:10.1200/jco.2020.38.15_suppl.8525.
    \251\ Raje N, Berdeja J, Lin Y, et al. Anti-BCMA CAR T-cell 
therapy bb2121 in relapsed or refractory multiple myeloma. N Engl J 
Med. 2019;380(18):1726-1737. doi:10.1056/NEJMoa1817226.
    \252\ Lonial S, Lee HC, Badros A, et al. Belantamab mafodotin 
for relapsed or refractory multiple myeloma (DREAMM-2): A two-arm, 
randomised, open-label, phase 2 study. Lancet Oncol. 2020;21(2):207-
221. doi:10.1016/S1470-2045(19)30788-0.
    \253\ Chari A, Vogl DT, Gavriatopoulou M, et al. Oral Selinexor-
Dexamethasone for Triple-Class Refractory Multiple Myeloma. N Engl J 
Med. 2019;381(8):727-738. doi:10.1056/nejmoa1903455.
    \254\ Munshi NC, Anderson, Jr LD, Shah N, et al. Idecabtagene 
vicleucel (ide-cel; bb2121), a BCMA-targeted CAR T-cell therapy, in 
patients with relapsed and refractory multiple myeloma (RRMM): 
Initial KarMMa results. J Clin Oncol. 2020;38(15_suppl):8503-8503.
---------------------------------------------------------------------------

    We noted in the proposed rule that in contrast with anti-CD-19 CAR 
T-cell therapies (for leukemia or lymphoma) where a high fraction of 
responders remained in remission even after 5 years, ABECMA[supreg] 
does not appear to result in long-term remission. In the KarMMA study, 
among responding patients, over 75% relapsed by 20 months, with no 
plateauing of the response curve.\255\
---------------------------------------------------------------------------

    \255\ Ibid.
---------------------------------------------------------------------------

    To support its assertion that ABECMA[supreg] has superior 
effectiveness compared to existing therapies, the applicant provided 
results from the KarMMa-RW study,\256\ a single-arm, open-label, phase 
2 trial, examining real-world treatment patterns in heavily pretreated 
patients with RRMM. The study also provides a comparison against 
outcomes in the KarMMa study. The KarMMa-RW study was conducted to 
assess treatment patterns in real-world RRMM patients with 
characteristics similar to the KarMMa population and to compare 
outcomes with currently available therapies in this synthetic cohort vs 
ABECMA[supreg] therapy in the KarMMa study. The primary endpoint of the 
KarMMA-RW study was overall response rate (ORR). Secondary endpoints of 
the study were complete response rate (CRR), very good partial response 
(VGPR) rate, progression free survival (PFS) and overall survival (OS). 
Subgroup analyses by age, sex, double-class refractory (IMiD agents and 
PIs) and number of prior anti-myeloma regimens per year (<=1 per year 
or >1) were conducted to compare ORR and PFS between the KarMMa cohort 
and eligible RRMM cohort. Since complete response assessment requires a 
bone marrow biopsy evaluation, per International Myeloma Working Group 
(IMWG) uniform response criteria for multiple myeloma, when data to 
assess a complete response were not available in eligible RRMM cohort, 
analyses were summarized for VGPR or better (>=VGPR) to avoid 
underestimating the response in the eligible RRMM cohort.
---------------------------------------------------------------------------

    \256\ Jagannath S, Lin Y, Goldschmidt H, et al. KarMMa-RW: A 
study of real-world treatment patterns in heavily pretreated 
patients with relapsed and refractory multiple myeloma (RRMM) and 
comparison of outcomes to KarMMa. J Clin Oncol. 
2020;38(15_suppl):8525-8525.
---------------------------------------------------------------------------

    Of 1,949 real-world RRMM patients, 1,171 were refractory to their 
last treatment regimen at baseline. Patients who had exposure to any 
BCMA-directed therapy or gene-modified therapy were excluded. Of the 
1,171 patients in the refractory RRMM cohort, 528 received the next 
line of therapy; 643 patients were excluded due to no new treatment due 
to death (n = 441) and no new treatment due to no follow-up (n = 202). 
Of the remaining 528 patients, 190 triple class exposed patients were 
selected as the eligible RRMM cohort based on the KarMMa eligibility 
criteria. The ORR in the KarMMa and eligible RRMM cohorts was 76% and 
32% ( p = <0.0001), respectively. The VGPR in the KarMMa and eligible 
RRMM cohorts was 57% and 14% (p = <0.0001), respectively.
    A matched-paired analysis was conducted and ORR was adjusted for 
matching. Results from the matched-paired analysis were consistent with 
the primary analysis: the ORR for the matched KarMMa cohort (n=76-80) 
and matched eligible RRMM (n=76-80) was 72% and 29% (p = <0.0001), 
respectively. According to the applicant, PFS was significantly 
improved in KarMMa vs the eligible RRMM cohort; median PFS was 11.3 
months and 3.5 months in the KarMMa and Eligible

[[Page 45033]]

RRMM cohorts, respectively (p = <0.0001). Median follow-up was 11.3 
months (KarMMa) and 10.2 months (eligible RRMM cohort) at data cutoff. 
According to the applicant, OS was significantly improved in KarMMa vs 
the eligible RRMM cohort. OR was 18.2 months for the KarMMa cohort 
(across all target doses from 150-450 x 10\6\ CAR T-cells) and 14.7 
months for the eligible RRMM cohort. The estimated 12-month probability 
of surviving was 80% in the KarMMa cohort and 56% in the eligible RRMM 
cohort. Median follow-up was 12.0 months (KarMMa) and 15.0 months 
(eligible RRMM cohort) among surviving patients at data cutoff.
    The applicant asserts that the results from the KarMMa-RW study 
confirm that there is no clear standard of care for RRMM patients who 
received at least 3 prior therapies, including IMiD agents, PIs, and 
anti-CD38 antibodies. Patients in the eligible RRMM cohort received 94 
different treatment regimens as next-line therapy and according to the 
applicant, outcomes were sub-optimal with currently available therapies 
in the real-world RRMM patients. The applicant asserts that 
significantly improved outcomes were demonstrated with ABECMA[supreg] 
treatment in the KarMMa cohort vs the similar real-world population 
(eligible RRMM cohort). The applicant noted that the real world myeloma 
patient population is older (MM incidence is known to increase with 
age, with over 60 percent of all new cases occurring in adults aged 
65+years).\257\ The applicant asserts that results were consistent 
across subgroups including patients aged >= 65 years.
---------------------------------------------------------------------------

    \257\ Cancer Stat Facts: Myeloma, NCI SEER, https://seer.cancer.gov/statfacts/html/mulmy.html (last visited October. 7, 
2020).
---------------------------------------------------------------------------

    The applicant also provided a comparison of the efficacy of 
ABECMA[supreg] and Xpovio[supreg] from the STORM study and Blenrep from 
the DREAMM-2 study. STORM is a prospective, multicenter phase 2 study 
of Xpovio[supreg] and dexamethasone in patients with RRMM (n = 122) in 
the 4L+ setting. The STORM trial served as the basis for regulatory 
approval in the US and demonstrated the clinical efficacy and safety of 
Xpovio[supreg]. The ORR was 26% for patients in the STORM study vs 73% 
for patients treated with ABECMA[supreg] in the KarMMa study, CR was 1% 
for patients in the STORM study vs 33% for patients treated with 
ABECMA[supreg] in the KarMMa study, medium duration of response (mDOR) 
was 4.4 months for patients in the STORM study vs 10.7 months for 
patients treated with ABECMA[supreg] in the KarMMa study, and PFS was 
3.7 months for patients in the STORM study vs 8.8 months for patients 
treated with ABECMA[supreg] in the KarMMa study. The DREAMM-2 study is 
a prospective, multicenter Phase 2 study of Blenrep in patients with 
RRMM (n = 122) in the 4L+ setting. The ORR was 31% for patients in the 
DREAMM-2 study vs 73% for patients treated with ABECMA[supreg] in the 
KarMMa study, CR was 3% for patients in the DREAMM-2 study vs 33% for 
patients treated with ABECMA[supreg] in the KarMMa study, medium 
duration of response (mDOR) was not reached in the Blenrep group 
whereas it was 10.7 months for patients treated with ABECMA[supreg] in 
the KarMMa study, and PFS was 2.9 months for patients in the DREAMM-2 
study vs 8.8 months for patients treated with ABECMA[supreg] in the 
KarMMa study.
    Because ABECMA[supreg] showed improved ORR, CR, medDOR and PFS when 
compared to Xpovio[supreg] and Blenrep, the applicant asserts that 
ABECMA[supreg] provides a substantial clinical improvement over these 
existing therapies.
    To support that ABECMA[supreg] fills an unmet need as demonstrated 
by the patient population in its registrational study, the Phase 2 
KarMMa study, the applicant asserted that in addition to showing deep 
and durable responses and a manageable safety profile in heavily 
pretreated, highly refractory RRMM patients in the context of 
controlled clinical studies, comparisons of outcomes in real world 
patients (that is, patients not enrolled in clinical trials) support 
the assertion that ABECMA[supreg] offers significantly improved 
outcomes for RRMM compared with currently available therapies. The 
applicant asserted that when compared to myeloma patients generally 
included in clinical studies, the real world myeloma patient population 
is older (MM incidence is known to increase with age, with over 60 
percent of all new cases occurring in adults aged  
65years)\258\ and sicker (due to the high proportion of elderly 
patients in this population, those with MM commonly also have 
additional comorbidities associated with increased age, including 
conditions such as osteoporosis, arthritis, diabetes, additional 
malignancies, cardiovascular disease, and renal dysfunction, amongst 
others).\259\ The applicant provided an abstract from the MAMMOTH 
study, a noninterventional, retrospective cohort analysis conducted to 
assess outcomes in patients after they become refractory to anti-CD38 
monoclonal antibodies, including a subset of patients who were triple-
class-exposed. Patients in STORM (analyzing Xpovio[supreg] plus 
dexamethasone) had an ORR of 32.8% versus 25% for patients receiving 
conventional care in MAMMOTH (p=0.078) and STORM patients had better OS 
than patients in MAMMOTH (median 10.4 vs 6.9 months) (p=0.043). The 
applicant asserts that these results highlight a high unmet need in a 
patient population refractory to anti-CD38 monoclonal antibody, 
including a subset of triple-class exposed patients.
---------------------------------------------------------------------------

    \258\ Cancer Stat Facts: Myeloma, NCI SEER, https://seer.cancer.gov/statfacts/html/mulmy.html (last visited Oct. 7, 
2020).
    \259\ Hari P et al. The impact of age and comorbidities on 
practice patterns and outcomes in patients with relapsed/refractory 
multiple myeloma in the era of novel therapies. Journal of Geriatric 
Oncology. 2018;9(2):138-144 (Hari, 2018).
---------------------------------------------------------------------------

    To support the assertion that ABECMA[supreg] improves quality of 
life for patients with RRMM, the applicant referenced ABECMA[supreg]'s 
impact on Health-related quality of life (HRQoL) as assessed in the 
KarMMa study as a secondary endpoint. HRQoL was assessed using the 
European Organization for Research and Treatment of Cancer (EORTC) 
Quality of Life C30 Questionnaire (QLQ-C30) and the EORTC Multiple 
Myeloma Module (MY20). The QLQ-C30 consists of 30 questions addressing 
5 functional domain scales, 3 symptom scales, a Global health/QoL 
scale, and 6 single item measures.\260\ The QLQ-MY20 consists of 20 
questions addressing 4 myeloma-specific HRQoL domains (disease 
symptoms, side effects of treatment, future perspectives, and body 
image). Primary subscales of interest were QLQ-C30 Fatigue, Pain, 
Physical Functioning, Cognitive Functioning, and Global Health/QoL 
subscales and QLQ-MY20 Symptom and Side Effects subscales. Subscales 
were preselected based on their relevance to this patient population. 
The data are based on a minimum of 10 months post-infusion. Median 
follow-up durations at the target dose levels of 150, 300, and 450 x 
10\6\ CAR T-cells were 17.8, 13.9, and 9.7 months, respectively. Of 140 
patients enrolled in KarMMa, 128 received ABECMA[supreg], of whom 121 
(94.5%) and 120 (93.8%) were evaluable for HRQoL by QLQ-C30 and QLQ-
MY20, respectively. At baseline, ABECMA[supreg]-treated patients had 
less favorable scores for all QLQ-C30 domains of interest (fatigue, 
pain, Global Health/QoL, physical functioning and cognitive 
functioning) than the general population. From baseline at multiple

[[Page 45034]]

time points through month 9 post-infusion, the applicant asserts that 
clinically meaningful improvements were observed in QLQ-C30 Fatigue, 
Pain, Physical Functioning, and Global Health subscale scores relative 
to baseline, as the mean score from baseline showed improvement in all 
domains. The applicant asserts that these results support that 
ABECMA[supreg] provides meaningful improvements in HRQoL and self-
reported symptoms associated with heavily pretreated RRMM and 
demonstrate that ABECMA[supreg] provides meaningful improvement in both 
global function and symptoms related to MM.
---------------------------------------------------------------------------

    \260\ Helena Maes & Michel Delforge (2015) Optimizing quality of 
life in multiple myeloma patients: current options, challenges and 
recommendations, Expert Review of Hematology, 8:3, 355-366, DOI: 
10.1586/17474086.2015.1021772
---------------------------------------------------------------------------

    After reviewing the information submitted by the applicant as part 
of its FY 2022 new technology add-on payment application for 
ABECMA[supreg], we stated in the proposed rule that we questioned 
whether, due to the lack of randomization, there is sufficient evidence 
to establish the efficacy of ABECMA[supreg] compared with current 
alternatives. We stated that it is unknown whether the superior 
outcomes for ABECMA[supreg] in the KarMMA study, which we stated has 
not been peer-reviewed, were due to more effective therapy or other 
factors, such as differences in patient population or treating 
oncologist. We also noted that the applicant chose to use ORR data as a 
measure of substantial clinical improvement rather than the more 
clinically relevant and available OS data.
    We invited public comment on whether ABECMA[supreg] meets the 
substantial clinical improvement criterion.
    Comment: In response to CMS' concerns regarding the substantial 
clinical improvement criterion, the applicant submitted a comment 
stating that ABECMA[supreg] is a substantial clinical improvement over 
existing technologies because: (1) The totality of the circumstances 
regarding ABECMA[supreg]'s clinical efficacy, safety, and data make 
clear that ABECMA[supreg] substantially improves, relative to services 
or technologies currently available, the treatment of Medicare 
beneficiaries with RRMM; (2) ABECMA[supreg] has superior effectiveness 
compared to existing therapies; (3) ABECMA[supreg] fills an unmet need 
as demonstrated by the patient population in its registrational study, 
which is reflective of real-world RRMM patients, and (4) ABECMA[supreg] 
improves quality of life for patients with RRMM.
    The applicant stated that it is essential for CMS to recognize that 
multiple myeloma is a different disease from NHL, where CD-19 CAR T 
directed therapies are approved.\261\ The applicant added multiple 
myeloma is a disease characterized by persistence of residual disease 
and multiple periods of remission and relapse, with cure not generally 
achieved by conventional therapies.\262\ The applicant added that only 
long-term follow-up data will definitively show if a plateau in 
survival occurs after BCMA directed CAR T-cell treatment and that the 
KarMMA study presented data after a median follow up of 13.3 months.
---------------------------------------------------------------------------

    \261\ Nair, R. and J. Westin, CAR T cells. Adv Exp Med Biol, 
2020. 1244: 215-233.
    \262\ Kumar, S.K., et al., Multiple myeloma. Nat Rev Dis 
Primers, 2017. 3: 17046; Rajkumar, S.V. and S. Kumar, Multiple 
Myeloma: Diagnosis and Treatment. Mayo Clin Proc, 2016. 91(1): 101-
19.
---------------------------------------------------------------------------

    The applicant stated that they believe it is not appropriate to 
compare outcomes between different CAR T-cell therapies approved and 
studied in patients with completely different diseases where the most 
appropriate comparison is between treatments indicated for the same 
patient population and disease. According to the applicant, the updated 
results, after a median follow up of 24.8 months, from the pivotal 
KarMMa study demonstrated outcomes remained consistent with those 
initially reported.\263\ The applicant stated that the CR/sCR rate 
remained 33% across all doses studied with an estimated median PFS was 
8.6 months for all patients and 12.2 months for patients treated at the 
450 x 106 dose; for the 33% of patients on the KarMMa study who had a 
CR/sCR, the median duration of response increased to 20.2 months.\264\
---------------------------------------------------------------------------

    \263\ Larry D. Anderson, J., Nikhil C. Munshi, Nina Shah, Sundar 
Jagannath, Jesus G. Berdeja, Sagar Lonial, Noopur S. Raje, David S. 
Siegel, Yi Lin, Albert Oriol, Philippe Moreau, Ibrahim Yakoub-Agha, 
Michel Delforge, Fabio Petrocca, Payal Patel, Liping Huang, Timothy 
B. Campbell, Kristen Hege, Jes[uacute]s F. San-Miguel, Idecabtagene 
vicleucel (ide-cel, bb2121), a BCMA-directed CAR T cell therapy, in 
relapsed and refractory multiple myeloma: Updated KarMMa results. 
ASCO 2021 Conference Proceedings, 2021: 8016.
    \264\ Munshi, N.C., et al., Idecabtagene Vicleucel in Relapsed 
and Refractory Multiple Myeloma. New England Journal of Medicine, 
2021. 384(8): p. 705-716.
---------------------------------------------------------------------------

    The applicant disagreed with CMS's concerns surrounding the lack of 
randomization, peer-review status, and use of ORR as a measure of 
substantial clinical improvement. The applicant states that the results 
from the KarMMa study, which supported the FDA approval of 
ABECMA[supreg], were published February 2021 in the New England Journal 
of Medicine.\265\
---------------------------------------------------------------------------

    \265\ Munshi, N.C., et al., Idecabtagene Vicleucel in Relapsed 
and Refractory Multiple Myeloma. New England Journal of Medicine, 
2021. 384(8): p. 705-716.
---------------------------------------------------------------------------

    The applicant stated that the KarMMa study, while using ORR as a 
primary endpoint, also demonstrated improvements in complete response 
(CR) rate, duration of response, PFS and OS compared with conventional 
therapies. The applicant stated that two analyses compared patients 
enrolled in the KarMMa clinical study to similar patients treated with 
conventional therapy enrolled on other observational studies: MAMMOTH 
266 267 in which a matched adjusted indirect comparison 
(MAIC) demonstrated that ABECMA[supreg] offers statistically 
significant, clinically meaningful improvements in ORR, OS, and PFS 
when compared with conventional care and regimens, and KarMMa-RW in 
which the median progression free survival was observed to be higher in 
the KarMMa group at 11.3 versus 3.5 months in the similar RW cohort and 
overall survival 18.2 versus 14.7 months, respectively.
---------------------------------------------------------------------------

    \266\ Gandhi, U.H., et al., Outcomes of patients with multiple 
myeloma refractory to CD38-targeted monoclonal antibody therapy. 
Leukemia, 2019. 33(9): 2266-2275.
    \267\ Shah, N., et al., A Matching-Adjusted Indirect Comparison 
of Efficacy Outcomes for Idecabtagene Vicleucel (ide-cel, bb2121), a 
BCMA-Directed CAR T Cell Therapy Versus Conventional Care in Triple-
Class-Exposed Relapsed and Refractory Multiple Myeloma. Blood, 2020. 
136 (Supplement 1): 6-7.
---------------------------------------------------------------------------

    The applicant concluded that the totality of the clinical efficacy 
and safety data from the prescribing information demonstrates that 
ABECMA[supreg] has equal or better efficacy and a better safety profile 
than existing therapeutic alternatives in a broad RRMM patient 
population, including patients aged 65+ years. Based on an updated 
analysis of overall survival for patients, the applicant asserts that 
after a median follow up of 24.8 months, 51% of patients remain alive 
two years after treatment with ABECMA[supreg] with an estimated median 
OS of 24.8 months.\268\ According to the applicant, median survival 
expectation with conventional therapies in this heavily pre-treated 
patient population (median 6 (3-16) prior lines), 94% refractory to 
anti-CD38 antibody, 84% refractory to all three of the main classes of 
antimyeloma drugs) is estimated at 9.3 months.\269\ Therefore

[[Page 45035]]

the applicant asserted ABECMA[supreg] is clearly a substantial clinical 
improvement over alternative therapies for patients with RRMM after 
four or more prior lines of therapy.
---------------------------------------------------------------------------

    \268\ Larry D. Anderson, J., Nikhil C. Munshi, Nina Shah, Sundar 
Jagannath, Jesus G. Berdeja, Sagar Lonial, Noopur S. Raje, David S. 
Siegel, Yi Lin, Albert Oriol, Philippe Moreau, Ibrahim Yakoub-Agha, 
Michel Delforge, Fabio Petrocca, Payal Patel, Liping Huang, Timothy 
B. Campbell, Kristen Hege, Jes[uacute]s F. San-Miguel, Idecabtagene 
vicleucel (ide-cel, bb2121), a BCMA-directed CAR T cell therapy, in 
relapsed and refractory multiple myeloma: Updated KarMMa results. 
ASCO 2021 Conference Proceedings, 2021: 8016.
    \269\ Larry D. Anderson, J., Nikhil C. Munshi, Nina Shah, Sundar 
Jagannath, Jesus G. Berdeja, Sagar Lonial, Noopur S. Raje, David S. 
Siegel, Yi Lin, Albert Oriol, Philippe Moreau, Ibrahim Yakoub-Agha, 
Michel Delforge, Fabio Petrocca, Payal Patel, Liping Huang, Timothy 
B. Campbell, Kristen Hege, Jes[uacute]s F. San-Miguel, Idecabtagene 
vicleucel (ide-cel, bb2121), a BCMA-directed CAR T cell therapy, in 
relapsed and refractory multiple myeloma: Updated KarMMa results. 
ASCO 2021 Conference Proceedings, 2021: 8016; Gandhi, U.H., et al., 
Outcomes of patients with multiple myeloma refractory to CD38-
targeted monoclonal antibody therapy. Leukemia, 2019. 33(9): 2266-
2275.
---------------------------------------------------------------------------

    Response: We appreciate the information provided by the applicant 
in their public comment. Based on the additional information received, 
we agree that ABECMA[supreg] represents a substantial clinical 
improvement over existing technologies for the treatment of adult 
patients with relapsed or refractory multiple myeloma after four or 
more prior lines of therapy, including an immunomodulatory agent, a 
proteasome inhibitor, and an anti-CD38 monoclonal antibody. We believe 
that the updated analysis information provided by the applicant 
demonstrated statistically significant and clinically meaningful 
improvements in ORR, OS, and PFS for patients treated with 
ABECMA[supreg]. We also agree with the applicant that ABECMA[supreg] 
fills an unmet need in the 4L+ treatment of RRMM as it offers a 
treatment option for patients unresponsive to currently available 
therapies.
    After consideration of the public comments we received and the 
information included in the applicant's new technology add-on payment 
application, we have determined that ABECMA[supreg] meets the criteria 
for approval of the new technology add-on payment. Therefore, we are 
approving new technology add-on payments for this technology for FY 
2022. Cases involving the use of ABECMA[supreg] that are eligible for 
new technology add-on payments will be identified by procedure codes 
XW033K7 (Introduction of idecabtagene vicleucel immunotherapy into 
peripheral vein, percutaneous approach, new technology group 7) or 
XW043K7 (Introduction of idecabtagene vicleucel immunotherapy into 
central vein, percutaneous approach, new technology group 7).
    In its application, the applicant estimated that the cost of 
ABECMA[supreg] is $419,500.00 per patient. Under Sec.  412.88(a)(2), we 
limit new technology add-on payments to the lesser of 65 percent of the 
average cost of the technology, or 65 percent of the costs in excess of 
the MS-DRG payment for the case. As a result, the maximum new 
technology add-on payment for a case involving the use of 
ABECMA[supreg] is $272,675.00 for FY 2022.
h. INDIGO Aspiration System With Lightning Aspiration Tubing
    Penumbra, Inc. submitted an application for the INDIGO[supreg] 
Aspiration System with Lightning Tubing (``INDIGO[supreg] with 
Lightning'') for FY 2022. Per the applicant, INDIGO[supreg] with 
Lightning is a mechanical thrombectomy aspiration system used in the 
treatment of pulmonary embolism, deep vein thrombosis and peripheral 
arterial thromboembolism that optimizes thrombus removal by 
differentiating between thrombus and blood.
    According to the applicant, INDIGO[supreg] with Lightning performs 
clot detection and removal via smart technology which enables the 
physician to determine when the catheter is in thrombus and when it is 
in patent flow resulting in blood loss reduction through intermittent 
aspiration mechanical thrombectomy. The applicant stated that 
INDIGO[supreg] with Lightning is used for the removal of fresh, soft 
emboli and thrombi from vessels of the peripheral arterial and venous 
systems, and for the treatment of pulmonary embolism. The applicant 
stated that the INDIGO[supreg] with Lightning is composed of a 
mechanical thrombectomy aspiration pump (known as the Penumbra Engine) 
that is packaged with INDIGO[supreg] CAT12 (12 French) and CAT8 (8 
French) catheters as well as Lightning, a clot detection/blood loss 
reduction technology embedded in the Penumbra Engine pump and tubing.
    Arterial thromboembolism can result in acute limb ischemia (ALI) 
which requires emergent treatment. Venous thromboembolism is a 
condition which includes both deep vein thrombosis (DVT) and pulmonary 
embolism (PE) and occurs in 1 to 2 individuals per 1000 per year and is 
predominantly a disease of older age.\270\ The 2020 American Society of 
Hematology guidelines for venous thromboembolism include 
recommendations for the treatment of patients with both pulmonary 
embolism and deep vein thrombosis, and recommended treatments include 
home care, systemic pharmacological thrombolysis, and procedural 
care.\271\
---------------------------------------------------------------------------

    \270\ Heit, John A. ``Epidemiology of venous thromboembolism.'' 
Nature reviews. Cardiology vol. 12,8 (2015): 464-74. doi:10.1038/
nrcardio.2015.83.
    \271\ Thomas L. Ortel, Ignacio Neumann, Walter Ageno, Rebecca 
Beyth, Nathan P. Clark, Adam Cuker, Barbara A. Hutten, Michael R. 
Jaff, Veena Manja, Sam Schulman, Caitlin Thurston, Suresh Vedantham, 
Peter Verhamme, Daniel M. Witt, Ivan D. Florez, Ariel Izcovich, 
Robby Nieuwlaat, Stephanie Ross, Holger J. Sch[uuml]nemann, Wojtek 
Wiercioch, Yuan Zhang, Yuqing Zhang; American Society of Hematology 
2020 guidelines for management of venous thromboembolism: Treatment 
of deep vein thrombosis and pulmonary embolism. Blood Adv 2020; 4 
(19): 4693-4738. doi: https://doi.org/10.1182/bloodadvances.2020001830.
---------------------------------------------------------------------------

    Procedural care may include open procedures as well as catheter-
directed thrombolysis and percutaneous mechanical thrombectomy.\272\ In 
catheter-directed thrombolysis, a thrombolytic agent is infused 
intravascularly adjacent to the clot burden through a percutaneous 
transcatheter.\273\ In percutaneous mechanical thrombectomy, the 
thrombus is lysed or removed mechanically. The therapies may be used 
separately or in conjunction with one another.\274\
---------------------------------------------------------------------------

    \272\ Karthikesalingam A, Young EL, Hinchliffe RJ, Loftus IM, 
Thompson MM, Holt PJ. A systematic review of percutaneous mechanical 
thrombectomy in the treatment of deep venous thrombosis. Eur J Vasc 
Endovasc Surg. 2011 Apr;41(4):554-65. doi: 10.1016/
j.ejvs.2011.01.010. Epub 2011 Feb 1. PMID: 21288745.
    \273\ Brown KN, Devarapally SR, Lee L, et al. Catheter Directed 
Thrombolysis Of Pulmonary Embolism. [Updated 2020 Apr 10]. In: 
StatPearls [internet]. Treasure Island (FL): StatPearls Publishing; 
2020 Jan. https://www.ncbi.nlm.nih.gov/books/NBK536918/.
    \274\ Karthikesalingam A, Young EL, Hinchliffe RJ, Loftus IM, 
Thompson MM, Holt PJ. A systematic review of percutaneous mechanical 
thrombectomy in the treatment of deep venous thrombosis. Eur J Vasc 
Endovasc Surg. 2011 Apr;41(4):554-65. doi: 10.1016/
j.ejvs.2011.01.010. Epub 2011 Feb 1. PMID: 21288745.
---------------------------------------------------------------------------

    The applicant stated that mechanical thrombectomy may be performed 
with a variety of devices. These methods include aspiration 
thrombectomy, rheolytic thrombectomy, and fragmentation 
thrombectomy.\275\
---------------------------------------------------------------------------

    \275\ Haude, M. Mechanical thrombectomy catheter systems. 
Interventional Cardiology 2007;2(1):58-60.
---------------------------------------------------------------------------

    The applicant stated that INDIGO[supreg] with Lightning differs 
from other mechanical thrombectomy devices on the basis of the use of a 
mechanical pump to generate a vacuum for aspiration and ``intelligent 
aspiration'' which differentiates clots and patient blood flow, thereby 
limiting blood loss. The applicant states that other endovascular 
mechanical thrombectomy devices do not provide aspiration using a 
vacuum. According to the applicant, the Lightning tubing performs clot 
detection using a proprietary algorithm. According to the applicant, 
once this ``smart technology'' detects free-flowing blood, it indicates 
patent flow to the physician and begins intermittent aspiration 
resulting in less blood loss during the procedure.
    The applicant submitted a request for a unique ICD-10-PCS code to 
identify the technology and was granted

[[Page 45036]]

approval for the following procedure codes effective October 1, 2021:
BILLING CODE 4120-01-P
[GRAPHIC] [TIFF OMITTED] TR13AU21.176

    INDIGO[supreg] with Lightning is a system with multiple components 
which have been reviewed by FDA both separately and as part of an 
overall system which includes catheters, tubing, and a vacuum pump. For 
the catheter portion of the system, INDIGO[supreg] aspiration catheter 
12 (12 French) and separator 12 received FDA 510(k) clearance on May 
28, 2020 for the removal of fresh, soft emboli and thrombi from vessels 
of the peripheral arterial and venous systems under FDA submission 
number K192981. The applicant stated that they submitted an application 
for FDA 510(k) clearance for that same technology (with a predicate 
which received clearance mentioned previously under submission number 
K192981) for indication of pulmonary embolism under FDA submission 
number K202821 for which clearance was completed on November 18, 2020. 
The INDIGO[supreg] aspiration catheter 12 and separator 12 received FDA 
510(k) clearance for the peripheral arterial and venous system on the 
basis of similarity to an earlier version of the same catheter and 
separator, which itself received FDA 510(k) clearance on May 26, 2015 
under FDA 510(k) number K142870 as part of the Penumbra Embolectomy 
System for the same indication. We note that the overall system 
received a second 510(k) clearance on December 20, 2019 under FDA 
510(k) number K192833 for the added indication of PE.
    With respect to the newness criterion for the tubing, the Lightning 
tubing received FDA 510(k) authorization for the removal of fresh, soft 
emboli and thrombi from vessels of the peripheral arterial and venous 
systems on March 13, 2020 under FDA 510(k) number K193244. The same 
tubing received

[[Page 45037]]

FDA 510(k) authorization for pulmonary embolism on April 22, 2020 under 
FDA 510(k) number K200771, which was granted based on substantial 
similarity to the same manufacturer's device. The predicate device for 
the peripheral arterial and venous system was an earlier version of the 
tubing without Lighting which itself received FDA 510(k) authorization 
on May 3, 2018 under FDA 510(k) number K180939.
    With respect to the newness criterion for the vacuum pump, the 
Penumbra Engine Pump and Canister received FDA 510(k) clearance for use 
in the peripheral arterial and venous systems (PAVS) on March 8, 2018 
under FDA 510(k) number K180105. The following table summarizes the FDA 
approval information listed in this section.
[GRAPHIC] [TIFF OMITTED] TR13AU21.177

BILLING CODE 4120-01-C
    The applicant has applied for new technology add-on payments for 
INDIGO[supreg] with Lightning when used for the treatment of venous 
thromboembolism, arterial thromboembolism, and pulmonary 
thromboembolism.
    As discussed previously, if a technology meets all three of the 
substantial similarity criteria, it would be considered substantially 
similar to an existing technology and would not be considered ``new'' 
for purposes of new technology add-on payments.
    With regard to the first criterion, whether a product uses the same 
or similar mechanism of action to achieve a therapeutic outcome, the 
applicant stated that INDIGO[supreg] with Lightning does not use the 
same or a similar mechanism of action when compared to an existing 
technology to achieve a therapeutic outcome. The applicant described 
differences between INDIGO[supreg] with Lightning and existing 
technologies based on the use of a mechanical pump to generate a vacuum 
for aspiration and the Lightning tubing, which the applicant stated 
limits blood loss and indicates clot versus patent flow. For pulmonary 
embolism and the peripheral system, the applicant identified Inari 
Flowtriever as an existing technology and noted that any aspiration 
provided using this system is provided via syringe as opposed to a 
vacuum pump. For the peripheral system, the applicant also identified 
Inari Flowtriever as using the same syringe method of aspiration. The 
applicant also identified two additional aspiration thrombectomy 
catheters, Angiojet[supreg] and Angiovac[supreg], used in the 
peripheral system and suggested that Angiojet[supreg] also uses a 
syringe for aspiration and that Angiovac[supreg] utilizes an 
extracorporeal bypass circuit that is created outside the body 
consisting of an outflow line, a centrifugal pump, a filter and an 
inflow line.
    With respect to the second criterion, whether a product is assigned 
to the same or a different MS-DRG, the applicant stated that services 
provided using this device would be captured under MS-DRGs 163-165 and 
270-272. MS-DRGs 163-165 address major chest procedures and MS-DRGs 
270-272 address other major cardiovascular procedures.
    With respect to the third criterion, whether the new use of the 
technology involves the treatment of the same or similar type of 
disease and the same or similar patient population when compared to an 
existing technology, the applicant did not address this criterion 
directly in the application, but stated that the new use of the 
INDIGO[supreg] System with Lighting is for the most recent FDA 
indication (April 2020) in PE. The applicant further stated that PE is 
not the same disease as arterial and venous thromboembolism; the 
patient populations may overlap, but are not identical.
    We noted the following concerns in the proposed rule (86 FR 25262 
through 25263) regarding whether the technology meets the substantial 
similarity criteria and whether it should be considered new. While the 
applicant discussed the differences between INDIGO[supreg] with 
Lighting and products made by other manufacturers, the applicant did 
not provide enough information regarding how INDIGO[supreg] with 
Lightning differs in its components from the existing aspiration 
thrombectomy catheters on the market to determine whether the 
technology uses a unique mechanism of action. We questioned whether the 
mechanism of action of the pump is different than that of the existing 
aspiration thrombectomy systems that also use a pump rather than a 
syringe, and how the mechanism of action of the separator, which is 
part of the catheter portion of the device, is different from that of 
existing thrombectomy systems that deploy a

[[Page 45038]]

device through the lumen of the catheter to break up the thrombus. We 
also noted that it was unclear what mechanism of action is used within 
the ``smart technology'' and how it may differ from other products 
which are intended to similarly reduce blood loss during the procedure. 
It was unclear if the ``smart technology'' resides within the pump, 
which was cleared by FDA 510(k) on March 8, 2018, or within the tubing, 
which was most recently cleared by FDA 510(k) on April 22, 2020. We 
noted that while the applicant did not directly address the third 
criterion within the application, based on the clinical uses of the 
device described in the application, we believed the INDIGO[supreg] 
with Lightning is intended for a patient population that is similar to 
the patient population treated by existing thrombectomy devices, 
including patients who receive percutaneous interventions for PE and 
peripheral arterial thromboembolism.
    We noted that the predicate device for the vacuum pump, the 
Penumbra Engine Pump and Canister, received FDA 510(k) clearance for 
use in the peripheral arterial and venous systems on March 8, 2018 
under FDA 510(k) number K180105 and therefore appears to no longer be 
considered new. We further noted that the catheter and tubing, as 
described in the 510(k) applications, appear to only have minor 
differences from their predicate devices such as length of tubing and 
shelf life, as opposed to elements that would affect the mechanism of 
action. If we determine that the catheter and tubing are substantially 
similar to the predicate devices cleared under FDA 510(k) numbers 
K142870 (May 26, 2015) and K180939 (May 3, 2018), respectively, the 
newness date of the INDIGO[supreg] with Lightning would correspond to 
the dates listed and therefore may no longer be considered new. We also 
noted that it is unclear whether the components of the system may be 
substantially similar to the overall system and whether the applicable 
newness date for each indication would therefore be the date of the 
overall system clearance for each indication, specifically May 26, 2015 
for peripheral arterial and venous systems and December 20, 2019 for 
pulmonary embolism.
    We invited public comment on whether INDIGO[supreg] with Lightning 
is substantially similar to other technologies and whether 
INDIGO[supreg] with Lightning meets the newness criterion.
    Comment: Several commenters asserted that INDIGO[supreg] with 
Lightning was substantially similar to other technologies and did not 
meet the qualifications for newness. These commenters suggested that 
the mechanism of action for INDIGO[supreg] with Lightning is identical 
to both previous versions of the same device (INDIGO[supreg] without 
Lightning) and other similar devices on the market. Specifically, a 
commenter identified the following examples of vacuum-based mechanical 
thrombectomy systems: Angiodynamics AngioVac System, the Philips 
QuickClear Mechanical Thrombectomy System, the Walk Vascular JETi 
Peripheral Thrombectomy System, and the Inari FlowTriever System. This 
commenter asserted that while INDIGO[supreg] with Lightning may be 
unique in using a pump to create a vacuum, other devices create a 
vacuum and the method of creating the vacuum is not relevant and does 
not represent a new mechanism of action. On the subject of the 
automated intermittent aspiration, some commenters noted that the same 
action can be completed using manual methods on the versions of 
INDIGO[supreg] without Lightning, such as by manually compressing the 
tubing to halt and restart suction, so that the automation does not 
represent a unique mechanism of action.
    Response: We thank the commenters for their input on the mechanism 
of action of INDIGO[supreg] with Lightning and have taken these 
comments into consideration in our evaluation of the newness criterion, 
which is discussed later in this section.
    Comment: The applicant submitted a letter stating that 
INDIGO[supreg] with Lightning meets the newness criterion. The 
applicant provided clarification regarding the INDIGO[supreg] with 
Lightning device and stated that the system is composed of two 
components: The engine that generates the vacuum (and can be used for 
multiple patients) which is a capital expense, and the Lightning 
device, tubing, catheter, and valve which are supplied together as a 
set and are single-use. The applicant stated that the Lightning device 
is the element of the system which is the subject of this application 
for new technology. The applicant also responded to our concern 
regarding when the device was cleared by the FDA, because we noted 
different dates of clearance for the pump and the tubing. The applicant 
asserted that because the Lightning device was an element of the 
tubing, it was cleared by the FDA for different indications on March 
13, 2020 (K193244) and April 22, 2020 (K200771). The applicant noted 
the INDIGO[supreg] device that was cleared by the FDA on May 26, 2015, 
was not relevant to the new technology application because it did not 
include the Lightning device.
    In response to our question whether the ``smart technology'' 
resided in the pump or within the tubing, the applicant stated that the 
``smart technology'' is contained in a standalone Lightning device, 
which is used once per patient and placed on top of the engine. The 
standalone Lightning device contains a computer, sensors, and a valve. 
The applicant asserted that the INDIGO[supreg] with Lightning 
represented a unique mechanism of action that involves an integrated, 
computer-run, proprietary, smart algorithm which allows for the removal 
of a blood clot while limiting blood loss. Per the applicant, the 
device itself controls the opening and closing of the valve which is 
distinct from manual operation. The applicant highlighted a number of 
competitor products and suggested that none of them have a systemic 
method to differentiate blood from a clot.
    In response to our concerns regarding how the mechanism of action 
of the separator differs from other existing thrombectomy systems, the 
applicant stated that the separator is not distinct from other 
technologies but was not integral to the consideration of newness for 
the device.
    One additional commenter noted support for INDIGO[supreg] with 
Lightning meeting the requirements for a novel mechanism of action, 
stating that no other competitive system uses a vacuum pump with 
automatic flow limitation.
    Response: We appreciate the commenter's input. We also thank the 
applicant for the additional information and for their comment 
regarding the newness criterion, including the clarification that the 
Lightning technology is the subject of this application. We agree with 
the applicant and commenter that this technology represents a new 
mechanism of action due to the way in which sensors and smart 
technology control the opening and closing of the valve allowing 
automated intermittent aspiration, as distinct from individual users' 
ability to manually compress the tubing, as described by a commenter. 
We agree that based on the clarification on the nature of the Lightning 
technology and how it integrates into the overall INDIGO[supreg] 
system, that the appropriate FDA clearances to consider are those for 
the Lightning technology for the indications of PAVS and PE, March 13, 
2020 and April 22, 2020 respectively.
    After consideration of the public comments we received and 
information submitted by the applicant as part of its FY 2022 new 
technology add-on payment application for INDIGO[supreg] with 
Lightning, we believe that INDIGO[supreg]

[[Page 45039]]

with Lightning has a unique mechanism of action in the treatment of 
patients for pulmonary embolism, deep vein thrombosis and peripheral 
arterial thromboembolism. Therefore, we believe that INDIGO[supreg] 
with Lightning is not substantially similar to existing treatment 
options and meets the newness criterion with the newness period 
beginning on March 13, 2020 for PAVS and April 22, 2020 for PE, the 
date on which the technology was cleared by FDA for each indication.
    With regard to the cost criterion, the applicant searched the FY 
2019 MedPAR claims data file with the FY 2019 Final Rule with 
Correction Notice IPPS Impact File to identify potential cases 
representing patients who may be eligible for treatment using the 
INDIGO[supreg] System. The applicant identified claims with any one of 
the following ICD-10-PCS codes for percutaneous mechanical 
thrombectomy:
BILLING CODE 4120-01-P

[[Page 45040]]

[GRAPHIC] [TIFF OMITTED] TR13AU21.178


[[Page 45041]]


[GRAPHIC] [TIFF OMITTED] TR13AU21.179

BILLING CODE 4120-01-C
    In its analysis, the applicant identified a primary cohort to 
assess whether this therapy met the cost criterion. The previously 
listed ICD-10-PCS procedure codes were used to identify claims 
involving percutaneous procedures. The claim search conducted by the 
applicant resulted in 15,580 claims mapping to six MS-DRGs: 270 (Other 
Major Cardiovascular Procedures with MCC), 271 (Other Major 
Cardiovascular Procedures with CC), 272 (Other Major Cardiovascular 
Procedures without CC/MCC), 163 (Major Chest Procedures with MCC), 164 
(Major Chest Procedures with CC), and 165 (Major Chest Procedures 
without CC/MCC).
    The applicant determined an average unstandardized case weighted 
charge per case of $126,211.
    The applicant did not remove charges for prior technology. The 
applicant stated that no prior technology is being replaced. The 
applicant then standardized the charges using the FY 2019 Final Rule 
with Correction Notice Impact File. Next, the applicant applied the 2-
year inflation factor used in the FY 2021 IPPS/LTCH PPS final rule to 
calculate outlier threshold charges (1.13218). To calculate the charges 
for the new technology, the applicant used what it stated was the 
national average CCR for the Supplies and Equipment cost center of 
0.299 from the FY 2021 IPPS final rule. However, we noted that the 
actual value for this cost center for FY 2021 was 0.297. The applicant 
calculated a final inflated average case-weighted standardized charge 
per case of $180,036, which exceeded the

[[Page 45042]]

average case-weighted threshold amount of $126,211 by $53,825. The 
applicant stated that because the final inflated average case-weighted 
standardized charge per case exceeded the average case-weighted 
threshold amount, the therapy meets the cost criterion.
    We invited public comment on whether INDIGO[supreg] with Lightning 
meets the cost criterion.
    Comment: We received a public comment from the applicant on whether 
the INDIGO[supreg] Aspiration System with Lightning Aspiration Tubing 
meets the cost criterion. The applicant noted that CMS stated in the 
proposed rule that they did not remove charges for prior technology (86 
FR 25265). The applicant clarified that in their cost analysis they did 
remove charges of $11,505 per case for existing technology based on a 
calculation of using the current price of $3,440 and dividing it by the 
FY 2019 national cost-to-charge ratio for supplies and equipment of 
0.299 to determine charges for the existing technology. The applicant 
stated that they applied the national cost-to-charge ratio for supplies 
and equipment of 0.299 to the known cost of existing equipment because 
the claims data are from the FY 2019 MedPAR claims data file. The 
applicant believes this would have been the charges applied for the 
existing technology in 2019 and was therefore the most appropriate 
cost-to-charge ratio to use. The applicant further commented that they 
think it is important to note that in performing the cost calculation, 
they used the national average cost-to-charge ratio for the Supplies 
and Equipment cost center of 0.297 from the FY 2021 IPPS final rule. 
The applicant further commented that their application notes that they 
then added the weighted average charge for the new technology of 
$22,596 to the charges. The weighted average charge for the new 
technology (comprised of the catheter(s) and Lightning Device) is 
$6,711, which was divided by 0.297 to arrive at a charge of $22,596. 
The applicant noted that the appropriate charges for the existing 
technology were removed prior to standardizing the charges and the 
charges for the new technology were applied using the appropriate cost-
to-charge ratio. The applicant stated that since the final inflated 
average case-weighted standardized charge per case of $180,036 exceeds 
the average case-weighted threshold amount of $126,211 that the 
INDIGO[supreg] System meets the cost criterion.
    Response: We thank the applicant for their comment regarding the 
INDIGO[supreg] system meeting the cost criterion. Based on the 
information submitted by the applicant as part of its FY 2022 new 
technology add-on payment application, as discussed in the proposed 
rule (86 FR 25261 through 25266) and previously summarized and the 
comment received, we agree that the final inflated average case-
weighted standardized charge per case exceeded the average case-
weighted threshold amount as previously stated. Therefore, the 
INDIGO[supreg] System meets the cost criterion.
    With respect to the substantial clinical improvement criterion, the 
applicant asserted that the INDIGO[supreg] with Lightning represents a 
substantial clinical improvement over existing technologies because it 
results in lower rates of aspirated blood loss during the procedure, 
low major bleeding event rate, reduces blood loss, reduces ICU stays, 
and reduces procedure time. The applicant also suggested that the 
technology allows for revascularization without thrombolytics and no 
recurrence of pulmonary embolism after 30 days.
    To support its application, the applicant submitted a reference to 
the EXTRACT-PE prospective, single-arm study across 22 sites comparing 
the use of INDIGO[supreg] without Lightning to systemic thrombolysis in 
119 patients with PE who had not been previously treated with anti-
thrombolytics or an adjunctive device within 48 hours. The applicant 
stated that this study was completed under FDA Investigational Device 
Exception (IDE) G170064. The applicant claimed that the EXTRACT-PE 
study showed the INDIGO[supreg] without Lightning led to a significant 
mean reduction of 0.43 in right ventricle/left ventricle (RV/LV) ratio 
(a measure associated with poor clinical outcomes when greater than 1) 
that corresponded to a 27.3 percent reduction at 48 hours after 
intervention. They also cited a low major adverse event composite rate 
of 1.7 percent within 48 hours, device usage of only 37 minutes and 
median ICU length of stay of 1 day. According to the applicant, rates 
of cardiac injury, pulmonary vascular injury, clinical deterioration, 
major bleeding, and device-related death at 48 hours were 0%, 1.7%, 
1.7%, 1.7%, and 0.8%, respectively.
    The applicant cited a poster of an unpublished retrospective case 
review study by Hastings \276\ of 18 patients with DVT treated with 
INDIGO[supreg] followed by anticoagulation. Primary technical success 
(defined as restoration of blood flow with minimal residual thrombus 
(<10%) without the need for a second session of treatment) was achieved 
in 15 patients. Three patients required adjunctive methods for 
successful clearance of thrombus, undergoing two sessions of treatment. 
Two patients had recurrence of DVT following single-session treatment, 
both of whom were asymptomatic at time of diagnosis.
---------------------------------------------------------------------------

    \276\ Hastings, L.H., Perkowski, P.E. Single Session 
Percutaneous Mechanical Aspiration Thrombectomy for Symptomatic 
Proximal Deep Vein Thrombosis. Poster.
---------------------------------------------------------------------------

    The applicant cited the PRISM study,\277\ a single-arm, 
multicenter, retrospective analysis of 79 patients with arterial 
occlusion from 2018, to provide evidence that use of INDIGO[supreg] 
with Lightning has a low major bleeding event rate, can result in 
revascularization without thrombolytics, and causes no clinically 
significant distal embolization. The applicant also stated that the 
interim results of the INDIAN study, a prospective trial using 
INDIGO[supreg] without Lightning to treat patients with ALI showed no 
device-related adverse events or major bleeding complications.\278\
---------------------------------------------------------------------------

    \277\ Saxon, R.R., Benenati, J.F., Teigen, C., Adams, G.K., 
Sewall, L.E., and Trialists, P. (2018). Utility of a power 
aspiration-based extraction technique as an initial and secondary 
approach in the treatment of peripheral arterial thromboembolism: 
Results of the multicenter prism trial. J Vasc Interv Radiol. 29(1): 
p. 92-100.
    \278\ Donato, et al. Acute Lower Limb Malperfusion--(INDIAN) 
Registry: Protocol (as presented at VEITHsymposium 2019).
---------------------------------------------------------------------------

    The applicant asserted that an unpublished laboratory bench test 
using water found that the 20.3 mL/sec average flow rate of catheter 
with Lightning generates 18-fold reduction in blood loss when compared 
to the use of the same catheter and Penumbra engine pump without the 
Lightning technology. The applicant asserted that a bench test showed 
that the Penumbra aspiration pump demonstrates continuous pressure, as 
evidenced by a sustained -29 inHg (inches of Mercury) through 60 
seconds versus a 60-ml syringe which starts at -27 Hg and drops to 0 in 
Hg within 18 seconds.
    The applicant also asserted that an abstract of a single-center 
retrospective case-control trial of 38 patients by Muck, P., et al. 
comparing two versions of INDIGO[supreg] catheters (12F and 8F) showed 
that median blood loss was 250mL in the larger Lightning 12F arm (n=9, 
larger catheter) and 375mL in the 8F arm without Lightning (n=27, 
smaller catheter). Technical success (defined as greater than 70 
percent thrombus reduction) was achieved in 77 percent of patients in 
the Lightning 12F arm compared to 18.5 percent in the 8F arm without 
Lightning. The applicant also asserted that this study showed that

[[Page 45043]]

none (0/9) of the patients in the INDIGO[supreg] with Lightning group 
required post-procedure transfusion, whereas 18.5 percent (5/27) of the 
INDIGO[supreg] without Lightning group required post-procedure 
transfusion.
    In the proposed rule (86 FR 25265 through 25266), we noted the 
following concerns in regard to the substantial improvement criterion. 
Specifically, in its application, the applicant did not explicitly 
state what the comparator was for each of its claims in support of 
substantial clinical improvement; for example, whether INDIGO[supreg] 
is being compared to systemic thrombolysis, percutaneous catheter 
directed thrombolysis, or other aspiration thrombectomy catheters. We 
stated that comparing INDIGO[supreg] to a medical treatment modality 
may not be appropriate since percutaneous interventions for PE and DVT 
have different clinical indications, risks, and benefits compared to 
medical or surgical interventions.
    We also noted that the applicant relies mostly on studies of 
INDIGO[supreg] without Lightning to substantiate its claims regarding 
INDIGO[supreg] with Lightning. Of all the studies provided by the 
applicant, only one small, unpublished study of DVT patients by Muck, 
P., et al. includes patients treated with INDIGO[supreg] with Lightning 
(which has the intelligent aspiration) versus earlier versions of the 
applicant's device. We stated that the applicant did not demonstrate 
superior outcomes using INDIGO[supreg] with Lightning compared to 
INDIGO[supreg] without Lightning.
    We noted that outcomes for INDIGO[supreg] for the rates of 
pulmonary vascular injury at 48 hours, clinical deterioration, major 
bleeding and device-related deaths were stated by the applicant as low 
compared to systemic thrombolysis, but were not compared to outcomes 
for existing aspiration thrombectomy devices which may be a more 
appropriate comparator. We further noted that in the poster study, all 
patients were maintained on anticoagulation following thrombectomy with 
INDIGO[supreg], so it is difficult to assess the DVT recurrence rate 
(using INDIGO[supreg] alone) to support the claim that INDIGO[supreg] 
can be used with patients with high risk of bleeding.
    We also noted that suction generated through a vacuum may not be 
superior to other mechanisms of generating negative pressure used in 
other existing aspiration catheters. A study comparing suction forces 
and vacuum pressure of Penumbra pump to a 60-mL syringe and pumps 
manufactured by several other manufacturers showed that all catheters 
transmit similar vacuum pressure regardless of pump or 60-mL 
syringe.\279\
---------------------------------------------------------------------------

    \279\ Froehler, M.T. (2017). Comparison of vacuum pressures and 
forces generated by different catheters and pumps for aspiration 
thrombectomy in acute ischemic stroke. Interventional neurology, 
6(3-4), 199-206.
---------------------------------------------------------------------------

    Finally, we questioned whether there is enough evidence to support 
that ``intelligent aspiration'' associated with INDIGO with Lightning 
provides a substantial clinical improvement over existing aspiration 
catheters from INDIGO[supreg] and existing devices where the aspiration 
is controlled manually. No direct comparison of blood loss between 
INDIGO[supreg] with Lightning catheter and existing aspiration 
thrombectomy devices from other manufacturers was provided, 
specifically catheters that reduce blood loss by returning the 
aspirated blood back to the patient. The unpublished bench test 
included with the application may have demonstrated a reduction in 
average volume of water aspirated using the INDIGO[supreg] Catheter 
with Lightning fully functional compared to the INDIGO[supreg] catheter 
with Lightning deactivated (valve pin fixed to the open position). 
However, this study was not designed to compare blood loss during a 
thrombectomy procedure between aspiration controlled by a human versus 
by the Lightning ``intelligent aspiration.''
    We invited public comment on whether INDIGO[supreg] with Lightning 
meets the substantial clinical improvement criterion.
    Comment: Several commenters stated that they did not believe that 
INDIGO[supreg] with Lightning met the requirements for substantial 
clinical improvement. Some comments stated in general that their 
clinical experience with other competing mechanical thrombectomy 
products was superior. Other commenters noted that there was no 
published data to suggest that INDIGO[supreg] with Lightning offered 
improved outcomes over competitive products. Some commenters discussed 
personal experience with INDIGO[supreg] with Lightning and discussed 
concerns including a tendency for the catheter to be clogged with 
thrombus requiring removal and cleaning, which results in additional 
blood loss. A commenter noted their experience with many other products 
and asserted that blood loss was much higher using INDIGO[supreg] with 
Lightning. This same commenter stated that there was some difficulty in 
achieving good clearance of thrombus using INDIGO[supreg] with 
Lightning. A commenter reviewed the clinical evidence submitted by the 
applicant and asserted that no patients were treated with 
INDIGO[supreg] with Lightning in the studies demonstrating arterial or 
venous thromboembolism clinical evidence because the studies took place 
prior to the availability of the technology. The commenter also noted 
that the unpublished laboratory bench test which was submitted by the 
applicant used water as opposed to blood to demonstrate effectiveness. 
This same commenter asserted that only a single study of INDIGO[supreg] 
with Lightning was used to demonstrate clinical evidence and that it 
was an unpublished abstract which included nine patients with DVT. The 
same commenter then summarized a study of a competitive product, the 
Inari ClotTriever, stating that a multi-center study of DVT patients 
showed a median blood loss of 50ml.\280\ The same commenter summarized 
a multi-center study of pulmonary embolism patients treated with 
another competitive product, the Inari FlowTriever, that showed a 
median blood loss of 250ml.\281\ This commenter asserted that this 
evidence was both more robust due to the larger number of patients and 
demonstrated reduced blood loss when compared to evidence presented for 
INDIGO[supreg] with Lightning.
---------------------------------------------------------------------------

    \280\ Prospective data from first 250 DVT patients enrolled 
across 24 study site in the ClotTriever Outcomes Registry as 
presented at 2021 New Cardiovascular Horizons Annual Conference.
    \281\ Prospective data from first 230 PE patients enrolled in 
the FlowTriever All-Comer Registry for Patient Safety and 
Hemodynamics as presented at the 2020 American Heart Association and 
the 2020 Transcatheter Cardiovascular Therapeutics Conference.
---------------------------------------------------------------------------

    Response: We appreciate the commenters providing their personal 
experience with the device as well as their comments on the evidence 
that the applicant included provided and have taken these comments into 
consideration in our determination of substantial clinical improvement, 
which is discussed later in this section.
    Comment: The applicant submitted a comment in response to our 
concerns regarding whether INDIGO[supreg] with Lightning meets the 
substantial clinical improvement criterion.
    In response to the concern that the comparator for the submitted 
studies was unclear, the applicant stated that, in general, other 
aspiration thrombectomy systems are the appropriate comparators in the 
consideration of substantial clinical improvement for INDIGO[supreg] 
with Lightning. The applicant provided a table which indicated the 
comparators that were used in studies that were part of the application 
as well as one new study that was provided with the

[[Page 45044]]

comment submission, summarized in the table below.
BILLING CODE 4120-01-P
[GRAPHIC] [TIFF OMITTED] TR13AU21.180


[[Page 45045]]


[GRAPHIC] [TIFF OMITTED] TR13AU21.181

BILLING CODE 4120-01-C
    With regard to our concern that the application relied mostly on 
studies of INDIGO[supreg] without Lightning, the applicant described a 
recent presentation in May 2021 \288\ which compared the use of 
INDIGO[supreg] without Lightning to INDIGO[supreg] with Lightning. The 
applicant stated that the use of the intelligent aspiration associated 
with the Lightning device was associated with higher rates of technical 
success, less blood loss, and no need for blood transfusion when 
compared to continuous aspiration. With respect to technical success, 
the new submitted study reported that thrombus reduction of >70% or 
better was significantly higher in the Lightning group. The applicant 
further noted that 80% of patients in the Lightning group achieved 
thrombus reduction of >70% compared to only 20% of patients in the 
control group. With respect to blood loss, the investigators found a 
significant reduction in blood loss when using the Lightning Device 
(250mL versus 275mL blood loss, p=0.0044). They also noted that none of 
the patients in the Lightning group required a post-procedure 
transfusion whereas 16.7% of the patients without Lightning did.
---------------------------------------------------------------------------

    \282\ EXTRACT-PE: A Prospective, Multicenter Trial to Evaluate 
the Safety and Efficacy of the Indigo[supreg] Aspiration System in 
Acute Pulmonary Embolism--as presented at VIVA 2019; Saxon, R.R., 
Benenati, J.F., Teigen, C., Adams, G.K., Sewall, L.E., and 
Trialists, P. (2018). Utility of a power aspiration-based extraction 
technique as an initial and secondary approach in the treatment of 
peripheral arterial thromboembolism: Results of the multicenter 
prism trial. J Vasc Interv Radiol. 29(1): p. 92-100.
    \283\ EXTRACT-PE: A Prospective, Multicenter Trial to Evaluate 
the Safety and Efficacy of the Indigo[supreg] Aspiration System in 
Acute Pulmonary Embolism--as presented at VIVA 2019; Saxon, R.R., 
Benenati, J.F., Teigen, C., Adams, G.K., Sewall, L.E., and 
Trialists, P. (2018). Utility of a power aspiration-based extraction 
technique as an initial and secondary approach in the treatment of 
peripheral arterial thromboembolism: Results of the multicenter 
prism trial. J Vasc Interv Radiol. 29(1): p. 92-100.
    \284\ EXTRACT-PE: A Prospective, Multicenter Trial to Evaluate 
the Safety and Efficacy of the Indigo[supreg] Aspiration System in 
Acute Pulmonary Embolism--as presented at VIVA 2019; Saxon, R.R., 
Benenati, J.F., Teigen, C., Adams, G.K., Sewall, L.E., and 
Trialists, P. (2018). Utility of a power aspiration-based extraction 
technique as an initial and secondary approach in the treatment of 
peripheral arterial thromboembolism: Results of the multicenter 
prism trial. J Vasc Interv Radiol. 29(1): p. 92-100.
    \285\ Muck, P., et al. Aspiration Thrombectomy with and without 
Intelligent Aspiration for Lower Extremity Acute Deep Vein 
Thrombosis, Poster, presented at International Symposium on 
Endovascular Therapy (May 9-11, 2021).
    \286\ EXTRACT-PE: A Prospective, Multicenter Trial to Evaluate 
the Safety and Efficacy of the Indigo[supreg] Aspiration System in 
Acute Pulmonary Embolism--as presented at VIVA 2019; Muck, P., et 
al. SCVS Abstract; Hastings, L.H., Perkowski, P.E, Single Session 
Percutaneous Mechanical Aspiration Thrombectomy for Symptomatic 
Proximal Deep Vein Thrombosis Poster.
    \287\ Meyer et al (Apr. 2014). Fibrinolysis for Patients with 
Intermediate-Risk Pulmonary Embolism. N Engl J Med. 10;370(15):1402-
11); Tu et al (May 2019). A Prospective, Single-Arm, Multicenter 
Trial of Catheter-Directed Mechanical Thrombectomy for Intermediate-
Risk Acute Pulmonary Embolism: The FLARE Study. JACC Cardiovasc 
Interv. 13;12(9):859-869; EXTRACT-PE: A Prospective, Multicenter 
Trial to Evaluate the Safety and Efficacy of the Indigo[supreg] 
Aspiration System in Acute Pulmonary Embolism--as presented at VIVA 
2019; Hastings, L.H., Perkowski, P.E, Single Session Percutaneous 
Mechanical Aspiration Thrombectomy for Symptomatic Proximal Deep 
Vein Thrombosis Poster.
    \288\ Muck, P., et al. Aspiration Thrombectomy with and without 
Intelligent Aspiration for Lower Extremity Acute Deep Vein 
Thrombosis, Poster, presented at International Symposium on 
Endovascular Therapy (May 9-11, 2021).
---------------------------------------------------------------------------

    With regard to our concern that it was difficult to assess the DVT 
recurrence rate (using the INDIGO[supreg] System alone) to support the 
claim that the INDIGO[supreg] System can be used with patients with 
high risk of bleeding because in the poster study submitted with the 
application, all patients were

[[Page 45046]]

maintained on anticoagulation following thrombectomy with the 
INDIGO[supreg] System, the applicant asserted that anticoagulation for 
DVT is standard practice regardless of risk for bleeding. Thus, in 
order to isolate the outcomes associated with INDIGO[supreg], the 
applicant stated it was necessary to maintain DVT patients on 
anticoagulation, as it is the standard of care.
    With regard to our concern about whether suction generated through 
a vacuum (as in the case of the INDIGO[supreg] System) is superior to 
other mechanisms of generating negative pressure used in other existing 
aspiration catheters, the applicant noted that they do not believe the 
suction associated with the INDIGO[supreg] System, which is related to 
the Penumbra Engine, is relevant to the new technology add-on payment 
application because it is the Lightning device that is the component of 
import with respect to substantial clinical improvement, but noted 
their belief that the suction generated by the Penumbra engine is 
superior to other methods of generating a vacuum.
    Several other commenters noted their support for INDIGO[supreg] 
with Lightning demonstrating substantial clinical improvement. Some of 
these commenters did not offer specific points of comparison but spoke 
to their personal clinical experience with the device. Other commenters 
pointed to the ability of INDIGO[supreg] with Lightning to reduce blood 
loss, increase the likelihood of completing treatment in a single 
session and reduce the required use of thrombolytics.
    Response: We appreciate the comments and the additional data from 
the applicant received for INDIGO[supreg] with Lightning and have taken 
them into consideration in making our determination. We believe the 
applicant was able to address our concern regarding the continuation of 
anticoagulation for DVT. We also appreciate the clarification from the 
applicant regarding our concern that the Penumbra engine is not part of 
its application for new technology add-on payments, thereby resolving 
our concern with regard to the superiority of the vacuum suction. 
However, after review of all the data received to date, we continue to 
have concerns regarding the substantial clinical improvement criterion 
as noted in the FY 2022 IPPS/LTCH PPS proposed rule. Specifically, we 
remain concerned that the applicant primarily used data from studies 
that utilized INDIGO[supreg] without Lightning in their attempt to 
demonstrate superior outcomes using INDIGO[supreg] with Lightning which 
is the subject of this application. While the applicant provided an 
additional May 2021 presentation that compared INDIGO[supreg] with 
Lightning to INDIGO[supreg] without Lightning, we do not believe it is 
appropriate to consider INDIGO[supreg] without Lighting as a proxy for 
other existing mechanical thrombectomy devices as stated by the 
applicant. We note that multiple comments suggest that other mechanical 
thrombectomy devices may be superior to the comparator device of 
INDIGO[supreg] without Lightning, and the applicant did not provide 
data comparing INDIGO[supreg] with Lightning to any existing device 
(other than INDIGO[supreg] without Lightning) to demonstrate improved 
outcomes. For these reasons, we do not have sufficient evidence to 
support that INDIGO[supreg] with Lightning provides a substantial 
clinical improvement over existing aspiration catheters including 
INDIGO[supreg] and existing devices where the aspiration is controlled 
manually.
    After consideration of all the information from the applicant, as 
well as the comments we received, we are unable to determine that 
INDIGO[supreg] with Lightning represents a substantial clinical 
improvement over existing technologies, and we are not approving new 
technology add-on payments for INDIGO[supreg] with Lightning for FY 
2022.
i. Olumiant[supreg] (baricitinib)
    Eli Lilly and Company submitted an application for new technology 
add-on payments for Olumiant[supreg] (baricitinib) for FY 2022. 
Olumiant[supreg] is a Janus kinase (JAK) 1 and 2 inhibitor used in 
combination with remdesivir as a treatment option for coronavirus 
disease 2019 (COVID-19), a respiratory disease caused by severe acute 
respiratory syndrome coronavirus 2 (SARS-CoV-2). Olumiant[supreg] has 
not yet received marketing approval from FDA to treat COVID-19, but has 
received an emergency use authorization (EUA) by the FDA. 
Olumiant[supreg] has been previously approved by FDA for the treatment 
of adult patients with moderately to severely active rheumatoid 
arthritis, who have had inadequate response to one or more tumor 
necrosis factor (TNF) antagonist therapies.\289\
---------------------------------------------------------------------------

    \289\ Olumiant (baricitinib) [package insert]. US Food and Drug 
Administration. Available at https://www.accessdata.fda.gov/drugsatfda_docs/label/2020/207924s002lbl.pdf. Revised July 8, 2020. 
Accessed October 8, 2020.
---------------------------------------------------------------------------

    The applicant stated that patients diagnosed with COVID-19 are at 
an elevated risk for excess morbidity and mortality due to the 
underlying SARS-CoV-2 infection and subsequent cytokine activation. The 
applicant stated that the cause of respiratory failure in COVID-19 is a 
hyperinflammatory state characterized by upregulation of multiple 
cytokines and that Olumiant[supreg] may be a viable treatment in 
patients with COVID-19 requiring supplemental oxygen, invasive 
mechanical ventilation, or extracorporeal membrane oxygenation (ECMO) 
because of its anti-inflammatory activity and ability to reverse 
dysregulated inflammatory markers in patients with COVID-19.\290\ The 
applicant noted treatment with baricitinib 4 mg resulted in reduced 
plasma levels of the cytokine IL-6 in hospitalized patients with COVID-
19, a finding that was replicated after being observed in patients with 
rheumatoid arthritis.291 292 293 The applicant also claimed 
that Olumiant[supreg] potentially has anti-viral activity in inhibiting 
SARS-CoV-2 from entering and infecting lung cells due to its affinity 
for adaptor-associated kinase-1 (AAK1).\294\ The applicant noted that 
there are ongoing studies to evaluate the impact of the antiviral host 
activity of Olumiant[supreg].
---------------------------------------------------------------------------

    \290\ McInnes IB, Byers NL, Higgs RE, et al. Comparison of 
baricitinib, upadacitinib, and tofacitinib mediated regulation of 
cytokine signaling in human leukocyte subpopulations. Arthritis Res 
Ther. 2019;21(1):183. https://doi.org/10.1186/s13075-019-1964-1.
    \291\ Bronte V, Ugel S, Tinazzi E, et al. Baricitinib restrains 
the immune dysregulation in severe COVID-19 patients [published 
online August 18, 2020]. J Clin Invest. https://doi.org/10.1172/JCI141772.
    \292\ Sims JT, Krishnan V, Chang CY, et al. Characterization of 
the cytokine storm reflects hyperinflammatory endothelial 
dysfunction in COVID-19 [published online September 10, 2020]. J 
Allergy Clin Immunol. https://doi.org/10.1016/j.jaci.2020.08.031.
    \293\ Stebbing J, Krishnan V, de Bono S, et al; Sacco 
Baricitinib Study Group. Mechanism of baricitinib supports 
artificial intelligence-predicted testing in COVID-19 patients. EMBO 
Mol Med. 2020;12(8):e12697. https://doi.org/10.15252/emmm.202012697.
    \294\ Richardson P, Griffin I, Tucker C, Smith D, Oechsle O, 
Phelan A, Rawling M, Savory E, Stebbing J. Baricitinib as potential 
treatment for 2019-nCoV acute respiratory disease. Lancet. 2020 Feb 
15;395(10223):e30-e31. doi: 10.1016/S0140-6736(20)30304-4. Epub 2020 
Feb 4. Erratum in: Lancet. 2020 Jun 20;395(10241):1906. PMID: 
32032529; PMCID: PMC7137985.
---------------------------------------------------------------------------

    With respect to the newness criterion, Olumiant[supreg] received 
Emergency Use Authorization (EUA) from FDA on November 19, 2020 for the 
emergency use of Olumiant[supreg], indicated for use in combination 
with remdesivir for the treatment of suspected or laboratory confirmed 
COVID-19 in certain hospitalized patients requiring supplemental 
oxygen, invasive mechanical ventilation, or extracorporeal membrane 
oxygenation (ECMO). The applicant stated that it intends to submit a 
supplemental new drug application (sNDA) for Olumiant[supreg].

[[Page 45047]]

    In the FY 2009 IPPS final rule (73 FR 48561 through 48563), we 
revised our regulations at Sec.  412.87 to codify our longstanding 
practice of how CMS evaluates the eligibility criteria for new medical 
service or technology add-on payment applications. We stated that new 
technologies that have not received FDA approval do not meet the 
newness criterion. In addition, we stated we do not believe it is 
appropriate for CMS to determine whether a medical service or 
technology represents a substantial clinical improvement over existing 
technologies before the FDA makes a determination as to whether the 
medical service or technology is safe and effective. For these reasons, 
we first determine whether a new technology meets the newness 
criterion, and only if so, do we make a determination as to whether the 
technology meets the cost threshold and represents a substantial 
clinical improvement over existing medical services or technologies. We 
also finalized at 42 CFR 412.87(c) (subsequently redesignated as Sec.  
412.87(e)) that all applicants for new technology add-on payments must 
have FDA approval or clearance by July 1 of the year prior to the 
beginning of the fiscal year for which the application is being 
considered.
    In the FY 2021 IPPS/LTCH PPS final rule, to more precisely describe 
the various types of FDA approvals, clearances, licensures, and 
classifications that we consider under our new technology add-on 
payment policy, we finalized a technical clarification to Sec.  
412.87(e)(2) to indicate that new technologies must receive FDA 
marketing authorization (for example, pre-market approval (PMA); 510(k) 
clearance; the granting of a De Novo classification request; approval 
of a New Drug Application (NDA); or Biologics License Application (BLA) 
licensure) by July 1 of the year prior to the beginning of the fiscal 
year for which the application is being considered. As noted in the FY 
2021 IPPS/LTCH PPS final rule, this technical clarification did not 
change our longstanding policy for evaluating whether a technology is 
eligible for new technology add-on payment for a given fiscal year, and 
we continue to consider FDA marketing authorization as representing 
that a product has received FDA approval or clearance for purposes of 
eligibility for the new technology add-on payment under Sec.  
412.87(e)(2) (85 FR 58742).
    An EUA by the FDA allows a product to be used for emergency use, 
but under our longstanding policy, we believe it would not be 
considered an FDA marketing authorization for the purpose of new 
technology add-on payments, as a product that is available only through 
an EUA is not considered to have FDA approval or clearance. Therefore, 
under the current regulations at 42 CFR 412.87(e)(2) and consistent 
with our longstanding policy of not considering eligibility for new 
technology add-on payments prior to a product receiving FDA approval or 
clearance, we believe a product available only through an EUA would not 
be eligible for new technology add-on payments.
    We also refer the reader to our comment solicitation in section 
II.F.7. of the preamble of the proposed rule regarding how data 
reflecting the costs of a product with an EUA, which may become 
available upon authorization of the product for emergency use (but 
prior to FDA approval or clearance), should be considered for purposes 
of the 2-year to 3-year period of newness for new technology add-on 
payments for a product with or expected to receive an EUA, including 
whether the newness period should begin with the date of the EUA. With 
respect to Olumiant[supreg], we specifically requested comment on 
whether the newness period for this technology would begin on November 
19, 2020, the date of its EUA, when the product became available on the 
market. We summarize comments related to this comment solicitation and 
provide our responses as well as our finalized policy in section XXX of 
this final rule.
    In response to the COVID-19 public health emergency (PHE), we 
established the New COVID-19 Treatments Add-on Payment (NCTAP) under 
the IPPS for COVID-19 cases that meet certain criteria (85 FR 71155). 
We believe that as drugs and biological products become available and 
are authorized for emergency use or approved by FDA for the treatment 
of COVID-19 in the inpatient setting, it is appropriate to increase the 
current IPPS payment amounts to mitigate any potential financial 
disincentives for hospitals to provide new COVID-19 treatments during 
the PHE. Therefore, effective for discharges occurring on or after 
November 2, 2020 and until the end of the PHE for COVID-19, we 
established the NCTAP to pay hospitals the lesser of (1) 65 percent of 
the operating outlier threshold for the claim or (2) 65 percent of the 
amount by which the costs of the case exceed the standard DRG payment, 
including the adjustment to the relative weight under section 3710 of 
the Coronavirus Aid, Relief, and Economic Security (CARES) Act, for 
certain cases that include the use of a drug or biological product 
currently authorized for emergency use or approved for treating COVID-
19.\295\ Qualifying inpatient cases involving the use of 
Olumiant[supreg], in combination with VEKLURY[supreg], are currently 
eligible for NCTAP beginning November 19, 2020, the date 
Olumiant[supreg] received EUA, through the end of the PHE.
---------------------------------------------------------------------------

    \295\ Additional Policy and Regulatory Revisions in Response to 
the COVID-19 Public Health Emergency, 85 FR 71142, 71155 (November 
6, 2020). https://www.govinfo.gov/content/pkg/FR-2020-11-06/pdf/2020-24332.pdf.; For more information on NCTAP, refer to CMS' 
provider toolkit at https://www.cms.gov/medicare/covid-19/new-covid-19-treatments-add-payment-nctap.
---------------------------------------------------------------------------

    We stated in the proposed rule that we anticipated that there might 
be inpatient cases of COVID-19, beyond the end of the PHE, for which 
payment based on the assigned MS-DRG may not adequately reflect the 
additional cost of new COVID-19 treatments. In order to continue to 
mitigate potential financial disincentives for hospitals to provide new 
treatments, and to minimize any potential payment disruption 
immediately following the end of the PHE, we stated that we believe 
that the NCTAP should remain available for cases involving eligible 
treatments, including Olumiant[supreg], in combination with 
VEKLURY[supreg], for the remainder of the fiscal year in which the PHE 
ends (for example, until September 30, 2022). We refer the reader to 
our proposal in section II.F.8. of the preamble of the proposed rule to 
extend the NCTAP through the end of the fiscal year in which the PHE 
ends for certain products and discontinue the NCTAP for products 
approved for new technology add-on payments in FY 2022. We also refer 
the reader to section XXX of the preamble of this final rule, where we 
discuss our finalized policy to extend the NCTAP through the end of the 
fiscal year in which the PHE ends for all eligible products.
    The applicant indicated that Olumiant[supreg] could be reported 
using the ICD-10-PCS codes 3E0DXGC (Introduction of other therapeutic 
substance into mouth and pharynx, external approach) or 3E0G7GC 
(Introduction of other therapeutic substance into upper GI, via natural 
or artificial opening) but stated that these codes do not uniquely 
identify the administration of Olumiant[supreg]. We noted that ICD-10-
PCS codes XW0DXF5 (Introduction of other new technology therapeutic 
substance into mouth and pharynx, external approach, new technology 
group 5) and 3E0H7GC (Introduction of other therapeutic substance into 
lower G.I. via natural or artificial opening) could also be used to 
report use of Olumiant[supreg]. We noted that as of January 1, 2021, 
Olumiant[supreg] is

[[Page 45048]]

uniquely identified by ICD-10-PCS codes XW0DXM6 (Introduction of 
baricitinib into mouth and pharynx, external approach, new technology 
group 6), XW0G7M6 (Introduction of baricitinib into upper GI, via 
natural or artificial opening, new technology group 6), and XW0H7M6 
(Introduction of baricitinib into lower GI, via natural or artificial 
opening, new technology group 6).
    As discussed previously, if a technology meets all three of the 
substantial similarity criteria, it would be considered substantially 
similar to an existing technology and would not be considered ``new'' 
for purposes of new technology add-on payments.
    With respect to the first criterion, whether a product uses the 
same or similar mechanism of action to achieve a therapeutic outcome, 
according to the applicant, Olumiant[supreg] does not use the same or a 
similar mechanism of action when compared to an existing technology to 
achieve a therapeutic outcome, as there are no JAK inhibitor therapies 
that have received an EUA or an approval from FDA to treat COVID-19.
    The applicant notes that currently there is one therapy approved by 
FDA to treat COVID-19 in hospital inpatients, remdesivir, and one 
therapy, besides Olumiant[supreg], that has received EUA for the 
treatment of COVID-19, convalescent plasma.\296\ The applicant claims 
that the mechanism of action for both of these treatments differs from 
Olumiant[supreg], which works as a JAK inhibitor.
---------------------------------------------------------------------------

    \296\ The Federal Drug and Food Administration. Emergency Use 
Authorizations: Drug and Biological Products. 2020. https://www.fda.gov/emergency-preparedness-andresponse/mcm-legal-regulatory-and-policy-framework/emergency-useauthorization#coviddrugs.
---------------------------------------------------------------------------

    With respect to the second criterion, whether a product is assigned 
to the same or a different MS-DRG, the applicant stated that there are 
no JAK inhibitor therapies that have received an EUA or an approval 
from FDA for the treatment of patients with COVID-19 and that 
Olumiant[supreg] could therefore not be assigned to the same MS-DRG as 
existing technologies.
    With respect to the third criterion, whether the new use of the 
technology involves the treatment of the same or similar type of 
disease and the same or similar patient population, according to the 
applicant, Olumiant[supreg] represents a potential new treatment option 
for adult and pediatric patients 2 years or older with suspected or 
laboratory-confirmed COVID-19 requiring supplemental oxygen, invasive 
mechanical ventilation, or extracorporeal membrane oxygenation (ECMO). 
The applicant also stated that COVID-19 is an entirely distinct disease 
from those caused by other coronaviruses including severe acute 
respiratory syndrome (SARS) and the Middle East respiratory syndrome 
coronavirus (MERS-CoV).
    In summary, the applicant asserted that Olumiant[supreg] is not 
substantially similar to other available therapies because, as a JAK 
inhibitor, it has a unique mechanism of action; there are no other 
products assigned to the same MS-DRG; and it treats a different patient 
population and disease--COVID-19. However, we stated in the proposed 
rule that although there may not be any other JAK inhibitors for the 
treatment of COVID-19 assigned to the same MS-DRG as Olumiant[supreg], 
Olumiant[supreg] may map to the same MS-DRG as other existing COVID-19 
treatments. We also noted that Olumiant[supreg] involves the treatment 
of the same patient population and disease as other treatments for 
COVID-19, as Olumiant[supreg] is given to the same patients as 
remdesivir due to the EUA indication.
    As discussed in section II.F.7 of the preamble of the proposed 
rule, we requested comment regarding how data reflecting the costs of a 
product with an EUA, which may become available upon authorization of 
the product for emergency use (but prior to FDA approval or clearance), 
should be considered for purposes of the 2-year to 3-year period of 
newness for new technology add-on payments for a product with or 
expected to receive an EUA, including whether the newness period should 
begin with the date of the EUA. We also specifically requested comment 
on whether the newness period for Olumiant[supreg] would begin on 
November 19, 2020, the date of its EUA, when the product became 
available on the market. We summarize comments related to this comment 
solicitation and provide our responses as well as our finalized policy 
in section XXX of this final rule.
    As previously discussed, under the regulations at 42 CFR 
412.87(e)(2) and consistent with our longstanding policy of not 
considering eligibility for new technology add-on payments prior to a 
product receiving FDA approval or clearance, we believe a product 
available only through an EUA would not be eligible for new technology 
add-on payments.
    We invited public comment on whether Olumiant[supreg] meets the 
newness criterion.
    Comment: In response to CMS' statement in the proposed rule that an 
EUA would not be considered FDA marketing authorization for the purpose 
of new technology add-on payments, as a product that is available only 
through an EUA is not considered to have FDA approval or clearance, and 
therefore a product available only through an EUA would not be eligible 
for new technology add-on payments, the applicant submitted a comment. 
The applicant stated their belief that market authorization, not 
approval, is the criterion for new technology add-on payment 
eligibility and that an EUA is a formal FDA authorization to market. 
Further, the applicant stated that if an EUA was sufficient for CMS to 
authorize payment enhancements on COVID treatments under NCTAP, the 
same EUA should suffice for the new technology add-on payment's 
marketing authorization requirement and that in the case of COVID 
therapies, CMS should harmonize its payment policies to ensure 
consistency and prevent lapses in reimbursement that could lead to 
access barriers for patients. The applicant requested that CMS 
reconsider its stated position and acknowledge that an active EUA 
issued by the FDA for a COVID-19 treatment prior to July 1, 2021 is an 
appropriate form of authorization for the purposes of meeting the FY 
2022 new technology add-on payment eligibility requirements.
    Response: We thank the applicant for their comment. With regard to 
the applicant's statement that market authorization, not approval, is 
the criterion for new technology add-on payment eligibility, as we 
noted in the proposed rule, we revised our regulations at Sec.  412.87 
in the FY 2009 IPPS final rule (73 FR 48561 through 48563) to codify 
our longstanding practice of how CMS evaluates the eligibility criteria 
for new technology add-on payment applications. We specifically stated 
that new technologies that have not received FDA approval do not meet 
the newness criterion. More recently, in the FY 2021 IPPS/LTCH PPS 
final rule (85 FR 58742), we finalized a technical clarification to the 
language of Sec.  412.87 to more precisely describe the various types 
of FDA approvals, clearances, licensures, and classifications that we 
consider under our new technology add-on payment policy. As we stated 
at that time, this technical clarification did not change or modify the 
policy set forth in existing Sec.  412.87(e)(2). We explained that 
under our current policy, in evaluating whether a technology is 
eligible for new technology add-on payment for a given fiscal year, we 
consider whether the technology has received marketing

[[Page 45049]]

authorization by July 1 (such as Premarket Approval (PMA); 510(k) 
clearance; the granting of a De Novo classification request; or 
approval of a New Drug Application (NDA)). Accordingly, and consistent 
with our longstanding practice, we continue to consider FDA marketing 
authorization as representing that a product has received FDA approval 
or clearance for purposes of eligibility for the new technology add-on 
payment under Sec.  412.87(e)(2).
    In the FDA's press release regarding its issuance of an EUA for 
OlumiantTM, it states that ``[t]he issuance of an EUA is 
different than an FDA approval.'' \297\ To determine whether to issue 
an EUA, FDA ``evaluates the totality of available scientific evidence 
and carefully balances any known or potential risks with any known or 
potential benefits of the product for use during an emergency.'' This 
standard is different from the standard that FDA uses to evaluate 
whether to approve a drug. Therefore, we continue to believe that, for 
the purposes of new technology add-on payments, a product that is only 
available through an EUA is not considered to have FDA approval or 
clearance and therefore is not considered eligible for new technology 
add-on payments.
---------------------------------------------------------------------------

    \297\ U.S. Food and Drug Administration. (2020, November 19). 
Coronavirus (COVID-19) Update: FDA Authorizes Drug Combination for 
Treatment of COVID-19. U.S. Food and Drug Administration. https://www.fda.gov/news-events/press-announcements/coronavirus-covid-19-update-fda-authorizes-drug-combination-treatment-covid-19.
---------------------------------------------------------------------------

    In response to the applicant's comment that an EUA should suffice 
for the new technology add-on payment's marketing authorization 
requirement because an EUA was sufficient for CMS to authorize payment 
enhancements for COVID-19 treatments under NCTAP, we note that there 
are distinct eligibility criteria for new technology add-on payment as 
compared to NCTAP. As noted previously, historically, CMS has stated 
that for the purposes of new technology add-on payments, that new 
technologies that have not received FDA approval do not meet the 
newness criterion. In addition to the newness criterion, there is a 
substantial clinical improvement criterion to qualify for new 
technology add-on payments that is not required for NCTAP. We have 
previously stated (73 FR 48561 through 48563) that we do not believe it 
is appropriate for CMS to determine whether a medical service or 
technology represents a substantial clinical improvement over existing 
technologies before the FDA makes a determination as to whether the 
medical service or technology is safe and effective. For these reasons, 
we first determine whether a new technology meets the newness 
criterion, and only if so, do we make a determination as to whether the 
technology meets the cost threshold and represents a substantial 
clinical improvement over existing medical services or technologies. As 
stated by FDA in their November 19, 2020 news release announcing the 
issuance of the EUA for Olumiant[supreg], ``the safety and 
effectiveness of this investigational therapy for use in the treatment 
of COVID-19 continues to be evaluated.'' \298\ Therefore, while we 
believe that the FDA's issuance of an EUA for Olumiant[supreg] is 
sufficient to support NCTAP eligibility to ensure that providers are 
not disincentivized to provide this treatment to patients with COVID-
19, we do not believe that it would be appropriate for us to make a 
determination whether Olumiant provides a substantial clinical 
improvement over existing technologies for the purposes of new 
technology add-on payments.
---------------------------------------------------------------------------

    \298\ Ibid.
---------------------------------------------------------------------------

    In response to the applicant's comment that CMS should harmonize 
its payment policies to ensure consistency and prevent lapses in 
reimbursement that could lead to access barriers for patients, we do 
not believe that our position that an EUA is not considered an FDA 
marketing authorization for the purpose of new technology add-on 
payments will lead to patient access issues. As discussed in section 
XXX of this final rule, we are finalizing our proposal to extend the 
NCTAP through the end of the fiscal year in which the PHE ends for all 
eligible products. This means that qualifying inpatient cases involving 
the use of Olumiant[supreg], in combination with VEKLURY[supreg], will 
continue to be eligible for NCTAP through the end of the fiscal year in 
which the PHE ends. Additionally, as stated in the IPPS/LTCH PPS 
proposed rule (86 FR 25395), if a product with an EUA receives FDA 
approval by July 1, 2022, it would be eligible for consideration of new 
technology add-on payments beginning FY 2023, and new technology add-on 
payments, if approved, would begin on October 1, 2022 (the beginning of 
FY 2023).
    We refer the readers to section XXX of this final rule for a 
discussion of the comment solicitation including a summary of the 
comments received.
    As stated previously, Olumiant[supreg] has an EUA and is indicated 
for use in combination with remdesivir for the treatment of suspected 
or laboratory confirmed COVID-19 in certain hospitalized patients 
requiring supplemental oxygen, invasive mechanical ventilation, or 
extracorporeal membrane oxygenation (ECMO). However, because 
Olumiant[supreg] did not receive FDA clearance or approval by July 1, 
2021 for this indication, it is not eligible for consideration for new 
technology add-on payments for FY 2022 and therefore and we are not 
approving new technology add-on payments for Olumiant[supreg] for FY 
2022. We note that we received public comments from the applicant 
regarding the substantial clinical improvement criterion. However, 
because Olumiant[supreg] is ineligible for consideration for new 
technology add-on payments for FY 2022 because it did not receive FDA 
clearance or approval by July 1, 2021, we are not summarizing nor 
responding to public comments regarding the substantial clinical 
improvement or cost criteria for this application in this final rule. 
Under our finalized policy as discussed in section XXX of this final 
rule, qualifying inpatient cases involving the use of Olumiant[supreg], 
in combination with VEKLURY[supreg], are currently eligible for NCTAP 
beginning November 19, 2020, the date Olumiant[supreg] received EUA, 
through the end of the fiscal year in which the PHE ends.
j. Pure-Vu[supreg] System
    Motus GI holdings, Inc. submitted an application for new technology 
add-on payments for the Pure-Vu[supreg] System for FY 2022. The Pure-
Vu[supreg] System is an FDA cleared system designed to connect to 
currently marketed colonoscopes to provide high intensity, intra-
procedural cleansing of the colon during a colonoscopy. According to 
the applicant, the Pure-Vu[supreg] System is indicated for use in 
patients requiring therapeutic or diagnostic colonoscopies where the 
bowel has not been adequately prepared. The applicant asserted that the 
Pure-Vu[supreg] System would be used in situations such as a lower 
gastrointestinal bleed (LGIB), as LGIB does not allow for adequate 
bowel preparation.
    The applicant asserted that the Pure-Vu[supreg] System device helps 
to avoid aborted and delayed colonoscopy procedures due to poor 
visualization of the colon mucosa by creating a unique High Intensity, 
Pulsed Vortex Irrigation Jet that consists of a mixture of air and 
water to break-up fecal matter, blood clots, and other debris, and 
scrub the walls of the colon while simultaneously removing the debris 
through two suction channels. The applicant stated that the suction 
channels have a sensor

[[Page 45050]]

to detect the formation of a clog in the channels, triggering the 
system to automatically purge and then revert to suction mode once the 
channel is clear. According to the applicant, this combination of the 
agitation of the fluid in the colon via the pulsed vortex irrigation 
and simultaneous removal of the debris allows the physician to 
visualize the colon and achieve a successful colonoscopy or other 
advanced procedure through the colonoscope even if the patient is not 
properly prepped and has debris either blocking the ability to navigate 
the colon or covering the colon wall obscuring the mucosa and any 
pathology that may be present. The applicant asserted that the constant 
volume suction pumps do not cause the colon to collapse, which allows 
the physician to continue to navigate the colon while cleansing and 
avoids the need to constantly insufflate the colon, which may be 
required with other colonoscopy irrigation systems.
    The applicant stated that the Pure-Vu[supreg] System is comprised 
of a workstation that controls the function of the system, a disposable 
oversleeve that is mounted on a colonoscope and inserted into the 
patient, and a disposable connector with tubing (umbilical tubing with 
main connector) that provides the interface between the workstation, 
the oversleeve, and off the shelf waste containers.
    The applicant explained that the workstation has two main 
functions: Cleansing via irrigation and evacuation, and acting as the 
user interface of the system. The applicant explained that the 
irrigation into the colon is achieved by an electrical pump that 
supplies pressurized gas (air) and a peristaltic pump that supplies the 
liquid (water or saline). According to the applicant, the pressurized 
gas and liquid flow through the ``main connector'' and are mixed upon 
entry into the umbilical tubing that connects to the oversleeve. The 
applicant explained that the gas pressure and flow are controlled via 
regulators and the flow is adjusted up or down depending on the 
cleansing mode selected. The applicant stated that a foot pedal 
connected to the user interface activates the main functions of the 
system so that the user's hands are free to perform the colonoscope 
procedure in a standard fashion.
    The applicant stated that the evacuation mode (also referred to as 
suction) removes fecal matter and fluids out of the colon. The 
applicant noted that the evacuation function is active during cleansing 
so that fluid is inserted and removed from the colon simultaneously. 
The applicant explained that the evacuation pumps are designed in a 
manner that prevents the colon from collapsing when suctioning, which 
facilitates the ability to simultaneously irrigate and evacuate the 
colon. According to the applicant, during evacuation, the system 
continuously monitors the pressure in the evacuation channels of the 
oversleeve and if the pressure drops below pre-set limits the pumps 
will automatically reverse the flow. The applicant explained that the 
clog sensor triggers the system to automatically purge the material out 
of the channel and back into the colon where it can be further 
emulsified by the Pulsed Vortex Irrigation Jet, and then automatically 
reverts back into evacuation mode once the channel is cleared. The 
applicant stated that the evacuation (suction) that drains fecal matter 
and fluids out of the colon is generated by peristaltic pumps that can 
rotate in both directions, either to evacuate fluids and fecal matter 
from the colon through the evacuation tubes and into a waste container, 
or while in the reverse direction, to purge the evacuation tubes. The 
applicant claimed the suction created by this type of pump creates a 
constant volume draw of material from the colon and therefore prevents 
the colon from collapsing rapidly. According to the applicant, purging 
of evacuation tubes may be activated in two ways: The purging cycle is 
automatically activated when low pressure is noted by the evacuation-
line sensor (it is also activated for the first 0.5 seconds when 
evacuation is activated to make sure the line is clear from the start); 
or a manual purge may be activated by the user by pushing the ``manual 
purge'' button on the foot pedal. The applicant claimed the pressure-
sensing channel is kept patent by using an air perfusion mechanism 
where an electrical pump is used to perfuse air through the main 
connector and into the oversleeve, while the sensor located in the 
workstation calculates the pressure via sensing of the channel.
    The applicant explained the Pure-Vu[supreg] System is loaded over a 
colonoscope and that the colonoscope with the Pure-Vu[supreg] 
oversleeve is advanced through the colon in the same manner as a 
standard colonoscopy. The applicant stated that the body of the 
oversleeve consists of inner and outer sleeves with tubes intended for 
providing fluid path for the cleansing irrigation (2X), the evacuation 
of fluids (2X), the evacuation sensor (1X) and that the flexible head 
is at the distal end of the oversleeve and is designed to align with 
the colonoscope's distal end in a consistent orientation. The applicant 
explained that the distal cleansing and evacuation head contains the 
irrigation ports, evacuation openings, and a sensing port. According to 
the applicant, the system gives the physician the control to cleanse 
the colon as needed based on visual feedback from the colonoscope to 
make sure they have an unobstructed view of the colon mucosa to detect 
and treat any pathology. The applicant noted that since the Pure-
Vu[supreg] System does not interfere with the working channel of the 
colonoscope, the physician is able to perform all diagnostic or 
therapeutic interventions in a standard fashion with an unobstructed 
field of view.
    According to the applicant, multiple studies have shown that 
inadequate bowel visualization leads to missed pathology, delayed 
diagnosis, extended hospital stay, and in some cases, additional 
therapy being administered, especially in the acute LGIB population, 
which is the most common indication for inpatients that require 
colonoscopy.299 300 Unknown abdominal pain, infection, and 
foreign body removal were also cited by the applicant as being common 
indications for an inpatient colonoscopy.
---------------------------------------------------------------------------

    \299\ Garber A, Sarvepalli S, Burke CA, Bhatt A, Ibrahim M, 
McMichael J, et al. Modifiable Factors Associated with Quality of 
Bowel Preparation Among Hospitalized Patients Undergoing 
Colonoscopy. J Hosp Med. 2019;14(5):278-83.
    \300\ Yadlapati R, Johnston ER, Gregory DL, Ciolino JD, Cooper 
A, Keswani RN. Predictors of Inadequate Inpatient Colonoscopy 
Preparation and Its Association with Hospital Length of Stay and 
Costs. Dig Dis Sci. 2015;60(11):3482-90.
---------------------------------------------------------------------------

    The applicant explained that when a patient with LGIB is admitted 
to the hospital, they are stabilized and then started on bowel 
preparation for the colonoscopy procedure. The applicant claimed that 
the patient typically is placed on a liquid-only diet while consuming 
4-6 liters of polyethylene glycol (PEG) based solution until the rectal 
effluent is clear. If the rectal effluent is not clear, additional 
bowel preparation is prescribed. The applicant stated that for severe 
LGIB cases, a patient is prescribed to consume a rapid purge of 1 liter 
every 30-45 minutes with a total volume of 4-14 liters, which could 
lead to purgative intolerance or vomiting. The applicant claimed that 
even in situations where bowel preparation has been completed, and 
clear rectal effluent while on a clear liquid diet has been confirmed, 
there are no guarantees that a patient's bowel is clean for a 
successful colonoscopy. The applicant submitted data from a study by 
the Cleveland Clinic showing 51 percent of 8,819 patients observed over 
a 4-year period were inadequately

[[Page 45051]]

prepared for colonoscopies, leading to one extra day in the hospital 
compared to patients that were adequately prepared.\301\ The applicant 
cited another study, by Northwestern University, demonstrating an 
association between inadequate bowel preparation and increased length 
of stay (LOS) in hospitals, with inadequately prepared patients staying 
two more days than adequately prepared patients on average.\302\ The 
applicant claimed additional time spent in hospitals increases the 
patient's exposure to risks of hospital-acquired infections. The 
applicant claimed this risk is especially impactful to patients who are 
admitted for LGIB, which is seen at a higher prevalence in the elderly 
population.303 304 The applicant stated in the elderly 
population, continuous bowel preparation also poses increased risk due 
to their higher comorbidities and potential for electrolyte imbalances 
such as hyperphosphatemia, hypocalcemia, and hypokalemia.\305\
---------------------------------------------------------------------------

    \301\ Garber A, Sarvepalli S, Burke CA, Bhatt A, Ibrahim M, 
McMichael J, et al. Modifiable Factors Associated with Quality of 
Bowel Preparation Among Hospitalized Patients Undergoing 
Colonoscopy. J Hosp Med. 2019;14(5):278-83.
    \302\ Yadlapati R, Johnston ER, Gregory DL, Ciolino JD, Cooper 
A, Keswani RN. Predictors of Inadequate Inpatient Colonoscopy 
Preparation and Its Association with Hospital Length of Stay and 
Costs. Dig Dis Sci. 2015;60(11):3482-90.
    \303\ Parra-Blanco A, Ruiz A, Alvarez-Lobos M, Amoros A, Gana 
JC, Ibanez P, et al. Achieving the best bowel preparation for 
colonoscopy. World J Gastroenterol. 2014;20(47):17709-26.
    \304\ Hauck K, Zhao X. How dangerous is a day in hospital? A 
model of adverse events and length of stay for medical inpatients. 
Med Care. 2011;49(12):1068-75.
    \305\ Parra-Blanco A, Ruiz A, Alvarez-Lobos M, Amoros A, Gana 
JC, Ibanez P, et al. Achieving the best bowel preparation for 
colonoscopy. World J Gastroenterol. 2014;20(47):17709-26.
---------------------------------------------------------------------------

    The applicant cited a practical guide authored by Kim B., et al., 
to assert that poor visualization of the colon mucosa has a direct 
effect on the ability to detect the presence of a GI bleed or the 
aftermath stigmata and administer treatment successfully.\306\ The 
applicant used the Boston Bowel Preparation Scale (BBPS), developed by 
Lai E. et al.,\307\ as a reliable method to measure bowel preparation. 
The applicant stated that the scale is a range (0-9) of dirtiest to 
cleanest for the whole colon and 0 to 3 for each of the 3 segments of 
the colon; the right colon (including the cecum and ascending colon), 
the transverse colon (including the hepatic and splenic flexures), and 
the left colon (including the descending colon, sigmoid colon, and 
rectum). Therefore, the maximum BBPS score for a perfectly clean colon 
without any residual liquid is nine and the minimum BBPS score for an 
unprepared colon is zero. The points are assigned as follows: zero = 
Unprepared colon segment with mucosa not seen due to solid stool that 
cannot be cleared; one = Portion of mucosa of the colon segment seen, 
but other areas of the colon segment not well seen due to staining, 
residual stool and/or opaque liquid; two = Minor amount of residual 
staining, small fragments of stool and/or opaque liquid, but mucosa of 
colon segment seen well; three = Entire mucosa of colon segment seen 
well with no residual staining, small fragments of stool or opaque 
liquid.
---------------------------------------------------------------------------

    \306\ Kim BS, Li BT, Engel A, et al. Diagnosis of 
gastrointestinal bleeding: A practical guide for clinicians. World J 
Gastrointest Pathophysiol. 2014;5(4):467-478.doi: 10.4291/
wjgp.v5.i4.467.
    \307\ Lai EJ, Calderwood AH, Doros G, Fix OK, Jacobson BC. The 
Boston Bowel Preparation Scale: A valid and reliable instrument for 
colonoscopy-oriented research. Gastrointestinal Endoscopy. 
2009;69(3):620-625
---------------------------------------------------------------------------

    The applicant stated that evidence-based guidelines and clinical 
reviews in high impact biomedical journals recommend colonoscopy as the 
preferred initial modality for the diagnosis and treatment of acute 
lower gastrointestinal bleeding.308 309 The applicant stated 
that colonoscopy has been less frequently utilized than might otherwise 
be indicated because it suffers from the significant disadvantage of 
requiring the need for a large volume bowel preparation.\310\ The 
applicant states that even with a bowel preparation, poor visualization 
often occurs because of a poorly prepared colon. Based on these 
assertions, the applicant inferred that colonoscopy for acute lower 
gastrointestinal bleeding would be much more utilized and lead to more 
diagnoses and interventions with intraprocedural bowel preparation, 
which puts the control of the visualization (cleanliness) of the colon 
mucosa in the hands of the endoscopist. The applicant further stated it 
is important to appreciate that alternatives to colonoscopy, including 
angiography and vascular embolization treatments to create hemostasis, 
have risks of ischemic vascular injury, retroperitoneal bleeding and 
acute renal injury.\311\ The applicant stated that aside from the 
colonoscopy, other modalities such as tagged red blood cell scans, 
computed tomography (CT) angiograms, and mesenteric angiographies all 
require an active source of bleed in order to achieve a successful 
diagnostic yield. The applicant claimed that even when diagnosis is 
achieved using these modalities, a colonoscopy may still be ordered to 
treat the source of the bleed via epinephrine injections and clipping 
and thermal therapies, to prevent potential surgical interventions.
---------------------------------------------------------------------------

    \308\ Strate LL, Gralnek IM. ACG Clinical Guideline: Management 
of Patients With Acute Lower Gastrointestinal Bleeding. Am J 
Gastroenterol. 2016 Apr;111(4):459-74. doi: 10.1038/ajg.2016.41. 
Epub 2016 Mar 1. Erratum in: Am J Gastroenterol. 2016 
May;111(5):755. PMID: 26925883; PMCID: PMC5099081.
    \309\ Gralnek IM, Neeman Z, Strate LL. Acute Lower 
Gastrointestinal Bleeding. N Engl J Med. 2017 Mar 16;376(11):1054-
1063. doi: 10.1056/NEJMcp1603455. PMID: 28296600.
    \310\ Carney BW, Khatri G, Shenoy-Bhangle AS. The role of 
imaging in gastrointestinal bleed. Cardiovasc Diagn Ther. 2019 
Aug;9(Suppl 1):S88-S96. doi: 10.21037/cdt.2018.12.07. PMID: 
31559156; PMCID: PMC6732104.
    \311\ Ibid.
---------------------------------------------------------------------------

    With respect to the newness criterion, the Pure-Vu[supreg] System 
first received FDA 510(k) clearance on September 22, 2016 under 510(k) 
number K60015. Per the applicant, this initial device was very 
cumbersome to set up and required direct support from the company and 
therefore was not viable for a small company with limited resources to 
market the device. The applicant noted that the initial device could 
have been sold starting on January 27, 2017 when the first device came 
off the manufacturing line. Per the applicant, the device was allocated 
for clinical evaluations but 10 institutions throughout the country 
purchased the device outside of a clinical study, primarily to allow 
physicians to try the product prior to committing to a clinical trial. 
The applicant further noted that minor modifications were made to the 
Pure-Vu System in additional 510(k) clearances dated December 12, 2017 
and June 21, 2018. The current marketed Pure-Vu System was then granted 
510(k) clearance on June 6, 2019 under 510(k) number K191220. Per the 
applicant, this clearance changed the entire set-up of the device, 
redesigned the user interface, and reduced the size, among other 
changes. According to the applicant, this updated version was 
commercially available as of September 19, 2019.
    The applicant submitted a request for approval for a unique ICD-10-
PCS code for the use of the Pure-Vu[supreg] System technology and was 
granted approval for the following procedure code effective October 1, 
2021: XDPH8K7 (Irrigation of lower GI using intraoperative single-use 
oversleeve, via natural or artificial opening endoscopic, new 
technology group 7).
    If a technology meets all three of the substantial similarity 
criteria, it would be considered substantially similar to an existing 
technology and therefore would not be considered ``new'' for purposes 
of new technology add-on payments.
    With respect to the first criterion, whether a product uses the 
same or similar mechanism of action to achieve a therapeutic outcome, 
the applicant

[[Page 45052]]

asserted that the Pure-Vu[supreg] System has a different mechanism of 
action than existing technologies due to its ability to break up and 
remove a high volume of debris from the colon and dislodge adherent 
films from the colon wall in a safe manner that cannot be achieved with 
irrigation done through the working channel of a colonoscope. The 
applicant also asserted that due to the controlled simultaneous removal 
of the debris and fluid by the evacuation pumps in the system, the 
Pure-Vu[supreg] System eliminates the likelihood of creating a fluid 
load in the colon, which cannot be achieved with any other device on 
the market. The applicant further asserted a differing mechanism of 
action via the ability to sense and automatically clear a blockage 
versus manual suction through the working channel of a colonoscope, 
which can clog quickly if there is any appreciable debris. Lastly, the 
applicant explained that the Pure-Vu[supreg] System is an oversleeve 
device that allows use of the working channel of the colonoscope to be 
open and allows therapy to be administered in tandem with cleansing, 
unlike existing technologies on the market.
    The applicant noted that the ClearPath system, a colonoscopy system 
by the company Easy Glide, received FDA clearance, but according to the 
applicant, was never fully brought to the US market. ClearPath was 
listed as the predicate device for the initial version of the Pure-Vu 
System[supreg] approved on September 22, 2016 (FDA 510(K) number 
K160015), in which both devices are described as able to irrigate and 
suction at any time during the procedure without any tools needing to 
be removed from the colonoscope working channel.\312\ The applicant 
claimed that this system did not have the High Intensity Pulsed Vortex 
Irrigation Jet and controlled suction capabilities with the sensing and 
auto purge technology that is critical to get the desired clinical 
outcome.
---------------------------------------------------------------------------

    \312\ FDA. 2016, September. Pure Vu System 510(k) premarket 
notification. Deparment of Health and Human Services. Accessed at 
https://www.accessdata.fda.gov/cdrh_docs/pdf16/K160015.pdf.
---------------------------------------------------------------------------

    With respect to the second criterion, whether a product is assigned 
to the same or a different MS-DRG, the applicant stated that the Pure-
Vu System is assigned to the same MS-DRGs as existing technologies. The 
applicant lists 21 MS-DRGs as being applicable, with MS-DRG 378 
(gastrointestinal hemorrhage with complication or comorbidity (CC)) 
accounting for 37.1 percent of cases, and MS-DRG 377 (gastrointestinal 
hemorrhage with major complication or comorbidity (MCC)) accounting for 
18.9 percent of total cases.
    With respect to the third criterion, whether the new use of 
technology involves the treatment of the same or similar type of 
disease and the same or similar patient population when compared to an 
existing technology, the applicant stated that the Pure-Vu 
System[supreg] does involve treatment of the same or similar type of 
disease and patient population as existing technology.
    In the proposed rule, after reviewing the information submitted by 
the applicant, we noted that we were unclear whether the Pure-
Vu[supreg] System's mechanism of action is similar to that of the 
version of the product that received initial 510(k) clearance that was 
approved on September 22, 2016 or other versions of the system. In 
addition, with regard to the previous versions of Pure-Vu[supreg], we 
were unsure if the limited availability noted by the applicant would 
allow the technology to be considered commercially available. We were 
also unclear what the applicant meants regarding the ClearPath system 
being not fully brought to the U.S. market. We stated that if the 
ClearPath system and/or earlier versions of the Pure-Vu[supreg] System 
were considered to be available on the U.S. market, then we are 
concerned that the current version of Pure-Vu[supreg] would no longer 
be considered new, as we believe it may be substantially similar to 
ClearPath and/or earlier versions of the Pure-Vu[supreg] System because 
they also allow for irrigation and suction of the colon without 
utilizing the working channel. We stated that if the current version of 
Pure-Vu is substantially similar to ClearPath and/or previous versions, 
then it appeared that the current Pure-Vu system may no longer be 
within the newness period. We further noted that though the applicant 
states the Pure-Vu[supreg] System features a high intensity pulsed 
vortex irrigation jet and controlled suction capabilities with sensing 
and auto purge technology, the Pure-Vu[supreg] System irrigates the 
colon using water and gas like other existing irrigation methods. We 
were therefore uncertain as to whether these features of the Pure-
Vu[supreg] System result in a new mechanism of action. We invited 
public comment on whether the Pure-Vu[supreg] System has a new 
mechanism of action compared to these predicate devices.
    We invited public comments on whether the Pure-Vu[supreg] System is 
substantially similar to existing technologies and whether it meets the 
newness criterion.
    Comment: The applicant submitted a letter that stated the Pure-
Vu[supreg] System meets the newness criterion. The applicant provided 
clarifying information regarding the mechanisms of action of the Pure-
Vu[supreg] System compared to its predicate device, the ClearPath 
system. The applicant stated that the predicate device, ClearPath, 
allowed for much higher fluid flow rates to raise irrigation pressure, 
whereas the Pure-Vu[supreg] System can mix gas into the fluid to create 
the pulsatile action of the irrigation jet with a lower fluid load in 
the colon. Additionally, the applicant stated that the Pure-Vu[supreg] 
System has the ability to simultaneously irrigate and suction fluid and 
debris, whereas the ClearPath system was only able to do one or the 
other, similar to a colonoscope. The applicant further stated that the 
Pure-Vu[supreg] System maintains a built-in suction system that uses a 
constant volume suction pump and autopurge functions that do not cause 
the colon to collapse, whereas the suction in the ClearPath system was 
the same as that of using the working channel of a colonoscope, which 
tends to collapse the lumen of the colon and, therefore, requires the 
endoscopist to continually insufflate the colon to provide patency and 
visualization. Finally, the applicant stated that the irrigation and 
suction in the Pure-Vu[supreg] System are self-contained (without need 
to plug into wall suction), whereas the ClearPath system needed to 
connect to the wall suction in the hospital room. The applicant stated 
that the flexibility of the Pure-Vu[supreg] System is beneficial in 
performing cases in the ICU where availability of vacuum ports can be 
problematic.
    The applicant also addressed market availability by stating that 
early versions of the Pure-Vu[supreg] System after the original 510(k) 
in September 2016 were only sold on a limited basis as part of a beta 
launch to allow potential investigators to evaluate the Gen 1 Pure-
Vu[supreg] System to determine if they would be interested in 
participating in clinical trials. The applicant stated that after 
initial feedback was received for the Gen 1 Pure-Vu[supreg] System, the 
company decided to not make the product available to the market until 
the system was redesigned. The applicant reiterated that the commercial 
version (Gen 2) was subsequently FDA cleared in June 2019 and became 
commercially available in September 2019.
    Response: We appreciate the additional information from the 
applicant on whether the product meets the newness criterion. After 
consideration of the information submitted by the applicant in their

[[Page 45053]]

comment and as part of its FY 2022 new technology add-on payment 
application for the Pure-Vu[supreg] System, we agree that the Pure-
Vu[supreg] System has a new mechanism of action as compared to the 
ClearPath system and traditional colonoscopes because of the Pure-
Vu[supreg] System's oversleeve design, which enable use of irrigation 
and suction while leaving the working channel available for therapeutic 
interventions, as well as the ability to simultaneously irrigate and 
suction fluid and debris. We note that the applicant did not respond to 
our concern with regard to whether the Pure-Vu System has a new 
mechanism of action as compared to the predicate version and therefore 
we believe the two versions are substantially similar as they both 
allow for simultaneous irrigation and suction of the colon without 
utilizing the working channel. Based on further information from the 
applicant regarding the market availability of the predicate version, 
it appears that the predicate Gen 1 version of the Pure-Vu System 
cleared in 2016 was available for sale on a limited basis. The 
applicant maintains that it was not on the market. Therefore, without 
additional information, we are unsure with regard to the appropriate 
date on which the newness period should begin and whether it is new for 
FY 2022. However, based on the information from the applicant, it 
appears that the predicate Gen 1 version of the Pure-Vu System cleared 
in 2016 was available for sale on a limited basis. The applicant 
maintains that it was not on the market. Therefore, without additional 
information, we are unsure with regard to the appropriate date on which 
the newness period should begin and whether it is new for FY 2022.
    With regard to the cost criterion, the applicant searched the FY 
2019 MedPAR claims data file with the FY 2019 Final Rule with 
Correction Notice IPPS Impact File to identify potential cases 
representing patients who may be eligible for treatment using the Pure-
Vu[supreg] System. The applicant identified claims that reported an 
ICD-10-CM diagnosis code of ICD-10-CM Z12.11 (Encounter for screening 
for malignant neoplasm of colon), K92.2 (Gastrointestinal hemorrhage, 
unspecified), D50.0 (Iron deficiency anemia secondary to blood loss 
(chronic)), and C18*._\313\ (malignant neoplasm of colon). The ICD-10-
PCS procedure codes listed in following table were used to identify 
claims involving colonoscopy procedures.
---------------------------------------------------------------------------

    \313\ Fourth character is required to describe specific location 
of neoplasm.
[GRAPHIC] [TIFF OMITTED] TR13AU21.182

    The claim search conducted by the applicant resulted in 163,236 
claims mapping to 633 MS-DRGs. The applicant stated that MS-DRGs 377 
(G.I. Hemorrhage W MCC), 378 (G.I. Hemorrhage W CC), and 379 (G.I. 
Hemorrhage W/O CC/MCC) were the most common MS-DRGs to which cases 
reporting the listed ICD-10-PCS codes were assigned. The applicant 
stated that the large number of DRGs to which these cases were assigned 
suggests that patients were admitted to the hospital for a wide variety 
of reasons, but during the course of their hospital stay the patients 
received a colonoscopy. According to the applicant, since GI bleeding 
is among the most common reasons for a patient needing an urgent 
colonoscopy, MS-DRGs 377-379 would be expected to be the most common 
MS-DRGs to which cases involving the Pure-Vu technology would be 
assigned. Lastly, the applicant did not have any data available to 
suggest any specific reasons why potential patients who would be 
eligible for the Pure-Vu technology would map to specific MS-DRGs 
identified based on the claims search, such as MS-DRG 291 (Heart 
Failure and Stroke).
    The applicant determined an average unstandardized case weighted 
charge per case of $63,265.
    The applicant did not remove charges for prior technology. The 
applicant stated that no prior technology is being replaced. The 
applicant then standardized the charges using the FY 2019 Final Rule 
with Correction Notice Impact File. Next, the applicant applied the 2-
year inflation factor used in the FY 2021 IPPS/LTCH PPS final rule to 
calculate outlier threshold charges (1.13218). To calculate the charges 
for the new technology, the applicant used the national average CCR for 
the Supplies and Equipment cost center of 0.297 from the FY 2021 Final 
IPPS rule. The applicant calculated a final inflated average case-
weighted standardized charge per case of $93,914, which exceeded the 
average case-weighted threshold amount of $63,265 by $30,649. The 
applicant stated that because the final inflated average case-weighted 
standardized charge per case exceeded the average case-weighted 
threshold amount, the therapy meets the cost criterion.
    After reviewing the information submitted by the applicant as part 
of its FY 2022 new technology add-on payment application for the Pure-
Vu[supreg] System, we noted that the MS-DRGs used in the cost analysis 
were not limited to those describing conditions likely to require a 
colonoscopy. For example, the applicant included cases

[[Page 45054]]

assigned to MS-DRG 291 (Heart Failure and Shock with MCC). When 
included in the cost analysis, the assumption made is that all 1,948 
cases for heart failure also had a colonoscopy performed where the 
technology could have potentially been utilized. We questioned whether 
all cases identified by the applicant appropriately represent potential 
cases eligible for the Pure-Vu[supreg] System. We invited public 
comment on whether the Pure-Vu[supreg] System meets the cost criterion.
    Comment: The applicant, submitted a comment in response to concerns 
on whether the Pure-Vu System[supreg] meets the cost criterion. 
Regarding whether all cases identified by the applicant in its original 
cost criterion analysis appropriately represent potential cases 
eligible for treatment with the Pure-Vu[supreg] System, the applicant 
noted that not every MS-DRG included in the cost analysis was 
necessarily gastrointestinal in nature. The applicant explained that 
this is because patients may be admitted to the hospital for a variety 
of diagnoses, any of which may eventually lead to colonoscopy. For 
instance, although not all cases assigned to MS-DRG 291 (Heart Failure 
and Shock with MCC) would require a colonoscopy, some cases did and 
were thus included in the applicant's original analysis.
    To respond to CMS concerns about the clinical coherence of the 
selected MS-DRGs, the applicant submitted a revised cost criterion 
analysis that pared down the number of MS-DRGs to only the top 12 in 
terms of case volume. The applicant identified 106,770 cases across 
these twelve MS-DRGs. The applicant stated that, according to the ICD-
10 data, although all of these cases would have received a colonoscopy 
during their hospital stay, only a small portion would have met the 
clinical criteria for needing the Pure-Vu[supreg] System. The applicant 
asserted that the revised analysis includes a more clinically coherent 
set of MS-DRGS with 9 of 12 specifically labeled for gastrointestinal 
use. The applicant stated that while MS-DRGs 871, 812, and 811 are not 
specific to gastrointestinal diagnoses, they encompass conditions that 
commonly lead to GI bleeds and the need for colonoscopy and are 
therefore, appropriate to include in this analysis. The applicant noted 
that the Pure-Vu[supreg] System continues to exceed the case-weighted 
threshold when the MS-DRGs included in the analysis are pared down, 
albeit by a smaller margin than in the original analysis.
    Response: We thank the commenter for its input and its submission 
of the revised cost criterion analysis. After review of the comments 
received and information submitted by the applicant for FY 2022 new 
technology add-on payments, we agree that the Pure-Vu[supreg] System 
meets the cost criterion as the final inflated case-weighted 
standardized charge per case exceeded the case-weighted threshold under 
the revised analysis including only the top 12 MS-DRGs by volume. We 
believe the cases identified by the applicant using the top 12 MS-DRG's 
by volume more appropriately represents potential cases eligible for 
the Pure-Vu[supreg] System than all the cases in the MS-DRGs used in 
their initial cost analysis.
    With respect to the substantial clinical improvement criterion, the 
applicant asserted that the Pure-Vu[supreg] System offers the ability 
to achieve rapid beneficial resolution of the disease process treatment 
by achieving rapid and full visualization of the colon, which will 
improve diagnostic yield and the effectiveness of treatment of diseases 
of the bowel. The applicant claimed that due to the Pure-Vu[supreg] 
System's ability to cleanse the colon during the colonoscopy procedure 
in conjunction with a standard bowel preparation, or with an enema (to 
allow entry into the rectum) and without any purgative based 
preparation, the technology allows for earlier intervention. The 
applicant stated that in the case of an LGIB, this will reduce bleeding 
by achieving more rapid hemostasis and reduce the overall length of 
stay in the hospital for a portion of this population. The applicant 
also asserted the technology reduces the subsequent diagnostic and, in 
some instances, therapeutic interventions by minimizing aborted and 
early repeat procedures due to poor visualization caused by inadequate 
preparation. The applicant stated that the system can provide cleansing 
and removal of fecal matter, blood and other debris while maintaining 
the visibility of the colonoscope's camera and availability of the 
working channel to apply critical therapies.
    In support of its claims, the applicant submitted a self-sponsored, 
U.S.-based, multicenter, prospective, single arm study in the inpatient 
setting, analyzing 94 patients, 65 of which (68 percent) had a GI 
bleed.\314\ Of the 94 patients (41 percent females/59 percent males), 
the mean age was 62 years. According to the applicant, the study's 
primary endpoint was the rate of improved bowel cleansing level from 
baseline to after use of the Pure-Vu[supreg] System per colon segment 
using the Boston Bowel Preparation Scale (BBPS). The BBPS score was 
recorded for each colorectal segment (left colon, transverse colon, and 
right colon segments) both prior to (baseline) and after colon 
cleansing with the Pure-Vu[supreg] System. An adequate cleansing level 
was a priori defined as a BBPS >=2 in all evaluated colon segments. The 
study found that in 79 of the 94 patients (84 percent), the physician 
was able to successfully diagnose or rule out a GI bleed in the colon 
per the patients' colonoscopy indication using only the Pure-Vu[supreg] 
System. The analysis showed statistically significant visualization 
improvement in each colon segment after Pure-Vu[supreg] use with a mean 
BBPS score in the descending colon, sigmoid, and rectum of 1.74 pre-
Pure-Vu[supreg] use and 2.89 post-Pure-Vu[supreg] use (P<0.001); in the 
transverse colon of 1.74 pre-Pure-Vu[supreg] use and 2.91 post Pure-
Vu[supreg] use (P<0.001); and the ascending colon and cecum of 1.50 
pre-Pure-Vu[supreg] use and 2.86 post Pure-Vu[supreg] use (P<0.001). 
The study found only 2 percent of cases where the diagnosis could not 
be achieved due to inadequate preparation. Overall, the 84 (89.4 
percent) patients that received the Pure-Vu[supreg] System within the 
study improved BBPS scores from 38 percent (95 percent CI 28, 49) to 96 
percent (95 percent CI 90, 99) in segments evaluated. The study noted 
one procedure related perforation which required surgical repair, and 
the patient was discharged 48 hours post operatively and recovered 
fully.
---------------------------------------------------------------------------

    \314\ Helmut Neumann ML, Tim Zimmermann, Gabriel Lang, Jason B. 
Samarasena, Seth A. Gross, Bhaumik Brahmbhatt, Haleh Pazwash, 
Vladimir Kushnir. Evaluation of bowel cleansing efficacy in 
hospitalized patient population using the pure-vu system. 
Gastrointestinal Endoscopy. 2019;89(6).
---------------------------------------------------------------------------

    The applicant also provided three outpatient clinical studies to 
demonstrate the Pure-Vu[supreg] System's capability to convert patients 
to adequate preparation where preparation was previously inadequate, 
and the visualization was poor based on the BBPS. In the first study, 
Perez J., et al. conducted an outpatient prospective pilot study using 
the Pure-Vu[supreg] System.\315\ The study observed 50 patients with 
poorly prepared colons undergoing colonoscopy at two outpatient 
clinical sites in Spain and Israel, respectively. The applicant claimed 
study patients underwent a reduced bowel preparation consisting of the 
following: No dried fruits, seeds, or nuts starting 2 days before the 
colonoscopy, a clear liquid diet starting 18 to 24 hours before 
colonoscopy, and

[[Page 45055]]

a split dose of 20mg oral bisacodyl. The study found the number of 
patients with an adequate cleansing level (BBPS >=2 in each colon 
segment) increased significantly from 31 percent (15/49) prior to use 
of the Pure-Vu System (baseline) to 98 percent (48/49) after use of the 
Pure-Vu[supreg] System (P<0.001), with no serious adverse events 
reported.
---------------------------------------------------------------------------

    \315\ Perez Jimenez J, Diego Bermudez L, Gralnek IM, Martin 
Herrera L, Libes M. An Intraprocedural Endoscopic Cleansing Device 
for Achieving Adequate Colon Preparation in Poorly Prepped Patients. 
J Clin Gastroenterol. 2019;53(7):530-4.
---------------------------------------------------------------------------

    In the second study provided by the applicant, van Keulen, et al. 
also conducted a single-arm, prospective study on 47 patients with a 
median age of 61 years in the outpatient setting in the Netherlands 
using the Pure-Vu[supreg] System.\316\ Within the study, cecal 
intubation was achieved in 46/47 patients. This multicenter feasibility 
study found that the Pure-Vu[supreg] System significantly improved the 
proportion of patients with adequate bowel cleansing from 19.1 percent 
prior to the use of the Pure-Vu[supreg] System to 97.9 percent after 
its use (P<0.001) and median BBPS score (from 3.0 [IQR 0.0-5.0] to 9.0 
[IQR 8.0-9.0]).
---------------------------------------------------------------------------

    \316\ Van Keulen KE, Neumann H, Schattenberg JM, Van Esch AAJ, 
Kievit W, Spaander MCW, Siersema PD. A novel device for 
intracolonoscopy cleansing of inadequately prepared colonoscopy 
patients: a feasibility study. Endoscopy. 2019 Jan;51(1):85-92. doi: 
10.1055/a-0632-1927. Epub 2018 Jul 11.
---------------------------------------------------------------------------

    In the third study provided by the applicant that directly 
evaluated the Pure-Vu[supreg] System in a clinical setting, Bertiger 
G., et al. performed a United States-based single center, prospective, 
outpatient study investigating regimes of reduced outpatient bowel 
preparations, which included low doses of over-the-counter laxatives, 
and eliminating the typical 24 hour clear liquid diet restriction, 
which was replaced by a low residue diet the day before the procedure. 
In this study, 46 of a possible 49 patients received a colonoscopy, 8 
of which took the over-the-counter laxative (``MiraLAX arm''), 21 
patients ingested two doses of 7.5oz Magnesium Citrate (MgC) each taken 
with 19.5oz of clear liquid (``Mag Citrate 15oz arm''), and 18 patients 
ingested 2 doses of 5oz MgC taken with 16oz of clear liquid (``Mag 
Citrate 10oz arm''). Of the 46 subjects, 59 percent were males and 
there was a mean age of 619.48 years. The study found that 
each of the 3 study arms revealed significant differences in BBPS score 
between the baseline preparation and post-cleansing via Pure-Vu. All 
the preparation regimens resulted in inadequately prepped colons. 
Comparing the mean BBPS rating for both pre- and post- Pure-Vu[supreg] 
use, the MiraLAX arm was inferior (P <0.05) to both Mag Citrate arms. 
For the MiraLAX arm, the mean BBPS Score improved from 1.50 to 8.63. 
For the Mag Citrate 15oz arm, the mean BBPS score improved from 3.62 to 
8.95. For the Mag Citrate 10oz arm, the mean BBPS Score improved from 
4.76 to 9.0.
    In addition to the retrospective studies provided, the applicant 
also submitted three case studies to highlight the various clinical 
presentations of LGIB with the use of the Pure-Vu[supreg] System. In 
the first case, the applicant presented a 71-year-old woman with 
multiple episodes of bloody bowel movements and low hemoglobin levels 
for 2 days after a screening colonoscopy where 8 polyps were removed. 
The applicant stated that the patient underwent a successful 
colonoscopy using Pure-Vu without standard inpatient bowel preparation 
within 5 hours, and in addition to expediting the colonoscopy, four 
significant post-polypectomy ulcers were found and clipped by allowing 
the physician to cleanse the area and place the clips simultaneously. 
The applicant claimed that since the Pure-Vu[supreg] System does not 
impact the use of the endoscope's working channel, the physician was 
able to cleanse the area as needed during the intervention to allow 
precise placement of the clips applied to achieve hemostasis and the 
patient was discharged that same day.
    The applicant submitted another case example where a 52-year-old 
male was admitted from the emergency department to the ICU due to 
significant GI bleeding, hemorrhagic shock, and acute kidney injury 
(AKI) six days after a colonoscopy where nine polyps were removed, 
including two polyps greater than 2 cm. The applicant stated that 
angiographic control of the bleeding was not considered due to AKI with 
rising creatinine, and bedside colonoscopy was immediately performed 
with the Pure-Vu[supreg] System without any bowel prep. Per the 
applicant, the physician was able to visualize the entire colon to 
confirm all sources of bleeding and place two clips to obtain 
hemostasis, and the patient was downgraded out of the ICU that day and 
discharged from the hospital the following day.
    In the third case study submitted by the applicant, a 64-year-old 
male was admitted to the ICU with one day of bright red blood per 
rectum (BRBPR) along with a complex set of disorders including but not 
limited to alcohol use disorder, heart failure with reduced ejection 
fraction of 30 percent, and multidrug resistant tuberculosis. The Pure-
Vu[supreg] System was used to attempt to definitively identify the 
bleeding source in the ICU. The applicant stated that although no 
active sites of bleeding were seen, red blood was found in the entire 
colon, and the patient was transferred out of the ICU 2 days later and 
discharged 3 days after transfer to the floor. The applicant claimed 
that while the patient's bleeding had stopped by the time the colon was 
examined, the ability to directly visualize the entire colon using the 
Pure-Vu[supreg] System helped avoid a third CT angiography during this 
hospitalization and helped the physicians to confirm that prior coil 
embolization had not resulted in focal colonic ischemia. The applicant 
asserted that this case showed that the Pure-Vu[supreg] System can be 
used with minimal preparation, enabling rapid investigation of LGIB in 
a very complex patient. The applicant concluded that these case studies 
demonstrate that a change in patient management occurs when the option 
of the Pure-Vu[supreg] System is available, especially when there is an 
urgent or severe GI bleed, where circumstances where other procedures 
(such as CT angiography) are insufficient and the option to perform the 
colonoscopy sooner is preferred.
    After reviewing the information submitted by the applicant as part 
of its FY 2022 new technology add-on payment application for the Pure-
Vu[supreg] System, we had stated the following concerns in the proposed 
rule (86 FR 25304). While the studies provided in support of the Pure-
Vu[supreg] System measure improvement of bowel preparation using the 
BBPS, the applicant did not provide data indicating that the improved 
BBPS directly leads to improved clinical outcomes (for example, 
reduction of blood loss in LGIB or reduction of missed polyps) based on 
use of the Pure-Vu[supreg] System. Additionally, we noted that the 
applicant has not provided any studies comparing the efficacy of the 
Pure-Vu[supreg] System to other existing methods or products for 
irrigation in support of its claims that the product is superior at 
removing debris from the colon while simultaneously preventing the 
colon from collapsing, allowing use of the working channel, or 
improving outcomes. Furthermore, we noted that many of the provided 
studies were based on small sample sizes, which may affect the quality 
and reliability of the data provided in support of the technology. In 
addition, we noted that the methodology described in the provided 
studies often involved time to adequately prepare the colon and 
included outpatient planned procedures, which may not reflect the 
emergent situations that the applicant states the Pure-Vu[supreg] 
System is intended to address in the inpatient setting. We

[[Page 45056]]

also noted that the Helmut, et al. study noted one procedure related 
perforation which required surgical repair and we invited public 
comments regarding the concern of procedure related perforation.
    We invited public comments on whether the Pure-Vu[supreg] System 
meets the substantial clinical improvement criterion.
    Comment: Several commenters provided specific examples of 
individual instances where the use of the Pure-Vu[supreg] System was 
beneficial for a particular patient, including some patients with 
unique challenges that the commenters stated could not have been 
addressed without the use of the Pure-Vu[supreg] System. A commenter, 
offering support, claimed the Pure-Vu[supreg] System can help shorten 
hospital stays and maximize access to their hospital's endoscopy unit 
and cited cost as a limiting factor for the Pure-Vu[supreg] System's 
continued use. A commenter, offering support, did not consider Pure-
Vu[supreg] as a panacea for all poor bowel preparations and did not 
think it was an alternative to appropriate bowel cleansing in most 
patients but did think it can be a great addition and a useful tool in 
every endoscopy suite and that it provides clear clinical improvement 
in the appropriate patients.
    Response: We appreciate all of the comments received related to the 
Pure-Vu[supreg] System and have taken them into consideration in making 
our determination of substantial clinical improvement.
    Comment: The applicant submitted comments in response to CMS's 
concerns in the FY 2022 IPPS/LTCH PPS proposed rule regarding whether 
the Pure-Vu[supreg] System meets the substantial clinical improvement 
criterion. The applicant reiterated previously shared data from a study 
by the Cleveland Clinic showing 51 percent of 8,819 patients observed 
over a 4-year period were inadequately prepared for colonoscopies, 
leading to one extra day in the hospital compared to patients that were 
adequately prepared.\317\
---------------------------------------------------------------------------

    \317\ Garber A, Sarvepalli S, Burke CA, Bhatt A, Ibrahim M, 
McMichael J, et al. Modifiable Factors Associated with Quality of 
Bowel Preparation Among Hospitalized Patients Undergoing 
Colonoscopy. J Hosp Med. 2019;14(5):278-83.
---------------------------------------------------------------------------

    The applicant also presented a recently published study of 94 
patients that analyzed the ability of the Pure-Vu[supreg] System to 
improve visualization of the colon mucosa for hospitalized patients 
undergoing colonoscopy.\318\ The study demonstrated improvement in BBPS 
between a baseline for the patients prior to cleansing with the Pure-
Vu[supreg] System and following the cleansing, with 38% of patients 
showing adequate colon cleansing level before the use of Pure-
Vu[supreg] and 96% following the use of Pure-Vu[supreg]. The applicant 
also provided information on the Pure-Vu[supreg] System's performance 
within individual segments of the colon from this same study.
---------------------------------------------------------------------------

    \318\ 2 Neumann H, Latorre M, Zimmerman T, Lang G, Samarasena J, 
Gross S, Brahmbhatt B, Pazwash H, Kushnir V. A multicenter, 
prospective, inpatient feasibility study to evaluate the use of an 
intra-colonoscopy cleansing device to optimize colon preparation in 
hospitalized patients: the REDUCE study. BMC Gastroenterol. 2021 May 
22;21(1):232.
---------------------------------------------------------------------------

    In response to our concern that while the evidence presented 
demonstrated improvement in BBPS but did not provide data indicating 
that improved BBPS directly leads to improved clinical outcomes, the 
applicant provided a study demonstrating the correlation between the 
ability to visualize the mucosa and the ability to detect important 
pathology. The study generally demonstrated a linear increasing trend 
in advanced adenoma detection rates with improvement in BBPS.\319\ 
Lastly, the applicant submitted a modeling study indicating that the 
Pure-Vu[supreg] System can generate cost savings to health systems on a 
per patient basis if used in the colorectal cancer screening and 
surveillance population.
---------------------------------------------------------------------------

    \319\ Jain D, Momeni M, Krishnaiah M, Anand S, Singhal S. 
Importance of reporting segmental bowel preparation scores during 
colonoscopy in clinical practice. World J Gastroenterol. 2015 Apr 
7;21(13):3994-9. doi:10.3748/wjg.v21.i13.3994. PMID: 25852286; 
PMCID: PMC4385548.
---------------------------------------------------------------------------

    Response: We thank the applicant for their comment and appreciate 
the additional data submitted to address our concerns. After review of 
all the data received to date, we continue to have concerns regarding 
the substantial clinical improvement criterion as noted in the FY 2022 
IPPS/LTCH PPS proposed rule. Specifically, we remain concerned that the 
studies provided in support of the Pure-Vu[supreg] System measure 
improvement of bowel preparation using the BBPS but do not provide data 
indicating that the improved BBPS directly leads to improved clinical 
outcomes. In addition, the studies did not demonstrate outcomes in the 
emergent situations for which the Pure-Vu[supreg] System is intended to 
address. While an additional study provided by the applicant in their 
comment indicated a general link between improved BBPS and advanced 
adenoma detection rates, we note that the study occurred in patients 
undergoing screening colonoscopy, and did not include the use of Pure-
Vu. We also remain concerned about the lack of studies comparing the 
Pure-Vu[supreg] System to other existing methods or products for 
irrigation in support of its claims that the product is superior at 
removing debris from the colon while simultaneously preventing the 
colon from collapsing, allowing use of the working channel, or 
improving outcomes.
    After consideration of all the information from the applicant, as 
well as the comments we received, we are unable to determine that the 
Pure-Vu[supreg] System represents a substantial clinical improvement 
over existing technologies, and we are not approving new technology 
add-on payments for the Pure-Vu[supreg] System for FY 2022.
k. Rapid ASPECTS
    iSchemaView (which is in the process of a name change to RapidAI) 
submitted an application for new technology add-on payments for Rapid 
ASPECTS for FY 2022. According to the applicant, Rapid ASPECTS is a 
computer-aided diagnosis (CADx) software device used to assist the 
clinician in the assessment and characterization of brain tissue 
abnormalities using computed tomography (CT) image data. The applicant 
asserted that the software automatically registers images and segments 
and analyzes ASPECTS Regions of Interest (ROIs). According to the 
applicant, Rapid ASPECTS extracts image data for the ROI(s) to provide 
analysis and computer analytics based on morphological characteristics. 
The applicant stated that the imaging features are then synthesized by 
an artificial intelligence algorithm into a single ASPECT Score.
    The applicant stated Rapid ASPECTS is indicated for evaluation of 
patients presenting for diagnostic imaging workup with known Middle 
Cerebral Artery (MCA) or Internal Carotid Artery (ICA) occlusion, for 
evaluation of extent of disease. The applicant stated that extent of 
disease refers to the number of ASPECTS regions affected, which is 
reflected in the total score.
    According to the applicant, the Rapid ASPECTS device provides 
information that may be useful in the characterization of early 
ischemic brain tissue injury during image interpretation (within 6 
hours). The applicant stated Rapid ASPECTS provides a comparative 
analysis to the ASPECTS standard of care radiologist assessment using 
the ASPECTS atlas definitions and atlas display including highlighted 
ROIs and numerical scoring. The applicant stated that Rapid ASPECTS is 
not intended for primary interpretation of CT images; it is used to 
assist physician evaluation.

[[Page 45057]]

The applicant asserted Rapid ASPECTS has been validated in patients 
with known MCA or ICA occlusion prior to ASPECT scoring.
    According to the applicant, when patients with a suspected stroke 
arrive at an emergency department, they are rapidly triaged to the CT 
scanner for a non-contrast CT (NCCT) and CT angiography (CTA). The 
applicant stated that CTA directly images large vessel occlusions and 
the NCCT can exclude brain hemorrhage and identify early signs of brain 
infarction. The applicant asserted that automated large vessel 
occlusion (LVO) detection software is now used at many sites to quickly 
identify LVOs on CTA and provide physicians with early notification 
that an LVO has been identified. The applicant stated that following 
identification of an LVO, the next imaging evaluation required is for a 
physician, typically a radiologist or neuroradiologist, to determine 
the ASPECT score by taking a close look at the NCCT for evidence of 
early infarct signs. The applicant stated that patients with an ASPECT 
score between 6 and 10 who meet clinical criteria for thrombectomy 
should receive thrombectomy as soon as possible, if treatment can occur 
within 6 hours of symptoms onset. The applicant asserted that for 
patients who present beyond 6 hours, a CT perfusion or MRI scan are 
required to identify which patients are eligible for thrombectomy.
    The applicant stated approximately 800,000 primary (first-time) or 
secondary (recurrent) strokes occur each year in the U.S., with the 
majority being primary strokes (roughly 600,000). Of these strokes, 
approximately 87% are ischemic infarctions, 10% are primary 
hemorrhages, and 3% are subarachnoid hemorrhage.\320\ According to the 
applicant, the incidence of stroke rapidly increases with age, doubling 
for each decade after age 55. The applicant asserted that among adults 
ages 35 to 44, the incidence of stroke is 30 to 120 in 100,000 per 
year, and for those ages 65 to 74, the incidence is 670 to 970 in 
100,000 per year. Therefore, according to the applicant, the primary 
burden of stroke affects the Medicare-age population. The applicant 
stated the most disabling strokes are those due to large vessel 
occlusions (LVOs), and treatment of these strokes has the largest 
therapeutic benefits.\321\
---------------------------------------------------------------------------

    \320\ Ovbiagele B, et al. Stroke Epidemiology: Advancing Our 
Understanding of Disease Mechanism and Therapy Neurotherapeutics. 
(2011) 8:319-329.
    \321\ Ovbiagele B, et al. Stroke Epidemiology: Advancing Our 
Understanding of Disease Mechanism and Therapy Neurotherapeutics. 
(2011) 8:319-329.
---------------------------------------------------------------------------

    The applicant stated that Rapid ASPECTS received FDA 510(k) 
clearance as a CADx software device on June 26, 2020 and provided a 
date of first installation of September 1, 2020. The applicant 
described Rapid ASPECTS as a machine learning-based automated software 
for assessment of ASPECTS. The applicant asserted that Rapid ASPECTS 
remains the only cleared ASPECTS software and the only stroke imaging 
software to receive a CADx clearance by the FDA. The legally marketed 
predicate device that Rapid ASPECTS is substantially equivalent to, per 
FDA, is QuantX,\322\ which was granted De Novo authorization on July 
19, 2017. QuantX is a CADx software device used to assist radiologists 
in the assessment and characterization of breast abnormalities using 
magnetic resonance (MR) image data and is indicated for evaluation of 
patients presenting for high-risk screening, diagnostic imaging workup, 
or evaluation of extent of known disease.\323\
---------------------------------------------------------------------------

    \322\ Rapid ASPECTS 510(k) clearance letter from FDA: https://www.accessdata.fda.gov/cdrh_docs/pdf20/K200760.pdf.
    \323\ QuantX De Novo decision summary from FDA: https://www.accessdata.fda.gov/cdrh_docs/reviews/DEN170022.pdf.
---------------------------------------------------------------------------

    We note the applicant submitted a request for approval of a unique 
ICD-10-PCS procedure code to identify use of the technology and was 
granted approval for the following procedure code effective October 1, 
2021: XXE0X07 (Measurement of intracranial vascular activity, computer-
aided assessment, new technology group 7). According to the applicant, 
this new ICD-10-PCS code would be reported in addition to the non-
contrast CT using the appropriate code as listed in current coding 
systems.
    As discussed previously, if a technology meets all three of the 
substantial similarity criteria, it would be considered substantially 
similar to an existing technology and would not be considered ``new'' 
for purposes of new technology add-on payments.
    With regard to the first criterion, whether a product uses the same 
or a similar mechanism of action to achieve a therapeutic outcome, the 
applicant asserted Rapid ASPECTS uses a new mechanism of action 
(machine learning) to assess CT scans and synthesize a single ASPECT 
score when compared to existing options which are limited to clinical 
assessment by a human reader. According to the applicant, this software 
remains the only FDA-cleared ASPECTS software and the only stroke 
imaging software to receive a CADx clearance by the FDA. The applicant 
asserted Rapid ASPECTS is fully automated and produces a score for each 
of the 10 ASPECTS regions, as well as a total score in approximately 2 
minutes.
    With regard to the second criterion, whether the technology is 
assigned to the same or a different MS-DRG, the applicant stated that 
cases involving Rapid ASPECTS would be assigned to the same MS-DRGs as 
cases involving patients confirmed with an eligible LVO by a positive 
CTA. According to the applicant, in these cases, the traditional 
clinical pathway requires a physician to determine the ASPECT score 
through an imaging evaluation. The applicant noted that Rapid ASPECTS 
may result in patients being assigned to a different MS-DRG depending 
on whether or not a mechanical thrombectomy is performed as a result of 
the Rapid ASPECTS results.
    With regard to the third criterion, whether the new use of the 
technology involves the treatment of the same or similar type of 
disease and the same or similar patient population, the applicant 
asserted Rapid ASPECTS addresses the current stroke population.
    In summary, the applicant believes that Rapid ASPECTS is not 
substantially similar to other currently available therapies because 
Rapid ASPECTS uses a new mechanism of action (machine learning) to 
assess CT scans and synthesize a single ASPECT score. We stated in the 
proposed rule that we are unclear as to whether machine learning to 
assess CT scans and synthesize a single ASPECT score would represent a 
unique mechanism of action, or how the mechanism of action by which 
Rapid ASPECTS assesses stroke imaging is distinct from other automated 
stroke imaging analysis tools, or the traditional hospital workflow.
    We stated that we continue to be interested in public comments 
regarding issues related to determining newness for technologies that 
use AI, an algorithm or software, as discussed in the FY 2021 IPPS/LTCH 
PPS final rule (85 FR 58628). Specifically, we are interested in public 
comment on how these technologies, including devices classified as 
radiological computer aided triage and notification software and 
radiological computer-assisted diagnostic software, may be considered 
for the purpose of identifying a unique mechanism of action; how 
updates to AI, an algorithm or software would affect an already 
approved technology or a competing technology; whether software changes 
for an already approved technology could be

[[Page 45058]]

considered a new mechanism of action, and whether an improved algorithm 
by competing technologies would represent a unique mechanism of action 
if the outcome is the same as an already approved AI new technology.
    We invited public comments on whether Rapid ASPECTS is 
substantially similar to existing technologies, including specifically 
with respect to the mechanism of action, and whether it meets the 
newness criterion.
    Comment: The applicant submitted comments responding to CMS's 
concerns regarding newness as indicated in the proposed rule. With 
respect to our concern as to whether machine learning to assess CT 
scans and synthesize a single ASPECT score would represent a unique 
mechanism of action, or how the mechanism of action by which Rapid 
ASPECTS assesses stroke imaging is distinct from other automated stroke 
imaging analysis tools, or the traditional hospital workflow, the 
applicant stated that it used the framework for AI/ML that is 
differentiated within the FDA product codes for diagnostic imaging 
products. Per the applicant, these codes reflect the mechanism of 
action and also how products may be interpreted in terms of performance 
both against a reference standard and in informing the clinician.
    The applicant stated that ContaCT/Viz LVO was classified as (CADt) 
Computer Aided Triage and Notification as a mechanism of action. Per 
the applicant, products in this category have limitations in what the 
software may do; specifically, that it is limited to determining and 
notifying the end user of suspicion of a disease state. In contrast, 
more advanced implementations of AI/ML require the establishment of 
clinical utility which shows the device not only performs to 
specifications but provides some value in the clinical setting 
regarding the lesion under investigation. Per the applicant, Rapid 
ASPECTS is classified as CADe/x, which provides the added information 
of a standard of care score which goes beyond triage and notification 
to inform the end user regarding treatment decisions. Specifically, 
Rapid ASPECTS provides information to help determine if the patient is 
a candidate for treatment of the LVO or not, while the previously 
approved ContaCT only informs the end user of a suspicion but not the 
severity or extent of the disease. Furthermore, the applicant stated 
that Rapid ASPECTS normalizes the decision-making ability of physicians 
with different levels of expertise. The applicant emphasizes that Rapid 
ASPECTS allows the typical reader to perform at the level of an expert 
reader and that it is the only stroke related software product that has 
been cleared with the advanced CADe/x designation, both of which are 
novel features. It is also the only automated software for ASPECT score 
assessment that has been cleared by FDA with any designation.
    The applicant also concurred with other commenters in stating that 
AI, an algorithm, or software should be evaluated for newness in the 
same way as CMS evaluates any other medical device applying for new 
technology add-on payment. That is, the commenters stated that human 
intelligence and human processes are not FDA approved or cleared 
technologies and should not be used as a comparator to evaluate whether 
Rapid ASPECTS, or any technology, meets the definition of newness. A 
commenter also noted that each of the AI technologies that applied for 
new technology add-on payments for FY 2022 are distinctly different in 
that the technologies focus on different patient populations and/or 
would be assigned to different MS-DRGs. This commenter stated, along 
with the applicant, that Rapid ASPECTS is different from other 
technologies in that it uses machine learning to evaluate head CT scans 
and develops a single ASPECTS score in patients with suspected stroke.
    A commenter noted how updates to an AI, an algorithm or software 
would affect an already approved technology or a competing technology. 
This commenter noted a phenomenon known as ``model drift,'' which can 
occur over time due to changes in healthcare workflows, practices, 
populations, and data. The commenter explained that when this occurs, 
the underlying algorithm does not automatically change and adapt to the 
new inputs, but its output predictions can become less accurate over 
time. The commenter further noted that model drift can be detected 
using the same statistical analyses that rigorously tested the 
algorithm's initial training data inputs and output predictions to 
ensure that they are free of statistically significant variances or 
biases. The commenter stated that if the AI/Machine Learning model or 
the algorithms that comprise the model change over time, they ideally 
should be subjected to this extensive statistical testing regimen that 
occurred before its original deployment, and developers should gauge 
the nature and extent of any model drift that occurs and make slight 
modifications if possible that would allow for its continued use in 
clinical care.
    Response: We thank the applicant for its input. After consideration 
of the comments received and information submitted by the applicant, at 
this time and given our ongoing consideration of assessing newness for 
technology that use AI, an algorithm or software, we agree that Rapid 
ASPECTS does not use the same or a similar mechanism of action to 
achieve a therapeutic outcome when compared to existing treatment 
because it provides information, and specifically a standard of care 
score that characterizes the severity and extent of an LVO, to inform 
the end user of treatment decisions. Therefore, we believe that Rapid 
ASPECTS is not substantially similar to an existing technology and 
meets the newness criterion.
    We also thank the commenters for their input on determining newness 
for technologies that use AI, an algorithm or software, including the 
applicant's distinctions between devices classified as computer-aided 
triage and notification software (CADt) and computer-aided detection or 
diagnosis software (CADe/x), as discussed in the proposed rule. We will 
continue consider how these technologies may be used to identify a 
unique mechanism of action; how updates to AI, an algorithm or software 
would affect an already approved technology or a competing technology; 
whether software changes for an already approved technology could be 
considered a new mechanism of action, and whether an improved algorithm 
by competing technologies would represent a unique mechanism of action 
if the outcome is the same as an already approved AI new technology, as 
we gain more experience in this area.
    With respect to the cost criterion, the applicant provided three 
analyses: (1) A baseline analysis containing all cases reporting one of 
the targeted ICD-10-CM codes below as the principal diagnosis code for 
cerebral infarction that map to one of the applicant's targeted MS-
DRGs; (2) an analysis limited to MS-DRGs with a case volume over 100; 
and (3) an analysis limited to MS-DRGs 023, 062, 064, 065, and 066, 
which per the applicant would reflect 80 percent of all stays. For the 
baseline analysis, the applicant first extracted all inpatient stays 
from the CY 2018 Limited Data Set Standard Analytic File (LDS SAF) that 
contained a principal ICD-10-CM diagnosis code for cerebral infarction. 
The applicant used the following ICD-10-CM diagnosis codes.
BILLING CODE 4120-01-P

[[Page 45059]]

[GRAPHIC] [TIFF OMITTED] TR13AU21.183


[[Page 45060]]


[GRAPHIC] [TIFF OMITTED] TR13AU21.184

    The applicant then removed cases for hospitals that are not paid 
under the IPPS. The applicant also removed inpatient stays and their 
assigned MS-DRGs from its analysis where the assigned MS-DRG met any of 
the following conditions: (1) The MS-DRG is for a part of the body not 
related to the head; (2) the MS-DRG is a psychiatric MS-DRG, alcohol-
related MS-DRG, or a catchall MS-DRG; (3) the MS-DRG has a very small 
number of cases; or (4) the MS-DRG is unlikely to involve an LVO. The 
applicant identified 66,990 cases mapping to 27 MS-DRGs, as listed in 
the following table, in descending order by volume:

[[Page 45061]]

[GRAPHIC] [TIFF OMITTED] TR13AU21.185

BILLING CODE 4120-01-C
    The applicant then standardized the charges and applied the 2-year 
charge inflation factor of 13.2 percent used to adjust the outlier 
threshold determination (85 FR 59039). The applicant did not remove 
charges for prior technology, as the applicant believes Rapid ASPECTS 
does not eliminate or replace any prior technology or services. The 
applicant also noted that it did not remove charges related to the 
prior technology, as the applicant believes Rapid ASPECTS does not 
reduce costs during the inpatient stay.
    The applicant then added charges for the technology. The applicant 
stated that it estimated the cost per case of Rapid ASPECTS using 
historical

[[Page 45062]]

utilization data gathered from its Rapid CTA module. The applicant 
anticipates Rapid ASPECTS will be used in the same hospital sites as 
Rapid CTA, which also provides the applicant with a baseline number of 
Medicare and non-Medicare patients who were identified with a suspected 
LVO. The applicant estimated that approximately 20.5 percent of all 
patients who received a RAPID CTA scan qualified as inpatients eligible 
for a Rapid ASPECTS scan. The applicant divided the total number of 
qualified Medicare and non-Medicare inpatients by the total number of 
subscriber hospitals to arrive at an average number of inpatients 
eligible to be scanned with Rapid ASPECTS per subscriber hospital per 
year. The applicant then took the estimated average sales price per 
annual contract of Rapid ASPECTS per hospital and divided it across the 
estimated annual number of Rapid ASPECTS inpatients per site to 
estimate the average cost per case per subscriber hospital. Finally, 
the applicant divided the average cost per case by the national average 
CCR for radiology of 0.136 (85 FR 58601).
    The applicant calculated a case-weighted threshold amount of 
$76,398 and a final inflated average case-weighted standardized charge 
per case of $90,097. Based on this analysis, the applicant asserted 
that Rapid ASPECTS meets the cost criterion because the final inflated 
average case-weighted standardized charge per case exceeds the case-
weighted threshold amount. The applicant submitted two additional 
scenarios to demonstrate that the technology meets the cost criterion 
using the same methodology described but with limits on the cases. The 
first scenario limited the analysis to MS-DRGs with at least 100 cases. 
This resulted in a case-weighted threshold of $76,457 and a final 
inflated average case weighted standardized charge per case of $90,172. 
The second scenario limited the analysis to MS-DRGs 023, 062, 064, 065, 
and 066, which per the applicant reflect 80 percent of all stays. This 
second alternative method resulted in a case-weighted threshold of 
$67,890 and a final inflated average case-weighted standardized charge 
per case of $77,614. Across all three analyses, the applicant 
maintained that the technology meets the cost criterion because the 
final inflated average case-weighted standardized charge per case 
exceeds the average case-weighted threshold amount.
    We noted the following concerns in the proposed rule regarding the 
cost analysis for Rapid ASPECTS. The applicant stated it removed from 
its analysis those cases and their assigned MS-DRG where the assigned 
MS-DRG was for a body part that is not the head; however, the list of 
MS-DRGs the applicant presented included MS-DRGs 37 (Extracranial 
Procedures w/MCC) and 38 (Extracranial Procedures w/CC), which by 
definition describe procedures outside of the head. We stated that we 
would like to understand why these MS-DRGs and their assigned cases 
were included in the baseline analysis. We stated that we would also 
like to understand the time period of the claims the applicant selected 
from the CY 2018 SAF, as this could have implications for the inflation 
factor used to update charges if the applicant selected claims from FY 
2018 as opposed to FY 2019.
    We stated that the applicant appears to have used a single list 
price of Rapid ASPECTS per hospital with a cost per patient that can 
vary based on the volume of cases. We noted that the cost per patient 
varies based on the utilization of the technology by the hospitals. The 
cost per patient could be skewed by the small number of hospitals 
utilizing the technology and their low case volumes. It is possible, if 
hospitals with large patient populations adopt Rapid ASPECTS, the cost 
per patient would be significantly lower.
    In the FY 2021 IPPS/LTCH PPS final rule (85 FR 58630), we stated 
our understanding that there are unique circumstances to determining a 
cost per case for a technology that utilizes a subscription for its 
cost. We stated our intent to continue to consider the issues relating 
to the calculation of the cost per unit of technologies sold on a 
subscription basis as we gain more experience in this area. We stated 
that we continue to welcome comments from the public as to the 
appropriate method to determine a cost per case for such technologies, 
including comments on whether the cost per case should be estimated 
based on subscriber hospital data as described previously, and if so, 
whether the cost analysis should be updated based on the most recent 
subscriber data for each year for which the technology may be eligible 
for the new technology add-on payment.
    We invited public comment on whether Rapid ASPECTS meets the cost 
criterion.
    Comment: The applicant submitted comments addressing our concerns 
regarding whether Rapid ASPECTS meets the cost criterion. With respect 
to our inquiry regarding why cases assigned to MS-DRGs 37 (Extracranial 
Procedures w/MCC) and 38 (Extracranial Procedures w/CC) were included 
in the baseline, the applicant explained that it may be possible that 
some cases are assigned to those MS-DRGs after a full accounting of 
their diagnosis and reason for inpatient stay. The applicant provided 
the example of a blocked carotid artery delivering blood to the brain, 
which can be a cause of stroke. The applicant suggested that because 
the blockage occurred outside of the brain, these cases could be 
assigned to MS-DRG 37 or 38.
    The applicant also provided an additional scenario for the cost 
threshold analysis that excluded MS-DRGs 37 and 38. The applicant re-
ran its analysis with 2018 calendar year data to exclude MS-DRGs 37 and 
38 and found that Rapid ASPECTS continues to satisfy the NTAP new 
technology add-on payment cost criterion, as seen below.

[[Page 45063]]

[GRAPHIC] [TIFF OMITTED] TR13AU21.186

BILLING CODE 4120-01-C
    With respect to our inquiry regarding the time period of the claims 
the applicant selected for the CY 2018 SAF, the applicant stated that 
it used all relevant discharges during the 2018 calendar year (January 
1st 2018--December 31st 2018). The applicant explained that for 
standardizing charges it used information specific to each hospital for 
the applicable fiscal year. The applicant explained that for claims 
with discharge dates from January 1st 2018 through September 30th 2018, 
it used cost-to-charge ratios, IME, DSH, wage-index, GAF, and COLA 
information specific to each hospital for FY 2018. The applicant 
further explained that, for claims with discharge dates from October 
1st 2018 through December 31st 2018, it used cost-to-charge ratios, 
IME, DSH, wage-index, GAF, and COLA information specific to each 
hospital for FY 2019. The applicant also noted that, to maintain a 
conservative approach, it used an inflation factor of 13.22% for all 
discharges in the 2018 calendar year, even though it would be 
reasonable to use a higher inflation factor for claims with a discharge 
date prior to October 1st 2018.
    With respect to our concern that the cost per patient for Rapid 
ASPECTS can vary based on the volume of cases, and that the applicant's 
cost per case may be skewed by the small number of hospitals utilizing 
the technology and their low case volumes, the applicant stated that 
although the cost per patient for Rapid ASPECTS may be lower for 
hospitals with high utilization of the technology, it will also be 
higher for hospitals with lower utilization. The applicant also stated 
that Rapid ASPECTS can help save lives, and that it is important to 
ensure that hospitals have equitable access to this technology to 
conform to current AHA guidelines and address an unmet need. The 
applicant's comments agreed with other commenters that responded to our 
request for comments regarding technologies sold on a subscription 
basis and whether the cost per case should be estimated based on 
subscriber hospital data, and if so, whether the cost analysis should 
be updated based on the most recent subscriber data for each year for 
which the technology may be eligible for the new technology add-on 
payment. Most commenters agreed that in determining the cost per case 
for technologies seeking new technology add-on payment that utilize a 
subscription model, we should limit our analysis to subscriber 
hospitals and update the cost analysis on an annual basis. A commenter 
noted that alternative methodologies involving estimating the number of 
patients who would be eligible to receive treatment utilizing a 
technology sold on a subscription basis would be likely to result in a 
payment amount that does not adequately reflect the estimated average 
cost of such service or technology as required by the statute. The 
commenter believes that given the direct impact of utilization changes 
on cost per case when using a subscription model, it is reasonable for 
CMS to annually update the payment amount using the most recent 
subscriber utilization data.
    Response: We thank the commenter for its input. We appreciate the

[[Page 45064]]

explanation behind the inclusion of MS-DRG 37 and 38 in the applicant's 
original cost analysis and understand that stroke cases may be assigned 
to extracranial MS-DRGs after a full accounting of the patient's 
diagnosis and reason for inpatient stay. We also appreciate the 
additional information pertaining to the time period of the data used 
in the applicant's cost analysis submitted with its FY 2022 new 
technology add-on payment application and agree with the alignment of 
cost-to-charge ratios, IME, DSH, wage-index, GAF, and COLA information 
specific to each hospital with the respective fiscal year in which the 
discharge date falls. We agree with the applicant that, under the 
scenarios presented in its original application and in response to the 
FY 2022 IPPS/LTCH PPS proposed rule, the final inflated case-weighted 
standardized charge per case exceeded the case-weighted threshold and 
Rapid ASPECTS meets the cost criterion.
    We also appreciate the applicant's comments relating to calculation 
of the cost per unit of technologies sold on a subscription basis. CMS 
will continue to consider the issues relating to calculation of the 
cost per unit of technologies sold on a subscription basis, including 
the merits of calculating the cost per case across all IPPS hospitals 
versus limiting the cost per case analysis to current users and whether 
the cost analysis should be updated based on the most recent subscriber 
data for each year for which the technology may be eligible for the new 
technology add-on payment, as we gain more experience in this area.
    With respect to the substantial clinical improvement criterion, the 
applicant asserted Rapid ASPECTS represents a substantial clinical 
improvement over existing technologies because it improves diagnostic 
decisions by improving accuracy of ASPECT scoring. The applicant also 
asserted it improves diagnostic decisions by reducing inter-rater 
variability of ASPECT scoring. The applicant also asserted it 
represents a substantial clinical improvement by improving treatment 
decisions and by improving time to treatment.
    According to the applicant, the first stroke treatment, tissue 
plasminogen activator (tPA), was first approved in the United States 
for intravenous administration to patients with acute stroke in 1996, 
and a study demonstrating successful catheter-directed intra-arterial 
infusion of a thrombolytic agent for this indication was first 
published in 1999.\324\ The applicant asserted that the first positive 
randomized controlled studies using modern mechanical thrombectomy 
devices for LVO stroke were published in 2015 and support combined 
treatment with tPA and catheter-based thrombectomy as the most 
effective treatment approach for patients who can be treated within six 
hours of symptom onset.\325\ According to the applicant, following the 
publication of these trials, the American Heart Association (AHA) and 
American Stroke Association (ASA) released new guidelines in 2016, 2018 
and 2019 that all specified the following Level 1A recommendation:
---------------------------------------------------------------------------

    \324\ Furlan A, Higashida R, et al. Intra[hyphen]arterial 
prourokinase for acute ischemic stroke: The PROACT II study: A 
randomized controlled trial: Prolyse in Acute Cerebral 
Thromboembolism. JAMA. 1999;282:2003-2011.
    \325\ Goyal M, Menon BK, et al. for the HERMES collaborators. 
Endovascular thrombectomy after large[hyphen]vessel ischaemic 
stroke: A meta[hyphen]analysis of individual patient data from five 
randomised trials. Lancet 2016; 387: 1723-31.
---------------------------------------------------------------------------

    Patients should receive mechanical thrombectomy with a stent 
retriever if they meet all the following criteria:
     Pre-stroke modified Rankin Score (mRS) score of 0 to 1.
     Causative occlusion of the internal carotid artery (ICA) 
or middle cerebral artery (MCA) segment 1 (M1).
     Age >=18 years.
     NIH Stroke Scale (NIHSS) score of >=6.
     Alberta stroke program early CT score (ASPECTS) of >=6.
     Treatment can be initiated (groin puncture) within 6 hours 
of symptom onset.\326\
---------------------------------------------------------------------------

    \326\ Powers WJ, Rabinstein A, Ackerson T, et al. Guidelines for 
the Early Management of Patients With Acute Ischemic Stroke: 2019 
Update to the 2018 Guidelines for the Early Management of Acute 
Ischemic Stroke: A Guideline for Healthcare Professionals From the 
American Heart Association/American Stroke Association. Stroke. 
2019;50:e344-e418.
---------------------------------------------------------------------------

    According to the applicant, the previously recommended guidelines 
from the AHA/ASA have been widely accepted and outline the key 
requirements that are still used today to select early window (less 
than 6 hours) candidates for thrombectomy. The applicant asserted the 
imaging requirements (the second and the fifth criterion) require that 
patients be screened for an LVO with CTA and then once an LVO in the 
ICA or MCA is discovered, the ASPECTS score must be assessed to verify 
that it is 6 or higher. According to the applicant, the ASPECTS score 
is an assessment of the CT scan in a stroke patient to determine if 
there is evidence of irreversible injury in ten different brain 
regions. The applicant stated that patients who have more than five 
regions that are already irreversibly injured are not candidates for 
thrombectomy.
    According to the applicant, it is well validated in the stroke 
literature that faster treatment leads to better outcomes. The 
applicant stated that compared with the best medical therapy alone, in 
the first five positive LVO endovascular thrombectomy trials that were 
published in the New England Journal of Medicine and subsequently 
summarized in a pooled analysis by the HERMES group, thrombectomy was 
associated with improved outcomes when procedure start (arterial 
puncture) could be performed within the first 7.3 hours after symptom 
onset among patients meeting the brain imaging entry criteria for 
inclusion in these randomized trials.\327\ The applicant asserted that 
within this period, functional outcomes were better the sooner after 
symptom onset that endovascular reperfusion was achieved, emphasizing 
the importance of programs to enhance patient awareness, out-of-
hospital care, and in-hospital management to shorten symptom onset-to-
treatment times. The applicant asserted that the magnitude of the 
association between time to treatment and outcome is clinically 
meaningful. According to the applicant, in patients with acute ischemic 
stroke due to LVO, among every 1000 patients achieving substantial 
endovascular reperfusion, for every 15-minutes faster emergency 
department door-to-reperfusion time, an estimated 39 patients would 
have a less-disabled outcome at 3 months, including 25 more who would 
achieve functional independence (mRS 0-2).\328\ The applicant stated 
that in addition to faster time from emergency department door to 
reperfusion, faster time from brain imaging to reperfusion was 
associated with better 3-month functional outcomes.\329\
---------------------------------------------------------------------------

    \327\ Goyal M, Menon BK, et al. for the HERMES collaborators. 
Endovascular thrombectomy after large[hyphen]vessel ischaemic 
stroke: A meta[hyphen]analysis of individual patient data from five 
randomised trials. Lancet 2016; 387: 1723-31.
    \328\ Goyal M, Menon BK, et al for the HERMES collaborators. 
Endovascular thrombectomy after large[hyphen]vessel ischaemic 
stroke: A meta[hyphen]analysis of individual patient data from five 
randomised trials. Lancet 2016; 387: 1723-31.
    \329\ Ibid. Goyal M, Menon BK, et al for the HERMES 
collaborators. Endovascular thrombectomy after large[hyphen]vessel 
ischaemic stroke: A meta[hyphen]analysis of individual patient data 
from five randomised trials. Lancet 2016; 387: 1723-31.
---------------------------------------------------------------------------

    According to the applicant, the interpretation of early infarct 
signs in CT first became clinically important following the FDA 
approval of tPA for stroke treatment in 1996 because it was shown that 
the response to tPA could be

[[Page 45065]]

predicted based on the degree of early brain injury that could be 
visualized on the CT scan. The applicant asserted it was clear that 
intravenous tPA could be harmful in patients with advanced early 
infarct signs because they had a high risk of intracranial hemorrhage. 
The applicant stated, however, only rough qualitative estimates of the 
degree of early infarct signs were performed. The applicant asserted 
stroke clinicians generally felt believed it to be safe to give tPA if 
the early infarct signs were confined to less than one-third of the 
middle cerebral artery territory.\330\
---------------------------------------------------------------------------

    \330\ von Kummer R, Allen KL, Holle R, et al. Acute stroke: 
Usefulness of early CT findings before thrombolytic therapy. 
Radiology 1997; 205:327-33.
---------------------------------------------------------------------------

    According to the applicant, beginning in the 2000s, a more detailed 
and quantitative analysis of early infarct signs was proposed: The 
Alberta Stroke Program Early CT score (ASPECTS).\331\ The applicant 
stated this score requires the evaluation of 10 pre-defined MCA 
vascular territories. The applicant asserted these individual regions 
are assessed for focal hypoattenuation of the cortex and in the basal 
ganglia, reduction of gray and white matter differentiation, and the 
loss of the insular ribbon sign. According to the applicant, ASPECTS is 
calculated by subtracting 1 point for each involved region; scores less 
than 6 typically signify patients with an irreversible large 
hemispheric infarction.\332\
---------------------------------------------------------------------------

    \331\ Barber PA, Demchuk AM, et al. Validity and reliability of 
a quantitative computed tomography score in predicting outcome of 
hyperacute stroke before thrombolytic therapy. ASPECTS Study Group. 
Alberta Stroke Programme Early CT Score. Lancet. 2000 May 
13;355(9216):1670[hyphen]4.
    \332\ Albers GW, MD, Wald MJ, Mlynash M, et al. Automated 
Calculation of Alberta Stroke Program Early CT Score Validation in 
Patients With Large Hemispheric Infarct. Stroke. 2019;50:3277-3279.
---------------------------------------------------------------------------

    According to the applicant, the ASPECTS evaluation became 
clinically essential in 2015 after mechanical thrombectomy was found to 
be effective for treatment of patients with a large vessel occlusion 
within the 6-hour time frame.333 334 The applicant stated 
that some of the large randomized controlled trials that ultimately led 
to the establishment of thrombectomy as a standard procedure required 
an ASPECTS greater than or equal to 6 for inclusion. According to the 
applicant, the MR CLEAN trial, which enrolled patients with lower 
ASPECT scores than the other four trials, reported the smallest overall 
treatment effect and in particular, patients with an ASPECT score less 
than 5 did not show benefit with an adjusted odds ratio close to 
1.0.\335\ The applicant asserted that for these reasons, an ASPECTS 
evaluation is required in most national and international thrombectomy 
guidelines. The applicant stated most guidelines, including the AHA/ASA 
guidelines discussed previously, require an ASPECT score greater than 
or equal to six 6 for a patient to qualify for thrombectomy in the 
early treatment window.\336\
---------------------------------------------------------------------------

    \333\ Goyal M, Menon BK, et al for the HERMES collaborators. 
Endovascular thrombectomy after large[hyphen]vessel ischaemic 
stroke: A meta[hyphen]analysis of individual patient data from five 
randomised trials. Lancet 2016; 387: 1723-31.
    \334\ Powers WJ, Rabinstein A, Ackerson T, et al. Guidelines for 
the Early Management of Patients With Acute Ischemic Stroke: 2019 
Update to the 2018 Guidelines for the Early Management of Acute 
Ischemic Stroke A Guideline for Healthcare Professionals From the 
American Heart Association/American Stroke Association. Stroke. 
2019;50:e344-e418.
    \335\ Berkhemer OA, Fransen PS, et al; MR CLEAN Investigators. A 
randomized trial of intraarterial treatment for acute ischemic 
stroke. N Engl J Med. 2015;372:11-20.
    \336\ Powers WJ, Rabinstein A, Ackerson T, et al. Guidelines for 
the Early Management of Patients With Acute Ischemic Stroke: 2019 
Update to the 2018 Guidelines for the Early Management of Acute 
Ischemic Stroke A Guideline for Healthcare Professionals From the 
American Heart Association/American Stroke Association. Stroke. 
2019;50:e344-e418.
---------------------------------------------------------------------------

    The applicant asserted ASPECT score determination is challenging 
because early infarct signs are often very subtle and challenging to 
interpret correctly. According to the applicant, there is often 
disagreement between experts on the exact score and sometimes these 
disagreements preclude a definite answer regarding if the patient 
qualifies for thrombectomy or not. The applicant asserted these 
interpretation challenges are manifested by limited inter-rater 
agreement, even among experts.337 338 339 The applicant 
cited the DEFUSE 2 study in which two expert readers graded ischemic 
change on NCCT using the ASPECT score. The applicant asserted that 
full-scale agreement (measured by the intraclass correlation 
coefficient) for CT-ASPECTS was only moderate at 0.579.\340\ According 
to the applicant, these inter-rater differences can have important 
clinical implications, as discussed further. The applicant asserted 
that many physicians who evaluate acute stroke patients are not 
confident that they can accurately determine an ASPECT score, and 
oftentimes there are significant delays before a radiologist reads the 
scan. The applicant stated current AHA/ASA guidelines recommend a CT 
scan be performed within 25 minutes of Emergency Department arrival and 
the radiologist interpretation of the scan occur within 45 minutes of 
arrival.\341\ According to the applicant, based on these guidelines, 
radiologists have about 20 minutes to read the scan, however, many 
hospitals, especially community and primary stroke centers, do not meet 
these guidelines. The applicant asserted Medicare data indicate that 
only 72% of patients meet these guidelines. The applicant stated that 
automated software, such as Rapid ICH, Rapid LVO and Rapid ASPECTS can 
assess CT and CTA findings (both to rule out hemorrhage, confirm an LVO 
and to assess early signs of infarction with ASPECTS) within minutes.
---------------------------------------------------------------------------

    \337\ Albers GW, MD, Wald MJ, Mlynash M, et al. Automated 
Calculation of Alberta Stroke Program Early CT Score Validation in 
Patients With Large Hemispheric Infarct. Stroke. 2019;50:3277-3279.
    \338\ Kobkitsuksakul C, Tritanon O, Suraratdecha V. 
Interobserver agreement between senior radiology resident, 
neuroradiology fellow, and experienced neuroradiologist in the 
rating of Alberta Stroke Program Early Computed Tomography Score 
(ASPECTS). Diagn Interv Radiol. 2018.
    \339\ McTaggart RA, Jovin TG, Lansberg MG, et al. Alberta stroke 
program early computed tomographic scoring performance in a series 
of patients undergoing computed tomography and MRI: Reader 
agreement, modality agreement, and outcome prediction. Stroke. 2015 
Feb;46(2):407-12.
    \340\ McTaggart RA, Jovin TG, Lansberg MG, et al. Alberta stroke 
program early computed tomographic scoring performance in a series 
of patients undergoing computed tomography and MRI: Reader 
agreement, modality agreement, and outcome prediction. Stroke 2015 
Feb;46(2):407-12.
    \341\ AHA/ASA. Target: Stroke Campaign Manual, published 2010. 
http://www.strokeassociation.org/idc/groups/heart-public/@wcm/@hcm/@gwtg/documents/downloadable/ucm_308277.pdf.
---------------------------------------------------------------------------

    According to the applicant, the limited inter-rater agreement for 
traditional ASPECT scoring can lead to triaging ineligible patients to 
thrombectomy or failing to treat eligible patients. The applicant cited 
a study in which four experienced readers rated ASPECT scores in 
patients who presented with LVO and severe strokes. The applicant 
stated the inter-rater agreement between these raters was poor with an 
interclass correlation of 0.32.\342\ According to the applicant, the 
range of agreement for individual raters with the gold standard 
assessment of the score (obtained with a concurrent MRI) for 
identifying patients with a score less than six 6 ranged from 35% to 
94%. The applicant asserted this study demonstrates there can be 
substantial disagreement between physicians regarding if a patient is 
eligible for thrombectomy based on their assessment of the ASPECT 
score, which can lead to eligible patients not receiving this highly 
effective therapy, as well as the performance of unnecessary 
procedures.
---------------------------------------------------------------------------

    \342\ Albers GW, MD, Wald MJ, Mlynash M, et al. Automated 
Calculation of Alberta Stroke Program Early CT Score Validation in 
Patients with Large Hemispheric Infarct. Stroke. 2019;50:3277-3279.
---------------------------------------------------------------------------

    The applicant asserted that particularly the Medicare population 
might be at risk and impacted by these

[[Page 45066]]

limitations as the majority of LVOs occur in the Medicare population. 
The applicant stated that the average age of patients in the HERMES 
pooled analysis of thrombectomy studies was 68 years.\343\ Therefore, 
according to the applicant, inaccuracy of traditional ASPECT scoring 
translates into a substantial percentage of Medicare patients having 
erroneous triage decisions made regarding their eligibility for 
thrombectomy, which it asserted can result in unnecessary procedures 
and increased Medicare costs, as well as increased disability in 
eligible patients who are not treated because of inaccurate ASPECT 
scoring.
---------------------------------------------------------------------------

    \343\ Goyal M, Menon BK, et al for the HERMES collaborators. 
Endovascular thrombectomy after large[hyphen]vessel ischaemic 
stroke: A meta[hyphen]analysis of individual patient data from five 
randomised trials. Lancet 2016; 387: 1723-31.
---------------------------------------------------------------------------

    As stated previously, the applicant asserted Rapid ASPECTS 
represents a substantial clinical improvement over existing 
technologies because it improves diagnostic decisions by improving 
accuracy of ASPECT scoring. The applicant presented three retrospective 
cohort studies (two peer-reviewed and one under review) to support the 
claim that diagnostic decisions made by clinicians would have been 
improved with use of Rapid ASPECTS. According to the applicant, two of 
the studies showed that the automated Rapid ASPECTS score is 
significantly more accurate than the scores obtained by experienced 
clinicians.344 345
---------------------------------------------------------------------------

    \344\ Maegerlein C, Fischer J, M[ouml]nch S, MD et al. Automated 
Calculation of the Alberta Stroke Program Early CT Score: 
Feasibility and Reliability. Radiology 2019; 291:141-148.
    \345\ Albers GW, MD, Wald MJ, Mlynash M, et al. Automated 
Calculation of Alberta Stroke Program Early CT Score Validation in 
Patients With Large Hemispheric Infarct. Stroke. 2019;50:3277-3279.
---------------------------------------------------------------------------

    The applicant submitted a retrospective cohort study which compared 
ASPECT scoring of CT images from patients with MCA occlusion (n=100) 
between Rapid ASPECTS software and two expert neuroradiologist reads. 
According to the applicant, Rapid ASPECTS showed a substantial 
agreement (k=0.78) when imaging took place more than 1 hour after 
symptom onset, which increased to high agreement (k=0.92) for imaging 
occurring after 4 hours. The applicant asserted that the 
neuroradiologist raters did not achieve comparable results to the 
software until the time interval of greater than 4 hours (k=0.83 and 
k=0.76). In this study, experts developed the reference consensus score 
and then, after 6 weeks, the same two neuroradiologists again 
determined ASPECTS by using only the baseline CT. The experts had 
moderate agreement with the consensus score (k=0.57 and k=0.57) while 
Rapid ASPECTS had better agreement (k=0.9). There was minimal agreement 
across experts and software in the timeframe of less than 1 hour 
between symptom onset and imaging, but better software agreement when 
the time was between 1 and 4 hours. There was agreement across experts 
for imaging occurring after 4 hours. According to the applicant, this 
study showed that in acute stroke of the MCA, Rapid ASPECTS had better 
agreement than that of human readers with a predefined consensus 
score.\346\
---------------------------------------------------------------------------

    \346\ Maegerlein C, Fischer J, M[ouml]nch S, MD et al. Automated 
Calculation of the Alberta Stroke Program Early CT Score: 
Feasibility and Reliability. Radiology 2019; 291:141-148.
---------------------------------------------------------------------------

    The applicant submitted another retrospective cohort study to 
compare Rapid ASPECTS, as well as the mean score from four experienced 
readers, with a diffusion-weighted magnetic resonance imaging (DW-MRI) 
ASPECTS obtained following the baseline CT in patients (n=65) with 
large hemispheric infarcts.\347\ DW-MRI is sensitive in the detection 
of small and early infarcts. Small infarcts might not appear on CT 
scans for days. The AHA/ASA guidelines state that DW-MRI can be useful 
for selecting candidates for mechanical thrombectomy between 6 and 24 
hours after the patient was last known well (that is, the time at which 
the patient was known to be without signs and symptoms of the current 
stroke).\348\
---------------------------------------------------------------------------

    \347\ Albers GW, MD, Wald MJ, Mlynash M, et al. Automated 
Calculation of Alberta Stroke Program Early CT Score Validation in 
Patients With Large Hemispheric Infarct. Stroke. 2019;50:3277-3279.
    \348\ Powers WJ, Rabinstein A, Ackerson T, et al. Guidelines for 
the Early Management of Patients With Acute Ischemic Stroke: 2019 
Update to the 2018 Guidelines for the Early Management of Acute 
Ischemic Stroke A Guideline for Healthcare Professionals From the 
American Heart Association/American Stroke Association. Stroke. 
2019;50:e344-e418.
---------------------------------------------------------------------------

    According to the applicant, Rapid ASPECTS' automated score had a 
higher level of agreement with the mean of the DW-MRI ASPECTS, both for 
the full scale and for the dichotomized scale of either <6 or >=6 which 
is the difference for treatment/no treatment (difference in intraclass 
correlation coefficient, p<0.001). The applicant stated that the mean 
DW-MRI ASPECT score was <6 in 63/65 (97%) of the cases; of these, RAPID 
ASPECTS agreed with the DW-MRI score in 46/63 (73%) of the cases (95% 
confidence interval [CI] 60-83%) vs. 35/63 56% of the cases (95% CI 44-
69%) for the median score of the two experienced readers (p=0.027). The 
range of agreement for individual clinician CT ASPECTS with the median 
DW-MRI score for identifying patients with a score <6 was 35% to 94%. 
According to the applicant, this study demonstrated the accuracy for 
determining which patients have an ASPECTS <6 (which would exclude them 
from thrombectomy) was significantly higher with the software.\349\
---------------------------------------------------------------------------

    \349\ Albers GW, MD, Wald MJ, Mlynash M, et al. Automated 
Calculation of Alberta Stroke Program Early CT Score Validation in 
Patients With Large Hemispheric Infarct. Stroke. 2019;50:3277-3279.
---------------------------------------------------------------------------

    The applicant submitted an additional retrospective cohort study 
under review for publication which compared physicians' (two expert 
neuroradiologists and six typical readers) ability to read ASPECTS in 
patients with an LVO (n=50; 10 regions in each patients' scan for a 
total of 500 individual regions) within 6 hours of symptom onset when 
assisted by Rapid ASPECTS, compared with their unassisted score. The 
applicant stated that the average ASPECT score of three additional 
experienced neuroradiologists who were provided access to a follow-up 
MRI was used as the reference standard. The applicant asserted that 
when typical readers read the scan in conjunction with the Rapid 
ASPECTS software, their agreement with the expert reads improved from 
72% to 78% (p< 0.0001, test of proportions). According to the 
applicant, Rapid ASPECTS alone achieved correlations for total ASPECT 
scores that were similar to the three experienced neuroradiologist 
readers who had access to a follow-up MRI scan to help enhance the 
quality of their reads. The applicant asserted the results from this 
study showed that the aid of Rapid ASPECTS can significantly improve 
typical readers' scores and that the automated scores generated by 
Rapid ASPECTS are interchangeable with the scores generated by expert 
neuroradiologists.\350\
---------------------------------------------------------------------------

    \350\ Delio PR, Wong ML, Tsai JP, et al. Assistance from 
Automated ASPECTS Software Improves Reader Performance (under review 
2020).
---------------------------------------------------------------------------

    As stated previously, the applicant asserted Rapid ASPECTS 
represents a substantial clinical improvement over existing 
technologies because it improves diagnostic decisions by reducing 
inter-rater variability of ASPECT scoring. To support this claim the 
applicant submitted the study performed by iSchemaView and analyzed by 
an independent statistician that led to the FDA clearance of Rapid 
ASPECTS. According to the applicant, acute CT scans in patients with 
LVO (n=50) were read by eight readers both with and without Rapid 
ASPECTS. The

[[Page 45067]]

applicant asserted that the standard deviation of ASPECT scores ranged 
from 0.35 to 4.5 without assistance as compared to 0.46 to 4.7 with 
assistance. The applicant stated that the median standard deviation 
dropped from 2.2 to 1.4 when assistance was used to read the scans. 
According to the applicant, a t-test to evaluate the hypothesis of 
equal standard deviations supported a significant difference in 
standard deviations (p=0.0002), and non-parametric tests arrived at the 
same conclusion (p <0.0001 for a Wilcoxon Rank Sum Test).\351\
---------------------------------------------------------------------------

    \351\ Copeland K. Variability of ASPECT Scores Internal Analysis 
iSchemaView of data submitted to U.S. Food and Drug Administration 
(FDA) Center for Devices and Radiological Health, 2020a.
---------------------------------------------------------------------------

    As stated previously, the applicant asserted Rapid ASPECTS 
represents a substantial clinical improvement by improving treatment 
decisions and by improving time to treatment. The applicant asserted 
that in the study performed by iSchemaView of the acute CT scans in 
patients with LVO (n=50) which were read by eight readers both with and 
without Rapid ASPECTS, a Receiver Operating Characteristic (ROC) 
analysis demonstrated significant improvement in typical readers' 
ability to identify patients who have a score of 6 to 10 if they read 
the scan in conjunction with the automated score. According to the 
applicant, the area under the curve (AUC) improved from 0.78 without 
Rapid ASPECTS to 0.85 with Rapid ASPECTS (p=0.0049). The applicant 
asserted that of the 400 treatment assessments (50 scans * 8 readers) 
in this study, 7% were changed from an incorrect assessment to a 
correct assessment when the scan was read in conjunction with the 
automated score compared with traditional scoring, a statistically 
significant difference.\352\
---------------------------------------------------------------------------

    \352\ Copeland K. Treat/No Treat Analysis, Internal Analysis 
iSchemaView of data submitted to U.S. Food and Drug Administration 
(FDA) Center for Devices and Radiological Health, 2020.
---------------------------------------------------------------------------

    The applicant cited three retrospective studies that, according to 
the applicant, have shown treatment decisions made by experienced 
clinicians would have been improved with the use of Rapid 
ASPECTS.353 354 355 As stated previously, the applicant 
asserted that one study showed that agreement regarding whether a 
patient had a treatment-eligible score based on a concurrent MRI scan 
interpreted by two experts was significantly higher for the Rapid 
ASPECTS score than for experienced clinicians.\356\ According to the 
applicant, Rapid ASPECTS has also been shown to improve the reads of a 
typical CT scan reader to become as accurate as a neuroradiologist 
read.\357\ The applicant asserted that since radiologists are not 
immediately available at the time when many LVO patients present, and 
obtaining a read from a neuroradiologist often takes even longer, the 
time to determine an ASPECT score will be substantially improved with 
the software, leading to faster treatment times which have been shown 
to reduce disability. According to the applicant, Rapid ASPECTS 
provides an opportunity to impact the current selection and allocation 
pathway for stroke care.
---------------------------------------------------------------------------

    \353\ Albers GW, MD, Wald MJ, Mlynash M, et al. Automated 
Calculation of Alberta Stroke Program Early CT Score Validation in 
Patients With Large Hemispheric Infarct. Stroke. 2019;50:3277-3279.
    \354\ Delio PR, Wong ML, Tsai JP, et al. Assistance from 
Automated ASPECTS Software Improves Reader Performance (under review 
2020).
    \355\ Maegerlein C, Fischer J, M[ouml]nch S, MD et al. Automated 
Calculation of the Alberta Stroke Program Early CT Score: 
Feasibility and Reliability. Radiology 2019; 291:141-148.
    \356\ Albers GW, MD, Wald MJ, Mlynash M, et al. Automated 
Calculation of Alberta Stroke Program Early CT Score Validation in 
Patients With Large Hemispheric Infarct. Stroke. 2019;50:3277-3279.
    \357\ Delio PR, Wong ML, Tsai JP, et al. Assistance from 
Automated ASPECTS Software Improves Reader Performance (under review 
2020).
---------------------------------------------------------------------------

    After reviewing the information submitted by the applicant, we had 
the following questions regarding whether Rapid ASPECTS meets the 
substantial clinical improvement criterion.
    In the studies provided by the applicant, the reference ASPECT 
score to which Rapid ASPECTS was compared was generally derived from a 
mean value of the ASPECT scores rated from a small sample of expert 
radiologists. We noted that the radiologists used to identify the 
reference to which Rapid ASPECTS was compared may not be representative 
of radiologists in the United States. We were also unclear whether a 
mean ASPECT score, identified from radiologists whom the applicant 
describes as having low levels of agreement, is representative of a 
meaningful value as it does not represent the score of any particular 
radiologist. We further questioned whether individuals participating in 
these studies may have altered their behavior in a substantive way by 
interacting with computer-generated ratings, which would complicate 
study findings.
    We further noted that the correlation between the ASPECT scoring of 
expert and Rapid ASPECTS is the primary outcome in many of the articles 
provided. Though this information may be important and informative, we 
stated it is not clear that a high correlation between expert and Rapid 
ASPECTS scoring is necessarily indicative of substantial clinical 
improvement. Furthermore, whether these providers agree with the 
technology does not determine whether they are correct, and it could be 
the case that both AI and radiologists agree on an incorrect score.
    We noted that the applicant stated that inter-rater disagreement 
with ASPECT scores leads to erroneous triage and treatment of Medicare 
patients. We stated it was unclear how the applicant determined that 
disagreement between scores translates into inappropriate treatment, or 
necessarily shows that the scoring class (<6 vs >=6) was inaccurate. 
The applicant also asserted that many physicians who evaluate acute 
stroke patients are not confident that they can accurately determine an 
ASPECT score, but it did not provide evidence to support this claim. 
Additionally, we observed that the studies provided did not demonstrate 
improvements in clinical outcomes such as disability, mortality, or 
length of stay; rather, improved outcomes were inferred by relying on 
the assumption that faster treatment results in better outcomes. 
Without measuring the impact of the technology on treatment outcomes, 
we stated we are uncertain whether Rapid ASPECTS represents a 
substantial clinical improvement.
    Lastly, we noted that the applicant submitted the AHA/ASA 
guidelines and a review of stroke literature as support for clinical 
improvement. It is unclear how the guidelines support a finding of 
substantial clinical improvement for Rapid ASPECTS because the 
guidelines are for the current standard of care. Additionally, the 
applicant did not provide evidence to support its assertion that 
hospitals are not meeting the AHA/ASA guideline that radiologists read 
the CT scan of acute ischemic stroke patients within 20 minutes. The 
stroke literature review identified the inter-rater differences among 
ASPECT scoring, but did not demonstrate that inter-rater disagreements 
have led to triaging ineligible patients to thrombectomy or failing to 
treat eligible patients in clinical practice. We stated it is unclear 
how the literature on inter-rater reliability for ASPECT scoring would 
demonstrate a substantial clinical improvement in how Rapid ASPECTS 
supports improved triaging of stroke care. The applicant's stroke 
literature review also identified that faster treatment leads to better 
outcomes. While this supports the urgency of stroke care, we were 
unsure how it demonstrates a substantial clinical improvement in how 
Rapid ASPECTS supports the urgency of stroke care.

[[Page 45068]]

    We invited public comments on whether Rapid ASPECTS meets the 
substantial clinical improvement criterion.
    Comment: The applicant submitted comments in response to CMS' 
concerns regarding substantial clinical improvement as indicated in the 
proposed rule. With respect to our concern about sample representation, 
the applicant stated that two of the studies that were provided, GAMES-
RP and Delio et al., used expert readers from the United 
States.358 359 The applicant stated that these two studies 
included a total of 6 different experts and that the results for Rapid 
ASPECTS seen in the U.S. studies were similar to the benefits seen in 
the studies conducted outside of the United States.
---------------------------------------------------------------------------

    \358\ Delio PR, Wong ML, Tsai JP, et al. Assistance from 
Automated ASPECTS Software Improves Reader Performance (under review 
2020).
    \359\ Sheth KN, Elm JJ, Beslow LA, Sze GK, Kimberly WT, et al. 
Glyburide Advantage in Malignant Edema and Stroke (GAMES-RP) Trial: 
Rationale and design. Neurocrit Care. 2016; 24: 132-139.
---------------------------------------------------------------------------

    With respect to our concern that individuals participating in these 
studies may have altered their behavior in a substantive way by 
interacting with computer-generated ratings, the applicant asserted 
that the expert radiologists who determined the gold standard scores 
read the cases blinded to the computer-generated ratings, so that there 
is no possibility that the software influenced these reads. The 
applicant further stated that the exception to this was the Delio, et 
al study, where the gold standard was determined independent of the 
software by three expert neuroradiologists, followed by six ``typical 
readers'' judging the cases with and without the technology to 
determine if the assist from Rapid ASPECTS led to reader improvement. 
The applicant also noted that this study design was endorsed by FDA. 
Per the applicant, the readers in the first reading session saw the 
case without Rapid outputs half the time, while during the other half 
they saw the cases with the Rapid software to assist their read. In a 
subsequent session, the readers saw the same cases again in reverse: 
Cases that read without Rapid in the first session were read with Rapid 
and vice versa. The applicant maintained that the study demonstrated 
reader improvement with the software assist.
    The applicant also commented in response to our concern that the 
high correlation between the ASPECT scoring of expert and Rapid 
ASPECTS, which was the primary outcome in many of the articles the 
applicant provided, demonstrates the accuracy of the technology and is 
not necessarily indicative of substantial clinical improvement. The 
applicant maintained that this correlation was not the primary outcome 
in most studies, citing the example of the GAMES study where the 
accuracy of the software based on the MRI finding was used as a gold 
standard.\360\ In addition, the applicant cited the Delio, et al and 
Munich study studies where the gold standard for the primary analysis 
was the consensus read of multiple experts that was enhanced with the 
follow-up MRI. The applicant agreed with CMS that both the AI and 
radiologist could be incorrect, hence why the MRI was used in the GAMES 
study as the gold standard and in Delio, et al and Munich, the expert 
radiologists received additional data in the form of a follow-up MRI 
scan to improve their accuracy. The applicant pointed out that in the 
prospective study reported by Mansour, et al the door-to-needle time 
for the standard of care group was 52.3 +/- 16 minutes versus 36.8 +/- 
11 minutes (p=0.001) in the Rapid ASPECTS patients which resulted in a 
14-minute reduction in the door-to-treatment time. The applicant 
further noted there was also a significantly increased likelihood of 
functional independence and fewer hemorrhagic complications in patients 
treated with reperfusion therapy in the Rapid ASPECTS group (p<0.001).
---------------------------------------------------------------------------

    \360\ Id.
---------------------------------------------------------------------------

    With respect to our request for more information concerning how 
inter-rater disagreement with ASPECT scores translates into erroneous 
triage and treatment of Medicare patients, as well as how inter-rater 
reliability for ASPECT scoring demonstrates that Rapid ASPECTS supports 
improved triaging of stroke care, the applicant presented a two-fold 
argument. The applicant first noted that because appropriate treatment 
depends on an accurate ASPECT score, Rapid ASPECTS can avoid sending a 
patient to thrombectomy who has an ASPECT score that does not qualify 
or failing to treat a patient who does qualify for the procedure. The 
applicant pointed to the cases cited in its application where one 
radiologist believed that the score was less than six and the other 
reader believed that the score was greater than 6. Because only one of 
these readers can be correct, in these cases the incorrect reader may 
recommend the wrong treatment decision. By improving the accuracy of 
the score, the software can avoid these cases of over- or under-
treatment. The applicant also pointed to examples of cases where the 
typical reader's score disagreed with the gold standard score regarding 
if the patient had a qualifying score of greater than or equal to six, 
and that in 93 percent of these cases the Rapid ASPECTS score agreed 
with the gold standard score. Therefore, the applicant argued that a 
treatment decision based on Rapid ASPECTS would be in line with the 
more accurate gold standard score and differ from the typical reader's 
score.
    To further bolster their argument, the applicant reiterated that 
the method for obtaining a ``more accurate'' baseline ASPECT score 
using the data provided by a follow-up MRI has been accepted by 
Radiology, Stroke, and the Journal of Stroke and Cerebrovascular 
Disease as representing a more accurate score. The applicant pointed 
out that an MRI scan is much more sensitive than a CT for determining 
the extent of early brain injury; therefore, the use of a follow-up MRI 
scan can help increase the accuracy of the baseline ASPECTS read. The 
applicant acknowledged that while the ASPECTS reader does not have the 
advantage of knowing what the MRI will eventually show, it is well 
accepted that having information about the final size of a stroke can 
make it easier to identify subtle signs of a stroke on the baseline 
scan. The applicant pointed to the Munich study, GAMES ASPECT study, 
and Delio et al, which all used a combined baseline CT and follow-up 
MRI scan as the gold standard and where the Rapid ASPECTS software was 
demonstrated to be more accurate based on this gold standard than the 
typical reader.
    With respect to our observation that the applicant did not provide 
evidence to support the claim that many physicians who evaluate acute 
stroke patients are not confident that they can accurately determine an 
ASPECT score, the applicant clarified that readers who do not perform 
well, or read ASPECTS less frequently would have lower confidence, and 
that the key point is not confidence but rather the accuracy of their 
scoring. The applicant noted multiple publications showing that non-
neuroradiologists and less experienced readers are less accurate than 
experienced neuroradiologists when performing ASPECTS scoring, such as 
the Delio et al study where the scores of the neurologists and ER 
physician were considerably less accurate than the two 
neuroradiologists.\361\ In this same study, the scores of the 
neurologists and ER physician were as accurate as the two 
neuroradiologists during a Rapid

[[Page 45069]]

ASPECTS assisted read and using the gold standard score as the 
reference. The applicant referred CMS to two additional studies, where 
a better correlation between the expert consensus and the readers was 
documented for more experienced readers compared with less experienced 
readers.362 363
---------------------------------------------------------------------------

    \361\ Delio PR, Wong ML, Tsai JP, et al. Assistance from 
Automated ASPECTS Software Improves Reader Performance (under review 
2020).
    \362\ Kobkitsuksakul C, Tritanon O, Suraratdecha V. 
Interobserver agreement between senior radiology resident, 
neuroradiology fellow, and experienced neuroradiologist in the 
rating of Alberta Stroke Program Early Computed Tomography Score 
(ASPECTS). Diagn Interv Radiol. 2018.
    \363\ Culbertson CJ, Christensen S, Mlynash M, et al. Tilt-
Corrected Region Boundaries May Enhance the Alberta Stroke Program 
Early Computed Tomography Score for Less Experienced Raters. J 
Stroke Cerebrovasc Dis. 2020 Jul;29(7):104820.
---------------------------------------------------------------------------

    With respect to our concern that the studies provided did not 
demonstrate improvements in clinical outcomes such as disability, 
mortality, and length of stay, the applicant again pointed to the 
prospective study reported by Mansour, et al where the door-to-needle 
time for the standard care group was 52.3 +/- 16 minutes vs. 36.8 +/- 
11 minutes (p=0.001) in the Rapid ASPECTS patients which resulted in a 
14-minute reduction in the door-to-treatment time. The applicant 
reiterated that there was also a significantly increased likelihood of 
functional independence and fewer hemorrhagic complications in patients 
treated with reperfusion therapy in the Rapid ASPECTS group (p < 
0.001). The applicant then presented new data from the United States 
showing that time to treatment with thrombectomy was reduced following 
introduction of Rapid ASPECTS. Per the applicant, the study was 
performed at two comprehensive centers and one primary stroke center 
and observed a substantial reduction of approximately 35 minutes in the 
time from ER arrival to when the MDs were provided with an assessment 
of the non-contrast CT scan results for patients with suspected stroke. 
During the SOC phase of the study (pre-ASPECTS) the median time for the 
radiology read to be performed was 46 minutes vs 9.5 minutes for the 
treating MDs to receive the Rapid ASPECTS report in the post-ASPECTS 
phase. Furthermore, the radiologists were able to read the CT scan 6 
minutes faster when they had the Rapid interpretation available. In 
addition, although only a limited number of patients received 
thrombectomy during the study period, there were compelling trends 
toward lower mortality and a higher rate of functional recovery at 90 
days in the post-ASPECTS phase. Per the applicant, these data 
demonstrate that the Rapid ASPECTS software provides diagnostic data on 
suspected stroke patients considerably faster than SOC and provides 
evidence that earlier access to this diagnostic data improves stroke 
outcomes.
    With respect to our request for clarity on how the AHA/ASA 
guidelines for the current standard of care support a finding of 
substantial clinical improvement for Rapid ASPECTS, the applicant 
stated that these guidelines require an ASPECT score of 6 or higher for 
the patient to receive thrombectomy in the 6-hour treatment window, and 
that they therefore assume that an accurate ASPECT score can be 
calculated and used to make an appropriate treatment decision. The 
applicant stated that the accuracy of the ASPECT score can be improved 
with the Rapid ASPECTS software, especially for less experienced 
readers, and that in addition there is clear evidence that the ASPECTS 
score can be generated more quickly with the assistance of the 
software, especially in hospitals that do not have immediate access to 
expert neuroradiologists. Regarding the lack of evidence to support the 
assertion that hospitals are not meeting the AHA/ASA guideline that 
radiologists read the CT of acute ischemic stroke patients within 20 
minutes, the applicant pointed out that current Medicare guidelines 
state that the radiologist interpretation of the scan should occur 
within 45 minutes of arrival, and that they included Medicare data 
indicated that only 72 percent of patients meet these guidelines.
    The applicant commented in response to CMS' numerous concerns 
regarding the relevance of the stroke literature review provided in its 
application. Regarding the literature on inter-rater reliability for 
ASPECT scoring and how it demonstrates a substantial clinical 
improvement in how Rapid ASPECTS supports improved triaging of stroke 
care, the applicant pointed to the three retrospective studies showing 
that an incorrect ASPECT score was chosen by a typical clinical reader 
approximately seven percent of the time based on the gold standard 
determined in each study, and that this leads to either an unnecessary 
procedure or an eligible patient not being treated with thrombectomy. 
The applicant emphasized that unnecessary procedures are costly and 
that thrombectomy is associated with a small risk of serious 
complications. The applicant stated that patients who are not treated 
with thrombectomy because the ASPECTS score is erroneously low will 
miss out on the substantial benefits of thrombectomy which include 
shorter length of stay, faster recovery time, improvement in activities 
of daily living, and improved quality of life. Regarding our 
uncertainty over how the applicant's literature review, which supports 
the urgency of stroke care, also demonstrates a substantial clinical 
improvement in how Rapid ASPECTS supports the urgency of stroke care, 
the applicant maintained that Rapid ASPECTS is highly likely to provide 
diagnostic information to treating physicians much faster than the 
current standard of care. Per the applicant, the Rapid ASPECTS score is 
generated and made available to treating physicians within two and a 
half minutes after the CT scan is completed whereas current AHA 
guidelines recommend that a radiologist reads the CT scan within 20 
minutes, a metric that is often not met. The applicant pointed to a 
recent study from Johns Hopkins where use of the Rapid mobile app (app) 
for detection of large vessel occlusion (data presented to MDs about 
2.5 minutes after the scan is completed) resulted in a 33 min reduction 
in door to groin thrombectomy times (P=0.02), and 37 min reduction in 
door to recanalization time (P=0.02) when compared with patients 
treated pre-app. The applicant also noted that the National Institutes 
of Health Stroke Scale (NIHSS) 24 hours after procedure and at 
discharge were significantly lower in the post-app group (P=0.03).\364\ 
The applicant pointed to the new data that they cited in response to 
our concern that the studies provided did not demonstrate improvements 
in clinical outcomes, which show that time to treatment with 
thrombectomy was reduced following introduction of Rapid ASPECTS; 
specifically, that there was a 35-minute reduction in the time from ER 
arrival to when the MDs were provided with an assessment of the non-
contrast CT scan results for patients with suspected stroke, the 
radiologists were able to read the CT scan 6 minutes faster when they 
had the Rapid interpretation available, and although only a limited 
number of patients received thrombectomy during the study period, the 
applicant observed compelling trends toward lower mortality and a 
higher rate of functional recovery at 90 days in the post-ASPECTS 
phase.
---------------------------------------------------------------------------

    \364\ Al-Kawaz M, Primiani C, Urrutia V, Hui F. Impact of 
RapidAI mobile application on treatment times in patients with large 
vessel occlusion. J NeuroIntervent Surg 2021;0:1-4.
---------------------------------------------------------------------------

    The applicant then commented in response to our concerns regarding 
the additional data submitted in response to questions received at the 
New Technology Town Hall Meeting held in December 2020. With respect to 
our concerns about the generalizability of Mansour et al, given the 
small, non-

[[Page 45070]]

randomized sample generated from a single hospital in Egypt, the 
applicant acknowledged that there are indeed limitations to the study, 
and that it occurred outside of the United States. With respect to our 
concern regarding one patient in the retrospective study for whom the 
Rapid ASPECTS-generated score and agreement read differed, suggesting 
that the tPA treatment the patient received was not appropriate, the 
applicant noted that an ASPECTS score of less than six is a 
contraindication to thrombectomy but is not a contraindication to tPA. 
The applicant provided new data from the United States to supplement 
this data, which show that time to treatment with thrombectomy was 
reduced following introduction of Rapid ASPECTS. The applicant also 
provided the Johns Hopkins study summarized previously showing 
treatment times and improved outcomes.
    Other commenters cited their clinical experience using Rapid 
ASPECTS and echoed the applicant's comments regarding the importance of 
early intervention in stroke care. These commenters stated that, for 
patients with acute ischemic stroke with large vessel occlusions, these 
benefits from mechanical thrombectomy are time dependent. The 
commenters expressed their support of new technology add-on payments 
for Rapid ASPECTS, stating that incorporating technologies such as 
Rapid ASPECTS reduces the time to interpret the imaging studies needed 
to make treatment decisions, thus saving lives and reducing disability.
    Response: We appreciate the commenters' input and the additional 
data from the applicant to address our concerns. However, after review 
of all the data received to date, we continue to have concerns related 
to the substantial clinical improvement criterion as noted in the FY 
2022 IPPS/LTCH PPS proposed rule. Specifically, it remains unclear 
whether the use of Rapid ASPECTS significantly improves clinical 
outcomes for PE patients as compared to currently available treatments 
as the applicant did not measure the impact of the technology on 
outcome measures such as mortality, length of stay, and disability. 
This is in contrast to the data presented in response to CMS' concerns 
regarding Viz.ai's ContaCT, which demonstrated not only reduced time to 
notification but also an improved 5-day NIH Stroke Score (NIHSS) and 
lower Modified Rankin Score (mRS) post-ContaCT implementation among 
patients presenting to a primary stroke system who subsequently 
underwent mechanical thrombectomy. While the applicant has demonstrated 
that Rapid ASPECTS reduces time to notification, it has not shown that 
improved outcomes resulting from faster treatment are necessarily due 
to Rapid ASPECTS, as there are many variables in the hospital workflow 
that may influence management of the patient and time savings. We note 
that the Johns Hopkins study did not evaluate Rapid ASPECTS but rather 
the Rapid Mobile App for the detection of LVO. We also note that 
current Medicare guidelines, which state that the radiologist 
interpretation of the scan should occur within 45 minutes of arrival, 
do not apply to Rapid ASPECTS. The guidelines state that the CT should 
be read within 45 minutes of arrival in order to diagnose a stroke 
whereas Rapid ASPECTS is indicated for use in stroke patients only 
after the diagnosis has been made.
    Therefore, after consideration of the public comments we received 
and based on the information stated previously, we are unable to 
determine that Rapid ASPECTS represents a substantial clinical 
improvement over existing technologies, and we are not approving new 
technology add-on payments for Rapid ASPECTS for FY 2022.
l. Steripath[supreg] Micro\TM\ Blood Collection System
    Magnolia Medical Technologies, Inc. submitted an application for 
new technology add-on payments for the Steripath[supreg] Micro\TM\ 
Blood Collection System, which is also referred to as the 
Steripath[supreg] Micro\TM\ Initial Specimen Diversion Device 
(ISDD[supreg]), for FY 2022. The applicant described the 
Steripath[supreg] Micro\TM\ ISDD[supreg] (``Steripath Micro'') as a 
proprietary and patent-protected single-use, disposable device, which 
is indicated for use in the collection of blood cultures by nurses, 
phlebotomists, and technicians in emergency departments and inpatient 
units in acute care hospitals to reduce blood culture contamination and 
false positive diagnostic test results for sepsis. According to the 
applicant, Steripath[supreg] Micro\TM\ ISDD[supreg], along with the 
Steripath and Steripath[supreg] Gen2, are part of a product portfolio 
utilizing their Steripath[supreg] ISSD[supreg] technology.
    The applicant explained that the Steripath[supreg] Micro\TM\ 
ISDD[supreg] uses a syringe-driven (or blood culture bottle-driven) 
architecture that uses negative pressure to flip a proprietary internal 
bladder, which, in turn, creates gentle negative pressure to divert and 
sequester the initial 0.6 to 0.9 mL of blood, the portion known to most 
likely contain contaminants. According to the applicant, once diversion 
is complete, the user presses a side button to isolate the diverted 
blood. The applicant further explained that once the blood is isolated, 
a second independent blood flow pathway is opened to collect the blood 
specimen into the syringe (or blood culture bottle) for blood culture 
testing.
    The applicant stated that the design and development of the 
Steripath[supreg] Micro\TM\ ISDD[supreg] was inspired by patients who 
present with symptoms concerning for sepsis and who are hypotensive 
(low blood pressure) and hypovolemic (low blood volume), have difficult 
intravenous access (DIVA), or are small in stature with lower blood 
volume. According to the applicant, clinicians typically utilize a 
syringe technique to collect blood from this patient population to 
enable management of negative pressure (attempting to avoid vein 
collapse) while improving the opportunity to collect a sufficient 
volume of blood to culture, which the applicant stated is a critical 
determinant of blood culture sensitivity (that is, avoiding false 
negative results). The applicant claimed that this patient population 
is generally ineligible for existing ISDD[supreg] technologies due to 
risk of vein collapse. According to the applicant, the negative 
pressure created by Steripath[supreg] Micro\TM\ ISDD[supreg]'s bladder-
driven mechanism is designed to achieve initial specimen diversion 
while avoiding collapsing of the veins (losing venous access) of this 
patient population. The applicant stated that the Steripath[supreg] 
Micro\TM\ ISDD[supreg] is available with a preassembled sterile 
integrated syringe for syringe-driven diversion and blood culture 
sample collection, and components of the system may be used for 
infusion following sample collection after disconnection of the 
ISDD[supreg].
    According to the applicant, blood culture is the gold standard 
diagnostic test for bloodstream infections, including septicemia. The 
applicant explained that blood cultures are drawn from patients 
displaying symptoms of a potential bloodstream infection with results 
guiding therapeutic decisions and influencing outcomes for patients for 
their duration in acute care. The applicant stated that the standard of 
care is to collect two separate blood cultures, each consisting of two 
blood culture bottles containing aerobic or anaerobic medium. The 
applicant further noted that the major automated microbial blood 
culture detection systems (BACTEC and BacT/ALERT) recommend 8-10 mL of 
blood in each of the aerobic and anaerobic bottles--up to 40 mL total 
distributed across all four bottles.

[[Page 45071]]

    The applicant stated that despite the critical role blood culture 
plays in providing diagnoses, an estimated 20 percent to over 50 
percent of all positive blood culture results for sepsis are suspected 
to be false positive due to blood culture contamination, as explained 
in greater detail below.\365\ The applicant stated that blood culture 
contamination creates clinical confusion which leads to a risk of 
inappropriate antibiotic therapy,366 367 368 369 extended 
length of stay of an average of 2.0 to 2.4 days,370 371 
Clostridium difficile (CDI) infection,372 373 multidrug 
resistance organism (MDRO) infections, Acute Kidney Injury (AKI),\374\ 
hospital-acquired infection (HAI) or hospital-acquired condition 
(HAC),\375\ false-positive Central Line-Associated Blood Stream 
Infection (CLABSI) treatment, false positives reported to National 
Healthcare Safety Network (NHSN)/CMS (thus biasing the data), and 
additional lab and/or other diagnostic testing.\376\
---------------------------------------------------------------------------

    \365\ Snyder S, et al. Effectiveness of practices to reduce 
blood culture contamination: A Laboratory Medicine Best Practices 
systematic review and meta-analysis. Clinical Biochemistry. 2012; 
45(0):999-1011.
    \366\ Rupp M, et al. Reduction in Blood Culture Contamination 
Through Use of Initial Specimen Diversion Device. Clinical 
Infectious Diseases. 2017; 65(2):201-205.
    \367\ Bell M, et al. Effectiveness of a novel specimen 
collection system in reducing blood culture contamination rates. 
Journal of Emergency Nursing 44.6 (2018): 570-575.
    \368\ Doern G, et al. A Comprehensive Update on the Problem of 
Blood Culture Contamination and a Discussion of Methods for 
Addressing the Problem. Clinical Microbiology Reviews. 2020; 
33:e00009-19.
    \369\ Chang D, et al. Impact of blood culture diversion device 
on molecular pathogen identification on vancomycin use. Poster 
presented at: Society for Healthcare Epidemiology of America (2017).
    \370\ Skoglund E et al. Estimated Clinical and Economic Impact 
through Use of a Novel Blood Collection Device To Reduce Blood 
Culture Contamination in the Emergency Department: A Cost-Benefit 
Analysis. 2019; 57:e01015-18.
    \371\ Geisler B, et al. Model to evaluate the impact of 
hospital-based interventions targeting false-positive blood cultures 
oneconomic and clinical outcomes. Journal of Hospital Infection. 
2019; 102:438-444.
    \372\ Ibid. Geisler B, et al. Model to evaluate the impact of 
hospital-based interventions targeting false-positive blood cultures 
oneconomic and clinical outcomes. Journal of Hospital Infection. 
2019; 102:438-444.
    \373\ Doern G, et al. A Comprehensive Update on the Problem of 
Blood Culture Contamination and a Discussion of Methods for 
Addressing the Problem. Clinical Microbiology Reviews. 2020; 
33:e00009-19.
    \374\ Khalili H, et al. ``Antibiotics induced acute kidney 
injury: Incidence, risk factors, onset time and outcome.'' Acta 
Medica Iranica (2013): 51(12): 871-878.
    \375\ Doern G, et al. A Comprehensive Update on the Problem of 
Blood Culture Contamination and a Discussion of Methods for 
Addressing the Problem. Clinical Microbiology Reviews. 2020; 
33:e00009-19.
    \376\ Ibid. Doern G, et al. A Comprehensive Update on the 
Problem of Blood Culture Contamination and a Discussion of Methods 
for Addressing the Problem. Clinical Microbiology Reviews. 2020; 
33:e00009-19.
---------------------------------------------------------------------------

    The applicant explained that the detection of bacteremia is of 
particular concern for Medicare beneficiaries, given that the mean age 
for United States patients afflicted with sepsis in 2014 was 66.5, with 
sepsis present in 35 percent of all United States hospitalizations that 
resulted in death.\377\
---------------------------------------------------------------------------

    \377\ Rhee C, et al. Incidence and Trends of Sepsis in US 
Hospitals Using Clinical vs Claims Data, 2009-2014. JAMA. 2017; 
318:1241-1249.
---------------------------------------------------------------------------

    With regard to the newness criterion, the Steripath[supreg] 
Micro\TM\ ISDD[supreg] is a Class II medical device that received 
510(k) clearance from the FDA on October 8, 2020. The 510(k) clearance 
was based on substantial equivalence to an earlier version of the 
device, Steripath[supreg] Gen2, which received 510(k) clearance on 
February 28, 2020. According to the applicant, the Steripath[supreg] 
ISDD[supreg] product portfolio, including the Steripath[supreg] 
Micro\TM\ ISDD[supreg], is the only FDA 510(k)-cleared family of 
devices indicated to reduce blood culture contamination.\378\ According 
to the applicant, a supplemental Special 510(k) submission and 
clearance is anticipated for an additional configuration of the 
Steripath[supreg] Micro\TM\ ISDD[supreg] device that incorporates a 
butterfly safety venipuncture needle.
---------------------------------------------------------------------------

    \378\ Bell, Mary, et al. Effectiveness of a novel specimen 
collection system in reducing blood culture contamination rates. 
Journal of Emergency Nursing 44.6 (2018): 570-575.
---------------------------------------------------------------------------

    The applicant submitted a request for a new ICD-10-PCS procedure 
code and was granted approval for the following procedure code 
effective October 1, 2021: XXE5XR7 (Measurement of infection, 
mechanical initial specimen diversion technique using active negative 
pressure, new technology group 7).
    As discussed previously, if a technology meets all three of the 
substantial similarity criteria, it would be considered substantially 
similar to an existing technology and would not be considered ``new'' 
for purposes of new technology add-on payments.
    According to the applicant, diversion techniques use the same basic 
principle to reduce blood culture contamination by sequestering blood 
most likely to contain dislodged skin fragments and/or flora. With 
regard to the first criterion, whether a product uses the same or 
similar mechanism of action to achieve a therapeutic outcome, the 
applicant discussed current/alternative treatments to avoid blood 
contamination, but states that manual diversion, passive diversion, and 
the Steripath[supreg] Gen2 device are not comparable alternatives to 
Steripath[supreg] Micro\TM\.
    According to the applicant, manual diversion, which involves the 
phlebotomist or other medical professional first collecting blood into 
a waste tube and then manually switching to a sample collection tube, 
is not a replacement for Steripath[supreg] Micro\TM\ ISDD[supreg] 
because manual diversion inherently entails additional opportunities 
for human error through touch contamination and process variation, 
without the ability to manage and ensure healthcare worker compliance. 
The applicant further explained that manual diversion techniques 
introduce, at a minimum, one additional surface (waste tube top), which 
must either be sterilized (or carefully handled if pre-packaged 
sterile) to avoid cross contamination through the inoculation needle. 
The applicant noted that if the inoculation needle is contaminated in 
this manner, both blood culture bottles can become contaminated, which 
can be interpreted (inaccurately) as a true positive through laboratory 
testing. The applicant explained that Steripath[supreg] Micro\TM\ 
ISDD[supreg] is a closed system to prevent opportunities for touch 
contamination beyond conventional methods of blood culture sample 
acquisition. The applicant further explained that since 
Steripath[supreg] Micro\TM\ ISDD[supreg] is a pre-assembled and 
packaged sterile kit that does not require manual connections, it 
avoids touch-point contamination and prevents the need for additional 
time, focus, and manual diversion procedural compliance from the 
operator.
    The applicant stated that the Kurin product, a competitor diversion 
device that uses passive diversion (or relying on the patient's blood 
pressure), is not a comparable alternative to Steripath[supreg] 
Micro\TM\ ISDD[supreg] as it is not FDA-cleared to reduce blood-culture 
contamination. The applicant claimed that passive diversion, because of 
its limitations, is integrated into the Kurin product to redirect 0.15 
mL of blood. The applicant stated that passive devices are susceptible 
to bypassing diversion when the culture bottle is inoculated before 
diversion is complete, and that this limitation is not present within 
the Steripath[supreg] MicroTM ISDD[supreg] architecture. The 
applicant asserted that the Steripath[supreg] Micro\TM\ ISDD[supreg] 
uses a novel syringe-driven (or blood culture bottle-driven) negative 
pressure to flip an internal bladder which, in turn, creates gentle 
negative pressure to divert and

[[Page 45072]]

sequester the initial 0.6 to 0.9 mL of blood.
    The applicant further stated that the Steripath[supreg] Gen2 
ISDD[supreg] is not a comparable product to Steripath[supreg] Micro\TM\ 
ISDD[supreg], as it uses greater negative pressure to divert an initial 
1.5-2.0 mL of blood for the adult patient population. According to the 
applicant, the Steripath[supreg] MicroTM ISDD[supreg] 
platform leverages ISDD[supreg] technology but is smaller, easier-to-
use, and employs a novel proprietary diversion bladder technology to 
address patients who are hypotensive and hypovolemic, have difficult 
intravenous access, or are small in stature with lower blood volume. 
Specifically, the applicant explained that the Steripath[supreg] 
Micro\TM\ ISDD[supreg] uses syringe-driven (or blood culture bottle-
driven) negative pressure to flip an internal bladder which in turn 
creates gentle negative pressure to effectively and consistently divert 
and sequester the initial 0.6 to 0.9 mL of blood, the portion known to 
most likely contain contaminants, with this patient population. The 
applicant asserts this differentiates the Steripath[supreg] Micro\TM\ 
from the Steripath[supreg] Gen2. The applicant further explained that 
once diversion is complete, the user presses a button to isolate the 
diverted blood and, automatically, a second independent blood flow 
pathway opens to collect the blood specimen into the syringe (or blood 
culture bottle) for culture.
    With respect to the second criterion, whether the technology is 
assigned to the same or a different MS-DRG, the applicant did not 
indicate whether the Steripath[supreg] Micro\TM\ ISDD[supreg] would be 
assigned to the same MS-DRGs as cases representing patients who receive 
diagnostic information from competing technologies or traditional blood 
collection methods.
    With respect to the third criterion, whether the new use of the 
technology involves the treatment of the same or similar type of 
disease and the same or similar patient population, the applicant 
stated that the Steripath[supreg] Micro\TM\ ISDD[supreg] was 
fundamentally designed to address a specific and broader patient 
population than any other technology that is currently available and 
FDA 510(k) cleared to prevent blood culture contamination. The 
applicant explained that in a certain subset of `hard-stick' (low blood 
volume, hypovolemic and hypotensive) patients, blood culture using 
passive diversion or the Steripath[supreg] Gen2 ISDD[supreg] is not 
possible. According to the applicant, Steripath[supreg] 
MicroTM is the first ISDD designed specifically to address 
the unmet needs of the low blood volume, hypovolemic and hypotensive, 
`hard-stick' patient populations (many requiring integrated sterile 
syringe collection) that is FDA 510(k) cleared indicated to reduce 
blood culture contamination.
    In the proposed rule (86 FR 25316), we noted the following concerns 
regarding whether the technology meets the substantial similarity 
criteria and whether it should be considered new. Although we 
understand that the Steripath[supreg] Micro\TM\ ISDD[supreg] version 
may divert less blood volume and utilize less negative pressure than 
the Steripath[supreg] Gen2 ISDD[supreg], we noted that both devices 
utilize negative pressure and, according to the applicant, leveraged 
Magnolia Medical Technologies' foundational ISDD[supreg] technology, 
and it is unclear whether this represents a new mechanism of action. We 
further noted that the applicant also appears to consider the devices 
as similar, as they exclusively rely on studies conducted using the 
Steripath[supreg] Gen2 ISDD[supreg] to demonstrate substantial clinical 
improvement. We stated that we believe that the newness date for 
Steripath[supreg] Micro\TM\ ISDD[supreg] would begin on February 28, 
2020, the date on which the predicate device received 510(k) clearance. 
We also noted that the applicant claimed that the Steripath[supreg] 
ISDD[supreg] product portfolio, including the Steripath[supreg] 
MicroTM ISDD[supreg], is the only FDA 510(k)-cleared family 
of devices indicated to reduce blood culture contamination and we 
invited public comment on whether there are other FDA-cleared products 
designed to reduce blood culture contamination.
    We invited public comments on whether the Steripath[supreg] 
Micro\TM\ ISDD[supreg] is substantially similar to other technologies 
and whether the Steripath[supreg] Micro\TM\ ISDD[supreg] meets the 
newness criterion.
    Comment: The applicant submitted a letter asserting that 
Steripath[supreg] Micro\TM\ ISDD[supreg] meets the newness criterion. 
In response to our concern regarding whether the Steripath[supreg] 
Micro\TM\ ISDD[supreg] difference constituted a new mechanism of 
action, the applicant stated that the reduced diversion volume, the 
lower average peak negative pressure of Steripath[supreg] Micro\TM\ 
ISDD[supreg] compared to Steripath[supreg] Gen2 ISDD[supreg], and the 
pre-assembled integrated syringe configuration allowing for precise 
end-user control of the negative pressure constitute a new mechanism of 
action. The applicant stated that these features allow the 
Steripath[supreg] Micro\TM\ ISDD[supreg] to offer the same clinical 
benefits of the Steripath[supreg] Gen2 ISDD[supreg] to the DIVA, 
hypovolemic, hypotensive, and small-in-stature populations. The 
applicant also stated that initial feedback from commercial users of 
the Steripath[supreg] Micro\TM\ ISDD[supreg] is overwhelmingly 
positive, noting ease of use and utility for patients with fragile 
veins and vasculature. The applicant stated that clinical use data and 
end-user feedback to date shows that the novel mechanism of action is 
meeting the needs of the previously unserved DIVA population; however, 
the applicant did not provide data to support this claim. The applicant 
also stated that Steripath[supreg] Micro\TM\ ISDD[supreg] enables an 
equitable standard of care for sepsis testing accuracy and prevention 
of misdiagnosis for an expanded Medicare-eligible patient population.
    In response to our concern regarding the applicant's reliance of on 
clinical data from the Steripath[supreg] Gen2 ISDD[supreg] indicating 
that the two devices may be substantially similar, the applicant stated 
that reliance on a predicate device's supporting clinical literature is 
not one of the newness criteria. The applicant stated that the unique 
mechanism of action of Steripath[supreg] Micro\TM\ ISDD[supreg] and the 
new target population differentiate the two devices. The 
Steripath[supreg] Micro\TM\ ISDD[supreg] was FDA cleared on October 8, 
2020. The applicant stated, however, that the commercial launch date 
was March 31, 2021, and should function as the newness date.
    A few commenters stated that the Steripath[supreg] Micro\TM\ 
ISDD[supreg] is needed for the DIVA population. These commenters 
generally noted the efficacy of the Steripath[supreg] Gen2 
ISDD[supreg], but stated that it may not be appropriate for use in the 
DIVA population, and welcome the arrival of the Steripath[supreg] 
Micro\TM\ ISDD[supreg].
    Response: We thank the commenters for their perspective on the 
mechanism of action and potential benefits of Steripath[supreg] 
Micro\TM\ ISDD[supreg] to the DIVA population and have taken them under 
into consideration. We also appreciate the information provided by the 
applicant regarding the newness criterion. However, after consideration 
of the information provided, we continue to believe that the mechanism 
of action is substantially similar to that of its predicate device, 
Steripath[supreg] Gen2 ISDD[supreg]. While the applicant provides 
information that differentiates the Steripath[supreg] 
MicroTM ISDD[supreg] from the Steripath[supreg] Gen2 
ISDD[supreg], we do not believe that these differences rise to the 
level of a new mechanism of action. We believe that the differences of 
reduced diversion volume, lower average peak negative pressure, and the 
pre-assembled integrated syringe configuration allowing for precise 
end-user control of the negative pressure are iterative updates. The 
two devices still

[[Page 45073]]

work using the same mechanism of action, which is sequestration of the 
initial flash of blood during blood collection to remove skin flora and 
or other contaminants. We also continue to believe that the DIVA 
population may already be served by the Steripath[supreg] Gen2 product 
since the Magnolia Medical Steripath[supreg] Gen2 website states so 
directly.379 380 Lastly, we believe cases involving 
Steripath[supreg] MicroTM ISDD[supreg] would be assigned to 
the same MS-DRGs as cases involving Steripath[supreg] Gen2 
ISDD[supreg].
---------------------------------------------------------------------------

    \379\ Magnolia Medical Launches New Steripath Gen2 with 
Integrated Syringe. Magnolia Medical Technologies. (July 8, 2020) 
https://magnolia-medical.com/press-releases/steripath-gen2-with-integrated-syringe/.
    \380\ Steripath[supreg] Gen2 Initial Specimen Diversion Device. 
Magnolia Medical Technologies. (n.d.) https://magnolia-medical.com/steripath/gen2/.
---------------------------------------------------------------------------

    After consideration of all the information from the applicant, as 
well as the comments we received, we believe that the Steripath[supreg] 
MicroTM ISDD[supreg] is substantially similar to the 
Steripath Gen2 ISDD[supreg]. Since the Steripath[supreg] Gen2 received 
marketing authorization on February 28, 2020, we therefore consider the 
newness date for the Steripath MicroTM ISDD[supreg] to begin 
on February 28, 2020.
    With regard to the cost criterion, the applicant searched the FY 
2019 MedPAR FR claims data file with the FY 2019 Final Rule IPPS Impact 
File to identify potential cases representing patients who may be 
eligible for treatment using Steripath[supreg] Micro\TM\ ISDD[supreg].
    The applicant used 37 Infection ICD-10-CM Diagnosis Codes and 15 
Sepsis ICD-10-CM Diagnosis codes to identify patients who could 
potentially benefit from the Steripath[supreg] Micro\TM\ ISDD[supreg] 
during an inpatient stay. These ICD-10-CM codes are provided in the 
following table:
BILLING CODE 4120-01-P
[GRAPHIC] [TIFF OMITTED] TR13AU21.187


[[Page 45074]]


[GRAPHIC] [TIFF OMITTED] TR13AU21.188

[GRAPHIC] [TIFF OMITTED] TR13AU21.189

BILLING CODE 4120-01-C
    In its analysis, the applicant identified a primary cohort to 
assess whether this therapy met the cost criterion. The applicant 
stated that clinical literature suggests the DIVA population represents 
anywhere from 17 percent to 59 percent of all patients that present as 
symptomatic for sepsis and require blood 
cultures.381 382 383 The applicant added that the literature 
did not provide any additional information on the distribution of the 
DIVA population within the larger infection/sepsis population. To 
account for this, the applicant randomly selected 33% of claims that 
included one of the ICD-10 codes listed previously in one of the first 
two diagnosis code positions on the claim to include in the cost 
analysis.
---------------------------------------------------------------------------

    \381\ Sou, V., et al. A clinical pathway for the management of 
difficult venous access. BMC Nursing 16, 64 (2017).
    \382\ Armenteros-Yeguas V., et al. Prevalence of difficult 
venous access and associated risk factors in highly complex 
hospitalized patients. J Clin Nurs. 2017;26(23-24):4267-4275.
    \383\ Van Loon, FH, et al. Development of the A-DIVA Scale: A 
Clinical Predictive Scale to Identify Difficult Intravenous Access 
in Adult Patients Based on Clinical Observations. Medicine. 2016 
Apr;95(16)e3428.
---------------------------------------------------------------------------

    The applicant removed MS-DRGs describing kidney and urinary tract 
infections and renal failure because these cases are not likely to 
benefit from use of the Steripath[supreg] MicroTM 
ISDD[supreg]. The applicant stated that these diagnoses rely on 
technologies not relevant to Steripath[supreg] MicroTM 
ISDD[supreg], such as urine cultures and blood cultures specific to 
urea and creatinine. Lastly the applicant excluded cases in MS-DRGs 
that accounted for less than 1% of the total cases in the identified 
sample.
    The claim search conducted by the applicant resulted in 295,790 
claims mapping to six MS-DRGs: 871 (Septicemia or severe sepsis w/o mv 
>96 hours w mcc), 872 (Septicemia or severe sepsis w/o mv >96 hours w/o 
mcc), 853 (Infectious & parasitic diseases w O.R. procedure w mcc), 870 
(Septicemia or severe sepsis w mv >96 hours or peripheral 
extracorporeal membrane oxygenation (ECMO)), 854 (Infectious & 
parasitic diseases w O.R. procedure w cc), and 177 (Respiratory 
infections & inflammations w mcc). The applicant determined an average 
unstandardized case weighted charge per case of $69,973.
    The applicant stated that studies show blood culture contamination 
(BCC) increases length of stay (LOS) and leads to unnecessary 
antimicrobial therapy and/or hospital-acquired conditions. The 
applicant stated that a retrospective analysis involving hospitalized 
patients with septicemia-compatible symptoms found that avoiding BCC 
would decrease costs by $6,463, including $4,818 in savings for 
inpatient care. 53 percent of savings were attributed to reduced LOS 
and 26 percent to reduced antibiotic use.\384\ The applicant stated 
that to account for these savings, they removed $2,500 by inflating 
costs to charges using the national average cost-to-charge ratio (CCR) 
for routine days and $2,300 by inflating costs to charges using the 
pharmacy national average CCR. Because the previous study cited did not 
describe where non-LOS related inpatient savings arose, the applicant 
assumed that the savings arose from reduced drug use and therefore the 
pharmacy national average CCR was used.
---------------------------------------------------------------------------

    \384\ Geisler, BP, et al. Model to evaluate the impact of 
hospital-based interventions targeting false-positive blood cultures 
on economical and clinical outcomes. J Hosp Infect. 2019 
Aug;102(4):438-444.
---------------------------------------------------------------------------

    Because, according to the applicant, savings accrue in around 3% of 
cases where the Steripath[supreg] MicroTM ISDD[supreg] is 
used, the applicant applied three percent of the savings described 
previously to every case in the sample population. The applicant stated 
that removing the $4,800 in cost savings from 3 percent of the cases is 
mathematically the same as removing 3 percent of the cost savings from 
all cases. The applicant then standardized the charges using the FY 
2019 Final Rule Impact File. Next, the applicant applied the 2-year 
inflation factor used in the FY 2021 IPPS/LTCH PPS final rule to 
calculate outlier threshold charges (1.13218). To calculate the charges 
for the technology, the applicant used the national average CCR for the 
Supplies and Equipment cost center of 0.297 from the FY 2021 Final IPPS 
rule. The applicant calculated a final inflated

[[Page 45075]]

average case-weighted standardized charge per case of $76,796, which 
exceeded the average case-weighted threshold amount of $69,973 by 
$6,824. The applicant stated that because the final inflated average 
case-weighted standardized charge per case exceeded the average case-
weighted threshold amount, the therapy meets the cost criterion.
    Based on the information provided by the applicant, we noted the 
following concerns with regard to the cost criterion in the proposed 
rule. In its analysis, the applicant stated it randomly selected 33% of 
claims that included one of the ICD-10 codes listed previously in one 
of the first two diagnosis code positions on the claim to include in 
the cost analysis. Implicit in this decision to randomly select a 
subsample is the belief that Steripath[supreg] Micro\TM\ ISDD[supreg] 
cases are randomly distributed across all cases identified. If 
performed properly, the intent of random sampling from a population is 
to identify a smaller group of cases which remains representative or 
similar to the greater population. An added effect of proper random 
sampling is that the sample often has less variance than the population 
from which it was drawn. We stated that we are therefore concerned that 
random sampling may be inappropriate in this situation if the potential 
cases are not similarly randomly distributed. Furthermore, if it is 
true that a subset of cases would be more representive of cases 
eligible for use of the Steripath[supreg] Micro\TM\ ISDD[supreg], it 
may be more likely that those cases will be distributed based on 
certain characteristics, not randomly distributed. We sought public 
comment on whether the random sample used by the applicant would 
appropriately identify the cases eligible for the use of Steripath.
    In its cost analysis, the applicant stated that, in order to 
account for savings from the use of Steripath[supreg] Micro\TM\ 
ISDD[supreg], it removed $2,500 by inflating costs to charges using the 
national average cost-to-charge ratio (CCR) for routine days and $2,300 
by inflating costs to charges using the pharmacy national average CCR. 
We stated in the proposed rule that from a methodological standpoint, 
we are not certain that the data from which savings were calculated are 
generalizable to the broader Medicare population's experience if 
Steripath[supreg] MicroTM Blood Collection System is used. 
Specifically, we were not certain that the patient population and the 
resulting conclusions from the aforementioned study \385\ adequately 
generalize to the Medicare population.
    Lastly, the applicant stated that because savings accrue in around 
three percent of cases where the Steripath[supreg] Micro\TM\ 
ISDD[supreg] is used, the applicant applied three percent of the 
savings described previously to every case in its sample population. We 
stated we were unclear whether the three percent of cases which 
experienced savings in the one study provided by the applicant is 
adequately representative of the Medicare population. We were not 
certain that three percent of a sample experiencing some level of 
savings is the same as all cases experiencing three percent savings. 
Therefore, we were not certain that it is appropriate to apply three 
percent of savings across all cases in the applicant's cost analysis. 
As with the reduction in charges discussed previously, while the 
applicant's approach provides a more conservative estimate for purposes 
of the cost criterion, we questioned whether it accurately reflects the 
experiences of providers and Medicare beneficiaries.
    We invited public comment on whether Steripath[supreg] Micro\TM\ 
ISDD[supreg] meets the cost criterion.
    Comment: A commenter, the applicant, submitted comments in response 
to our concerns on whether Steripath[supreg] MicroTM 
ISDD[supreg] meets the cost criterion. With respect to our concern 
regarding the random sampling used by the applicant and whether it 
appropriately identified the cases eligible for the use of 
Steripath[supreg] MicroTM ISDD[supreg], the applicant 
pointed to clinical literature suggesting that the DIVA population 
represents approximately 17 to 59 percent of all patients that present 
symptomatic for sepsis and require blood cultures. The applicant 
further explained that it did not have evidence that patients who are 
eligible for Steripath[supreg] MicroTM ISDD[supreg] would 
match any particular profile that could be identified through claims 
data. For instance, the applicant did not have any evidence to suggest 
that patients in the DIVA population have more or less costly inpatient 
stays. Accordingly, in its original analysis, the applicant randomly 
selected 33 percent of claims from its full sample that included one of 
the ICD-10 codes listed in its application in one of the first two 
diagnosis code positions. The applicant acknowledged that selecting 
claims is an imperfect process that requires assumptions to be made in 
the absence of clear selection criteria, and in response to CMS' 
concern reran its analysis using the full sample cases, which resulted 
in a final inflated case-weighted standardized charge per case that 
exceeded the case weighted threshold. Thus, the applicant maintained 
that Steripath[supreg] MicroTM ISDD[supreg] meets the cost 
criterion.
    With respect to our concern that the savings calculated may not be 
generalizable to the broader Medicare population, the applicant pointed 
to a retrospective analysis involving hospitalized patients with 
septicemia-compatible symptoms. The applicant stated that this analysis 
found that avoiding blood culture contamination would decrease costs by 
$6,463, including $4,818 in savings for inpatient care, 53 percent of 
which were attributed to reduced length of stay and 26 percent to 
reduced antibiotic use. The applicant removed $2,500 by inflating costs 
to charges using the national average cost-to-charge ratio for routine 
days and $2,300 by inflating costs to charges using the pharmacy 
national average cost to charge ratio. The applicant recognized that 
accounting for anticipated savings is an imperfect process that 
requires assumptions be made on the best available evidence, and that 
given the absence of more detailed demographic data, CMS is correct in 
its uncertainty on whether the experiences of the 270 true-negative and 
false-negative patients included in the data from which savings were 
calculated can be adequately generalized to the Medicare population. 
However, the applicant pointed to a 2011 study published by the 
National Center for Health Statistics which found that rates of 
hospitalizations for septicemia or sepsis were significantly higher for 
those aged 65 and over than for those under age 65. Moreover, the 
applicant noted that, according to this study, the septicemia or sepsis 
hospitalization rate for those aged 85 and over was about 30 times the 
rate for those under age 65 and was more than four times higher than 
the rate for the 65-75 age group. Additionally, the study found that 
two-thirds of patients hospitalized for septicemia or sepsis in 2008 
were aged 65 and over and had Medicare as their payer. The applicant 
concluded that while it cannot definitively say that the patient 
population in the study evaluating cost savings from use of Steripath 
is generalizable to the Medicare population, it is reasonable to assume 
that some portion of the patient population accounted for in the study 
would be representative of the Medicare population based on the high 
incidence of septicemia and sepsis among Medicare beneficiaries.
    Finally, in response to our concern that the three percent of the 
applicant's sample population experience some level of savings is not 
the same as all cases in the sample experiencing three

[[Page 45076]]

percent savings, the applicant reran its cost analysis to randomly 
select three percent of cases from its full sample population and 
removed savings for those three percent of cases only. The applicant 
used the same methodology described previously to account for these 
savings. After randomly selecting three percent of cases from the full 
sample population and applying the anticipated savings from use of 
Steripath[supreg] MicroTM ISDD[supreg], the applicant found 
that the final inflated case-weighted standardized charge per case 
exceeded the case-weighted threshold and that Steripath[supreg] 
MicroTM ISDD[supreg] meets the cost criterion.
    Response: We thank the commenter for the additional information 
provided, including its supplementary cost analyses. After 
consideration of the comments received and the cost analyses provided 
by the appliant, we agree that the final inflated case-weighted 
standardized charge per case for Steripath[supreg] MicroTM 
ISDD[supreg] exceeds the case-weighted threshold and that 
Steripath[supreg] MicroTM ISDD[supreg] meets the cost 
criterion.
    With respect to the substantial clinical improvement criterion, the 
applicant asserted that the Steripath[supreg] Micro\TM\ ISDD[supreg] 
represents a substantial clinical improvement over existing technology. 
The applicant stated that data from studies show that Steripath 
Micro\TM\ ISDD[supreg] offers the ability to reduce blood collection 
contamination with skin flora and asserted that it improves clinical 
outcomes relative to services or technologies previously available as 
demonstrated by reducing clinically significant adverse events (that 
is, a decrease in inappropriate antibiotic use and a decrease in 
inappropriate hospitalizations).
    The applicant submitted with its application 17 Steripath[supreg] 
ISDD[supreg] technology-specific studies, including 5 peer-reviewed 
studies published in scientific journals, that it stated support the 
contamination rate reduction with Steripath[supreg] Gen2 ISDD [supreg] 
of 73.6 percent to 100 percent, with resulting sustained contamination 
rates of 0.97 percent to 0.0 percent, which the applicant stated is 
below the 3.0 percent gold standard benchmark rate for blood culture 
contamination.\386\
---------------------------------------------------------------------------

    \386\ Zimmerman, F. et al. ``Reducing blood culture 
contamination using an initial specimen diversion device.'' American 
Journal of Infection Control 47.7 (2019): 822-826.
---------------------------------------------------------------------------

    The applicant submitted a retrospective controlled study by Bell M, 
et al.\387\ that showed that investigators seeking to lower the blood 
culture contamination rate at four different Lee Health (a healthcare 
system in Florida) emergency departments found that Steripath[supreg] 
Gen2 ISDD[supreg] implementation reduced their blood culture 
contamination rate by 83.0 percent when compared to conventional 
methods of sample acquisition, (that is without diversion). The Lee 
Health emergency departments compared contamination rates obtained 
using Steripath[supreg] Gen2 ISDD[supreg] device as the standard of 
care from May 2016 through November 2016 to conventional methods which 
were collected from October 2015 through November 2016. The applicant 
stated that these findings support their claim that Steripath[supreg] 
ISDD[supreg] reduces the risk of blood culture contamination.
---------------------------------------------------------------------------

    \387\ Bell M, et al. Effectiveness of a novel specimen 
collection system in reducing blood culture contamination rates. 
Journal of Emergency Nursing 44.6 (2018): 570-575.
---------------------------------------------------------------------------

    The applicant submitted the Bauman, K, poster,\388\ where 
investigators seeking to lower the blood culture contamination rate at 
the Inova Fairfax Medical Center found that Steripath[supreg] Gen2 
implementation reduced their blood culture contamination rate by 81.5% 
when compared to conventional methods of sample acquisition. The trial 
use of Steripath[supreg] Gen2 lasted for one year, and results were 
compared to conventional methods for the year preceding the trial. 
According to the applicant, findings support the claim that 
Steripath[supreg] reduces the risk of blood culture contamination, 
while historical patient data from this hospital supported the claim 
that the lower contamination rate Steripath[supreg] enables will 
translate into a reduced patient length of stay of one day per avoided 
false positive event.
---------------------------------------------------------------------------

    \388\ Bauman, K. ``Don't Stick Me Again! Reducing Blood Culture 
Contamination'' Poster presented at: Emergency Nursing Annual 
Conference
---------------------------------------------------------------------------

    The applicant submitted the Blakeney J, et al.\389\ poster, a 
prospective controlled study comparing the use of Steripath[supreg] 
ISDD[supreg] to standard collection methods and the effect on blood 
culture contamination rates. Over a 16-week period, participants' blood 
was collected using both the Steripath[supreg] and conventional 
methods, with each being recorded. Per the applicant, outcomes showed 
that Steripath[supreg] ISDD[supreg] implementation reduced Beebe 
Healthcare's blood culture contamination rate by 74.6 percent when 
compared to conventional methods of sample acquisition. The applicant 
stated that the findings support the claim that Steripath[supreg] 
ISDD[supreg] reduces the risk of blood culture contamination.
---------------------------------------------------------------------------

    \389\ Blakeney J, et al. ``Reduction of Blood Culture 
Contamination Using Initial Specimen Diversion Device''Poster 
presented at: American Society for Microbiology Annual Meeting 
(2018).
---------------------------------------------------------------------------

    The applicant submitted the Church K, et al.\390\ prospective 
controlled study, which showed that investigators at the Medical 
University of South Carolina emergency department found that 
Steripath[supreg] Gen2 ISDD[supreg] implementation reduced their blood 
culture contamination rate by 73.6 percent when compared to 
conventional methods of sample acquisition. In this 20-month study, 
nurses were given autonomy to decide if a patient would be best served 
by the Steripath[supreg] Gen2 device or conventional methods, with 
choices being recorded. The uptake rate of the Steripath[supreg] Gen2 
device was 66%, with exclusions being uncooperative patients and 
difficult to stick patients.
---------------------------------------------------------------------------

    \390\ Church K, et al. ``Novel Blood Culture Collection Device 
Reduces False-Positive Blood Cultures, Saves Costs, and Increases 
Accuracy of Bloodstream Infection Diagnosis'' Poster presented at: 
IHI National Forum (2017).
---------------------------------------------------------------------------

    The applicant submitted the Gauld L, et al.\391\ study, an eight 
month long prospective controlled study which showed that investigators 
seeking to lower the blood culture contamination rate at the Medical 
University of South Carolina emergency department found that 
Steripath[supreg] Gen2 ISDD[supreg] implementation reduced their blood 
culture contamination rate by 86.3 percent when compared to 
conventional methods of sample acquisition.
---------------------------------------------------------------------------

    \391\ Gauld L, et al. ``Reducing the laboratory cost of false-
positive blood cultures in the adult emergency department.'' Poster 
presented at: IHI National Forum on Quality Improvement in 
Healthcare (2016).
---------------------------------------------------------------------------

    The applicant submitted a poster, Lanteri C, et al.,\392\ with 
preliminary data and a paper, Huss, J, et al.,\393\ that includes all 
of the poster data with additional data gathered. This prospective 
controlled study at Brooke Army Medical Center showed that 
Steripath[supreg] Gen2 ISDD[supreg] implementation reduced blood 
culture contamination rate by 91.7 percent from September 2015 through 
January 2016, and 89.7 percent from September 2015 through March 2016 
when compared to conventional methods of sample acquisition.
---------------------------------------------------------------------------

    \392\ Lanteri C, et al. ``Reduction of Blood Culture 
Contaminations in the Emergency Department.'' Poster presented at: 
Department of Defense Healthcare Quality and Safety Awards (2016).
    \393\ Huss, Jody L, et al. ``Reducing Blood Culture 
Contamination with the Steripath[supreg] Blood Collection Kit.'' 
Uniformed Services University, 2016
---------------------------------------------------------------------------

    The applicant submitted the Rupp M, et al.\394\ paper, which is a 
12-month,

[[Page 45077]]

single center, prospective, controlled, open label trial. Investigators 
at the University of Nebraska Medical Center emergency department 
seeking to gauge the efficacy of the Steripath[supreg] Gen2 
ISDD[supreg] without confounding variables conducted a matched-set 
controlled study and found that Steripath[supreg] implementation 
reduced their blood culture contamination rate by 87.6 percent when 
compared to conventional methods of sample acquisition.
---------------------------------------------------------------------------

    \394\ Rupp M, et al. ``Reduction in blood culture contamination 
through use of initial specimen diversion device.'' Clinical 
Infectious Diseases 65.2 (2017): 201-205.
---------------------------------------------------------------------------

    The applicant submitted the Stonecypher K, et al.\395\ 8 week pilot 
study, which showed that investigators at the Michael E. DeBakey VA 
Medical Center emergency department found that Steripath[supreg] Gen2 
ISDD[supreg] implementation reduced their blood culture contamination 
rate by 83.1 percent when compared to conventional methods of sample 
acquisition.
---------------------------------------------------------------------------

    \395\ Stonecypher K, et al. ``ER Pilot Leads to Hospital-wide 
Implementation of Blood Culture Device'' Poster presented at: 
Emergency Nurses Association Annual Conference (2018)
---------------------------------------------------------------------------

    The applicant submitted the Tompkins L, et al.\396\ abstract, which 
showed that investigators seeking to lower the blood culture 
contamination rate at Stanford Health Care found that Steripath[supreg] 
Gen2 ISDD[supreg] implementation reduced their blood culture 
contamination rate by 100 percent over a 4-month period when compared 
to conventional methods of sample acquisition. According to the 
applicant, full results are anticipated but not presently published.
---------------------------------------------------------------------------

    \396\ Tompkins L, et al. ``Eliminating Blood Culture 
Contamination with an Initial-Specimen Diversion Device'' Abstract 
presented at: IDWeek (2020).
---------------------------------------------------------------------------

    The applicant submitted the Tongma C, et al.\397\ prospective 
controlled study, which showed that investigators seeking to lower the 
blood culture contamination rate at Rush University Medical Center 
emergency department found that Steripath[supreg] Gen2 ISDD[supreg] 
implementation reduced their blood culture contamination rate by 87.0 
percent when compared to conventional methods of sample acquisition. 
The 6-month study was split into an initial 3 months of usual care and 
a subsequent 3 months using the Steripath[supreg] Gen2 ISDD[supreg].
---------------------------------------------------------------------------

    \397\ Tongma C, et al. ``Significant Reduction of Blood Culture 
Contamination in the Emergency Department (ED) Using the 
Steripath[supreg] Blood Diversion Device.'' Poster presented: 
Infectious Diseases Society of America IDWeek Conference, Fall 
(2017).
---------------------------------------------------------------------------

    The applicant provided the following studies to support secondary 
claims of substantial clinical improvement:
    The applicant submitted the Buchta C, et al.\398\ animal (pig) 
model study, in which investigators hypothesized that despite proper 
skin antiseptic use, contamination may occur because flora from deeper 
regions (such as pores) are not effectively eliminated. The applicant 
stated that results confirmed the hypothesis that cannula may cause 
tissue fragments to be punched in the process of blood sample 
acquisition, supporting the mechanism by which Steripath[supreg] Gen2 
ISDD[supreg] primarily addresses blood culture contamination (that is, 
diversion).
---------------------------------------------------------------------------

    \398\ Buchta C, et al. Skin plugs in phlebotomy puncture for 
blood donation. Wiener klinische Wochenschrift 117.4 (2005): 141-
144.
---------------------------------------------------------------------------

    The applicant submitted the Rhee C, et al.\399\ retrospective 
cohort study, which featured adult patients admitted to 409 academic, 
community, and Federal hospitals from 2009-2014. Investigators sought 
to estimate national sepsis incidence and trends, concluding that 
sepsis was present in 6 percent of adult hospitalizations and 35 
percent of hospitalizations resulting in death. According to the 
applicant, this helps put into context the role of Steripath[supreg] 
ISDD[supreg] in improving the efficacy of the primary tool used to 
guide therapy for bloodstream infections: Blood culture.
---------------------------------------------------------------------------

    \399\ Rhee C, et al. Incidence and trends of sepsis in US 
hospitals using clinical vs claims data, 2009-2014. JAMA 318.13 
(2017): 1241-1249.
---------------------------------------------------------------------------

    The applicant submitted the Zimmerman F, et al.\400\ paper (a 
randomized clinical trial) and the Binkhamis K and Forward K \401\ 
paper (a prospective controlled study), which demonstrated that manual 
diversion reduced blood culture contamination rate by 60.0 percent and 
28.2 percent, respectively, when compared to conventional methods of 
sample acquisition.
---------------------------------------------------------------------------

    \400\ Zimmerman F, et al. Modification of blood test draw order 
to reduce blood culture contamination: A randomized clinical trial. 
Clinical Infectious Diseases 71.5 (2020): 1215-1220.
    \401\ Binkhamis K and Forward K. Effect of the initial specimen 
diversion technique on blood culture contamination rates. Journal of 
Clinical Microbiology 52.3 (2014): 980-981.
---------------------------------------------------------------------------

    The applicant also submitted the Patton R and Schmitt T \402\ 
prospective controlled study, which showed that investigators seeking 
to trial manual diversion of 1 mL to lower the blood culture 
contamination rate at the Northwest Hospital and Medical Center 
Emergency Department found that manual diversion reduced their blood 
culture contamination rate by 43.8 percent when compared to 
conventional methods of sample acquisition. The applicant further 
stated that the findings additionally support the volume of diversion 
utilized by Steripath[supreg] Micro\TM\ ISDD[supreg].
---------------------------------------------------------------------------

    \402\ Patton R and Schmitt T. Innovation for reducing blood 
culture contamination: Initial specimen diversion technique. Journal 
of Clinical Microbiology 48.12 (2010): 4501-4503.
---------------------------------------------------------------------------

    The applicant also submitted the Syed S, et al.\403\ 
preintervention and postintervention study, which showed that 
investigators at the AMITA Health Saint Francis Hospital Emergency 
Department found that manual diversion reduced their blood culture 
contamination rate by 30.9 percent when compared to conventional 
methods of sample acquisition.
---------------------------------------------------------------------------

    \403\ Syed S, et al. Diversion Principle Reduces Skin Flora 
Contamination Rates in a Community Hospital. Archives of Pathology & 
Laboratory Medicine 144.2 (2020): 215-220.
---------------------------------------------------------------------------

    According to the applicant, the findings from these four studies 
support the claim that manual diversion reduces the risk of blood 
culture contamination relative to conventional methods of sample 
acquisition. We note that these studies discussed manual diversion and 
not Steripath[supreg] Micro\TM\ or other diversion devices.
    The applicant submitted the Alahmadi Y, et al.\404\ study, which is 
a retrospective case-control study that showed that false positive 
blood cultures were associated with an average 5.4 day increase in 
patient length of stay and average increases of more than $7,500 in 
total charges to a healthcare system. The applicant also submitted the 
Bates D, et al.,\405\ which is a prospective controlled study that 
showed false positive blood cultures were associated with an average of 
a 4.5 day increase in patient length of stay and average increases of 
more than $4,000 in total charges to a healthcare system. According to 
the applicant, investigators also noted that contaminants were 
independently correlated with a 39 percent increase in antibiotic 
charges.
---------------------------------------------------------------------------

    \404\ Alahmadi Y, et al. Clinical and economic impact of 
contaminated blood cultures within the hospital setting. Journal of 
Hospital Infection 77.3 (2011): 233-236.
    \405\ Bates D, et al. Contaminant blood cultures and resource 
utilization: The true consequences of false-positive results. JAMA 
265.3 (1991): 365-369.
---------------------------------------------------------------------------

    The applicant provided a study to support its claim that the 
Steripath[supreg] ISDD[supreg] reduces the average length of stay for 
patients requiring blood culture, thereby lowering their risk of 
hospital-acquired infections (HAI) and conditions (HAC). The applicant 
explained that the Skoglund E, et al.\406\ decision tree health care 
economic model paper showed that investigators found that overall, each 
false positive blood culture was on average associated

[[Page 45078]]

with 2 day increases in patient length of stay and an average increase 
of more than $4,500 in total charges to a healthcare system. According 
to the applicant, Steripath[supreg] ISDD[supreg] implementation may 
reduce costs associated with contamination and reduce the average 
patient length of stay.
---------------------------------------------------------------------------

    \406\ Skoglund E, et al. Estimated clinical and economic impact 
through use of a novel blood collection device to reduce blood 
culture contamination in the emergency department: A cost-benefit 
analysis. Journal of Clinical Microbiology 57.1 (2019).
---------------------------------------------------------------------------

    The applicant provided four studies to support its claim that 
Steripath[supreg] ISDD[supreg] reduces the inappropriate administration 
of vancomycin and other antibiotics to drive antibiotic stewardship. 
The applicant submitted the Chang D, et al.\407\ poster, a 
retrospective, nonrandomized study that recorded the San Antonio 
Military Medical Center Emergency Department's days of therapy (DOT) of 
vancomycin for 18 months as a baseline. Then, the hospital implemented 
a new blood culture test, and recorded the DOT of vancomycin for 7 
months. Subsequently, the hospital implemented the Steripath[supreg] 
Gen2 device and recorded the DOT of vancomycin for an additional 14 
months to complete the 39-month trial. Investigators found that 
Steripath[supreg] Gen2 ISDD[supreg] implementation reduced vancomycin 
days of therapy by 14.4 days per 1,000 patient days when compared to 
conventional methods of sample acquisition. According to the applicant, 
findings from the study, as reported by the study authors, support the 
claim that Steripath[supreg] ISDD[supreg] reduces the unnecessary 
administration of antibiotics by reducing the rate of false positive 
blood cultures.
---------------------------------------------------------------------------

    \407\ Chang D, et al. ``Impact of blood culture diversion device 
on molecular pathogen identification on vancomycin use.'' Poster 
presented at: Society for Healthcare Epidemiology of America (2017).
---------------------------------------------------------------------------

    The applicant also submitted the Souvenir D, et al.\408\ cohort 
study of 3,276 cultures of blood from 1,433 patients in which 
investigators found that physicians treated almost half of all patients 
receiving a false positive blood culture result with antibiotics, with 
vancomycin misuse occurring in 34 percent of patients. The applicant 
also submitted the Heijden Y, et al.\409\ study in which investigators 
found that physicians treated 27% of patients receiving a false 
positive blood culture result with antibiotics unnecessarily, with the 
median antibiotic regimen being 7 days in length. The applicant also 
submitted the Bates study,\410\ as discussed previously, which showed 
contaminants were independently correlated with a 39 percent increase 
in antibiotic charges. According to the applicant, as Steripath[supreg] 
ISDD[supreg] is designed to reduce the incidence of blood culture 
contamination, Steripath[supreg] ISDD[supreg] implementation may reduce 
unnecessary antibiotic administration while supporting antimicrobial 
stewardship.
---------------------------------------------------------------------------

    \408\ Souvenir D, et al. Blood cultures positive for coagulase-
negative staphylococci: Antisepsis, pseudobacteremia, and therapy of 
patients. Journal of Clinical Microbiology 36.7 (1998): 1923-1926.
    \409\ Heijden, Yuri F., et al. ``Clinical impact of blood 
cultures contaminated with coagulase-negative staphylococci at an 
academic medical center. Infection Control and Hospital Epidemiology 
32.6 (2011): 623.
    \410\ Bates D, et al. Contaminant blood cultures and resource 
utilization: The true consequences of false-positive results. JAMA 
265.3 (1991): 365-369.
---------------------------------------------------------------------------

    In the proposed rule (86 FR 25320 through 25321), we stated the 
following concerns regarding the substantial clinical improvement 
criterion. We noted that much of the evidence submitted by the 
applicant to support that Steripath[supreg] Micro\TM\ represents a 
substantial clinical improvement over existing technologies spoke to 
the overall clinical value of reducing blood contamination, or the 
benefit of manual diversion over no diversion, but did not directly 
link the Steripath[supreg] Micro\TM\ to improved clinical endpoints. We 
noted that the applicant stated that all of the studies provided that 
address the specific technology used to reduce blood contamination 
through diversion of the initial sample during blood collection 
utilized the Steripath[supreg] Gen2 ISDD[supreg], not the 
Steripath[supreg] Micro\TM\ ISDD[supreg] and we therefore question 
whether we have sufficient information to assess the clinical impact of 
Steripath[supreg] MicroTM. Furthermore, we noted that the 
applicant did not present any clinical data to compare 
Steripath[supreg] Micro\TM\ ISDD[supreg] to the Steripath[supreg] Gen2 
ISDD[supreg]. We also noted that comparative studies between 
Steripath[supreg] Micro\TM\ and either manual diversion or competitor 
devices were not provided, and we question whether the standard of care 
used in the studies (that is, no diversion) is an appropriate 
comparator against which to test this technology. Additionally, we 
noted that the applicant did not provide any clinical data 
demonstrating that the Steripath[supreg] Micro\TM\ directly reduced 
length of stay, C. difficile infections, or other secondary results of 
antibiotic overuse. We noted our interest in any clinical data that 
directly links the Steripath[supreg] Micro\TM\ to these outcomes.
    Finally, we noted that the claim of gentle negative pressure in 
support of the applicant's assertion that the technology would provide 
a treatment option for a new patient population was not addressed by 
any of the studies submitted. In addition, no data was supplied that 
quantified appropriate levels of negative pressure for either the 
typical or DIVA populations. Furthermore, no data was provided which 
compared the asserted appropriate level of negative pressure to levels 
of negative pressure created by the Steripath[supreg] Micro\TM\ and 
Steripath[supreg] Gen2 devices. We noted our interest in any evidence 
of clinical improvement using the Steripath[supreg] Micro\TM\ 
ISDD[supreg] in the specific population identified by the applicant, 
the difficult intravenous access population.
    We invited public comments on whether the Steripath[supreg] 
Micro\TM\ ISDD[supreg] meets the substantial clinical improvement 
criterion.
    Comment: The applicant submitted a letter that asserted the 
Steripath[supreg] Micro\TM\ ISDD[supreg] meets the substantial clinical 
improvement criteriona. The applicant stated that the Steripath[supreg] 
Micro\TM\ ISDD[supreg] meets the CMS regulatory definition of 
``substantial clinical improvement'' because it offers the DIVA, 
hypovolemic, hypotensive, and small-in-stature populations access to a 
technology for which these groups currently have no other available 
option. Per the applicant, Steripath[supreg] Micro\TM\ ISDD[supreg] 
confers the same benefits of the Steripath[supreg] Gen2 ISDD[supreg] 
onto new patient populations. The applicant further stated that 
Steripath[supreg] Micro\TM\ ISDD[supreg] initial results (over 500 
blood culture draws with zero contaminations at multiple facilities) 
indicate an efficacy profile substantially equivalent to Steripath Gen2 
ISDD[supreg].
    In response to our concern regarding the lack of clinical data for 
the Steripath[supreg] Micro\TM\ ISDD[supreg], the applicant reiterated 
that the reduced diversion volume is supported by the literature,\411\ 
initial data indicates a substantially equivalent efficacy profile, the 
DIVA population is eligible for the device, and the FDA cleared the 
Steripath[supreg] Micro\TM\ ISDD[supreg] with specific indications for 
use to reduce blood culture contamination.
---------------------------------------------------------------------------

    \411\ Patton, Richard G., and Timothy Schmitt. ``Innovation for 
reducing blood culture contamination: Initial specimen diversion 
technique.'' Journal of Clinical Microbiology 48.12 (2010): 4501-
4503.
---------------------------------------------------------------------------

    In response to our concern regarding the lack of studies that 
compare the Steripath[supreg] Micro\TM\ ISDD[supreg] to any relevant 
standard of care or technology, the applicant stated that studies 
provided by the applicant regarding manual diversion can be compared to 
studies featuring the Steripath[supreg] Gen2 ISDD[supreg], despite the 
studies taking place in different times, settings, and patient 
populations. The applicant further stated that the initial results 
since the commercial launch of the Steripath[supreg]

[[Page 45079]]

Micro\TM\ ISDD[supreg] are equivalent to the Steripath[supreg] Gen2 
ISDD[supreg]. The applicant also notes that there are no FDA-cleared 
competitive devices that are indicated to reduce blood culture 
contamination. The applicant also stated that no diversion is the 
standard of care and therefore an appropriate comparator.
    In response to our concern that there is no evidence linking the 
Steripath[supreg] Micro\TM\ ISDD[supreg] directly to reduced length of 
stay, C. difficile infections, or other secondary results of antibiotic 
overuse, the applicant stated that the equivalent efficacy of the 
Steripath[supreg] Micro\TM\ ISDD[supreg] to the Steripath[supreg] Gen2 
ISDD[supreg] indicated that the Steripath[supreg] Micro\TM\ 
ISDD[supreg] will have equivalent effects on outcomes demonstrated by 
use of Steripath[supreg] Gen2 including reduced blood culture 
contamination,\412\ reduced length-of-stay \413\ and reduced antibiotic 
use.\414\
---------------------------------------------------------------------------

    \412\ Doern G, et al. A Comprehensive Update on the Problem of 
Blood Culture Contamination and a Discussion of Methods for 
Addressing the Problem. Clinical Microbiology Reviews. 2020; 
33:e00009-19.
    \413\ Bauman, K. ``Don't Stick Me Again! Reducing Blood Culture 
Contamination'' Poster presented at: Emergency Nursing Annual 
Conference.
    \414\ Chang D, et al. ``Impact of blood culture diversion device 
on molecular pathogen identification on vancomycin use.'' Poster 
presented at: Society for Healthcare Epidemiology of America (2017).
---------------------------------------------------------------------------

    In response to our concerns regarding the lack of quantifiable data 
related to the pressure of the devices, the applicant noted that the 
Steripath[supreg] Micro\TM\ ISDD[supreg] novel bladder architecture 
utilizes 78% lower average peak negative pressure compared to Steripath 
Gen2 ISDD[supreg] (average range of -0.5 psi compared to -2.3 psi) to 
help reduce the risk of vascular compromise and/or interrupted blood 
flow during blood culture collection.
    We also received additional comments in support of the technology. 
A commenter noted that in their hospital's experience with using the 
Steripath[supreg] Micro\TM\ ISDD[supreg] in pediatric patients, no 
contaminations have occurred. Another commenter stated that the 
Steripath[supreg] Micro\TM\ ISDD[supreg] will allow their health system 
to reduce blood contamination equitably across populations as it serves 
the DIVA population who was previously ineligible for Steripath[supreg] 
ISDD[supreg] technology.
    Response: We appreciate the commenters' perspectives on the 
substantial clinical improvement criterionaand have taken them into 
consideration. However, after review of all the data received to date, 
we continue to have concerns regarding the substantial clinical 
improvement criterion as noted in the FY 2022 IPPS/LTCH PPS proposed 
rule. Specifically, we remain concerned that the applicant did not 
provide any studies that featured the Steripath[supreg] 
MicroTM ISDD[supreg], which is the subject of this 
application, and we therefore cannot adequately determine if the 
product fully meets the substantial clinical improvement criterion. 
While the applicant stated that initial results of blood draws with 
Steripath[supreg] MicroTM indicate a substantially 
equivalent efficacy profile to that of the Gen2, we did not receive any 
data to support this claim, and furthermore, substantial equivalence 
does not demonstrate superiority. We agree that existing FDA-cleared 
devices are not indicated to reduce blood culture contamination and are 
therefore not an appropriate comparator. Though the applicant compared 
blood culture contamination reduction rates of manual diversion as 
compared to Steripath[supreg] Gen2 and asserted that the 
MicroTM has been proven to perform as well as Gen2, without 
data using the Steripath[supreg] MicroTM to demonstrate 
improved outcomes we are unable to come to this conclusion. Thus, we 
also continue to have concerns that the applicant also did not provide 
studies that compared the Steripath[supreg] MicroTM 
ISDD[supreg] to other Steripath[supreg] devices (specifically 
Steripath[supreg] Gen2) or other forms of diversion or best practices 
used to reduce blood culture contamination to demonstrate an 
improvement in clinical outcomes such as length of stay, treatment 
decisions, C. difficile infections, or other secondary results of 
antibiotic overuse, as the applicant only reiterated evidence linking 
the Steripath[supreg] Gen2 to these outcomes. Though the applicant 
asserts that the Micro[supreg]'s comparable efficacy to the Gen2 gives 
them no reason to believe these outcomes will be affected with the DIVA 
population, we disagree that this is a new patient population as 
discussed further below, and believe that this does not speak to the 
technology's superiority over existing technologies.
    We also continue to have concerns with the applicant's assertion 
that Steripath[supreg] MicroTM treats patients ineligible 
for current treatments. As discussed previously, the applicant's 
website states that the Gen2 is also targeted to treat DIVA patients, 
and patients with difficult access are still able to receive blood 
cultures. The applicant states that the standard of care is no 
diversion, and therefore it follows that these patients will not 
require it to receive blood cultures using other forms of best 
practices. Since we did not receive any data demonstrating the use of 
Steripath[supreg] Micro[supreg] in DIVA patients, we are unable to 
determine that it offers a treatment option for patients ineligible for 
current therapies.
    After consideration of the information previously submitted in the 
Steripath[supreg] MicroTM ISDD[supreg] application and 
previously summarized in this final rule, and the public comments we 
received, we are unable to determine that the Steripath[supreg] 
MicroTM ISDD[supreg] meets the substantial clinical 
improvement criterion. Therefore, we are not approving new technology 
add-on payments for the Steripath[supreg] MicroTM 
ISDD[supreg] for FY 2022.
m. StrataGraft\TM\ Skin Tissue
    Stratatech Corporation, a Mallinckrodt company, submitted an 
application for new technology add-on payments for the StrataGraft\TM\ 
skin tissue (``StrataGraft'') for topical application for FY 2022. The 
applicant describes StrataGraft\TM\ skin tissue as a viable, 
bioengineered, regenerative skin construct (BRSC) consisting of an 
epidermal layer of viable, fully stratified, allogeneic human 
NIKS[supreg] \415\ keratinocytes growing on a dermal layer composed of 
viable human dermal fibroblasts embedded in a collagen-rich matrix. The 
applicant noted that StrataGraft\TM\ is intended for the treatment of 
adult patients with severe thermal burns that contain intact dermal 
elements and require surgical intervention (hereinafter referred to as 
severe thermal burns [STB]). The applicant stated that StrataGraft\TM\ 
skin tissue is produced in a rectangular format of approximately 100 
cm\2\, approximately 8 cm by 12.5 cm.
---------------------------------------------------------------------------

    \415\ Registered trademark of Stratatech Corporation, Madison, 
WI.
---------------------------------------------------------------------------

    The applicant explained that the StrataGraft\TM\ skin tissue 
promotes durable wound closure and regenerative healing for adult 
patients with STB. The applicant stated that in addition to providing 
immediate wound coverage and epidermal barrier function, the viable and 
metabolically active keratinocytes and fibroblasts in StrataGraft\TM\ 
skin tissue provide sustained expression and secretion of growth 
factors, cytokines, and wound healing factors, which are anticipated to 
promote regenerative healing. The applicant stated that the 
StrataGraft\TM\ skin tissue does not engraft; rather, it promotes 
regenerative healing and is replaced by the patient's own cells, 
eliminating the need for autografting to attain definitive closure of 
treated wounds.
    The applicant explained that a thermal burn is the most common type

[[Page 45080]]

of burn injury and accounts for approximately 86 percent of burn 
cases.\416\ The applicant noted that burns are classified according to 
the depth of tissue injury as superficial (first-degree burns), 
partial-thickness (superficial and deep partial-thickness; second-
degree burns), full-thickness (FT, third-degree burns), and fourth-
degree burns (burns that have injured deeper structures such as muscle, 
fascia, and bone).417 418 The applicant also noted the 
percentage of total body surface area (TBSA) determines burn severity 
and directly correlates with mortality.\419\
---------------------------------------------------------------------------

    \416\ Schaefer TJ, Tannan SC. Thermal Burns. [Updated 2020 Jun 
7]. In: StatPearls [internet]. Treasure Island (FL): StatPearls 
Publishing; 2020 Jan-. https://www.ncbi.nlm.nih.gov/books/NBK430773//.
    \417\ Kagan RJ, Peck MD, Ahrenholz DH, et al. Surgical 
management of the burn wound and use of skin substitutes: An expert 
panel white paper. J Burn Care Res. 2013;34(2):e60-e79.
    \418\ Rice PL, Orgill DP. Assessment and classification of burn 
injury. UpToDate. https://www.uptodate.com/contents/assessment-and-classification-of-burn-injury. Literature review current through 
September 2020. Accessed September 25, 2020.
    \419\ Girard D, Laverdet B, Buh[eacute] V, et al. 
Biotechnological Management of Skin Burn Injuries: Challenges and 
Perspectives in Wound Healing and Sensory Recovery. Tissue Eng Part 
B Rev. 2017;23(1):59-82.
---------------------------------------------------------------------------

    The applicant stated that in the U.S., approximately 500,000 burn 
injuries receive emergency medical treatment each year, leading to 
40,000 burn injury hospitalizations with 30,000 at hospital burn 
centers.420 421 The applicant noted that children and the 
elderly represent especially vulnerable populations at increased risk 
for death due to the skin loss and its complications.\422\ The 
applicant explained that in 2013, the rate of burn-related hospital 
stays was highest for infants aged younger than 1 year (29.6 per 
100,000 population) and older adults (20.7 per 100,000 population for 
adults aged 65-84 and 26.3 per 100,000 population for adults aged 85 
and older).\423\ The applicant also stated that unintentional fire or 
burn injuries was the 8th leading cause of death in those 65 years or 
older.\424\
---------------------------------------------------------------------------

    \420\ Burn Injury Fact Sheet. American Burn Association. https://ameriburn.org/wp-content/uploads/2017/12/nbawfactsheet_121417-1.pdf. Published February 2018. Accessed July 1, 2020.
    \421\ HCUPnet, Healthcare Cost and Utilization Project. Agency 
for Healthcare Research and Quality, Rockville, MD. https://hcupnet.ahrq.gov/. Accessed June 5, 2019.
    \422\ Burn Injury Fact Sheet. American Burn Association. https://ameriburn.org/wp-content/uploads/2017/12/nbawfactsheet_121417-1.pdf. Published February 2018. Accessed July 1, 2020.
    \423\ McDermott KW, Weiss AJ, Elixhauser A. Burn-Related 
Hospital Inpatient Stays and Emergency Department Visits, 2013: 
Statistical Brief #217. 2016 Dec. In: Healthcare Cost and 
Utilization Project (HCUP) Statistical Briefs [internet]. Rockville 
(MD): Agency for Healthcare Research and Quality (US); 2006 Feb. 
https://www.ncbi.nlm.nih.gov/books/NBK409513/. Accessed September 
30, 2020.
    \424\ Burn Injury Fact Sheet. American Burn Association. https://ameriburn.org/wp-content/uploads/2017/12/nbawfactsheet_121417-1.pdf. Published February 2018. Accessed July 1, 2020.
---------------------------------------------------------------------------

    The applicant explained that today, 96.7 percent of burn patients 
treated in burn centers will survive. The applicant noted that many of 
those survivors will sustain serious scarring and life-long physical 
disabilities.\425\ The applicant stated that burn injuries pose a 
significant burden to patients; they can have a considerably negative 
effect on the patient's health-related quality of life (HRQoL), which 
was estimated to be reduced by 30 percent at the time of injury and by 
9 percent in the long term.\426\ The applicant explained that although 
most functional domains affected by burn injuries recover over time, 
HRQoL scores pertaining to physical and emotional role participation, 
anxiety, depression, pain, work, and heat sensitivity remained low at 
12 months after the injury.\427\
---------------------------------------------------------------------------

    \425\ Burn Injury Fact Sheet. American Burn Association. https://ameriburn.org/wp-content/uploads/2017/12/nbawfactsheet_121417-1.pdf. Published February 2018. Accessed July 1, 2020.
    \426\ Miller T, Bhattacharya S, Zamula W, et al. Quality-of-life 
loss of people admitted to burn centers, United States. Qual Life 
Res. 2013;22(9):2293-2305.
    \427\ Spronk I, Legemate C, Oen I, van Loey N, Polinder S, van 
Baar M. Health related quality of life in adults after burn 
injuries: A systematic review. PLoS One. 2018;13(5):e0197507. 
Published 2018 May 24.
---------------------------------------------------------------------------

    The applicant explained that the standard of care for STB injuries 
is early excision and skin grafting.428 429 430 The 
applicant noted that common surgical interventions for burn injury 
include: Escharotomy, debridement, excision, and skin grafting.\431\ 
The applicant explained that these burns have been treated with 
autografts, allografts, and xenografts in the past. The applicant 
stated that autologous grafts (autografts) are used most frequently 
because of the problems of infection and rejection when using 
allografts or xenografts.\432\
---------------------------------------------------------------------------

    \428\ Bittner EA, Shank E, Woodson L, Martyn JA. Acute and 
perioperative care of the burn-injured patient. Anesthesiology. 
2015;122(2):448-464.
    \429\ Girard D, Laverdet B, Buh[eacute] V, et al. 
Biotechnological Management of Skin Burn Injuries: Challenges and 
Perspectives in Wound Healing and Sensory Recovery. Tissue Eng Part 
B Rev. 2017;23(1):59-82.
    \430\ Ibid.
    \431\ Kagan RJ, Peck MD, Ahrenholz DH, et al. Surgical 
management of the burn wound and use of skin substitutes: An expert 
panel white paper. J Burn Care Res. 2013;34(2):e60-e79.
    \432\ Shevchenko RV, James SL, James SE. A review of tissue-
engineered skin bioconstructs available for skin reconstruction. J R 
Soc Interface. 2010;7(43):229-258.
---------------------------------------------------------------------------

    The applicant explained that autografting involves surgical 
harvesting of healthy tissue from the patient (donor site) and 
transplantation of this skin to an injured site on the same 
patient.\433\ The applicant noted that autografts can be harvested as 
split thickness or full thickness. According to the applicant, split-
thickness skin grafts (STSGs), also called partial-thickness grafts, 
transfer a portion of the donor site skin, including the epidermis and 
some of the underlying dermis. The applicant also explained that this 
allows the donor site to heal from the epidermal elements left behind. 
The applicant also stated that full-thickness skin grafts (FTSGs) 
harvest the entire layer of skin as the graft; no dermal or epidermal 
elements remain at the donor site, which must be closed by local 
advancement of the adjoining skin or by a secondary local flap. The 
applicant stated that the process of revascularization takes longer for 
an FTSG than for an STSG because of the increased thickness of the 
tissue.\434\
---------------------------------------------------------------------------

    \433\ Girard D, Laverdet B, Buh[eacute] V, et al. 
Biotechnological Management of Skin Burn Injuries: Challenges and 
Perspectives in Wound Healing and Sensory Recovery. Tissue Eng Part 
B Rev. 2017;23(1):59-82.
    \434\ Leon-Villapalos J. Skin autografting. UpToDate. https://www.uptodate.com/contents/skin-autografting. Literature review 
current through September 2020. Accessed October 1, 2020.
---------------------------------------------------------------------------

    The applicant explained that early excision and skin grafting 
reduce the chance of wound infections and systemic sepsis, and have 
become the standard of care.435 436 437 The applicant noted 
that without autografting, an STB that contains some dermal elements 
usually requires greater than 3 weeks to heal, thereby increasing the 
risk for infection and other complications that may lead to the 
development of significant scarring and 
contracture.438 439 440 The applicant stated that while STBs 
require surgical debridement and grafting, superficial first-degree 
burns do not; \441\ however, in the acute phase of the burn injury,

[[Page 45081]]

the clinical presentation of the severely injured burn patient usually 
involves a range of burn depths from a superficial burn to a FT 
burn.\442\
---------------------------------------------------------------------------

    \435\ Bittner EA, Shank E, Woodson L, Martyn JA. Acute and 
perioperative care of the burn-injured patient. Anesthesiology. 
2015;122(2):448-464.
    \436\ Girard D, Laverdet B, Buh[eacute] V, et al. 
Biotechnological Management of Skin Burn Injuries: Challenges and 
Perspectives in Wound Healing and Sensory Recovery. Tissue Eng Part 
B Rev. 2017;23(1):59-82.
    \437\ Id.
    \438\ Deitch EA, Wheelahan TM, Rose MP, Clothier J, Cotter J. 
Hypertrophic burn scars: Analysis of variables. J Trauma. 
1983;23(10):895-898.
    \439\ Kagan RJ, Peck MD, Ahrenholz DH, et al. Surgical 
management of the burn wound and use of skin substitutes: An expert 
panel white paper. J Burn Care Res. 2013; 34(2):e60-79.
    \440\ Shupp JW, Nasabzadeh TJ, Rosenthal DS, Jordan MH, Fidler 
P, Jeng JC. A review of the local pathophysiologic bases of burn 
wound progression. J. Burn Care Res. 2010; 31(6):849-873.
    \441\ Bittner EA, Shank E, Woodson L, Martyn JA. Acute and 
perioperative care of the burn-injured patient. Anesthesiology. 
2015;122(2):448-464
    \442\ Ibid.
---------------------------------------------------------------------------

    The applicant explained that although autografting is effective in 
closing wounds and has been a standard treatment for decades, it has 
limitations. The applicant stated that donor sites are often associated 
with several complications, including excessive pain, pruritus, 
infection, dyschromia, hypertrophic scarring, delayed healing, and the 
potential for conversion to a FT wound.\443\ The applicant also noted 
that donor-site pain is typically more painful than that in the 
treatment (burned) site and may become chronic.444 445 In 
patients with burns of 50-60 percent TBSA, autograft is limited by 
donor-site availability.\446\ The applicant explained that donor sites 
may be re-harvested if they heal in time without infection; however, 
this practice can lead to prolonged hospitalization and decreased 
quality of the skin from re-harvested sites. The applicant stated that 
after patients undergo skin grafting, in the long term, both the 
grafted wound site and the donor site require continuous physical and 
rehabilitative therapy to maintain the range of movement, minimize scar 
and contracture development, and maximize functional ability.\447\
---------------------------------------------------------------------------

    \443\ 4 Osborne SN, Schmidt MA, Harper JR. An Automated and 
Minimally Invasive Tool for Generating Autologous Viable Epidermal 
Micrografts. Adv Skin Wound Care. 2016;29(2):57-64.
    \444\ Birchall MA, Varma S, Milward TM. The Moriarty sign: An 
appraisal. Br J Plast Surg. 1991;44(2):149-150.
    \445\ Sinha S, Schreiner AJ, Biernaskie J, et al. Treating pain 
on skin graft donor sites. J. Trauma Acute Care Surg. 2017;83(5)954-
964.
    \446\ Girard D, Laverdet B, Buh[eacute] V, et al. 
Biotechnological Management of Skin Burn Injuries: Challenges and 
Perspectives in Wound Healing and Sensory Recovery. Tissue Eng Part 
B Rev. 2017;23(1):59-82.
    \447\ Procter F. Rehabilitation of the burn patient. Indian J 
Plast Surg. 2010;43(Suppl):S101-S113.
---------------------------------------------------------------------------

    The applicant noted that autografting is especially undesirable in 
vulnerable patient populations, such as the elderly. The applicant 
stated that the healing of donor sites may be delayed or even lacking 
in elderly patients or patients whose wound-healing capabilities are 
compromised.\448\ The applicant explained that because patients in 
these populations have thinner dermis and epidermis than non-elderly 
adults,449 450 there is a higher likelihood that the donor 
sites will go deep into the dermis during harvest or transform into FT 
wounds with their anatomical characteristics. The applicant stated that 
these patients are disproportionately affected and are at increased 
risk for death due to the skin loss and its complications.\451\ The 
applicant also noted that the American College of Surgeons (ACS) 
developed guidelines to educate surgeons and other medical 
professionals about the significance of older adult burns and evidence-
based prevention activities.\452\
---------------------------------------------------------------------------

    \448\ Bradow BP, Hallock GG, Wilcock SP. Immediate Regrafting of 
the Split Thickness Skin Graft Donor Site Assists Healing. Plast 
Reconstr Surg Glob Open. 2017;5(5):e1339. Published 2017 May 23.
    \449\ King A, Balaji S, Keswani SG. Biology and function of 
fetal and pediatric skin. Facial Plast Surg Clin North Am. 
2013;21(1):1-6.
    \450\ Wainwright DJ, Bury SB. Acellular dermal matrix in the 
management of the burn patient. Aesthet Surg J. 2011;31(7 
Suppl):13S-23S.
    \451\ Greenhalgh DG. Management of the skin and soft tissue in 
the geriatric surgical patient. Surg Clin North Am. 2015;95(1):103-
114.
    \452\ Statement on Older Adult Burn Prevention. American College 
of Surgeons (ACS). https://www.facs.org/aboutacs/statements/81-older-adult-burn. Published January 1, 2018. Accessed September 26, 
2020.
---------------------------------------------------------------------------

    The applicant stated that burn injuries result in substantial 
economic burden for healthcare systems and society. The applicant noted 
the average total hospital charges for a surviving patient with burns 
was estimated to be $98,062 and a patient who did not survive burns was 
estimated at $309,546.\453\ For patients undergoing inpatient 
autografting, the applicant asserted that significant healthcare costs 
were observed during the first year, including per patient mean all-
cause healthcare costs which ranged from $155,272 to $184,805.\454\ The 
applicant explained that the primary cost driver in the first year was 
the cost incurred from the initial inpatient episode with autografting, 
accounting for 85 percent of the total costs.\455\
---------------------------------------------------------------------------

    \453\ American Burn Association. National Burn Repository 2019 
update. 2019.
    \454\ Yu TC, Zhang X, Smiell J, Zhou H, Tan R, Boing E, Tan H. 
Healthcare resource utilization, treatment patterns, and cost of 
care among patients with thermal burns and inpatient autografting in 
two large privately insured populations in the United States. Burns. 
2020;46(4):825-835.
    \455\ Ibid.
---------------------------------------------------------------------------

    The applicant stated in their application that there is currently 
no skin replacement product approved or available that leads to durable 
wound closure while eliminating the need for harvesting an 
autograft.456 457
---------------------------------------------------------------------------

    \456\ Kagan RJ, Peck MD, Ahrenholz DH, et al. Surgical 
management of the burn wound and use of skin substitutes: An expert 
panel white paper. J Burn Care Res. 2013;34(2):e60-e79.
    \457\ Carter JE, Holmes JH. The Surgical Management of Burn 
Wounds. 2016.
---------------------------------------------------------------------------

    The applicant explained that skin substitutes are a heterogeneous 
group of biologic, synthetic, or biosynthetic materials that can 
provide temporary or permanent coverage of open skin wounds. The 
applicant stated that the aim of skin substitutes is to replicate the 
properties of the normal skin,\458\ and to provide the protective 
barrier function until definitive closure of the skin.\459\ The 
applicant noted that synthetic skin substitutes need to be removed or 
undergo biodegradation or resorption so the skin can heal and 
regenerate.\460\ The applicant also stated that biological skin 
substitutes have an architecture that resembles native skin and may 
allow the construction of a more natural new dermis.\461\
---------------------------------------------------------------------------

    \458\ Shahrokhi S. Skin substitutes. UpToDate. https://www.uptodate.com/contents/skin-substitutes. Literature review 
current through August 2020.
    \459\ MacNeil S. Progress and opportunities for tissue-
engineered skin. Nature 2007;445(7130)874-880.
    \460\ Halim A, Khoo T, Shah JY. Biologic and synthetic skin 
substitutes: An overview. Indian J. Plast. Surg. 2010;43(3)23.
    \461\ Ibid. Halim A, Khoo T, Shah JY. Biologic and synthetic 
skin substitutes: An overview. Indian J. Plast. Surg. 2010;43(3)23.
---------------------------------------------------------------------------

    The applicant explained that skin substitutes are an important 
adjunct in the management of acute or chronic wounds and can be used to 
cover defects following burns or other injuries, or for reconstruction, 
such as for release of extensive severe post-burn 
contractures.462 463 The applicant also stated that Kumar's 
3-category system, as shown in the table that follows, is currently the 
most frequently used classification system in the field. However, the 
applicant notes that there is no universally accepted classification 
system that allows for simple categorization of all the products that 
are commercially available.\464\ The applicant stated that several 
biologic and biosynthetic materials are currently used as skin 
substitutes to temporarily cover wounds. The applicant provided the 
following table which, according to the applicant, classifies skin 
substitutes according to Kumar (2008) and summarizes the applicant's 
assertions regarding existing skin substitute products.
---------------------------------------------------------------------------

    \462\ Shahrokhi S. Skin substitutes. UpToDate. https://www.uptodate.com/contents/skin-substitutes. Literature review 
current through August 2020.
    \463\ Leon-Villapalos J. Skin autografting. UpToDate. https://www.uptodate.com/contents/skin-autografting. Literature review 
current through September 2020. Accessed October 1, 2020.
    \464\ Shahrokhi S. Skin substitutes. UpToDate. https://www.uptodate.com/contents/skin-substitutes. Literature review 
current through August 2020. Accessed September 25, 2020.

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[[Page 45082]]

[GRAPHIC] [TIFF OMITTED] TR13AU21.190

    The  applicant stated that StrataGraft\TM\ skin tissue is a novel 
BRSC which possesses many of the physical and biological properties of 
an ideal skin substitute, including both epidermis and dermis with a 
barrier function comparable to that of intact human skin.\466\ The 
applicant asserted that upon FDA approval, StrataGraft\TM\ skin tissue 
will be the only skin substitute for treatment of STB classified by the 
FDA as a biologic (as opposed to other available treatments that are 
medical devices) that promotes durable wound closure and regenerative 
healing, thereby reducing or eliminating the need of autologous skin 
harvesting. According to the applicant, on June 5, 2020, Mallinckrodt 
finalized the rolling submission of a Biologics License Application 
(BLA) to the FDA seeking approval to market StrataGraftTM 
skin tissue for the treatment of adult patients with STB. On June 15, 
2021, the FDA approved StratagraftTM for the treatment of 
adult patients with thermal burns containing intact dermal elements 
(remaining deep skin layers) for which surgical intervention is 
clinically indicated (also referred to as deep partial thickness 
burns). The applicant submitted a request for a unique ICD-10-PCS code 
for the use of StratagraftTM beginning FY 2022 and was 
granted approval to use the following ICD-10-PCS code effective October 
1, 2021: XHRPXF7 (Replacement of skin with bioengineered allogeneic 
construct, external approach, new technology group 7).
---------------------------------------------------------------------------

    \465\ Kumar P. Classification of skin substitutes. Burns. 
2008;34(1)148-149.
    \466\ Schurr MJ, Foster KN, Centanni JM, et al. Phase I/II 
clinical evaluation of StrataGraft: A consistent, pathogen-free 
human skin substitute. J Trauma. 2009;66(3):866-874.
---------------------------------------------------------------------------

    The applicant explained that StrataGraft\TM\ skin tissue is a 
viable BRSC that may be applied universally to patients, that is, it is 
not a patient-specific product. The applicant stated that the active 
cellular components of StrataGraft\TM\ skin tissue are the viable and 
metabolically active allogeneic human NIKS[supreg] keratinocytes and 
normal human dermal fibroblasts (NHDF).
    The applicant noted that StrataGraft\TM\ skin tissue comprises an 
epidermal layer and a dermal layer. The

[[Page 45083]]

applicant explained that the epidermal layer of StrataGraft\TM\ skin 
tissue is composed of differentiated, multilayered, viable epidermal 
keratinocytes that are adherent through normal hemidesmosomes to a 
dermal equivalent.\467\ The applicant stated that human epidermal 
keratinocytes used are NIKS[supreg] keratinocytes, a continuous and 
consistent source of well-characterized, non-tumorigenic, long-lived 
keratinocyte precursors that are derived from a single neonatal human 
foreskin donor. The applicant asserted that NIKS[supreg] keratinocytes 
have normal steady state of messenger ribonucleic acid (mRNA) and 
protein expression levels for autocrine regulators and growth factors 
such as transforming growth factor (TGF)-[alpha], TGF-[beta]1, 
epidermal growth factor, and c-myc, providing further evidence of the 
normal function of these cells.\468\ The applicant also explained that 
NIKS[supreg] keratinocytes produce normal adhesion proteins (example, 
integrins and cadherins) that permit tight adherence to each other and 
the dermal equivalent.\469\ The applicant stated that cell-cell and 
cell-substratum adhesions confer excellent handling characteristics to 
StrataGraft\TM\ skin tissue, enabling it to be meshed and secured in 
place as is routinely done with STSGs. The applicant noted that the 
dermal layer of StrataGraft\TM\ skin tissue contains NHDF derived from 
a single healthy tissue donor.
---------------------------------------------------------------------------

    \467\ Schurr MJ, Foster KN, Centanni JM, et al. Phase I/II 
clinical evaluation of StrataGraft skin tissue: A consistent, 
pathogen-free human skin substitute. J Trauma. 
2009;66(3):866[hyphen]874.
    \468\ Allen-Hoffmann BL, Schlosser SJ, Ivarie CA, Sattler CA, 
Meisner LF, O'Connor SL. Normal growth and differentiation in a 
spontaneously immortalized near-diploid human keratinocyte cell 
line, NIKS. J Invest Dermatol. 2000;114(3):444-455
    \469\ Ibid.
---------------------------------------------------------------------------

    The applicant explained that viable cells within StrataGraft\TM\ 
skin tissue express and secrete a wide variety of peptides, growth 
factors, and cytokines that are known to promote healing, thereby 
reducing or eliminating the need for autograft in the management of 
thermal burns.\470\ The applicant also stated that no currently 
available technology (competitor) for the treatment of STB is 
characterized by the autologous (endogenous) tissue regeneration of the 
burned skin.
---------------------------------------------------------------------------

    \470\ Harvestine J, Pradhan-Bhatt S, Steiglitz BM, Maher RJ, 
Comer AR, Gratz KR, Allen-Hoffmann BL. StrataGraft[supreg] Skin 
Tissue, a Bioengineered Regenerative Skin Construct for Severe Acute 
Wounds. Poster presented at: 2020 Biomedical Engineering Society 
(BMES) Virtual Annual Meeting, October 14-17, 2020.
---------------------------------------------------------------------------

    The applicant stated that the StrataGraft\TM\ skin tissue is 
manufactured through organotypic culture under aseptic conditions in 
compliance with current Good Manufacturing Practices. The applicant 
explained that in organotypic culture, NIKS[supreg] keratinocytes 
undergo tissue-appropriate differentiation and stratification to 
produce a skin tissue that exhibits many of the structural and 
biological properties of intact human skin. The applicant noted that 
the epidermal layer of StrataGraft\TM\ skin tissue exhibits typical 
production and organization of cell-type specific proteins (example, 
keratin, filaggrin, involucrin, and transglutaminase), development of a 
normal cornified envelope, and production of lipid-filled granules that 
are necessary for the generation and maintenance of robust epidermal 
barrier function similar to that found in vivo.\471\
---------------------------------------------------------------------------

    \471\ Ibid.
---------------------------------------------------------------------------

    As discussed previously, if a technology meets all three of the 
substantial similarity criteria, it would be considered substantially 
similar to an existing technology and would not be considered ``new'' 
for purposes of new technology add-on payments.
    With regard to the first criterion, whether a product uses the same 
or similar mechanism of action to achieve a therapeutic outcome, 
according to the applicant, the mechanism of action of StrataGraft\TM\ 
skin tissue in severe thermal burns is not the same or similar to an 
existing technology. The applicant states that StrataGraft\TM\ skin 
tissue will be the first and only FDA-approved biologic for the 
treatment of STB that reduces or eliminates the need of autograft and 
for which the mechanism of action is a sustained expression and 
secretion of growth factors, cytokines, and wound healing factors, 
which are anticipated to promote regenerative healing and durable wound 
closure.472 473 The applicant explains that this unique 
mechanism of action is the reason StrataGraft\TM\ skin tissue reduces 
or eliminates the need for harvest of donor site tissue.
---------------------------------------------------------------------------

    \472\ Proposed prescribing information. for Stratagraft\TM\ skin 
tissue;. Submitted to FDA, April 2020.
    \473\ Harvestine J, Pradhan-Bhatt S, Steiglitz BM, Maher RJ, 
Comer AR, Gratz KR, Allen-Hoffmann BL. StrataGraft[supreg] Skin 
Tissue, a Bioengineered Regenerative Skin Construct for Severe Acute 
Wounds. Poster presented at: 2020 Biomedical Engineering Society 
(BMES) Virtual Annual Meeting, October 14-17, 2020.
---------------------------------------------------------------------------

    With respect to the second criterion, whether a product would be 
assigned to the same MS-DRGs as existing technologies, the applicant 
indicated that the StrataGraft\TM\ skin tissue would be assigned to the 
same MS-DRGs as cases representing patients who receive standard of 
care (autograft) or existing technologies used to treat STB. The 
applicant stated that the MS-DRGs in question do not differentiate 
between patients with burns of differential severity degree, in 
different body sites, due to thermal injury or corrosion, or with 
different percent TBSA involved.\474\
---------------------------------------------------------------------------

    \474\ MDC 22 Burns. Non-Extensive Burns. In: ICD-10-CM/PCS MS-
DRG v37.2 Definitions Manual. Centers for Medicare & Medicaid 
Services. https://www.cms.gov/icd10m/version372-fullcode-cms/fullcode_cms/P0353.html. Accessed October 1, 2020.
---------------------------------------------------------------------------

    With respect to the third criterion, whether a product would be 
used to treat the same or similar type of disease and patient 
population, the applicant asserted that StrataGraft\TM\ will treat the 
same or similar type of disease but not the same or similar patient 
population when compared to existing technologies. The applicant 
claimed that StrataGraft\TM\ skin tissue will treat a burn patient 
population for whom the current standard of care and/or other available 
technologies may not be clinically feasible solutions to achieve 
durable wound closure. The applicant explains that in patients with 
burns of 50-60 percent of the TBSA, donor-site availability is 
limited.\475\ The applicant also stated that autografting is especially 
undesirable in vulnerable patient populations, such as the elderly; 
healing of donor sites may be delayed or even lacking in elderly 
patients or patients whose wound-healing capabilities are 
compromised.\476\ The applicant explained that these patients are 
disproportionately affected and are at increased risk for death due to 
the skin loss and its complications.\477\ The applicant also states 
that the label for StrataGraft\TM\ skin tissue will not be reserved for 
a patient population diagnosed with STB for whom standard-of-care 
treatment is not feasible or clinically desirable. The applicant 
asserts that this does not imply that StrataGraft\TM\ skin tissue will 
not offer a treatment option to a new patient population.
---------------------------------------------------------------------------

    \475\ Girard D, Laverdet B, Buh[eacute] V, et al. 
Biotechnological Management of Skin Burn Injuries: Challenges and 
Perspectives in Wound Healing and Sensory Recovery. Tissue Eng Part 
B Rev. 2017;23(1):59-82.
    \476\ Bradow BP, Hallock GG, Wilcock SP. Immediate Regrafting of 
the Split Thickness Skin Graft Donor Site Assists Healing. Plast 
Reconstr Surg Glob Open. 2017;5(5):e1339. Published 2017 May 23.
    \477\ Greenhalgh DG. Management of the skin and soft tissue in 
the geriatric surgical patient. Surg Clin North Am. 2015;95(1):103-
114.
---------------------------------------------------------------------------

    In the FY 2022 IPPS/LTCH PPS proposed rule (86 PR 25321 through 
25329), we noted that with respect to the first criterion, there may be 
other biologic dressings that use some combination of keratinocytes, 
collagen,

[[Page 45084]]

glycosaminoglycans (GAGs), cytokines, chemokines, and/or other growth 
factors in either a single, double, or triple layer configuration. 
While StrataGraft\TM\ may have a unique combination of these features, 
we stated that we were interested in further information on whether 
there are any dressings with a regenerative mechanism of action that 
may be approved for burns.
    With respect to the third criterion, we stated that we believed 
that StrataGraft\TM\ may treat the same or similar patient population 
as the standard of care or existing technologies to treat STB. While we 
agreed that in patients with burns of 50-60 percent of the TBSA, donor-
site availability is more limited, we observed that neither of the two 
pivotal studies included patients with burns of 50 percent or greater 
of the TBSA.\478\ We were unclear whether this suggests 
StratagraftTM is intended for treatment of patients with 
burns of less than 50 percent TBSA. We also questioned whether 
vulnerable patients, such as the elderly, are a new population as they 
are currently treated using standard of care or other technologies.
---------------------------------------------------------------------------

    \478\ Girard D, Laverdet B, Buh[eacute] V, et al. 
Biotechnological Management of Skin Burn Injuries: Challenges and 
Perspectives in Wound Healing and Sensory Recovery. Tissue Eng Part 
B Rev. 2017;23(1):59-82.
---------------------------------------------------------------------------

    We invited public comments on whether StratagraftTM is 
substantially similar to other technologies and whether 
StratagraftTM meets the newness criterion.
    Comment: The applicant submitted a public comment responding to our 
concerns. With respect to our concerns that StrataGraftTM 
may have a similar mechanism of action to other biologic dressings, the 
applicant stated that StrataGraftTM is an allogeneic 
cellularized scaffold product and the first-ever FDA-approved biologic 
(drug) product indicated for the treatment of adults with thermal burns 
containing intact dermal elements for which surgical intervention is 
clinically indicated (DPT burns). The applicant stated that 
StrataGraftTM incorporates a unique, biodegradable barrier 
layer which does not require physical removal at some point after its 
application. The applicant stated that StrataGraftTM 
supports the body's ability to heal itself by providing metabolically 
active cells that are gradually replaced by the patient's own cells, 
and releasing the cytokines and growth factors associated with the 
stimulation of healing. The applicant stated that the manner in which 
StrataGraftTM supports healing is distinct from that of 
autograft, which is reflected in the speed at which healing takes 
place--complete healing of DPT burns treated with 
StrataGraftTM may lag autografting by a few weeks.
    The applicant stated that several medical devices may be available 
to Medicare beneficiaries who are receiving treatment for burns; 
however, a device, by definition, achieves ``its primary intended 
purposes through chemical action within or on the body of man or other 
animals and which is not dependent upon being metabolized for the 
achievement of its primary intended purposes''. The applicant stated 
that such devices are so classified as they are all products in some 
way supplemented with cells (the active ingredient). The applicant 
stated that in contrast, StrataGraft is a biologic drug product, its 
own active ingredient, and a functional unit at the time of delivery 
whose functions are to (i) secrete growth factors and cytokines by the 
viable cells of the mature tissue to facilitate wound repair and 
regenerative healing; and (ii) protect the wound bed by serving as a 
natural protective epidermal barrier. The applicant noted that the 
actions of the various constituents of StrataGraft are synergic and 
cannot be separated. The applicant stated that input collagen is a 
structural component that provides a biologically relevant environment 
which enables cellular maturation and paracrine signaling between the 
NIKS keratinocytes and human dermal fibroblasts (NHDF) during 
manufacture, resulting in epidermal differentiation and dermal 
compartment organization with endogenous synthesis of human 
extracellular matrix (ECM) proteins. The applicant stated that since 
StrataGraft is both (i) its own active ingredient and (ii) unique, its 
mechanism of action cannot be the same or similar to that of any 
existing technology. The applicant noted that StrataGraft does not 
share an active ingredient with any other product--the FDA established 
a whole new active ingredient descriptor for StrataGraft as part of its 
assignment of the Unique Ingredient Identifier (UNII) code.
    The applicant noted that StrataGraft supports the body's ability to 
heal itself by (i) providing metabolically active cells that are 
gradually replaced by the patient's own cells, and (ii) releasing the 
cytokines and growth factors associated with the stimulation of 
healing. The applicant stated that cells incorporated into StrataGraft 
are sourced from the NIKS keratinocyte cell line--a proprietary, 
single-source, karyotypically stable, nontumorigenic, and pathogen-free 
human keratinocyte progenitor that provides a stable, source of donor 
tissue. The applicant asserted that NIKS is not present in any other 
technology available to Medicare beneficiaries for the treatment of 
burns or any other type of wounds. The applicant stated that this 
newness is reflected in the FDA's designation of StrataGraft as a 
regenerative medicine advanced therapy (RMAT)--the only RMAT-designated 
product for the treatment of burns; a drug is eligible for RMAT 
designation if it is a ``regenerative medicine therapy''.
    The applicant stated that StrataGraftTM incorporates a 
unique, biodegradable allogenic cellularized scaffold comprised of a 
purified murine Type I collagen matrix embedded with fibroblasts that 
is not present in any medical device, and is eventually replaced by the 
patient's own tissue. The applicant noted that a second procedure to 
remove StrataGraftTM is not required.
    In response to our concern regarding the applicability of 
StrataGraftTM to a new patient population of >50% TBSA 
burns, the applicant stated that although StrataGraftTM was 
not studied in patients with more than 50% total body surface area 
(TBSA) burns in STRATA2011 or STRATA2016, this was due to the 
intrapatient comparator trial design and is not a limitation of the 
product. The applicant also noted that separate from the STRATA2011 and 
STRATA2016 clinical trials, StrataGraftTM was used to treat 
four adult patients as part of the FDA Single Patient Expanded Access 
Program (EAP). The applicant stated that two of these patients had 
burns >50% TBSA and one had a major burn (40% TBSA). The applicant 
stated that two out of three patients had successful wound closure, and 
one patient died three weeks post-surgery for reasons unrelated to 
StrataGraftTM treatment. The applicant noted that one 
additional request was received for a 74-year-old male with 65% TBSA 
flame burn with inhalation injury, but this patient became unstable and 
succumbed to his injuries prior to excision and grafting of his burn 
wounds.
    In response to our concern regarding StrataGraftTM 
treating a new subpopulation, the elderly, the applicant reiterated the 
undesirability of treating elderly patients with the current standard 
of care--autograft--primarily due to co-morbidities or decreased skin 
thickness. The applicant also highlighted that diabetic patients may 
have impaired wound healing, making the harvest of an autograft 
particularly undesirable. The applicant stated that elderly patients 
have thinner dermis and epidermis than do non-elderly adults, and their 
skin is prone to tears and bruising, which complicates donor

[[Page 45085]]

autograft harvesting. The applicant stated that 
StrataGraftTM is the only skin substitute product FDA-
approved for DPT thermal burns of any TBSA that does not require donor 
skin harvest and/or subsequent autografts. The applicant asserted that 
other technologies, such as Integra, Epicel, and RECELL all require 
some degree of skin harvest. The applicant stated that the need for 
new, autograft-sparing treatments in this patient population is 
reflected in the FDA's decision to allow StrataGraft to be used as part 
of the EAP, which the FDA characterizes as a potential pathway for a 
patient with an immediately life-threatening condition or serious 
disease or condition to gain access to an investigational medical 
product (drug, biologic, or medical device) for treatment outside of 
clinical trials when no comparable or satisfactory alternative therapy 
options are available.
    The applicant noted that because StrataGraftTM does not 
have to be removed, there is no potential for skin injury similar to 
that potentially experienced during removal of other products. The 
applicant stated that the directions for use for Epicel note that its 
backing layer must be removed after the procedure seven to ten days 
after grafting with extreme care to prevent damage to the graft. The 
applicant noted that directions for use for RECELL caution providers to 
use extreme care when removing dressings to ensure that it is 
atraumatic. Additionally, the applicant notes that Integra incorporates 
a silicone layer that must be removed about twenty-one days after 
application, and prior to autografting, in a separate procedure.
    Several commenters asserted that StrataGraftTM will be 
the only DPT burn treatment that is an FDA-approved biologic (drug) 
product capable of achieving durable wound closure by 3 months similar 
to autograft, while eliminating autograft harvest in 96% of patients; 
is in receipt of Regenerative Medicine Advanced Therapy (RMAT) 
designation; and is characterized by a mechanism of action which 
leverages the regenerative capacity of the patient's skin. Several 
commenters also asserted that prior to the approval of 
StrataGraftTM, the only FDA-approved skin substitutes were 
medical devices that required either initial donor harvest (for 
example, Epicel[supreg] and RECELL[supreg]) or a subsequent autograft 
(for example, Integra[supreg]) for promoting wound closure.
    Response: We appreciate the commenters' input on the newness of 
StrataGraftTM and the additional information from the 
applicant in regard to the newness criterion. We agree that 
StrataGraftTM utilizes a unique mechanism of action among 
FDA approved treatments for DPT burns because it is a regenerative 
technology that allows growth of the patient's own tissue until it is 
completely replaced, while functioning as a protective barrier. We 
believe this is different than autografting and other burn treatments 
that require skin harvest and become incorporated, with the skin 
healing around it. We thank the applicant for providing examples of 
patients with burns of 50% or more TBSA treated with 
StrataGraftTM though these patients were excluded from the 
clinical trials. However, we note that this patient population is not 
excluded from the standard of care or other technologies, such as 
Epicel, which is indicated for use in patients with burns of 30% or 
greater TBSA. Further, we note that we do not consider the elderly a 
new patient population in regard to the use of StrataGraftTM 
as they are currently not excluded from the standard of care or other 
technologies. Therefore, we believe that StrataGraftTM 
treats the same or similar patient population as existing technologies.
    After consideration of the public comments we received and 
information submitted by the applicant as part of its FY 2022 new 
technology add-on payment application for StrataGraftTM, we 
agree with the applicant and commenters that StrataGraftTM 
has a unique mechanism of action. Therefore, we believe that 
StrataGraftTM is not substantially similar to existing 
treatment options and meets the newness criterion. We consider the 
newness period to begin on June 15, 2021 when StrataGraft\TM\ was 
approved by the FDA.
    With regard to the cost criterion, the applicant stated in their 
application that StrataGraftTM skin tissue is seeking FDA 
approval for the proposed indication of treatment of adult patients 
with STBs that contain intact dermal elements and require surgical 
intervention. In order to identify the range of MS-DRGs that eligible 
patients may map to, the applicant conducted a claims search for cases 
that include ICD-10-CM codes for thermal burns of second, third degree, 
or those classified according to TSBA to identify cases eligible for 
use of StrataGraftTM skin tissue utilization. The applicant 
identified cases reporting ICD-10-CM codes for diagnoses of second-
degree thermal burns, any location (T20.2XXX to T25.2XXX); third-degree 
thermal burns, any location (T20.3XXX to T25.3XXX); and thermal burns 
classified according to extent of body surface involved (T31.XX).
    The applicant used the FY 2019 MedPAR Hospital LDS with the FY 2022 
thresholds, and the FY 2019 IPPS/LTCH Final Rule Impact File and 
Standardizing File. The applicant's claim search in the aggregate 
identified 58,624 cases mapping to 21 MS-DRGs as listed in the 
following table. Of the total 21 MS-DRGs, only six had case volume 
greater than or equal to one percent across all cohorts and 
cumulatively represent 97.54 percent of cases. In cases where MS-DRGs 
had fewer than 11 discharges, the applicant imputed a minimum value of 
11 cases for each MS-DRG.

[[Page 45086]]

[GRAPHIC] [TIFF OMITTED] TR13AU21.191

    To demonstrate that the technology meets the cost criterion, the 
applicant first identified four separate patient cohorts: Cohort (1) 
Patients with thermal burns of second or third degree in any body area, 
or thermal burns classified according to TBSA, who received autograft 
for reasons only related to thermal burns (n=14,774, MS-DRGs=21); 
Cohort (2) Patients with thermal burns of second or third degree in any 
body area, or thermal burns classified according to TBSA, who received 
autograft for reasons only related to thermal burns, and who underwent 
excisional debridement in the inpatient setting (n=13,640, MS-DRGs=20); 
Cohort (3) Patients with thermal burns of second or third degree in any 
body area, or thermal burns classified according to TBSA, who received 
autograft for thermal burns, with or without other conditions 
(n=15,744, MS-DRGs=21); and Cohort (4) Patients with thermal burns of 
second or third degree in any body area, or thermal burns classified 
according to TBSA, who received autograft for thermal burns, with or 
without other conditions, and who underwent excisional debridement in 
the inpatient setting (n=14,466, MS-DRGs=20). The applicant then 
identified eight analyses for the cost criterion: (1) Calculations for 
Cohort one (all MS-DRGs); (2) Calculations for cohort two (all MS-
DRGs); (3) Calculations for Cohort three (all MS-DRGs); (4) 
Calculations for cohort four (all MS-DRGs); (5) Calculations for Cohort 
one (top 4 MS-DRGs by case volume); (6) Calculations for Cohort two 
(top 4 MS-DRGs by case volume); (7) Calculations for Cohort three (top 
4 MS-DRGs by case volume);

[[Page 45087]]

and (8) Calculations for Cohort 4 (top 4 MS-DRGs by case volume).
    The applicant determined an average unstandardized case weighted 
charge per case of $173,650 for analysis one, $168,282 for analysis 
two, $178,530 for analysis three, $172,277 for analysis four, $158,851 
for analysis five, $155,700 for analysis six, $162,377 for analysis 
seven, and $158,452 for analysis eight.
    The applicant stated that charges for and related to the prior 
technologies were not removed from the cost analysis.
    After calculating the average standardized charge per case for all 
scenarios, the applicant calculated the standardized charge per case 
for each MS-DRG. Next, the applicant applied the 2-year inflation 
factor used in the FY 2021 IPPS/LTCH PPS final rule to calculate 
outlier threshold charges of 13.2 percent (1.13218). The applicant 
stated that the price for StratagraftTM skin tissue has not 
yet been established and therefore it did not add charges for the 
technology. Lastly, the applicant calculated the final average inflated 
standardized charge per case and the inflated case weighted 
standardized charge per case for each scenario.
    The applicant stated that, for analysis one, the final inflated 
average case-weighted standardized charge per case of $304,347 exceeded 
the average case-weighted threshold amount of $173,650 by $130,697. For 
analysis two, the final inflated average case-weighted standardized 
charge per case of $279,373 exceeded the average case-weighted 
threshold amount of $168,282 by $111,091. For analysis three, the final 
inflated average case-weighted standardized charge per case of $332,006 
exceeded the average case-weighted threshold amount of $178,530 by 
$153,477. For analysis four, the final inflated average case-weighted 
standardized charge per case of $299,228 exceeded the average case-
weighted threshold amount of $172,277 by $126,951. For analysis five, 
the final inflated average case-weighted standardized charge per case 
of $241,186 exceeded the average case-weighted threshold amount of 
$158,851 by $82,336. For analysis six, the final inflated average case-
weighted standardized charge per case of $229,661 exceeded the average 
case-weighted threshold amount of $155,700 by $73,961. For analysis 
seven, the final inflated average case-weighted standardized charge per 
case of $257,800 exceeded the average case-weighted threshold amount of 
$162,377 by $95,423. For analysis eight, the final inflated average 
case-weighted standardized charge per case of $244,042 exceeded the 
average case-weighted threshold amount of $158,452 by $85,590.
    The applicant stated that because the final inflated average case-
weighted standardized charge per case exceeded the average case-
weighted threshold amount, StratagraftTM meets the cost 
criterion.
    We invited public comment on whether StrataGraftTM meets 
the cost criterion.
    Comment: A commenter, the applicant, maintained that 
StrataGraftTM meets the cost criterion because, across 
several cost analysis scenarios, the final inflated average case-
weighted standardized charge per case exceeded the average case-
weighted threshold amount.
    Response: We appreciate the applicant's response. Based on the 
applicant's cost analysis as previously summarized and consideration of 
the comment received, we agree that the average case-weighted 
standardized charge per case exceeds the average case-weighted 
threshold amount. Therefore, StrataGraftTM meets the cost 
criterion.
    With respect to the substantial clinical improvement criterion, the 
applicant asserted that StrataGraft\TM\ skin tissue is a substantial 
clinical improvement over existing technology for the treatment of 
adult patients with severe thermal burns with intact dermal elements 
because it achieves a significant rate of durable wound closure for 
patients with severe burns while minimizing or eliminating the 
complications associated with autograft harvest.
    According to the applicant, the totality of the circumstances 
otherwise demonstrates that StrataGraft\TM\ skin tissue, relative to 
technologies previously available, substantially improves the treatment 
of STB patients including Medicare beneficiaries. The applicant stated 
that because the benefits associated with its use are not accompanied 
by an increased incidence of adverse events as compared to autograft, 
StrataGraft\TM\ skin tissue is a substantial clinical improvement. The 
applicant explained that by significantly reducing or eliminating the 
harvest of donor sites, patients who receive StrataGraft\TM\ skin 
tissue are spared short- and long-term sequelae and complications and, 
to a lesser extent, infection or conversion to a full-thickness wound 
of the donor sites.\479\ The applicant stated that by significantly 
reducing or eliminating the need for autograft,\480\ StrataGraft\TM\ 
skin tissue is especially relevant for the elderly population where 
autograft is undesirable; these patients are disproportionately 
affected and are at increased risk for death due to the skin loss and 
its complications.\481\ The applicant explained that aging and 
environmental factors can influence the severity of burns in vulnerable 
skin.482 483 The applicant stated that geriatric skin also 
exhibits slower wound healing and is at increased risk of excessive 
scarring.484 485 486 487 488 According to the applicant, 
age-related changes in wound healing capacity can include delayed 
infiltration of immune cells, decreased secretion of growth factors, 
and altered collagen remodeling.\489\
---------------------------------------------------------------------------

    \479\ Greenhalgh DG. Management of the skin and soft tissue in 
the geriatric surgical patient. Surg Clin North Am. 2015;95(1):103-
114.
    \480\ Holmes JH, Shupp JW, Smith DJ, et al. T5: Preliminary 
analysis of a phase 3 open-label, controlled, randomized trial 
evaluating the efficacy and safety of a bioengineered regenerative 
skin construct in patients with deep partialthickness thermal burns. 
J. Burn Care Res. 2020;41(Supplement_1)S3-S4.
    \481\ Greenhalgh DG. Management of the skin and soft tissue in 
the geriatric surgical patient. Surg Clin North Am. 2015;95(1):103-
114.
    \482\ Gosain A, DiPietro LA. Aging and wound healing. World J 
Surg. 2004;28(3):321-326.
    \483\ Landau M. Exogenous factors in skin aging. Curr Probl 
Dermatol. 2007;35:1-13.
    \484\ Greenhalgh DG. Management of the skin and soft tissue in 
the geriatric surgical patient. Surg Clin North Am. 2015;95(1):103-
114.
    \485\ Gosain A, DiPietro LA. Aging and wound healing. World J 
Surg. 2004;28(3):321-326.
    \486\ Greenhalgh DG. Management of the skin and soft tissue in 
the geriatric surgical patient. Surg Clin North Am. 2015;95(1):103-
114.
    \487\ Ibid.
    \488\ Gosain A, DiPietro LA. Aging and wound healing. World J 
Surg. 2004;28(3):321-326.
    \489\ Ibid.
---------------------------------------------------------------------------

    The applicant further explained that use of StrataGraft\TM\ skin 
tissue can preserve limited donor sites for the treatment of other 
wounds, such as areas of FT injury and wounds in cosmetically sensitive 
areas. The applicant noted that it may also reduce the need for 
repeated harvest of autograft donor sites, potentially reducing the 
number of surgical procedures and total length of time to wound 
closure. The applicant explained that burn injury is associated with a 
high prevalence of posttraumatic stress disorder, ranging between 11 
percent and 50 percent across studies,\490\ and may also lead to 
anxiety and depression due to scarring and body image concerns.\491\ 
Lastly, the applicant stated

[[Page 45088]]

that use of StrataGraft\TM\ skin tissue reduces pain while offering a 
comparable scar quality to autograft.\492\
---------------------------------------------------------------------------

    \490\ Summer G J, Puntillo KA, Miaskowski C, et al. Burn Injury 
Pain: The Continuing Challenge. J. Pain 2007;8(7)533-548.
    \491\ Calot[abreve] DR, Ni[tcedil]escu C, Marinescu S, et al. 
Correlations between morphological appearance and psychosocial 
difficulties in patients with extensive burns who received 
allotransplant. Rom J Morphol Embryol. 2012;53(3 Suppl):703-711.
    \492\ Holmes JH, Shupp JW, Smith DJ, et al. T5: Preliminary 
analysis of a phase 3 open-label, controlled, randomized trial 
evaluating the efficacy and safety of a bioengineered regenerative 
skin construct in patients with deep partialthickness thermal burns. 
J. Burn Care Res. 2020;41(Supplement_1)S3-S4.
---------------------------------------------------------------------------

    The applicant provided two controlled and randomized studies, 
STRATA2011 and STRATA2016, to support its claims of substantial 
clinical improvement. The applicant stated that with the exception of 
subject age (STRATA2011, 18 to 64 years of age; STRATA2016, >=18 years 
of age), the inclusion and exclusion criteria for the two studies were 
similar. According to the applicant, the STRATA2016 study 
(NCT03005106--Phase 3 trial--71 patients) 493 494 was a 12-
month, open-label, multicenter, controlled, randomized study that 
evaluated the efficacy and safety of StrataGraft\TM\ skin tissue in 
promoting autologous skin tissue regeneration of severe thermal burns. 
The applicant explained that the STRATA2011 study (NCT01437852--Phase 
1b trial--30 patients) 495 496 was a 12-month, open-label, 
multicenter, controlled, randomized, dose-escalation study that 
evaluated the safety, tolerability, and efficacy of StrataGraft\TM\ 
skin tissue in promoting the healing of the STB component of complex 
skin defects due to thermal injury as an alternative to autografting. 
The applicant noted that, in both studies, eligible subjects had 3 
percent to 49 percent TBSA burns with two comparable treatment sites 
that were prospectively identified, and the sites were randomized to 
receive either a single topical application of StrataGraft\TM\ skin 
tissue or autograft, such that each subject received both treatments. 
The applicant noted that in this intrapatient comparator design, the 
area that was autografted served as a subject's own paired control.
---------------------------------------------------------------------------

    \493\ StrataGraft skin tissue[supreg] Skin Tissue in the 
Promotion of Autologous Skin Regeneration of Complex Skin Defects 
Due to Thermal Burns That Contain Intact Dermal Elements. 
ClinicalTrials.gov. https://clinicaltrials.gov/ct2/show/NCT03005106. 
Accessed June 15, 2020.
    \494\ Holmes JH, Shupp JW, Smith DJ, et al. T5: Preliminary 
analysis of a phase 3 open-label, controlled, randomized trial 
evaluating the efficacy and safety of a bioengineered regenerative 
skin construct in patients with deep partialthickness thermal burns. 
J. Burn Care Res. 2020;41(Supplement_1)S3-S4.
    \495\ StrataGraft skin tissue[supreg] Skin Tissue as an 
Alternative to Autografting Deep Partial-Thickness Burns. 
ClinicalTrials.gov. https://clinicaltrials.gov/ct2/show/NCT01437852. 
Accessed June 15, 2020.
    \496\ Holmes JH, Schurr MJ, King BT, et al. An open-label, 
prospective, randomized, controlled, multicenter, phase 1b study of 
StrataGraft skin tissue versus autografting in patients with deep 
partial-thickness thermal burns. Burns 2019;45(8)1749-1758.
---------------------------------------------------------------------------

    To support the claim that the use of StrataGraft\TM\ skin tissue 
significantly reduces the percent area of the treatment sites 
autografted, the applicant explained that the STRATA2016 study showed 
the average percent area of the StrataGraft\TM\ skin tissue treatment 
site autografted by Month 3 was lower than the average percent area of 
the autograft control treatment site autografted by Month 3 (mean 
difference: 97.77 percent; P < 0.0001).\497\ We note that the applicant 
did not provide detailed information regarding the measurement 
methodology.
---------------------------------------------------------------------------

    \497\ Holmes JH, Shupp JW, Smith DJ, et al. T5: Preliminary 
analysis of a phase 3 open-label, controlled, randomized trial 
evaluating the efficacy and safety of a bioengineered regenerative 
skin construct in patients with deep partialthickness thermal burns. 
J. Burn Care Res. 2020;41(Supplement_1)S3-S4.
---------------------------------------------------------------------------

    To support the claim that StrataGraft\TM\ skin tissue is effective 
in achieving durable wound closure similar to that of autografting, the 
applicant states that the STRATA2016 study showed that the majority of 
subjects (59 of 71 subjects, or 83.1 percent, with a 95 percent CI of 
74.4 to 91.8) achieved durable wound closure of the StrataGraft\TM\ 
skin tissue-treated site at Month 3 without the need for autograft 
harvest and placement.\498\ The applicant also explained that the 
STRATA2011 study showed that no StrataGraft\TM\ treatment sites 
required autografting by Day 28. The applicant noted that at Month 3 in 
the STRATA2016 study, 93.1 percent of StrataGraft\TM\ treatment sites 
were assessed as closed. The applicant stated that all StrataGraft\TM\ 
skin tissue-treated areas evaluated at 6 months and 12 months remained 
closed. The applicant noted that, when comparing these results to that 
of autografting, the proportion of wounds that achieved closure was not 
statistically different.\499\
---------------------------------------------------------------------------

    \498\ Ibid.
    \499\ Holmes JH, Schurr MJ, King BT, et al. An open-label, 
prospective, randomized, controlled, multicenter, phase 1b study of 
StrataGraft skin tissue versus autografting in patients with deep 
partial-thickness thermal burns. Burns 2019;45(8)1749-1758.
---------------------------------------------------------------------------

    To support the claim of reduction in donor site pain using 
StrataGraft, the applicant stated that the STRATA2016 study showed that 
the difference between the donor sites preserved for StrataGraft\TM\ 
skin tissue treatment site failure and autograft donor sites in the 
average pain intensity through Day 14 based on the Wong-Baker 
FACES[supreg] Pain Rating Scale (FPRS) \500\ was 2.40  
1.313 (P <0.0001), indicating significantly less mean donor-site pain 
intensity in the reserved StrataGraft\TM\ skin tissue donor sites 
compared with autograft donor sites.\501\ The applicant also stated 
that the STRATA2011 study showed that patients experienced pain at 
harvested donor sites used for autograft, but minimal pain at 
unharvested donor sites that had been set aside for potential use with 
StrataGraft\TM\ skin tissue.\502\
---------------------------------------------------------------------------

    \500\ Wong-Baker FACES Foundation. https://wongbakerfaces.org/. 
Accessed July 1, 2020.
    \501\ Holmes JH, Shupp JW, Smith DJ, et al. T5: Preliminary 
analysis of a phase 3 open-label, controlled, randomized trial 
evaluating the efficacy and safety of a bioengineered regenerative 
skin construct in patients with deep partialthickness thermal burns. 
J. Burn Care Res. 2020;41(Supplement_1)S3-S4.
    \502\ Holmes JH, Schurr MJ, King BT, et al. An open-label, 
prospective, randomized, controlled, multicenter, phase 1b study of 
StrataGraft skin tissue versus autografting in patients with deep 
partial-thickness thermal burns. Burns 2019;45(8)1749-1758.
---------------------------------------------------------------------------

    According to the applicant, the elimination of autografting leads 
to superior scar quality outcome of the presumptive StrataGraft\TM\ 
skin tissue donor site (that is lack of scarring in the donor sites 
reserved for StrataGraft\TM\ treatment site failure), which is a 
substantial clinical improvement. The applicant explained that the 
STRATA2016 study showed that the evaluation of scarring using the 
Patient and Observer Scar Assessment Scale (POSAS) 503 504 
observer total scores demonstrated a significant difference in scar 
quality between the StrataGraft\TM\ skin tissue and autograft donor 
sites at Month 3, 10.0  7.92 (P <0.0001), favoring 
StrataGraft\TM\ skin tissue.\505\ The applicant stated that the 
STRATA2016 study showed scores for every POSAS category were lower for 
StrataGraft\TM\ skin tissue donor sites when compared with autograft 
donor sites, indicating they were more like normal skin (that is, the 
patient's tissue in the donor sites reserved for StrataGraft\TM\ 
failure were more like normal skin than tissue present in autograft 
donor sites that were harvested).\506\ The applicant explained that the 
STRATA2011 study showed

[[Page 45089]]

that observer POSAS total scores from the StrataGraft\TM\ tissue 
treatment site and autograft were not significantly different 
throughout the study.\507\ The applicant stated that the STRATA2011 
showed that mean overall POSAS opinion scores of observers or patients 
decreased (that is, became more favorable) from Month 3 through Month 
12 after application for both the StrataGraft\TM\ tissue and 
autograft.\508\According to the applicant, although direct comparisons 
between StrataGraft\TM\ skin tissue and other skin substitutes cannot 
be drawn, StrataGraft\TM\ skin tissue, relative to device technologies 
previously available, improves the clinical outcomes of STB patients. 
The applicant stated that most skin substitutes do not claim to promote 
wound closure without the need for subsequent autograft because they 
have not been studied in this context,\509\ while clinical studies for 
StrataGraft\TM\ skin tissue assessed wound closure as a pre-specified 
endpoint.510 511 The applicant further stated that 
reparative healing mechanisms, used by most available skin substitutes, 
are more likely to result in scarring when compared with regenerative 
healing mechanisms used by StrataGraftTM.\512\
---------------------------------------------------------------------------

    \503\ Van de Kar AL, Corion LUM, Smeulders MJC, et al. Reliable 
and Feasible Evaluation of Linear Scars by the Patient and Observer 
Scar Assessment Scale. Plast. Reconstr. Surg. 2005;116(2)514-522.
    \504\ The Patient and Observer Scar Assessment Scale (POSAS). 
https://www.posas.nl/. Accessed July 1, 2020.
    \505\ Holmes JH, Shupp JW, Smith DJ, et al. T5: Preliminary 
analysis of a phase 3 open-label, controlled, randomized trial 
evaluating the efficacy and safety of a bioengineered regenerative 
skin construct in patients with deep partialthickness thermal burns. 
J. Burn Care Res. 2020;41(Supplement_1)S3-S4.
    \506\ Ibid.
    \507\ Holmes JH, Schurr MJ, King BT, et al. An open-label, 
prospective, randomized, controlled, multicenter, phase 1b study of 
StrataGraft skin tissue versus autografting in patients with deep 
partial-thickness thermal burns. Burns 2019;45(8)1749-1758.
    \508\ Ibid.
    \509\ Stone Ii R, Natesan S, Kowalczewski CJ, et al. 
Advancements in Regenerative Strategies Through the Continuum of 
Burn Care. Front Pharmacol. 2018;9:672. Published 2018 Jul 9.
    \510\ Holmes JH, Schurr MJ, King BT, et al. An open-label, 
prospective, randomized, controlled, multicenter, phase 1b study of 
StrataGraft skin tissue versus autografting in patients with deep 
partial-thickness thermal burns. Burns 2019;45(8)1749-1758.
    \511\ Holmes JH, Shupp JW, Smith DJ, et al. T5: Preliminary 
analysis of a phase 3 open-label, controlled, randomized trial 
evaluating the efficacy and safety of a bioengineered regenerative 
skin construct in patients with deep partialthickness thermal burns. 
J. Burn Care Res. 2020;41(Supplement_1)S3-S4.
    \512\ Hu MS, Maan ZN, Wu JC, et al. Tissue engineering and 
regenerative repair in wound healing. Ann Biomed Eng. 
2014;42(7):1494-1507.
---------------------------------------------------------------------------

    In the proposed rule (86 FR 25329), after reviewing the information 
provided by the applicant with regard to the substantial clinical 
improvement criterion, we noted a lack of study data provided comparing 
StrataGraft\TM\ to other biologic dressings and stated that we were 
interested in further information related to whether there are any 
dressings that may be approved for burns that demonstrate durable wound 
closure. The applicant provided published results of one randomized 
trial (STRATA2011), but we questioned whether the sample size of 30 is 
adequately generalizable to the larger Medicare population. In 
addition, we noted that the STRATA2016 study has not been published and 
the results of this study were not submitted in full, and we therefore 
may not have the complete outcomes and study results for these 
additional patients. We further noted that in the studies provided, 
patients with 50 percent or greater TBSA burns were excluded. The 
applicant indicated that the product could be especially meaningful for 
patients with burns of 50-60 percent TBSA, but we questioned whether we 
can fully evaluate this claim because these patients were not assessed.
    We invited public comments on whether StrataGraftTM 
meets the substantial clinical improvement criterion.
    Comment: In its comment, the applicant stated that, subsequent to 
publication of the FY 2022 proposed rule, the full results of the 
STRATA2016 trial were published. The applicant provided a copy of the 
study in full. Seventy-one adult patients aged 19 to 79 who sustained 
3% to 37% TBSA thermal burns on the torso, arms, or legs were enrolled 
in the phase 3 clinical trial. In each patient, two DPT areas of 
comparable depth were randomized to either StrataGraftTM or 
autograft. The study results indicated that the safety profiles, 
cosmesis, and durable wound closure of autograft and 
StrataGraftTM are similar, but StrataGraftTM is 
associated with a significant reduction in donor site harvesting. 
StrataGraftTM eliminated the need for autograft donor site 
harvesting in 96% of cases. Since StrataGraftTM eliminates 
the need for harvesting a donor site in most patients, typical donor 
site sequelae such as pain and scarring were also reduced.
    In response to our concern regarding autograft as the only study 
comparator, the applicant noted that StrataGraftTM is the 
only product to have demonstrated not just durable wound closure, but 
autograft-sparing durable wound closure in clinical trials, and that is 
FDA- approved for the treatment of DPT burns in adults. The applicant 
noted that when treating DPT burns, durable wound closure is just one 
treatment goal. Other treatment goals include mitigating sequelae such 
as scarring, scar-complications, and infections; autografts are a major 
source of these sequelae.
    In response to our question about the generalizability of the 
sample size, the applicant provided the STRATA2016 \513\ study with an 
additional 71 patients. The applicant also noted that the percentage of 
patients >65 years old is in line with clinical trial composition of 
other products that have previously received new technology add-on 
payments.
---------------------------------------------------------------------------

    \513\ Gibson ALF, Holmes JH 4th, Shupp JW, Smith D, Joe V, 
Carson J, Litt J, Kahn S, Short T, Cancio L, Rizzo J, Carter JE, 
Foster K, Lokuta MA, Comer AR, Smiell JM, Allen-Hoffmann BL. A phase 
3, open-label, controlled, randomized, multicenter trial evaluating 
the efficacy and safety of StrataGraft[supreg] construct in patients 
with deep partial-thickness thermal burns. Burns. 2021 Apr 23:S0305-
4179(21)00110-8. doi: 10.1016/j.burns.2021.04.021. Epub ahead of 
print. PMID: 34099322.
---------------------------------------------------------------------------

    Several commenters stated that StrataGraft\TM\ reduces donor site 
pain and scarring, and achieves clinically similar cosmesis to 
autograft at the treatment site in a single procedure. Several 
commenters also noted that StrataGraft\TM\ has the potential to reduce 
repeated hospitalizations by limiting or even eliminating sequelae 
associated with donor site morbidities. Several commenters stated that 
autografting is especially undesirable in elderly patient populations 
because of compromised wound healing, comorbidities, and risk of 
complications. The commenters asserted that these patients also have a 
thinner dermis and epidermis compared to younger adults.
    Response: We thank the commenters for their input and have taken 
these comments into consideration. We also thank the applicant for its 
comment as well as the provision of the newly published study and 
additional information. After review of the information provided, we 
agree with the applicant and commenters that StrataGraftTM 
demonstrates substantial clinical improvement by facilitating durable 
wound closure without the need for skin harvest and/or autograft. 
Because StrataGraftTM does not any require any skin harvest, 
it also reduces the necessity for additional healing sites, as well as 
the additional scarring and pain that come along with it. For this 
reason, we believe it offers a valuable treatment option for patients 
at risk for poor wound healing and complications.
    After consideration of the public comments we received and the 
information included in the applicant's new technology add-on payment 
application, we have determined that StrataGraftTM meets the 
criteria for approval of the new technology add-on payment. Therefore, 
we are approving new technology add-on payments for this technology for 
FY 2022.

[[Page 45090]]

    Cases involving the use of StrataGraftTM that are 
eligible for new technology add-on payments will be identified by ICD-
10- PCS procedure code XHRPXF7 (Replacement of skin with bioengineered 
allogeneic construct, external approach, new technology group 7). The 
applicant stated that the cost per sheet of StrataGraftTM is 
$4,000. According to the applicant, the per-patient utilization for 
StrataGraftTM is based on a 10 percent burn of a 1700cm\2\ 
body surface area skin burn: 17000 cm\2\ (average adult body surface 
area) x 10% = 1700 cm\2\ burned body area. This translates to an 
average of 17 sheets needed per patient case involving the use of 
StrataGraftTM (1700 cm\2\ burned body area/100 cm\2\ 
StrataGraft skin tissue sheet = 17 sheets). The applicant noted that 
the number of sheets needed may vary from one patient to the next, 
based on the size of the burn injury and therefore size of the 
StrataGraft-treated area.
    The applicant estimated that the average cost of 
StrataGraftTM to the hospital is $6,800 (17 sheets x $4000 
per sheet). Under Sec.  412.88(a)(2), we limit new technology add-on 
payments to the lesser of 65 percent of the costs of the new medical 
service or technology, or 65 percent of the amount by which the costs 
of the case exceed the MS-DRG payment. As a result, the maximum new 
technology add-on payment for a case involving the use of 
StrataGraftTM is $44,200 for FY 2022.
n. TECARTUS[supreg] (brexucabtagene autoleucel)
    Kite Pharma submitted an application for new technology add-on 
payment for FY 2022 for TECARTUS[supreg] (brexucabtagene autoleucel). 
TECARTUS[supreg] is a CD19 directed genetically modified autologous T-
cell immunotherapy for the treatment of adult patients with relapsed 
and refractory (r/r) mantle cell lymphoma (MCL). We noted that Kite 
Pharma previously submitted an application for new technology add-on 
payments for TECARTUS[supreg] for FY 2021, as summarized in the FY 2021 
IPPS/LTCH PPS proposed rule, under the name KTE-X19 (85 FR 32634).
    TECARTUS[supreg] is a form of chimeric antigen receptor (CAR) T-
cell immunotherapy that modifies the patient's own T-cells to target 
and eliminate tumor cells. More specifically, according to the 
applicant, TECARTUS[supreg] is a single infusion product consisting of 
autologous T-cells that have been engineered to express an anti-CD19 
chimeric antigen receptor. According to the applicant, this therapy 
targets the CD19 antigen on the cell surface of normal and malignant B-
cells. The applicant stated that TECARTUS[supreg] is different from 
other previously approved technologies because it has a distinct 
cellular product that requires a unique manufacturing process.
    According to the applicant, Mantle Cell Lymphoma (MCL) is a rare 
and aggressive subtype of non-Hodgkin lymphoma (NHL) with distinct 
characteristics 514 515 that accounts for 3-10% of all cases 
of NHL in the United States and differs from diffuse large B-cell 
lymphoma (another subtype of NHL).516 517 518 The applicant 
stated that MCL has an annual incidence of 0.5 to 1 cases per 100,000 
population with a male-to-female ratio of 3:1 with a median age at 
diagnosis for patients with MCL of 68 years.\519\ MCL results from a 
malignant transformation of the B lymphocyle in the outer edge of a 
lymph node follicle (the mantle zone). Prognosis varies for relapsed/
refractory MCL, but the median survival for MCL is 3-5 years depending 
on the risk group (the Mantle Cell Lymphoma International Prognostic 
Index categorizes patients into low, intermediate and high risk 
groups), according to the applicant.\520\ According to the applicant, 
the preferred first line therapy is bendamustine- rituximab which has 
decreased toxicity and improved progression-free survival as compared 
to rituximab with cyclophosphamide, doxorubicin, vincristine, and 
prednisone.\521\ According to the applicant, rituximab is also the only 
approved therapy for maintenance for patients in remission. The 
applicant stated the median progression free survival ranges from 29-51 
months with most of MCL patients eventually relapsing. The applicant 
contended that approximately 40% of patients end up with durable long-
term remission after a chemoimmunotherapy first line 
therapy.522 523 524
---------------------------------------------------------------------------

    \514\ Fakhri B, Kahl B. Current and emerging treatment options 
for mantle cell lymphoma. Ther Adv Hematol. 2017;8(8):223-34.
    \515\ National Comprehensive Cancer Network. Clinical Practice 
Guidelines in Oncology; B-cell Lymphomas, Version 1.2019 [November 
30, 2018]. 2017 Available from: https://www.nccn.org/professionals/physician_gls/pdf/b-cell.pdf.
    \516\ The Non-Hodgkin's Lymphoma Classification Project. A 
clinical evaluation of the International Lymphoma Study Group 
classification of non-Hodgkin's lymphoma. Blood. 1997;89(11):3909-
3918.
    \517\ Zhou Y, et al. Incidence trends of mantle cell lymphoma in 
the United States between 1992 and 2004. Cancer. 2008;113(4):791-
798.
    \518\ Teras LR, et al. 2016 US lymphoid malignancy statistics by 
World Health Organization subtypes CA Cancer J Clin. 2016;6:443-459.
    \519\ Fu S, et al. Trends and variations in mantle cell lymphoma 
incidence from 1995 to 2013: A comparative study between Texas and 
National SEER areas. Oncotarget. 2017;8(68):112516-29.
    \520\ Cheah CY, et al. Mantle cell lymphoma. J Clin Oncol. 
2016;34:1256-1269.
    \521\ Rummel MJ, et al. Bendamustine plus rituximab versus CHOP 
plus rituximab as first-line treatment for patients with indolent 
and mantle-cell lymphomas: An open-label, multicentre, randomized, 
phase 3 non-inferiority trial. Lancet. 2013;381: 1203-1210.
    \522\ Flinn IW, et al. First-line treatment of patients with 
indolent non-Hodgkin lymphoma or mantle-cell lymphoma with 
bendamustine plus rituximab versus R-CHOP or R-CVP: Results of the 
BRIGHT 5-year follow-up study. J Clin Oncol. 2019 Apr 20;37(12):984-
991. doi: 10.1200/JCO.18.00605. Epub 2019 Feb 27.
    \523\ LaCasce AS, et al. Comparative outcome of initial therapy 
for younger patients with mantle cell lymphoma: an analysis from the 
NCCN NHL Database. Blood. 2012;19(9):2093-2099.
    \524\ Lenz G, et al. Immunochemotherapy with rituximab and 
cyclophosphamide, doxorubicin, vincristine, and prednisone 
significantly improves response and time to treatment failure, but 
not long-term outcome in patients with previously untreated mantle 
cell lymphoma: Results of a prospective randomized trial of the 
German Low Grade Lymphoma Study Group (GLSG). J Clin Oncol. 
2005:23(9): 1984-1992.
---------------------------------------------------------------------------

    The applicant indicated that there is no standard of care that 
exists for second-line and higher chemotherapy when a patient has 
relapsed or refractory MCL.\525\ According to the applicant, second 
line therapies typically depend on the front-line therapy utilized, 
comorbidities, the tumor's sensitivity to chemotherapy, and overall 
risk-benefit. According to the applicant, currently available options 
for second line therapy include: Cytotoxic chemotherapy, proteasome 
inhibitors (PI), immunomodulatory drugs (IMiD), tyrosine kinase 
inhibitors, and stem cell transplant (both autologous and allogenic 
stem cell transplant [ASCT, allo-SCT]). According to the applicant, 
Bruton's tyrosine kinase (BTK) inhibitors, ibrutinib, zanubrutinib, and 
acalabrutinib, are common third-line therapy used for patients with r/r 
MCL and have shown to offer improvements over other chemotherapy-based 
regimens for r/r MCL patients. The applicant performed a literature 
review and meta-analysis of patients with r/r MCL whose disease had 
progressed during or following treatment with a BTK inhibitor and found 
that despite high initial response rates, most patients eventually 
developed progressive disease. Therefore, according to the applicant, 
new therapeutic strategies are needed to improve the prognosis of 
patients with r/r MCL whose disease has not been effectively controlled 
with chemo-immunotherapy, stem cell transplant, and BTK inhibitors.
---------------------------------------------------------------------------

    \525\ Campo E, Rule S. Mantle cell lymphoma: Evolving management 
strategies. Blood. 2015;125(1):48-55.

---------------------------------------------------------------------------

[[Page 45091]]

    With respect to the newness criterion, the applicant indicated that 
the FDA approved the TECARTUS[supreg] Biologics License Application 
(BLA) on July 24, 2020 for the indication of the treatment of adult 
patients with relapsed/refractory mantle cell lymphoma (MCL). According 
to the applicant, TECARTUS[supreg] was granted Breakthrough Therapy 
designation for the treatment of patients with r/r MCL on June 15, 2018 
and received Orphan Drug designation in 2016 for the treatment of MCL, 
acute lymphoblastic leukemia and chronic lymphocytic leukemia. The 
following ICD-10-PCS codes were established effective October 1, 2020 
to identify the administration of TECARTUS[supreg]: XW23346 
(Transfusion of brexucabtagene autoleucel immunotherapy into peripheral 
vein, percutaneous approach, new technology group 6) and XW24346 
(Transfusion of brexucabtagene autoleucel immunotherapy into central 
vein, percutaneous approach, new technology group 6). We note that the 
following new ICD-10-PCS codes to describe procedures involving the 
administration of TECARTUS[supreg] are effective October 1, 2021: 
XW033M7 (Introduction of brexucabtagene autoleucel Immunotherapy into 
peripheral vein, percutaneous approach, new technology group 7) and 
XW043M7 (Introduction of brexucabtagene autoleucel Immunotherapy into 
central vein, percutaneous approach, new technology group 7).
    As previously discussed, if a technology meets all three of the 
substantial similarity criteria, it would be considered substantially 
similar to an existing technology and would not be considered ``new'' 
for purposes of new technology add-on payments.
    With regard to the first criterion for substantial similarity, 
whether a product uses the same or similar mechanism of action to 
achieve a therapeutic outcome, according to the applicant, 
TECARTUS[supreg] is the first CAR T-cell immunotherapy indicated for 
the treatment of r/r MCL. The applicant further asserted that it does 
not use a substantially similar mechanism of action. The applicant 
asserts the FDA concluded and approved TECARTUS[supreg] as distinct 
from YESCARTA[supreg] based on differences in the manufacturing 
process, certain product specifications and impurities, and formulation 
of the final products. Furthermore, the applicant stated that 
TECARTUS[supreg] is distinct from currently available CAR T-cell 
immunotherapies, namely YESCARTA[supreg] and KYMRIAH[supreg], because 
neither prior CAR T-cell therapy is indicated for the treatment of 
patients with r/r MCL, and other differences include the manufacturing 
process, certain product specifications and impurities, and the final 
dose formulation as determined by the FDA. The applicant stated that 
MCL is a unique subtype of B-cell Non-Hodgkin's Lymphoma (NHL) and is 
distinct from DLBCL as determined by the 2016 WHO classification. The 
applicant stated it reviewed data from the FY 2019 100 percent MedPAR 
Hospital Limited Data Set to obtain a reference of currently available 
products used in the treatment of r/r MCL. The applicant stated that 
based on this analysis, available products used in the treatment of r/r 
MCL included: Chemotherapies, PIs, IMiDs, or BTK inhibitors. The 
applicant described TECARTUS[supreg] as an autologous CAR T-cell 
immunotherapy, which genetically modifies the patient's own T-cells to 
target and eliminate tumor cells for the treatment of r/r MCL and 
asserted that because TECARTUS[supreg] is an autologous CAR T-cell 
immunotherapy, it does not use the same mechanism of action as other 
treatments currently used to treat r/r MCL (chemotherapies, PIs, IMiDs, 
or BTK inhibitors).
    To further note the differences between TECARTUS[supreg]'s 
mechanism of action and other available therapies for r/r MCL, the 
applicant stated that TECARTUS[supreg] represents a unique product that 
is customized for B-cell malignancies bearing high levels of 
circulating CD19-expressing tumor cells. Given these genetic 
modifications and differences, as previously described, the applicant 
described TECARTUS[supreg] as having a different mechanism of action 
from existing r/r MCL therapies.
    The applicant stated that TECARTUS[supreg] is a distinct cellular 
product and is produced by a unique manufacturing process customized 
for B-cell malignancies characterized by circulating tumor cells and is 
designed to minimize the number of CD19-expressing tumor cells in the 
final product. The T cells in the leukapheresis product are enriched by 
positive selection, activated by culturing with anti-CD3 and anti-CD28 
antibodies, and then transduced with a retroviral vector containing the 
anti-CD19 CAR gene. These engineered T cells are then propagated in 
culture to generate a sufficient number of cells to achieve a 
therapeutic effect upon infusion back into the patient. The applicant 
further stated that TECARTUS[supreg] has a different mechanism of 
action as compared to YESCARTA[supreg] given that the European 
Medicines Agency (EMA) deemed TECARTUS[supreg] and YESCARTA[supreg] as 
different products.
    With respect to the second criterion for substantial similarity, 
whether a product is assigned to the same or a different MS-DRG, the 
applicant noted that CMS has established the new MS-DRG 018 (Chimeric 
Antigen Receptor (CAR) T-cell Immunotherapies), effective October 1, 
2020, for CAR T-cell therapies. However, the applicant asserted that 
TECARTUS[supreg] will be uniquely identified by ICD-10-PCS codes 
different from those used to identify YESCARTA[supreg] and 
KYMRIAH[supreg]. As previously noted, under the current coding system, 
cases reporting the use of TECARTUS[supreg] would be coded with ICD-10-
PCS codes XW23346 and XW24346, which are currently assigned to MS-DRG 
018, and therefore we believe that cases reporting the use of 
TECARTUS[supreg] would be assigned to the same MS-DRG as existing CAR 
T-cell therapies.
    With respect to the third criterion for substantial similarity, 
whether the new use of the technology involves the treatment of the 
same or similar type of disease and the same or similar patient 
population, the applicant stated that TECARTUS[supreg] is the first and 
only CAR T-cell immunotherapy indicated for the treatment of r/r MCL 
which is identified by ICD-10-CM C83.1X, mantle cell lymphoma, 
unspecified site. The applicant noted that the patients treated by 
YESCARTA[supreg] and KYMRIAH[supreg] are not assigned ICD-10-CM 
diagnosis code C83.1X (Mantle cell lymphoma, unspecified site), as 
would patients treated with TECARTUS[supreg]. As previously mentioned, 
the applicant described that MCL results from a malignant 
transformation of a B lymphocyte in the outer edge of the lymph node 
follicle. The applicant further stated that diffuse large b-cell 
lymphoma (DLBCL), which YESCARTA[supreg] and KYMRIAH[supreg] treat, is 
defined as a neoplasm of large B cells arranged in a diffuse pattern. 
The applicant described this distinction as evidence that 
TECARTUS[supreg] treats a different subtype of NHL, r/r MCL, as 
compared to other FDA approved CAR T-cell therapies. However, we noted 
in the proposed rule that the applicant recognized in its application 
that MCL and DLBCL patients share similar clinical presentation of 
lymphadenopathy, splenomegaly and constitutional symptoms. The 
applicant also noted that the disease courses for MCL and DLBCL are 
different given that MCL has a unique molecular pathogenesis. The 
applicant stated that patients with r/r MCL often present with high 
levels of circulating tumor cells

[[Page 45092]]

which are inherent to the disease 526 527 or due to 
peripheral mobilization of tumor cells induced by BTK inhibitor 
therapy.\528\ According to the applicant, MCL requires a customized CAR 
T-cell therapy for B-cell malignancies bearing high levels of 
circulating CD19-expressing tumor cells in order to provide a 
functional autologous cellular therapy. Unlike MCL, the presence of 
circulating tumor cells occurs only rarely in patients with DLBCL.\529\
---------------------------------------------------------------------------

    \526\ Argatoff LH, et al. Mantle cell lymphoma: A 
clinicopathologic study of 80 cases. Blood. 1997;89 (6):2067-78.
    \527\ Gu J, et al. Evaluation of peripheral blood involvement of 
mantle cell lymphoma by fluorescence in situ hybridization in 
comparison with immunophenotypic and morphologic findings. Mod 
Pathol. 2004;17 (5):553-60.
    \528\ Chang BY, et al. Egress of CD19(+)CD5(+) cells into 
peripheral blood following treatment with the Bruton tyrosine kinase 
inhibitor ibrutinib in mantle cell lymphoma patients. Blood. 
2013;122(14):2412-24.
    \529\ Muringampurath-John D, et al. Characteristics and outcomes 
of diffuse large B-cell lymphoma presenting in leukaemic phase. B. 
J. Haematol. (2012) 158: 608-614.
---------------------------------------------------------------------------

    With respect to the first criterion, the applicant asserted that 
TECARTUS[supreg] would provide a new treatment option for adult 
patients with r/r MCL and therefore is not substantially similar to any 
existing technologies. We noted that for FY 2019 (83 FR 41299), CMS 
approved two CD19 directed CAR T-cell therapies, YESCARTA[supreg] and 
KYMRIAH[supreg], for new technology add-on payments. In regard to the 
mechanism of action, the applicant acknowledged that TECARTUS[supreg] 
is a form of CAR T-cell immunotherapy that modifies the patient's own 
T-cells, as are YESCARTA[supreg] and KYMRIAH[supreg]. However, the 
applicant asserted that the manufacturing process used by 
TECARTUS[supreg] makes the therapy significantly different from 
YESCARTA[supreg]. The applicant further asserted that its unique 
manufacturing process which includes a T-cell selection step for 
patients with MCL, ALL, and CLL is distinct from that used for the 
manufacture of YESCARTA[supreg] for the treatment of patients with 
malignancies characterized by high numbers of circulating tumor types.
    Similar to our discussion of the FY 2021 application in the FY 2021 
IPPS/LTCH PPS proposed rule (85 FR 32636 and 32637), in the FY 2022 
IPPS/LTCH PPS proposed rule, we were concerned as to whether the 
differences the applicant described in the manufacturing process should 
be considered a different mechanism of action as compared to previous 
CAR T-cell therapies. We noted, in their review, the FDA identified 
many similarities between TECARTUS[supreg] and YESCARTA[supreg] to 
include that, ``the YESCARTA[supreg] and KTE-X19 final products are 
very similar and are formulated identically. The same release testing 
methods are used for both products.'' \530\ Further, as 
TECARTUS[supreg] is also a CD19-directed T-cell immunotherapy for the 
treatment of patients with an aggressive subtype of NHL, we continued 
to question whether the differences identified by the applicant would 
mean that TECARTUS[supreg] does not have a similar mechanism of action 
to existing CD19-directed CAR T-cell therapies. We sought public 
comment as to whether the differences the applicant described in the 
manufacturing process should be considered a different mechanism of 
action, as compared to previous CAR T-cell therapies.
---------------------------------------------------------------------------

    \530\ Price G, Reiser J, Salz T. CBER CMC BLA Review Memorandum, 
BLA #125703, TECARTUS brexucabtagene autoleucel. FDA.
---------------------------------------------------------------------------

    With regard to the third criterion for substantial similarity, 
though the applicant described differences between MCL and DLBCL, the 
applicant also stated that patients with MCL and DLBCL share similar 
clinical presentation of lymphadenopathy, splenomegaly and 
constitutional symptoms, and they are both subtypes of NHL. We 
therefore questioned whether this therapy may involve the treatment of 
a similar type of disease when compared to existing CAR T-cell 
therapies.
    We invited public comments on whether TECARTUS[supreg] is 
substantially similar to other technologies and whether 
TECARTUS[supreg] meets the newness criterion.
    Comment: In response to CMS's concerns, a commenter stated that MCL 
and DLBCL differ because MCL is considered largely incurable with 
standard treatment approaches and has a propensity to evolve toward 
increasing drug resistance over time leading to shorter periods of 
remission. The commenter added that clinically, MCL more frequently 
involves the bone marrow, spleen, and extranodal sites, such as the 
intestinal tract, tonsils--and, in more aggressive cases, the skin, 
lungs, and central nervous system--in addition to enlarged lymph nodes. 
In contrast, the commenter stated that DLBCL more commonly involves the 
lymph nodes, with lower predisposition to marrow and/or organ 
involvement. The commenter added that in many ways, the treatment of 
MCL has come to more closely resemble that of multiple myeloma, where 
there may be limited, if any, freedom from therapy--but with MCL 
showing poorer outcomes. The commenter summarized that TECARTUS[supreg] 
couples very high response rates and remission duration without a need 
for any ongoing therapy.
    A second commenter emphasized that MCL has important clinical 
features which distinguish it from DLBCL. Most importantly according to 
the commenter, where DLBCL is curable in up to 60% of cases, MCL 
remains incurable with known therapies. The commenter added that MCL 
cases have a median age of 65 as compared to DLBCL of 58 according to 
the ZUMA 1 and ZUMA 2 trials respectively. Third, the commenter stated 
patients with MCL often have tumor cells circulating in the peripheral 
blood unlik5e patients with DLBCL.
    A few commenters encouraged CMS to consider assigning new 
technology add-on payments for new CAR T-cell therapies to ensure 
patient access.
    Finally, a commenter stated support for CMS' desire for additional 
data and comment to illustrate support that TECARTUS[supreg] meets the 
newness criterion to support new technology add-on payment status.
    Response: We appreciate the input from the commenters and the 
information they have highlighted, and we have taken these comments 
into consideration in our final decision, which is discussed later in 
this section.
    Comment: In response to CMS' concerns the applicant submitted a 
public comment. The applicant stated that TECARTUS[supreg] is a 
distinct CAR T-cell immunotherapy approved for the treatment of r/r MCL 
which is different from large B-cell lymphoma and necessarily requires 
a different manufacturing process in order to produce a functional 
autologous therapy. The applicant stated that the leukapheresis 
material required for TECARTUS[supreg] has a more heterogeneous cell 
composition than that required for YESCARTA[supreg]. The applicant 
stated that the presence of B-lineage cells in MCL patient apheresis, 
unlike diffuse large B-cell lymphoma patient apheresis, necessitated 
the development of a CD4+ and CD8+ T-cell manufacturing selection step, 
which reduced the likelihood of circulating CD19 expressing tumor cells 
in the product and ensured a consistent efficacious and safe product 
for the R/R MCL patient population.
    The applicant added that both the FDA and European Medicines Agency 
(EMA) have concluded that TECARTUS[supreg] is a unique product distinct 
from YESCARTA[supreg].
    In its comment, the applicant further asserted that MCL is a unique 
subtype of B-cell non-Hodgkin lymphoma (NHL)

[[Page 45093]]

and is distinct from DLBCL. The applicant added that while MCL patients 
may present with similar symptoms as patients with DLBCL, the 
conditions differ based on histopathology, genetics, clinical 
characteristics, treatment approaches, and clinical outcomes. The 
applicant asserted that the most critical distinction between MCL and 
DLBCL is the difference in durable complete remissions and cure with 
available therapies. According to the applicant, the standard of care 
for patients newly diagnosed with DLBCL is the immuno-chemotherapy 
regimen R-CHOP (rituximab, cyclophosphamide, doxorubicin, vincristine, 
and prednisone) which leads to a `cure' in 50-60% of patients.\531\ The 
applicant added, in contrast, although many combinations of rituximab-
based immuno-chemotherapy have been examined in patients newly 
diagnosed with MCL, none is considered curative.\532\ Further, the 
applicant stated that another important distinction is that patients 
with r/r MCL often present with high levels of circulating tumor cells 
which are inherent to the disease 533 534 535 or due to 
peripheral mobilization of tumor cells induced by BTK inhibitor 
therapy.\536\ The applicant stated that MCL requires a customized CAR 
T-cell therapy for B-cell malignancies bearing high levels of 
circulating CD19-expressing tumor cells in order to provide a 
functional autologous cellular therapy; unlike MCL, the presence of 
circulating tumor cells rarely occurs in patients with DLBCL.\537\ 
Lastly, the applicant stated that the World Health Organization has 
classified MCL and DLBCL as two distinct B-cell lymphoid neoplasms 
based on the pathogenetic differences.\538\
---------------------------------------------------------------------------

    \531\ Liu, Y. and Barta, SK. Diffuse large B-cell lymphoma: 2019 
update on diagnosis, risk stratification, and treatment. Am. J. 
Hematol. (2019) 94: 604-616.
    \532\ Maddocks K. Update on mantle cell lymphoma. Blood. (2018) 
132: 1647-1656.
    \533\ Argatoff LH, et al. Mantle cell lymphoma: A 
clinicopathologic study of 80 cases. Blood. 1997;89 (6):2067-78.
    \534\ Gu J., et al. Evaluation of peripheral blood involvement 
of mantle cell lymphoma by fluorescence in situ hybridization in 
comparison with immunophenotypic and morphologic findings. Mod 
Pathol. 2004;17 (5):553-60.
    \535\ Muringampurath-John D., et al. Characteristics and 
outcomes of diffuse large B-cell lymphoma presenting in leukaemic 
phase. B. J. Haematol. (2012) 158: 608-614.
    \536\ Chang BY., et al. Egress of CD19(+)CD5(+) cells into 
peripheral blood following treatment with the Bruton tyrosine kinase 
inhibitor ibrutinib in mantle cell lymphoma patients. Blood. 
2013;122(14):2412-24.
    \537\ Muringampurath-John D., et al. Characteristics and 
outcomes of diffuse large B-cell lymphoma presenting in leukaemic 
phase. B.J. Haematol. (2012) 158: 608-614.
    \538\ Swerdlow SH., et al. The updated classification of 
hematological malignancies; the 2016 revision of the World Health 
Organization classification of lymphoid neoplasms. Blood (2016) 127 
(20): 2375-2390.
---------------------------------------------------------------------------

    Response: We appreciate the additional information from the 
applicant regarding whether TECARTUS[supreg] is substantially similar 
to existing treatment options. After consideration of the public 
comments we received and information submitted by the applicant in its 
application, we agree with the applicant that TECARTUS[supreg] does not 
use the same or similar mechanism of action as other technologies used 
for the treatment of r/r MCL because it is the only CAR T-cell therapy 
available for the treatment of r/r MCL. Furthermore, as mentioned by 
the applicant, due to the differences based on histopathology, 
genetics, clinical characteristics, treatment approaches, and clinical 
outcomes we agree that this is a unique disease population as compared 
to that treated by other existing CAR T-cell therapies. Based on this 
information, we believe that TECARTUS[supreg] is not substantially 
similar to existing treatments and meets the newness criterion. We 
consider the beginning of the newness period to commence on the date 
TECARTUS[supreg] was approved by the FDA, July 24, 2020.
    With regard to the cost criterion, the applicant searched the FY 
2019 MedPAR claims data file with the FY 2019 Final Rule IPPS Impact 
File to identify potential cases representing patients who may be 
eligible for treatment using TECARTUS[supreg].
    The applicant identified claims that reported an ICD-10-CM 
diagnosis code of ICD-10-CM C83.1X (Mantle cell lymphoma, unspecified 
site). The applicant stated that claims reporting ICD-10-CM code C83.1X 
would not involve the use of the other two approved CAR T-cell 
therapies because those therapies are not used to treat this diagnosis, 
MCL. As such, the applicant stated that it used C83.1X to identify 
potential MCL cases and ICD-10-PCS codes XW033C3 and XW043C3 to 
identify patients receiving CAR T-cell therapy. In its analysis, the 
applicant identified two sets of cohorts (Primary Cohort and 
Sensitivity Analysis Cohort) to assess whether this therapy met the 
cost criterion. The ICD-10-PCS procedure codes listed in the following 
table were used to identify claims involving chemotherapy and the 
applicant noted that these were used for both cohorts.
BILLING CODE 4120-01-P

[[Page 45094]]

[GRAPHIC] [TIFF OMITTED] TR13AU21.192

    The applicant identified two cohorts for these analyses and used 
two CCRs to account for the cost of their technology. The Primary 
Cohort included cases with an ICD-10-CM primary diagnosis of MCL, at 
least one procedure code indicating receipt of chemotherapy, and no 
ICD-10-PCS procedure codes indicating CAR T-cell therapy. The applicant 
believed the Primary Cohort most closely aligned with the 
characteristics and health of r/r MCL patients who would receive 
TECARTUS[supreg] given that this cohort includes patients with far 
advanced disease (comparable to the ZUMA-2 study, as discussed later in 
this section). The Sensitivity Analysis Cohort included patients with 
the ICD-10-CM principal or secondary diagnosis of MCL, at least one 
procedure code indicating receipt of chemotherapy, and no ICD-10-PCS 
procedure codes indicating CAR T-cell therapy. For each cohort, the 
applicant performed two sub-analyses that varied the CCR used to 
calculate TECARTUS[supreg] charges: (1) The national pharmacy CCR of 
0.187; and (2) the applicant calculated CAR T-cell CCR of 0.314.
    According to the applicant, based on the primary diagnosis code and 
the presence of chemotherapy, these cases signify that the primary 
reason for hospitalization was treatment of the patient's MCL, 
including the complications of their advancing disease and 
chemotherapy-related complications, and resulted in charges and longer 
lengths of stay believed to be most reflective of the r/r MCL 
population that is treated by TECARTUS. The applicant added that this 
group of MCL cases with MCL as a primary diagnosis most closely 
compares with the characteristics and health resource utilization of r/
r MCL patients that will receive TECARTUS. Furthermore, the applicant 
stated that the cases in the Primary Cohort had higher charges across 
all categories than the cases with MCL as a secondary diagnosis. The 
cases with MCL as a primary diagnosis are according to the applicant 
more reflective of the r/r MCL population as those cases were more 
likely being treated for the complications of their advancing disease 
and chemotherapy-related complications. The average length of stay for 
hospitalizations in the Primary Cohort was 15.1 days. Lastly, in 
explaining why CAR T-cell MCL cases from FY 2019 were excluded from the 
cost analysis, the applicant stated that they could not identify 
specific charges for CAR T-cell therapy, no individual revenue center 
had charges similar to those expected for CAR T-cell therapy, and there 
were no CAR T-cell therapy products approved for the treatment of MCL 
in FY 2019.
    The applicant stated that to estimate the CAR T-cell CCR, they 
obtained the MS-DRG 018 arithmetic mean charge in the AOR/BOR FY 2021 
Proposed Rule File released by CMS ($1,387,946). The applicant 
subtracted non-drug charges for TECARTUS of $201,610 (based on the 
TECARTUS FY 2021 new technology add-on payment application) from the 
total arithmetic mean charge to estimate CAR T-cell charges 
(approximately $1,186,336). The applicant then divided a WAC of CAR T-
cell therapy of $373,000 by the estimated CAR T-cell charges to 
estimate a charge-to-cost ratio of 0.314 (CCR = 373,000/1,186,336).

[[Page 45095]]

    The claim search conducted by the applicant resulted in 267 claims 
in the Primary Cohort, mapped to 13 MS-DRGs, and 1,100 claims in the 
Sensitivity Analysis Cohort, mapped to 59 MS-DRGs using the FY 2019 
MedPAR Hospital LDS based on the requirements for each cohort outlined 
by the applicant. The applicant stated that because TECARTUS cases are 
mapped to MS-DRG 018, the cost criterion analysis utilized the 
threshold for MS-DRG 018 for all MS-DRGs included in each cohort rather 
than the MS-DRG specific threshold. The applicant determined an average 
unstandardized case weighted charge per case of $1,251,126 for the 
Primary cohort and $1,251,126 for the Sensitivity Analysis Cohort.
BILLING CODE 4120-01-P
[GRAPHIC] [TIFF OMITTED] TR13AU21.193

[GRAPHIC] [TIFF OMITTED] TR13AU21.194


[[Page 45096]]


[GRAPHIC] [TIFF OMITTED] TR13AU21.195


[[Page 45097]]


[GRAPHIC] [TIFF OMITTED] TR13AU21.196

BILLING CODE 4120-01-C
    The applicant then removed charges for the prior technology. The 
applicant stated that the cases representing patients who had received

[[Page 45098]]

chemotherapy, as reflected by the Medicare claims data, would generally 
not receive both chemotherapy and TECARTUS[supreg] as an inpatient 
because conditioning chemotherapy would be administered in the 
outpatient setting before the patient would be admitted for 
TECARTUS[supreg] infusion and monitoring. Otherwise, the applicant 
asserted that patients receiving TECARTUS[supreg] would be expected to 
incur similar charges to those cases in the Medicare claims data for 
patients with a primary diagnosis of MCL and receiving chemotherapy 
(Primary Cohort). In its analysis, the applicant noted that in the FY 
2019 MedPAR Hospital LDS, charges for chemotherapy drugs were grouped 
with charges for oncology, diagnostic radiology, therapeutic radiology, 
nuclear medicine, CT scans, and other imaging services. The applicant 
believed that removing all radiology charges would understate the cost 
of adverse event (AE) clinical management for TECARTUS[supreg] patients 
needed. The applicant found that when using data from the Q4 2017 and 
Q1 Q3 2018 Standard Analytic files and comparing total chemotherapy 
charges to total radiology charges, 2 percent of radiology charges were 
chemotherapy charges, on average. Therefore, instead of removing all 
radiology charges, the applicant excluded 2 percent of the radiology 
charge amount to capture the effect of removing chemotherapy pharmacy 
charges.
    The applicant then standardized the charges and applied the 2-year 
inflation factor used in the FY 2021 IPPS/LTCH PPS final rule to 
calculate outlier threshold charges (1.13218). For the Primary and 
Sensitivity cohorts, the applicant performed two sub-analyses that 
varied the CCR used to calculate TECARTUS[supreg] charges: (1) Using 
the national pharmacy CCR (0.187); and (2) using the CAR T-cell CCR 
(0.314).
    The applicant stated that when comparing the Primary Cohort to the 
MS-DRG 018 average case-weighed threshold amount (based on the FY 2021 
IPPS/LTCH PPS final rule) and using the national pharmacy CCR, the 
final inflated average case-weighted standardized charge per case of 
$2,207,969 exceeded the average case-weighted threshold amount of 
$1,251,126 by $956,843. When using the CAR T-cell CCR, the final 
inflated average case-weighted standardized charge per case of 
$1,399,653 exceeded the average case-weighted threshold amount of 
$1,251,126 by $148,527. The applicant stated that because the final 
inflated average case-weighted standardized charge per case exceeded 
the average case-weighted threshold amount, the therapy meets the cost 
criterion.
    When conducting the same review to assess cost for the Sensitivity 
Analysis Cohort, the applicant noted that the sensitivity analysis 
cohort also meets the cost criterion when compared to the MS-DRG 018 
average case-weighted threshold amount (based on the FY 2021 IPPS/LTCH 
PPS data file thresholds for FY 2022). As reported by the applicant, 
when using the national pharmacy CCR in the sensitivity analysis cohort 
the final inflated average case-weighted standardized charge per case 
of $2,142,149 exceeded the average case-weighted threshold amount of 
$1,251,126 by $891,023. When using the CAR T-cell CCR in the 
sensitivity analysis cohort, the final inflated average case-weighted 
standardized charge per case of $1,333,833 exceeded the average case-
weighted threshold amount of $1,251,126 by $82,707. The applicant 
stated that because the final inflated average case-weighted 
standardized charge per case exceeded the average case-weighted 
threshold amount, the therapy meets the cost criterion.
    Because the final inflated average case-weighted standardized 
charge per case for both the Primary Cohort and the Sensitivity 
Analysis Cohort exceeds the average case-weighted threshold amount for 
MS-DRG 018, the applicant maintained that the technology meets the cost 
criterion.
    As noted in previous discussions, the submitted costs for CAR T-
cell therapies vary widely due to differences in provider billing and 
charging practices for this therapy. Therefore, with regard to the use 
of this data for purposes of calculating a CAR T-cell CCR we stated we 
were uncertain how representative this data is for use in the 
applicant's cost analyses given this potential for variability.
    We stated in the proposed rule that we continue to be interested in 
public comments regarding the eligibility of CAR T-cell technologies 
for new technology add-on payments when assigned to MS-DRG 018. As we 
have noted in prior rulemaking with regard to the CAR T-cell therapies 
(83 FR 41172 and 85 FR 58603 through 58608), if a new MS-DRG were to be 
created, then consistent with section 1886(d)(5)(K)(ix) of the Act, 
there may no longer be a need for a new technology add-on payment under 
section 1886(d)(5)(K)(ii)(III) of the Act.
    We invited public comment on whether TECARTUS[supreg] meets the 
cost criterion.
    Comment: We received a comment from MEDPAC which addressed the cost 
criterion in general as it relates to CAR T-cell therapies.
    Response: Please refer to the response in the BREYANZI[supreg] 
application in section II.F.X.c. of the preamble of this final rule for 
a detailed discussion of this issue.
    Comment: We received multiple comments in response to our concern 
for CAR T-cell therapy, the MS-DRG 018 assignment, and new technology 
add-on payment eligibility.
    Response: For a complete discussion of these comments and our 
response, please see the BREYANZI[supreg] application in section 
II.F.X.c. of the preamble of this final rule.
    Comment: A commenter stated support for CMS' desire for additional 
data and comment to illustrate support that TECARTUS[supreg] meets the 
cost criterion to support new technology add-on payment status.
    Response: We appreciate the input from the commenter and have taken 
this comment into consideration in determining whether TECARTUS[supreg] 
meets the cost criterion.
    Comment: A commenter, the applicant, maintained that the cost 
analyses demonstrate that TECARTUS[supreg] meets the cost criterion. In 
response to CMS' concern regarding the representativeness of the cost 
data for TECARTUS[supreg] based on the CAR T-cell CCR, the applicant 
stated it appreciates CMS' concern regarding the ``representativeness'' 
of the estimated CAR T-cell CCR and agree that CCRs are likely to vary 
widely for CAR T-cell therapies. The applicant stated that while it is 
standard to use the pharmacy CCR to convert drug costs to charges and 
CMS has accepted the use of this CCR in the past for cost criterion 
analyses, CAR T-cell therapies, including TECARTUS[supreg], are new and 
novel therapeutics, and they were concerned that CMS would question the 
applicability of the pharmacy CCR for purposes of demonstrating that 
TECARTUS[supreg] met the cost criterion. Therefore, the applicant 
created two sets of analyses to demonstrate that TECARTUS[supreg] meets 
the cost criterion, using both the national pharmacy CCR and an 
estimate of the CAR T-cell CCR. Furthermore, the applicant stated that 
the CAR T-cell therapy CCR of 0.314 is similar to the CAR T-cell 
therapy CCR of 0.295 used by other applicants for CAR T-cell therapy 
for FY 2022 new technology add-on payment applications as summarized in 
the FY 2022 CMS IPPS/LTCH PPS proposed rule: BREYANZI (86 FR 25231), 
ciltacabtagene autoleucel (86 FR 225237), and idecabtagene vicleucel 
(86 FR 225258). Lastly, the applicant

[[Page 45099]]

commented TECARTUS[supreg] would also have met the cost criterion if 
the 0.295 CCR had been used in their analyses.
    The applicant stated that in the proposed rule, CMS solicited 
comments on whether with the creation of MS-DRG 018 there may no longer 
be a need for CAR T-cell products to receive a new technology add-on 
payment. The applicant stated their belief that the creation of MS-DRG 
018 does not alter the new technology add-on payment eligibility of 
future CAR T-cell products. The applicant stated the language under 
section 1886(d)(5)(K)(ix) is long-standing and has never before been 
interpreted as potentially imposing a blanket exclusion from new 
technology add-on payment eligibility. The applicant asserted that 
instead, CMS has historically operationalized section 1886(d)(5)(K)(ix) 
by establishing the new technology add-on payment criteria of newness, 
cost, and substantial clinical improvement. In particular, the 
applicant contends that CMS has viewed its evaluation under the cost 
criterion as directly satisfying the agency's obligation under section 
1886(d)(5)(K)(ix) of the Act. The applicant stated, in 2005 rulemaking 
where the agency first recognized the addition of section 
1886(d)(5)(K)(ix) of the Act, as amended by section 503(c) of Medicare 
Prescription Drug, Improvement, and Modernization Act of 2003,\539\ CMS 
stated that ``at the time an application for new technology add-on 
payments is submitted, the DRGs associated with the new technology are 
identified.'' \540\ The applicant added CMS went on to state that it 
``only determine[s] that a new DRG assignment is necessary or a new 
technology add-on payment is appropriate when the reimbursement under 
these currently assigned DRGs is not adequate for this new 
technology.'' The applicant asserted that the current MS-DRG assignment 
for a case using a new CAR T-cell product would be MS-DRG 018 and CMS 
should follow the same approach for a new CAR T-cell product as for all 
other products applying for a new technology add-on payment: Determine 
whether the current MS-DRG assignment is inadequate and if so, either 
make a new MS-DRG assignment or provide for a new technology add-on 
payment. The applicant added if the fact that the current MS-DRG 
assignment takes into consideration the use of a particular therapy 
would disqualify new products from being eligible for a new technology 
add-on payment, then many more products in addition to CAR T-cell would 
be affected (for example, new pacemakers and the MS-DRGs 242-244 to 
which pacemaker cases are assigned).
---------------------------------------------------------------------------

    \539\ Public Law 108-173 (Dec. 8, 2003).
    \540\ 70 FR 47278, 47343 (Aug. 12, 2005).
---------------------------------------------------------------------------

    Response: We appreciate the information provided by the applicant 
in their comment in regard to their calculation of a CAR T-cell CCR. As 
we stated in section E.2.b. of this rule, we continue to believe that 
it is premature to make structural changes to the IPPS at this time to 
pay for CAR T-cell therapies (78 FR 58453). As we gain more experience 
paying for these therapies under the IPPS, we may consider these 
comments to inform future rulemaking. However, we appreciate the 
thoughtfulness used by the applicant to provide as clear as possible a 
description of CAR T-cell therapy cost calculations. We appreciate the 
usage of multiple cost analyses, such as varying the CCR used to 
inflate cost to charges, which potentially allowed for a more 
conservative markup.
    After consideration of the public comments we received and based on 
the information included in the applicant's new technology add-on 
payment application, we believe that the TECARTUS[supreg] meets the 
cost criterion.
    With respect to the substantial clinical improvement criterion, the 
applicant asserted that TECARTUS[supreg] represents a new treatment 
option for an adult patient population unresponsive to, or ineligible 
for, currently available treatments. The applicant also believes that 
the use of TECARTUS[supreg] significantly improves clinical outcomes 
for a patient with r/r MCL as compared to currently available 
therapies, including BTK inhibitors. The applicant stated that 
TECARTUS[supreg] provides access to a treatment option for patients 
with r/r MCL who have not been responsive to first line or second line 
therapies. The applicant provided further detail regarding these 
assertions, referencing the results of a Phase 2 study (Zuma-2) and 
historical and meta analyses, which are summarized in this section of 
this rule.
    According to the applicant, because no effective standard therapy 
for subjects with r/r MCL who have progressed following a prior BTK 
inhibitor therapy exists, ZUMA-2 lacked a comparison arm. The applicant 
described how a historical control was the only ethical and feasible 
study design for patients with r/r MCL who had not responded to the 
most promising therapies available, including BTK inhibitors. 
Therefore, the historical control was identified from prior studies 
identified in a meta-analysis of six studies, which included two 
studies by Martin et al., (2016) and Cheah et al., (2015), and covered 
255 subjects. The ORRs in these six studies ranged from 20%-42% with 
the applicant identifying 26%\541\ and 32%\542\ for use as their 
comparator.
---------------------------------------------------------------------------

    \541\ Martin P, et al. Postibrutinib outcomes in patients with 
mantle cell lymphoma. Blood. 2016;127 (12):1559-63.
    \542\ Cheah CY, et al. Patients with mantle cell lymphoma 
failing ibrutinib are unlikely to respond to salvage chemotherapy 
and have poor outcomes. Ann Oncol. 2015;26(6):1175-9.
---------------------------------------------------------------------------

    According to the Martin et al. (2016) retrospective cohort study 
referenced by the applicant, the investigators reported best response 
rate (RR) to ibrutinib was 55% (43% partial response [PR], 12% complete 
response [CR]), with 35% of patients having a best response of 
progressive disease. But among patients who received subsequent 
therapy, local clinicians reported that 13 patients (19%) achieved PR, 
and 5 (7%) achieved CR. The median overall survival (OS) following 
cessation of ibrutinib was 2.9 months (95% confidence interval [CI], 
1.6-4.9). Of the 104 patients with data available, 73 underwent at 
least one additional line of currently available treatment after 
stopping ibrutinib with a median OS of 5.8 months (95% confidence 
interval [CI], 3.7-10.4).\543\
---------------------------------------------------------------------------

    \543\ Martin P, et al. Postibrutinib outcomes in patients with 
mantle cell lymphoma. Blood. 2016;127 (12):1559-63.
---------------------------------------------------------------------------

    A second retrospective study by Cheah et al. identified 42 (54%) 
who had discontinued therapy of 78 patients with MCL who had been 
treated at MD Anderson Cancer Center between 2011 and 2014.\544\ All 42 
patients had received ibrutinib with a median number of cycles of 6.5 
(range 1-43). Twenty-eight patients (67%) had disease progression as 
the main reason for therapy discontinuation. Of the 31 patients who 
experienced disease progression following ibrutinib and underwent 
salvage therapy, the overall objective response rate (ORR) and complete 
response rate (CRR) was 32% and 19%, respectively. After a median 
follow-up of 10.7 (range 2.4-38.9) months from discontinuation of 
ibrutinib, the median OS among patients with disease progression was 
8.4 months and the estimated one-year OS was 22.1% (95% CI 8.3% to 
40.2%).
---------------------------------------------------------------------------

    \544\ Cheah CY, et al. Patients with mantle cell lymphoma 
failing ibrutinib are unlikely to respond to salvage chemotherapy 
and have poor outcomes. Ann Oncol. 2015;26(6):1175-9.
---------------------------------------------------------------------------

    The applicant summarized further studies that featured BTK therapy. 
Dreyling et al. and Epperla et al. identified ORRs of 20% and 42% 
respectively while Wang et al. identified an ORR of 29%, CR rate of 
14%, and PR rate of 15% and Jaln et al. identified an

[[Page 45100]]

ORR of 29%, CR rate of 14%, and PR rate of 
15%.545 546 547 548
---------------------------------------------------------------------------

    \545\ Dreyling M, et al. Ibrutinib versus temsirolimus in 
patients with relapsed or refractory mantle-cell lymphoma: An 
international, randomised, open-label, phase 3 study. Lancet. 
2016;387(10020):770-8.
    \546\ Epperla N, et al. Predictive factors and outcomes for 
ibrutinib therapy in relapsed/refractory mantle cell lymphoma--a 
``real world'' study. Hematological Oncology. 2017:1-8.
    \547\ Wang M, et al. Observational study of lenalidomide in 
patients with mantle cell lymphoma who relapsed/progressed after or 
were refractory/intolerant to ibrutinib (MCL-004). J Hematol Oncol. 
2017;10:171.
    \548\ Jain P, et al. Long-term outcomes and mutation profiling 
of patients with mantle cell lymphoma (MCL) who discontinued 
ibrutinib. Br J Haematol. 2018a;183:578-87.
---------------------------------------------------------------------------

    To evaluate the effectiveness of TECARTUS[supreg], the applicant 
noted it used an ORR comparison of 25%, which was derived from two 
aforementioned studies (Martin et al. and Cheah et al.) with patients 
with r/r MCL who progressed on the most predominantly prescribed BTK 
inhibitor, ibrutinib. The results of these two studies showed a median 
OS of 5.8 months after receiving at least 1 additional line of 
currently available therapy to treat r/r MCL. Those who did not receive 
salvage therapy had a median OS of 0.8 months.\549\
---------------------------------------------------------------------------

    \549\ Martin P, et al. Postibrutinib outcomes in patients with 
mantle cell lymphoma. Blood. 2016;127 (12):1559-63.
---------------------------------------------------------------------------

    According to the applicant, the ZUMA-2 study of TECARTUS[supreg] is 
the only pivotal study of CAR T-cell therapy for r/r MCL. ZUMA-2 is a 
multicenter, open label, Phase 2 study which evaluated the safety and 
efficacy of TECARTUS[supreg] in patients with r/r MCL that relapsed or 
are refractory to prior therapy, including BTK inhibitors. The primary 
endpoint compared the ORR from the study to the ORR 25% historical 
control at a one-sided alpha level of 0.025. The applicant stated that 
ZUMA-2 was not designed to compare the efficacy and safety of TECARTUS 
to BTK inhibitors, and the results of ZUMA-2 are not intended to 
indicate that TECARTUS should definitively be utilized to replace any 
existing therapies. Participants were required to have received prior 
treatment for MCL, no more than five prior regimens, which must have 
included anthracycline (or bendamustine containing chemotherapy), an 
anti-CD20 monoclonal antibody and BTK inhibitor. The ZUMA-2 study 
included 68 subjects treated with TECARTUS[supreg] out of 75 patients 
enrolled. The safety analysis included a review of all 68 subjects, 
with the primary analysis of efficacy reviewing the first 60 subjects 
treated with TECARTUS[supreg]. ZUMA-2 was conducted at 20 sites in the 
United States and Europe. Of the 60 subjects in the primary analysis 
set, 59 were from U.S. sites. Of the 68 subjects in the safety analysis 
set, 62 were from U.S. sites. Among the 68 subjects, the median age was 
65 years (range 38-79) and 57 subjects (84%) were male. Additionally, 
58 subjects (85%) had stage IV disease. The sample had a median of 3 
prior therapies with 55 (81%) having received >=3 prior therapies. In 
addition, 43% had relapsed after a prior autologous stem cell 
transplant (ASCT); the remaining subjects had either relapsed after or 
were refractory to their last therapy for MCL.
    The applicant asserted that the use of TECARTUS[supreg] 
significantly improves clinical outcomes for a patient population as 
compared to currently available treatments. The applicant contended 
that ibrutinib, a BTK inhibitor, is the most common third-line therapy 
used for patients with r/r MCL 550 551 and has been shown to 
offer improvements over other chemotherapy-based regimens for r/r MCL 
patients. The applicant also referenced a more selective BTK inhibitor, 
acalabrutinib, which was approved in the US for the treatment of 
patients with r/r MCL.552 553 In registrational trials, the 
ORR and CRR were 66% and 17%, respectively for ibrutinib, and 81% and 
40%, respectively, for acalabrutinib.554 555 The applicant 
contended that primary and secondary resistance to BTK inhibitors \556\ 
is common, and subsequent therapies currently available are minimally 
effective.557 558 559
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    \550\ Campo E, Rule S. Mantle cell lymphoma: Evolving management 
strategies. Blood. 2015;125(1):48-55.
    \551\ Vose JM. Mantle cell lymphoma: 2017 update on diagnosis, 
risk-stratification, and clinical management. Am J Hematol. 
2017;92(8):806-813.
    \552\ Kantar Health. CancerMPact[supreg] United States. 
September 2018, v1.2.
    \553\ Vose JM. Mantle cell lymphoma: 2017 update on diagnosis, 
risk-stratification, and clinical management. Am J Hematol. 
2017;92(8):806-813.
    \554\ Ibrutinib USPI. Available from: https://www.imbruvica.com/docs/librariesprovider7/default-document-library/prescribing_information.pdf.
    \555\ Acalabrutinib USPI. Available from: https://www.azpicentral.com/calquence/calquence.pdf#page=1.
    \556\ Rule S, et al. Median 3.5-year follow-up of ibrutinib 
treatment in patients with relapsed/refractory Mantle Cell Lymphoma: 
a pooled analysis. Blood Dec. 2017;130(Suppl 1):151.
    \557\ Cheah CY, et al. Patients with mantle cell lymphoma 
failing ibrutinib are unlikely to respond to salvage chemotherapy 
and have poor outcomes. Ann Oncol. 2015;26(6):1175-9.
    \558\ Martin P, et al. Postibrutinib outcomes in patients with 
mantle cell lymphoma. Blood. 2016;127 (12):1559-63.
    \559\ DerSimonian R, Laird N. Meta-analysis in clinical trials. 
Control Clin Trials. 1986;7(3):177-88.
---------------------------------------------------------------------------

    Among the 68 patients treated in the ZUMA-2 study, the primary 
efficacy analysis was conducted after 60 patients had been enrolled, 
treated, and evaluated for response for six months after the week four 
disease assessment. Based on the primary analysis of the 60 subjects 
included in the ZUMA-2 study, there was an ORR of 93% after a single 
dose of TECARTUS[supreg] (56 of 60 subjects with a 95% CI of 83.8%, 
98.2%). The applicant reported that the complete response rate was 67% 
(40 of 60 subjects with a 95% CI of 53.3%, 78.3%). The applicant noted 
the ORR of 93% and CR 67% were observed across age groups (94% ages 
>=65; 93% ages <65 and, of the 40 subjects achieving CR, 22 subjects 
were aged >=65 and 18 were aged <65). The applicant highlighted that 
the ORR of 93% was significantly higher than the prespecified 
historical control rate of 25%. Furthermore, the applicant noted that 
among the 42 subjects who initially had a partial response (PR) or 
stable disease (SD), 24 subjects (57%) went on to achieve a CR after a 
median of 2.2 months (range: 1.8 to 8.3 months). Twenty-one subjects 
converted from PR to CR, and 3 subjects converted from stable disease 
(SD) to CR.
    According to the applicant, the median DOR was not reached with a 
median follow-up time for DOR of 8.6 months (95% CI: 7.8, 19.6 months) 
with a median study follow-up of 12.3 months; this result was 
consistent across age groups. Kaplan-Meier estimates of the progression 
free survival (PFS) rates at 6 months and 12 months were 77.0% and 
60.9%, respectively, and the median PFS was not reached at the median 
potential follow-up of 12.3 months. Additionally, 57% of all patients 
and 78% of patients with a CR remained in remission (results consistent 
across age groups). Furthermore, as reported by the applicant, among 
the first 28 subjects studied as part of the interim analysis, 43% 
remained in continued remission without additional therapy at the 
follow-up period of 27 months (range, 25.3-32.3).
    The applicant also conducted an additional analysis of OS among the 
first 28 subjects (ZUMA-2 interim analysis) who were treated with 
TECARTUS[supreg] and had a potential follow-up of >=24 months. Among 
these subjects, the OS rate estimate at 24 months was 67.9% and the 
median OS was not reached. In comparison, the Cheah et al. (2015) post-
ibrutinib salvage therapy study reported a lower one-year survival rate 
of 22%. Additionally, among the subjects in CR at month 3 who had the 
opportunity to

[[Page 45101]]

be followed to month 12, 90% remained in CR at month 12. The applicant 
contended that this statistic showcased that early responses to 
TECARTUS[supreg] are likely indicative of long-term remission after the 
single infusion of TECARTUS[supreg]. Furthermore, the applicant 
suggested that a substantial number of patients with r/r MCL treated 
with TECARTUS[supreg] will achieve a CR, and that this suggests these 
patients will likely experience a long-term remission after a single 
infusion of TECARTUS[supreg]. The applicant also noted that these 
results were consistent across age groups at the time of the primary 
data analysis cut-off (July 24, 2019). By contrast, the applicant noted 
that patients with r/r MCL who had prior BTK inhibitor treatment had CR 
rates ranging from 7-22%. Additionally, the applicant noted that the 
majority of patients on BTK inhibitor treatment go on to have 
progressive disease given that the responses achieved with currently 
available salvage therapies are short lived and have a DOR ranging from 
3 to 5.8 months.560 561 562 563
---------------------------------------------------------------------------

    \560\ Kochenderfer JN, et al. Lymphoma Remissions Caused by 
Anti-CD19 Chimeric Antigen Receptor T Cells Are Associated With High 
Serum Interleukin-15 Levels. J Clin Oncol. 2017a;35(16):1803-13.
    \561\ Kochenderfer JN, et al. Long-Duration Complete Remissions 
of Diffuse Large B Cell Lymphoma after Anti-CD19 Chimeric Antigen 
Receptor T Cell Therapy. Mol Ther. 2017b;25(10):2245-53.
    \562\ Gupta S, et al. Recommendations for the design, 
optimization, and qualification of cell-based assays used for the 
detection of neutralizing antibody responses elicited to biological 
therapeutics. Journal of Immunological Methods. 2007;321(1-2):1-18.
    \563\ Davila ML, et al. Efficacy and toxicity management of 19-
28z CAR T cell therapy in B cell acute lymphoblastic leukemia. Sci 
Transl Med. 2014;6(224):224ra25.
---------------------------------------------------------------------------

    With regard to the safety of TECARTUS[supreg], the applicant argued 
that the ZUMA-2 study demonstrated a positive benefit-risk of 
TECARTUS[supreg] over the current therapy options for patients with r/r 
MCL. The applicant stated that the toxicity profile that is associated 
with TECARTUS[supreg] therapy can be managed based upon established 
guidance. The applicant further stated that the risk evaluation and 
mitigation strategies (REMS) program will ensure that hospitals 
providing TECARTUS[supreg] therapy are certified so that all who 
prescribe, dispense, or administer TECARTUS[supreg] are aware of how to 
manage the risk of cytokine release syndrome (CRS) and neurologic 
events. However, the applicant notes that patients who were >=65 years 
old showed a trend toward a higher incidence of Grade 3 or higher CRS 
compared to those <=65 years old. (21% versus 7%). Additionally, all 
subjects in the ZUMA-2 primary analysis had at least one adverse event 
(AE), 99% of subjects had at least one AE that was Grade 3 or higher, 
and 68% of subjects had at least one serious adverse event (SAE). Among 
all 68 treated patients, the most common Grade 3 or higher AEs were 
anemia (51%), neutropenia (53%), and leukopenia (41%). Furthermore, CRS 
occurred in 62 subjects (91%) in the ZUMA-2 safety analysis. Of these, 
10 subjects (15%) had Grade 3 CRS or higher. No subject had Grade 5 
CRS, according to the applicant. Furthermore, according the applicant, 
the most common CRS symptoms of any grade were pyrexia, hypotension, 
and hypoxia. The most common Grade 3 or higher CRS symptoms were 
hypotension (35 subjects, 51%), hypoxia (23 subjects, 34%), and pyrexia 
(62 subjects, 91%). No patient in the ZUMA-2 study treated with 
TECARTUS[supreg] died from CRS.
    The applicant mentioned that 43 of the 68 patients (63%) in the 
ZUMA-2 study also experienced forms of neurologic events. Of these, 15 
subjects (22%) had a worst Grade 3 neurologic event, and 6 subjects 
(9%) had a worst Grade 4 neurologic event. Twenty-two subjects (32%) 
had serious neurologic events, however, the applicant noted no subject 
had a Grade 5 neurologic event. The most common neurologic events of 
any grade were encephalopathy (21 subjects, 31%), confusional state (14 
subjects, 21%), and tremor (24 subjects, 35%). Compared with subjects 
who were <65 years of age, subjects who were >=65 years of age showed a 
trend toward a higher incidence of Grade 3 or higher neurologic events 
(36% versus 24%). The applicant noted that these neurologic events 
resolved for all but 6 subjects and that among those whose neurologic 
events had resolved, the median duration was 12 days. Additionally, no 
patient died from neurologic events.
    In response to CMS's concern as discussed in the FY 2021 IPPS/LTCH 
PPS proposed rule (85 FR 32646 through 32647) regarding the 
generalizability of the findings from ZUMA-2 to the general Medicare 
population, the applicant stated that the ZUMA-2 study sample is 
representative of the Medicare population. The applicant stated that 
57% of the sample were 65 to 79 years of age, and that MCL 
predominantly affects older adults, with a median age at diagnosis 
ranging from 65 to 73.564 565 The applicant asserted that 
the advanced disease characteristics, including Stage IV disease in 
85%, bone marrow involvement in 54%, and splenic involvement in 34%, 
closely align with those observed in the general MCL population where 
newly diagnosed and previously untreated patients present with stage 
III/IV disease and commonly exhibit splenomegaly and bone marrow 
infiltration.\566\ The applicant added that the key baseline 
characteristics of the ZUMA-2 population mirror the r/r MCL Medicare 
population refractory to BTK inhibitors, including age of study 
subjects and stage of disease at study initiation. Overall, ZUMA-2 
primary results showed that at the time of the analysis cutoff (July 
2019), 16 of 68 subjects (24%) had died; 4 deaths occurred >30 days 
through 3 months after infusion of TECARTUS[supreg] and 12 deaths 
occurred >=3 months after infusion of TECARTUS[supreg]. Fourteen of the 
16 subjects died as a result of progressive disease and two of the 16 
subjects died due to AEs (Grade 5 AE of staphylococcal bacteremia and 
Grade 5 AE of organizing pneumonia).
---------------------------------------------------------------------------

    \564\ Smith A, et al. Lymphoma incidence, survival and 
prevalence 2004-2014: Sub-type analyses from the UK's Haematological 
Malignancy Research Network. Br J Cancer. 2015;112(9):1575-84.
    \565\ Romaguera JE, et al. High rate of durable remissions after 
treatment of newly diagnosed aggressive mantle-cell lymphoma with 
rituximab plus hyper-CVAD alternating with rituximab plus high-dose 
methotrexate and cytarabine. J Clin Oncol. 2005;23(28):7013-23.
    \566\ McKay P, et al. Guidelines for investigation and 
management of mantle cell lymphoma. Br J Haematol. (2012) 159, 405-
426.
---------------------------------------------------------------------------

    Based on the information provided by the applicant, we had several 
concerns with regard to the substantial clinical improvement criterion. 
As we noted in the FY 2021 IPPS/LTCH PPS proposed rule, the combined 
sample size from the literature search and ZUMA-2 study performed by 
the applicant is relatively small. While the applicant stated that it 
closely communicated with FDA in the development of the ZUMA-2 study, 
including in the development of the sample size, we questioned whether 
the ZUMA-2 study results would support a determination of substantial 
clinical improvement given the small sample size. Although the 
applicant's analysis of the ZUMA-2 study concluded that 
TECARTUS[supreg] offers a treatment option for a patient population 
unresponsive to, or ineligible for, currently available treatments, we 
questioned whether the sample size and research presented in this 
application support extrapolating these results across the Medicare 
population.
    Relatedly, we had concerns regarding the potential for selection 
bias and its effects on results from the ZUMA-2 study. Seventy-four 
patients were enrolled in the trial and underwent leukapheresis, of 
which TECARTUS[supreg] was successfully manufactured for 71

[[Page 45102]]

(96%) and administered for 68 (92%).\567\ According to the authors, the 
primary efficacy analysis was performed among the 60 first treated 
patients who had at least 7 months of follow up. We also noted that the 
reported ORR among the first 60 is 93% (95% CI 84-98) and the ORR among 
all 74 patients enrolled is 85%. We had concerns, given the small 
sample, about the potential effects of selection bias and of patients 
being selected out of a study on the results of ZUMA-2, which forms the 
keystone of the applicant's assertions regarding substantial clinical 
improvement. Further, some research suggests that trials stopped early 
for benefit overestimate treatment effects 568 569 570 and 
that formal stopping rules do not reduce this bias, particularly in 
samples less than 500 events or cases.\571\ Given the lack of 
confidence intervals around the ORR among all 74 patients and the 
potential for the overestimation of treatment effects, we stated it was 
unclear whether there was sufficient information to determine a 
substantial clinical improvement.
---------------------------------------------------------------------------

    \567\ Wang M, et al. KTE-X19 CAR T-Cell therapy in relapsed or 
refractory mantle-cell lymphoma. N Engl J Med. (2020) 382(14): 1331-
1342.
    \568\ Pocock SJ. When (not) to stop a clinical trial for 
benefit. JAMA 2005;294:2228e30.
    \569\ Pocock SJ, Hughes MD. Practical problems in interim 
analyses, with particular regard to estimation. Control Clin Trials 
1989;10(4 Suppl): 209Se21S.
    \570\ Montori VM, Devereaux PJ, Adhikari NK, Burns KE, Eggert 
CH, Briel M, et al. Randomized trials stopped early for benefit: A 
systematic review. JAMA 2005;294:2203e9.
    \571\ Bassler D, Briel M, Montori VM, Lane M, Glasziou P, Zhou 
Q, et al. Stopping randomized trials early for benefit and 
estimation of treatment effects: systematic review and meta-
regression analysis. JAMA 2010;303:1180e7.
---------------------------------------------------------------------------

    As noted in the FY 2021 IPPS/LTCH PPS proposed rule, there had not 
been a direct study completed comparing outcomes of patients with r/r 
MCL treatment with TECARTUS[supreg] and BTK inhibitors. According to 
the applicant, ZUMA-2 remains the only study to evaluate patient 
outcomes after receiving TECARTUS[supreg] for the treatment of r/r MCL, 
but this study did not include a direct comparison to other existing 
therapies for r/r MCL. Despite there being no standard of second-line 
care for r/r MCL patients that failed on previous therapies, according 
to the applicant, a BTK inhibitor reflects the best currently available 
therapy for treating r/r MCL.\572\
---------------------------------------------------------------------------

    \572\ Campo E, Rule S. Mantle cell lymphoma: evolving management 
strategies. Blood. 2015;125(1):48-55.
---------------------------------------------------------------------------

    The applicant's assertions of substantial clinical improvement are 
based on the ZUMA-2 trial that uses a historical control ORR of 25%. 
Given that the ORR in the provided literature review of six articles 
ranges from 20%-42%, and that, according to the applicant, two specific 
articles were used to develop the pre-specified historical control rate 
(26% \573\ and 32% \574\ respectively),we stated it was unclear whether 
the historical control is appropriate or representative of r/r MCL 
patients. Furthermore, given that the applicant states that ZUMA-2 was 
not designed to compare efficacy and safety of TECARTUS[supreg] to BTK 
inhibitors, we were uncertain whether it would support a determination 
of substantial clinical improvement.
---------------------------------------------------------------------------

    \573\ Martin P, et al. Postibrutinib outcomes in patients with 
mantle cell lymphoma. Blood. 2016;127 (12):1559-63.
    \574\ Cheah CY, et al. Patients with mantle cell lymphoma 
failing ibrutinib are unlikely to respond to salvage chemotherapy 
and have poor outcomes. Ann Oncol. 2015;26(6):1175-9.
---------------------------------------------------------------------------

    We stated that, as noted in the FY 2021 IPPS/LTCH PPS proposed 
rule, a longer-term analysis of this population is not available to 
evaluate the overall survival and mortality data. We noted that the 
applicant did conduct an additional analysis of OS among the first 28 
subjects (ZUMA-2 interim analysis) which showed an OS rate estimate at 
24 months of 67.9% while the median OS was not reached. Additionally, 
the applicant referenced that all subjects in the ZUMA-2 primary 
analysis had at least 1 adverse event, and that throughout the course 
of the ZUMA-2 study, 16 deaths were recorded. However, while the 
applicant noted only 2 of these 16 deaths were related to adverse 
events, we stated that we remained concerned that further analysis may 
be needed to evaluate the safety of TECARTUS[supreg] and the longer 
term effects of the CRS and neurological events associated with the 
TECARTUS[supreg] therapy.
    We invited public comments on whether TECARTUS[supreg] meets the 
substantial clinical improvement criterion.
    Comment: A commenter submitted a comment stating that with regard 
to whether there is a high unmet need for Medicare patients with R/R 
MCL, two observations are important: (1) Median age at diagnosis of MCL 
is approximately 68 years old and (2) MCL is considered an incurable 
malignancy. The commenter stated that the median duration of remission 
is 3 to 5 years suggesting that the age at first relapse is 
approximately 70 years; this was reflected by the pivotal trial, Zuma 
2, where over half of the patients were over age 65. The commenter 
stated that the decision to treat older patients with comorbid 
conditions was not taken lightly. The commenter stated that, rather 
then focus on the specific clinical outcomes observed with 
TECARTUS[supreg] in CMS' review and in publication, that they desired 
to lend support as evidenced by their experience with the technology 
and respond directly to CMS' concerns. The commenter concluded that 
they were able to demonstrate safety and efficacy data that parallel 
the clinical trial experience in spite of treating older patients with 
comorbid conditions, many of which would have failed to meet trial 
eligibility.
    A second commenter stated their agreement with the assertion 
included in the new technology add-on payment application that the 
registration study population for the ZUMA-2 trial and the overall U.S. 
mantle cell lymphoma population are both representative of the Medicare 
population. The commenter stated that TECARTUS[supreg] has the 
potential to impact this population with an efficacy profile that is 
even stronger than that of approved CAR T-cell therapies for DLBCL.
    A third commenter stated that while MCL and DLBCL share similar 
clinical presentations, they believe the key distinction between MCL 
and large B cell Lymphoma (LBCL) in relation to CAR T-cell therapy is 
that MCL has a leukemic phase in all MCL patients that both needs to be 
accounted for in production and accounts for a higher disease burden 
driving TECARTUS[supreg] CAR19 expansion. The commenter added that the 
real-world use of TECARTUS[supreg] is heavily skewed to an elderly 
patient population with most being age 65 or older and having new 
technology add-on payment support is critical to continued 
TECARTUS[supreg] usage.
    Finally, a commenter stated support for CMS' desire for additional 
data and comment to illustrate that TECARTUS[supreg] meets the 
substantial clinical improvement criterion to support new technology 
add-on payment status.
    Response: We appreciate the input from the commenters with regard 
to TECARTUS[supreg] and we have taken these comments into consideration 
in determining whether to approve TECARTUS[supreg] for the new 
technology add-on payment, as discussed below in this section.
    Comment: In response to CMS' concern about the small sample size of 
the ZUMA-2 study, the applicant stated that sample size and power 
calculations for ZUMA-2 were carefully designed to demonstrate that 
TECARTUS[supreg] is an effective treatment for patients with r/r MCL 
who have not responded to currently available therapy. The

[[Page 45103]]

applicant reiterated that the ORR achieved in ZUMA-2 was 93% which was 
significantly higher than the prespecified historical control and the 
pooled meta-analysis ORR. The applicant asserted the ZUMA-2 study 
design called for the primary analysis to be conducted after 60 
subjects in Cohort 1 were treated with TECARTUS[supreg] and had the 
opportunity to be assessed for response 6 months after the week 4 
disease assessment. The applicant added that a sample size of 60 
subjects in cohort 1 had at least 96% power to distinguish between an 
active therapy with a true response rate of 50% or higher from a 
therapy with an ORR of 25% or less 575 576 with a 1-sided 
alpha level of 0.025. The applicant added that the ZUMA-2 study 
reported an ORR of 93% (95% CI: 83.8%, 98.2%) after a single-dose of 
TECARTUS[supreg], significantly higher than the prespecified historical 
control rate of 25% (p <0.0001) and the meta-analysis pooled ORR rate 
of 28% (95% CI: 23%, 34%) to salvage therapies that are currently 
available.\577\ Lastly, in regard to this concern, the applicant stated 
the ZUMA-2 population, in which 57% of the study subjects were 65 years 
of age or older, was representative of the Medicare population.
---------------------------------------------------------------------------

    \575\ Cheah CY, et al. Patients with mantle cell lymphoma 
failing ibrutinib are unlikely to respond to salvage chemotherapy 
and have poor outcomes. Ann Oncol. 2015;26(6):1175-9.
    \576\ Martin P, et al. Postibrutinib outcomes in patients with 
mantle cell lymphoma. Blood. 2016;127 (12):1559-63.
    \577\ Wang M, et al. KTE-X19 CAR T-Cell therapy in relapsed or 
refractory mantle-cell lymphoma. N Engl J Med. (2020) 382(14): 1331-
1342.
---------------------------------------------------------------------------

    In response to CMS' concerns about the potential for selection bias 
and the differences of the ORR among the first 60 patients as compared 
to that from all 74 patients, the applicant commented that the observed 
ORR in ZUMA-2 is consistently higher than the prespecified historical 
control rate or the pooled ORR reported in the meta-analysis whether 
comparing the 60 subjects of the primary analysis or the 74 subjects in 
the full analysis. The applicant stated that the ORR from the 6-study 
meta-analysis was 28% (95% CI: 23-34%) which when compared to the 
updated analysis for the efficacy analysis (n=60) ORR of 92% (95% CI: 
81.6%, 97.2%) and the full analysis set (n=74) ORR of 84% (95% CI: 
73.4%, 91.3%) continues to show no overlap of confidences intervals. 
Lastly, in response to this concern, the applicant states that it is 
important to note that ZUMA-2 was not stopped early and is ongoing with 
18 months of follow-up data available.
    In response to CMS' concern that the historical control may not be 
appropriate or representative of r/r MCL patients, and that ZUMA-2 was 
not designed to compare efficacy and safety of TECARTUS[supreg] to BTK 
inhibitors, the applicant commented that the prespecified historical 
control rate for ORR in ZUMA-2, the meta-analyses subsequently 
conducted, and a separate systematic literature review and sensitivity 
meta-analysis provide a complete review of published clinical studies 
(through February 2019). The applicant stated the prespecified 
historical control rate was based on two retrospective studies that 
were published at the time of ZUMA-2 protocol development; these two 
studies demonstrated that patients with r/r MCL who had >=3 prior lines 
of therapy before receiving a BTK inhibitor had ORRs to salvage therapy 
of approximately 25%.578 579 The applicant asserted that 
subsequent to the initial historical control rate estimation, the 
applicant conducted a meta-analysis of 6 published clinical studies and 
commissioned an independent systematic literature review, resulting in 
an updated, sensitivity meta-analysis. The applicant added that the 
pooled ORR estimate from the 6-study meta-analysis 
580 581 582 583 584 585 (ORR: 28%, 95% CI, 23%, 34%) is 
reported in Table 3 in the TECARTUS[supreg] new technology add-on 
payment application. The applicant stated ZUMA-2 had no comparator arm 
because there was no effective standard therapy for patients with r/r 
MCL after they had progressed. Therefore, according to the applicant, 
an historical control was the only ethical and feasible study design 
for patients with r/r MCL who have not responded to the most promising 
therapies available, including BTK inhibitors. Lastly, the applicant 
asserts that the FDA recognizes a historical control as a valid 
comparison of the experimental group in clinical trials used to provide 
evidence that a product is safe and effective for its intended 
use.\586\
---------------------------------------------------------------------------

    \578\ Cheah CY, et al. Patients with mantle cell lymphoma 
failing ibrutinib are unlikely to respond to salvage chemotherapy 
and have poor outcomes. Ann Oncol. 2015;26(6):1175-9.
    \579\ Martin P, et al. Postibrutinib outcomes in patients with 
mantle cell lymphoma. Blood. 2016;127 (12):1559-63.
    \580\ Cheah CY, et al. Patients with mantle cell lymphoma 
failing ibrutinib are unlikely to respond to salvage chemotherapy 
and have poor outcomes. Ann Oncol. 2015;26(6):1175-9.
    \581\ Martin P, et al. Postibrutinib outcomes in patients with 
mantle cell lymphoma. Blood. 2016;127 (12):1559-63.
    \582\ Dreyling M, et al. Ibrutinib versus temsirolimus in 
patients with relapsed or refractory mantle-cell lymphoma: an 
international, randomised, open-label, phase 3 study. Lancet. 
2016;387(10020):770-8.
    \583\ Epperla N, et al. Predictive factors and outcomes for 
ibrutinib therapy in relapsed/refractory mantle cell lymphoma--a 
``real world'' study. Hematological Oncology. 2017:1-8.
    \584\ Wang M, et al. Observational study of lenalidomide in 
patients with mantle cell lymphoma who relapsed/progressed after or 
were refractory/intolerant to ibrutinib (MCL-004). J Hematol Oncol. 
2017;10:171.
    \585\ Jain P, et al. Long-term outcomes and mutation profiling 
of patients with mantle cell lymphoma (MCL) who discontinued 
ibrutinib. Br J Haematol. 2018a;183:578-87.
    \586\ Rare Diseases and Orphan Products--Institute of Medicine 
(US) Committee on Accelerating Rare Diseases Research and Orphan 
Product Development; Field MJ, Boat TF, editors. Rare Diseases and 
Orphan Products: Accelerating Research and Development. Washington 
(DC): National Academies Press (US); 2010. 3, Regulatory Framework 
for Drugs for Rare Diseases. Available from: https://www.ncbi.nlm.nih.gov/books/NBK56185/.
---------------------------------------------------------------------------

    Lastly, in response to CMS' concern that a longer-term analysis of 
the population of interest is not available to evaluate the overall 
survival and mortality data, the applicant commented that updated 
efficacy and safety data was submitted in the TECARTUS[supreg] new 
technology add-on payment application dated December 31, 2019, which 
represented the first update following the primary analysis. The 
applicant then stated that an updated 18-month analysis, with a cut-off 
date of December 31, 2020, has been completed but is confidential. The 
applicant then stated that the data confirmed there were no changes to 
overall incidence in the following safety categories as compared to the 
primary analysis results: Adverse events, serious adverse events, 
related adverse events, related serious adverse events, any cytokine 
release syndrome (CRS), grade 3 or higher CRS, overall neurologic 
events, and grade 3 or higher neurologic events. The applicant added 
that there were no changes to comparisons of CRS or neurologic events 
across age group comparisons (>=65 years of age and <65 years of age). 
The applicant further stated two additional deaths occurred between the 
data cutoff dates for the primary analysis and that updated analysis 
due to disease progression: 18 of 68 Subjects in ZUMA-2 (26%) had died 
as of the December 31, 2019 updated analysis cutoff. The applicant 
added, of these, 4 deaths occurred >30 days through 3 months after 
infusion of TECARTUS[supreg] and 14 deaths occurred >=3 months after 
infusion of TECARTUS[supreg]. The applicant further added that sixteen 
(16) of the 18 subjects died as a result of progressive disease; two 
subjects died due to AEs other than disease progression: 1 subject had 
a Grade 5 AE of Staphylococcal bacteremia (deemed

[[Page 45104]]

related to conditioning chemotherapy and TECARTUS[supreg]), and 1 
subject had a Grade 5 AE of organizing pneumonia (deemed related to 
conditioning chemotherapy).
    Response: We thank the applicant for its comment and additional 
information regarding the substantial clinical improvement criterion. 
After consideration of the comments received, we agree with the 
applicant and commenters that TECARTUS[supreg] represents a substantial 
clinical improvement over existing therapies for relapsed and 
refractory MCL because TECARTUS[supreg] allows access to a treatment 
option for patients unresponsive to or ineligible for currently 
available therapies, including patients who have progressed following a 
prior BTK inhibitor. In addition, we believe that the ORR of 93% seen 
after one dose with TECARTUS[supreg], and the difference in ORR between 
use of TECARTUS[supreg] and the historical controls demonstrate a 
substantial clinical improvement over existing technologies.
    After consideration of the public comments we received and the 
information included in the applicant's new technology add-on payment 
application, we have determined, for the reasons stated previously, 
that TECARTUS[supreg] meets the criteria for approval of the new 
technology add-on payment. Therefore, we are approving new technology 
add-on payments for this technology for FY 2022. Cases involving the 
use of TECARTUS[supreg] that are eligible for new technology add-on 
payments will be identified by procedure codes XW033M7 (Introduction of 
brexucabtagene autoleucel immunotherapy into peripheral vein, 
percutaneous approach, new technology group 7) or XW043M7 (Introduction 
of brexucabtagene autoleucel immunotherapy into central vein, 
percutaneous approach, new technology group 7).
    In its application, the applicant estimated that the cost of 
TECARTUS[supreg] is $373,000.00 per patient. Under Sec.  412.88(a)(2), 
we limit new technology add-on payments to the lesser of 65 percent of 
the average cost of the technology, or 65 percent of the costs in 
excess of the MS-DRG payment for the case. However, in their public 
comment the applicant stated that effective April 15, 2021, the WAC for 
TECARTUS[supreg] is $399,000.00 per each patient-specific, single-
infusion bag.\587\ As a result, the maximum new technology add-on 
payment for a case involving the use of TECARTUS[supreg] is $259,350 
for FY 2022.
---------------------------------------------------------------------------

    \587\ FDB MedKnowledge Product Update Report: 4/15/2021.
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o. VEKLURY[supreg] (remdesivir)
    Gilead Sciences, Inc. submitted an application for new technology 
add-on payments for VEKLURY[supreg] (remdesivir) for FY 2022. 
VEKLURY[supreg] is a nucleotide analog that inhibits viral RNA-
dependent RNA polymerases, demonstrating activity countering viral 
pathogens such as severe acute respiratory syndrome coronavirus 2 
(SARS-CoV-2), the virus that causes coronavirus disease 2019 (COVID-
19).
    According to the applicant, spread of COVID-19 is presumed largely 
to occur through respiratory droplets and approximately 80% is 
predicted to occur by pre- and asymptomatic individuals. The applicant 
asserted viral incubation averages 3-7 days and can occur for up to 2 
weeks.\588\ According to the applicant, once infected, approximately 
81% of COVID-19 patients experience mild disease, 14% experience severe 
disease, and 5% experience critical disease.\589\ The applicant stated 
that severity of disease changes with age--approximately 113 in 100,000 
people aged 18-49 years are hospitalized, compared to 250 in 100,000 
aged 50-64 years and 451 in 100,000 aged 65+.\590\ The applicant 
asserted that other risk factors for severity include underlying 
comorbidities but severe illness can occur in otherwise healthy 
individuals at any age.\591\
---------------------------------------------------------------------------

    \588\ Cascella M, Rajnik M, Cuomo A, et al. Features, 
Evaluation, and Treatment of Coronavirus (COVID-19). StatPearls, 
published August 10, 2020. https://www.ncbi.nlm.nih.gov/books/NBK554776/.
    \589\ McIntosh K, Hirsch MS (ed), and Bloom A (ed). Coronavirus 
disease 2019 (COVID-19): Clinical features. UpToDate, updated 
September 14, 2020. https://www.uptodate.com/contents/coronavirusdisease-2019-covid-19-clinical-features.
    \590\ Centers for Disease Control and Prevention (CDC). 
COVIDView A weekly Surveillance Summary of U.S. COVID-19 Activity, 
published September 11, 2020. https://www.cdc.gov/coronavirus/2019-ncov/covid-data/covidview/index.html.
    \591\ McIntosh K, Hirsch MS (ed), and Bloom A (ed). Coronavirus 
disease 2019 (COVID-19): Clinical features. UpToDate, updated 
September 14, 2020. https://www.uptodate.com/contents/coronavirusdisease-2019-covid-19-clinical-features.
---------------------------------------------------------------------------

    According to the applicant, patients who present to the hospital 
with evidence of pneumonia may require supplemental oxygen in severe 
cases, or, those with critical illness may develop hypoxemic 
respiratory failure, acute respiratory distress syndrome, and 
multiorgan failure that requires ventilation support.\592\ The 
applicant cited one study of 2,482 hospitalized COVID-19 patients, in 
which 32% of patients were admitted to the intensive care unit (ICU) 
for a median stay of 6 days and 19% received invasive mechanical 
ventilation, 53% of whom died in the hospital.\593\
---------------------------------------------------------------------------

    \592\ Ibid.
    \593\ Kim L, Garg S, O'Halloran A, et al. Risk Factors for 
Intensive Care Unit Admission and Inhospital Mortality Among 
Hospitalized Adults Identified through the US Coronavirus Disease 
2019 (COVID-19)-Associated Hospitalization Surveillance Network 
(COVID-NET). Clinical Infectious Diseases. 2020; ciaa1012, https://doi.org/10.1093/cid/ciaa1012.
---------------------------------------------------------------------------

    According to the applicant, VEKLURY[supreg] received FDA approval 
for use in the inpatient setting on October 22, 2020 via Priority 
Review and had received Fast Track designation.\594\ Under the New Drug 
Application (NDA) FDA approval, VEKLURY[supreg] is indicated for adults 
and pediatric patients (12 years of age and older and weighing at least 
40 kg) for the treatment of COVID-19 requiring 
hospitalization.595 596 Prior to its approval, on May 1, 
2020, VEKLURY[supreg] received an Emergency Use Authorization (EUA) 
from FDA for the treatment of suspected or laboratory-confirmed COVID-
19 in adults and children hospitalized with severe disease.\597\ 
VEKLURY[supreg] continues to have an EUA for pediatric patients (12 
years of age or younger weighing at least 3.5 kg or weighing 3.5 kg to 
less than 40 kgs) for emergency use to treat suspected or laboratory-
confirmed COVID-19 in hospitalized pediatric 
patients.598 599
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    \594\ FDA. FDA News Release: FDA Approves First Treatment for 
COVID-19, published October 22, 2020. https://www.fda.gov/news-events/press-announcements/fda-approves-first-treatment-covid-19.
    \595\ VEKLURY[supreg] NDA approval: https://www.accessdata.fda.gov/drugsatfda_docs/appletter/2020/214787Orig1s000ltr.pdf; https://www.fda.gov/media/143189/download.
    \596\ FDA. Fact Sheet for Health Care Providers Emergency Use 
Authorization (EUA) of VEKLURY[supreg] (remdesivir): https://www.fda.gov/media/137566/download.
    \597\ FDA News Release: Coronavirus (COVID-19) Update: FDA 
Issues Emergency Use Authorization for Potential COVID-19 Treatment. 
Published May 1, 2020. https://www.fda.gov/news-events/press-announcements/coronavirus-covid-19-update-fda-issues-emergency-use-authorization-potential-covid-19-treatment.
    \598\ VEKLURY[supreg] EUA: https://www.fda.gov/media/137564/download.
    \599\ FDA News Release: COVID-19 Update: FDA Broadens Emergency 
Use Authorization for VEKLURY[supreg] (remdesivir) to Include All 
Hospitalized Patients for Treatment of COVID-19, published August 
28, 2020. https://www.fda.gov/news-events/press-announcements/covid-19-update-fda-broadens-emergency-use-authorization-VEKLURY[supreg]-
remdesivir-include-all-hospitalized.
---------------------------------------------------------------------------

    According to the applicant, VEKLURY[supreg] has been available 
under the EUA since it was first issued in May 2020 for emergency use 
in the inpatient setting for patients with COVID-19. The applicant 
asserted that between July 1, 2020 and September 30, 2020, it entered

[[Page 45105]]

into an agreement with the U.S. Government to allocate and distribute 
commercially-available VEKLURY[supreg] across the country.\600\ The 
applicant stated that under this agreement, the first sale of 
VEKLURY[supreg] was completed on July 10, 2020. The applicant stated 
that they transitioned to a more traditional, unallocated model of 
distribution as of October 1, 2020.
---------------------------------------------------------------------------

    \600\ Veklury (remdesivir)--ASPR's Portfolio of COVID-19 Medical 
Countermeasures Made Available as a Licensed Product https://www.phe.gov/emergency/events/COVID19/investigation-MCM/Pages/Veklury.aspx.
---------------------------------------------------------------------------

    According to the applicant, as of August 1, 2020, VEKLURY[supreg] 
is uniquely identified by ICD-10-PCS codes XW033E5 (Introduction of 
remdesivir anti-infective into peripheral vein, percutaneous approach, 
new technology group 5) and XW043E5 (Introduction of remdesivir anti-
infective into central vein, percutaneous approach, new technology 
group 5). Prior to August 1, 2020, the generic, non-COVID-19 ICD-10-PCS 
codes 3E033GC (Introduction of other therapeutic substance into 
peripheral vein, percutaneous approach) and 3E043GC (Introduction of 
other therapeutic substance into central vein, percutaneous approach) 
could be reported for the use of VEKLURY[supreg].
    As discussed previously, if a technology meets all three of the 
substantial similarity criteria, it would be considered substantially 
similar to an existing technology and would not be considered ``new'' 
for purposes of new technology add-on payments.
    With regard to the first criterion, whether a product uses the same 
or a similar mechanism of action to achieve a therapeutic outcome, the 
applicant asserted VEKLURY[supreg] is a SARS-CoV-2 nucleotide analog 
RNA polymerase inhibitor, and that there are no other antiretroviral 
therapies that have received an EUA or an approval from FDA to treat 
COVID-19. The applicant stated, however, that convalescent plasma has 
also received an EUA for the treatment of hospitalized patients with 
COVID-19.601 602 According to the applicant, convalescent 
plasma is collected from individuals who have been infected with SARS-
CoV-2 and have developed antibodies to the virus. The applicant stated 
that plasma is transfused into infected patients with the expectation 
that the antibodies present will neutralize the virus.\603\ The 
applicant asserted this mechanism of action is different from 
VEKLURY[supreg] which works as a nucleotide analog to inhibit viral 
replication. We noted that, as a result of their evaluation of the most 
recent information available, on February 4, 2021 FDA reissued the EUA 
for convalescent plasma. The EUA authorizes only the use of high titer 
COVID-19 convalescent plasma, for the treatment of hospitalized 
patients early in the course of disease. The use of low titer COVID-19 
convalescent plasma is not authorized under the EUA.\604\
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    \601\ Convalescent plasma EUA: https://www.fda.gov/media/141477/download.
    \602\ FDA. Emergency Use Authorizations: Drug and Biological 
Products. 2020. https://www.fda.gov/emergency-preparedness-and-response/mcm-legal-regulatory-and-policy-framework/emergency-use-authorization#coviddrugs.
    \603\ Liu STH, Li MH, Baine I, at al. Convalescent plasma 
treatment of severe COVID-19: A propensity score-matched control 
study. Nature Medicine. 2020. https://doi.org/10.1038/s41591-020-1088-9.
    \604\ FDA reissued the EUA on March 9, 2021. FDA In Brief: FDA 
Updates Emergency Use Authorization for COVID-19 Convalescent Plasma 
to Reflect New Data, published February 4, 2021. https://www.fda.gov/news-events/fda-brief/fda-brief-fda-updates-emergency-use-authorization-covid-19-convalescent-plasma-reflect-new-data and 
https://www.fda.gov/media/141477/download.
---------------------------------------------------------------------------

    We noted that another inpatient treatment for COVID-19, 
Olumiant[supreg] (baricitinib), in combination with VEKLURY[supreg], 
has received an EUA. Specifically, the EUA for Olumiant[supreg], which 
should be administered in combination with VEKLURY[supreg], is for the 
treatment of COVID-19 in certain hospitalized patients requiring 
supplemental oxygen, invasive mechanical ventilation, or extracorporeal 
membrane oxygenation (ECMO).\605\ Olumiant[supreg] is a Janus kinase 
(JAK) inhibitor with prior FDA approval for another indication--the 
treatment of adult patients with moderately to severely active 
rheumatoid arthritis who have had inadequate response to one or more 
tumor necrosis factor (TNF) antagonist therapies.\606\
---------------------------------------------------------------------------

    \605\ Olumiant[supreg] EUA: https://www.fda.gov/media/143822/download.
    \606\ Olumiant[supreg] (baricitinib) [package insert]. FDA, 
revised July 8, 2020. https://www.accessdata.fda.gov/drugsatfda_docs/label/2020/207924s002lbl.pdf.
---------------------------------------------------------------------------

    According to the applicant, because of the rapidly evolving nature 
of the COVID-19 pandemic, there is not a current standard of care used 
across hospitals in the United States.
    With regard to the second criterion, whether the technology is 
assigned to the same or a different MS-DRG, the applicant asserted that 
as there no other antiretroviral therapies for the treatment of 
patients with COVID-19, VEKLURY[supreg] could not be assigned to the 
same MS-DRG as existing technologies.
    With regard to the third criterion, whether the new use of the 
technology involves the treatment of the same or similar type of 
disease and the same or similar patient population, the applicant 
asserted VEKLURY[supreg] represents a novel treatment option for 
patients with COVID-19 who are hospitalized. The applicant stated 
COVID-19 is a completely separate disease from those caused by other 
coronaviruses. The applicant asserted severe acute respiratory syndrome 
(SARS) is caused by the coronavirus SARS-CoV and was first reported in 
2003. The applicant stated SARS symptoms were similar to COVID-19 and 
included high fever, body aches, and mild respiratory symptoms but no 
treatments specific to SARS-CoV have been developed.\607\ According to 
the applicant, MERS-CoV, the Middle east respiratory syndrome 
coronavirus, was first identified in 2012 and has some similarities in 
etiology to SARS-CoV-2 but lacks treatment options.\608\
---------------------------------------------------------------------------

    \607\ CDC. Severe Acute Respiratory Syndrome (SARS), updated 
December 6, 2017. https://www.cdc.gov/sars/index.html.
    \608\ CDC. About MERS, Updated August 2, 2019. https://www.cdc.gov/coronavirus/mers/about/index.html.
---------------------------------------------------------------------------

    Based on the applicant's statements as summarized previously, the 
applicant believes that VEKLURY[supreg] is not substantially similar to 
other currently available therapies and/or technologies and meets the 
``newness'' criterion. In the proposed rule, we noted that although 
there may not be other antiretrovirals available for the treatment of 
COVID-19, cases involving VEKLURY[supreg] may map to the same MS-DRGs 
as other treatments for COVID-19. We also noted that VEKLURY[supreg] 
may not treat a different disease or patient population as existing 
treatments for COVID-19, as Olumiant[supreg] (administered with 
VEKLURY[supreg]) and convalescent plasma appear to treat the same 
disease and similar patient population.
    In the FY 2009 IPPS final rule (73 FR 48561 through 48563), we 
revised our regulations at Sec.  412.87 to codify our longstanding 
practice of how CMS evaluates the eligibility criteria for new medical 
service or technology add-on payment applications. We stated that new 
technologies that have not received FDA approval do not meet the 
newness criterion. In addition, we stated we do not believe it is 
appropriate for CMS to determine whether a medical service or 
technology represents a substantial clinical improvement over existing 
technologies before the FDA makes a determination as to whether the 
medical service or technology is safe and effective. For these reasons, 
we first determine whether a new technology meets the newness 
criterion, and only if so, do we make a determination as to whether the 
technology meets the cost threshold and represents a substantial

[[Page 45106]]

clinical improvement over existing medical services or technologies. We 
also finalized at 42 CFR 412.87(c) (subsequently redesignated as 
412.87(e)) that all applicants for new technology add-on payments must 
have FDA approval or clearance by July 1 of the year prior to the 
beginning of the fiscal year for which the application is being 
considered.
    In the FY 2021 IPPS/LTCH PPS final rule, to more precisely describe 
the various types of FDA approvals, clearances, licensures, and 
classifications that we consider under our new technology add-on 
payment policy, we finalized a technical clarification to Sec.  
412.87(e)(2) to indicate that new technologies must receive FDA 
marketing authorization (for example, pre-market approval (PMA); 510(k) 
clearance; the granting of a De Novo classification request; approval 
of a New Drug Application (NDA); or Biologics License Application (BLA) 
licensure) by July 1 of the year prior to the beginning of the fiscal 
year for which the application is being considered. As noted in the FY 
2021 IPPS/LTCH PPS final rule, this technical clarification did not 
change our longstanding policy for evaluating whether a technology is 
eligible for new technology add-on payment for a given fiscal year, and 
we continue to consider FDA marketing authorization as representing 
that a product has received FDA approval or clearance for purposes of 
eligibility for the new technology add-on payment under Sec.  
412.87(e)(2) (85 FR 58742).
    An EUA by the FDA allows a product to be used for emergency use, 
but under our longstanding policy, we believe it would not be 
considered an FDA marketing authorization for the purpose of new 
technology add-on payments, as a product that is available only through 
an EUA is not considered to have FDA approval or clearance. Therefore, 
under the current regulations at 42 CFR 412.87(e)(2) and consistent 
with our longstanding policy of not considering eligibility for new 
technology add-on payments prior to a product receiving FDA approval or 
clearance, we believe a product available only through an EUA would not 
be eligible for new technology add-on payments. Therefore, cases 
involving hospitalized pediatric patients (12 years of age or younger 
weighing at least 3.5 kg or weighing 3.5 kg to less than 40 kgs) 
receiving VEKLURY[supreg] for emergency use to treat suspected or 
laboratory-confirmed COVID-19 are not eligible for new technology add-
on payment.
    We refer the reader to our comment solicitation in section II.F.7 
of the preamble of the proposed rule (86 FR 25394 through 25395) 
regarding how data reflecting the costs of a product with an EUA, which 
may become available upon authorization of the product for emergency 
use (but prior to FDA approval or clearance), should be considered for 
purposes of the 2-year to 3-year period of newness for new technology 
add-on payments for a product with or expected to receive an EUA, 
including whether the newness period should begin with the date of the 
EUA.
    We also invited public comments on any implications of the 
distribution agreement described previously with regard to the market 
availability of VEKLURY[supreg].
    We also refer the reader to our proposal in section II.F.8 of the 
preamble of the proposed rule (86 FR 25394) to extend the new COVID-19 
treatments add-on payment (NCTAP) through the end of the fiscal year in 
which the PHE ends for certain products and discontinue NCTAP for 
products approved for new technology add-on payments in FY 2022. We 
also refer the reader to section II.F.8 of the preamble of this final 
rule, where we discuss our finalized policy to extend the NCTAP through 
the end of the fiscal year in which the PHE ends for all eligible 
products.
    We invited public comments on whether VEKLURY[supreg] meets the 
newness criterion.
    Comment: The applicant submitted a comment in response to our 
concerns regarding newness. With respect to our concern that cases 
involving VEKLURY[supreg] may map to the same MS-DRGs as other 
treatments for COVID-19 and that VEKLURY[supreg] may not treat a 
different disease or patient population as existing treatments for 
COVID-19, as Olumiant[supreg] (administered with VEKLURY[supreg]) and 
convalescent plasma appear to treat the same disease and similar 
patient population, the applicant agreed that cases involving 
VEKLURY[supreg] may map to the same MS-DRG as other treatments for 
COVID-19 because those cases are likely to have the same principal 
diagnosis.
    With regard to our concern that VEKLURY may not treat a different 
disease or patient population, the applicant stated that COVID-19 is 
noted to have discrete phases, including an early infectious phase, a 
pulmonary phase, and a hyperinflammatory phase. According to the 
applicant, VEKLURY[supreg] has a unique mechanism of action and may be 
used in patients at different phases of COVID-19, which differentiates 
it from other COVID-19 therapies.\609\ The applicant also stated that 
the utility of antiviral agents such as VEKLURY[supreg] is expected to 
be strongest in the earliest phases of COVID-19, while that of 
immunomodulators such as Olumiant or dexamethasone is likely strongest 
in the later phases of the COVID-19. The applicant also stated that 
COVID-19 drugs are currently used in conjunction with one another for 
effective treatment, depending on the patient population. For example, 
the NIH recommends VEKLURY[supreg] with or without dexamethasone for 
patients hospitalized on low-flow oxygen.\610\ Similarly, for patients 
hospitalized with high-flow oxygen/non-invasive ventilation the NIH 
guidelines recommend use of VEKLURY[supreg] with dexamethasone, and 
tocilizumab as an addition in case of rapidly progressive disease with 
systemic inflammation. The applicant noted that Olumiant is only 
recommended for use with VEKLURY[supreg] as an alternative to 
dexamethasone + VEKLURY[supreg] when corticosteroids cannot be used. 
Further, the applicant stated that the Olumiant EUA is for use in 
combination with VEKLURY[supreg], and Olumiant is not yet FDA approved 
for the treatment of COVID-19. Current NIH treatment guidelines 
recommend against use of low-titer convalescent plasma for treatment of 
COVID-19, and recommends against use of convalescent plasma for 
hospitalized patients who do not have impaired immunity.\611\
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    \609\ Siddiqi HK, Mehra MR. COVID-19 illness in native and 
immunosuppressed states: A clinical therapeutic staging proposal. J. 
Heart Lung Transplant. 2020; 39: 405-407. https://doi.org/10.1016/j.healun.2020.03.012.
    \610\ National Institutes of Health. Therapeutic Management of 
Adults with COVID-19. Last updated May 24, 2021. https://www.covid19treatmentguidelines.nih.gov/therapeutic-management/.
    \611\ Ibid.
---------------------------------------------------------------------------

    Response: We thank the applicant for its comment and additional 
input regarding the newness criterion. After consideration of the 
comment received and information submitted by the applicant, we 
continue to believe that the new use of the technology may involve the 
treatment of the same or similar type of disease and the same or 
similar patient population as existing technologies that treat COVID-
19, such as Olumiant (administered with VEKLURY[supreg]). However, we 
agree that VEKLURY[supreg] does not use the same or a similar mechanism 
of action to achieve a therapeutic outcome when compared to existing 
treatment. VEKLURY[supreg] works as a nucleotide analog to inhibit 
viral replication and there are no other antiretroviral therapies that 
have received an EUA or an approval from

[[Page 45107]]

FDA to treat COVID-19. Therefore, we believe that VEKLURY[supreg] is 
not substantially similar to an existing technology and meets the 
newness criterion with an indication for use in adults and pediatric 
patients (12 years of age and older and weighing at least 40 kg) for 
the treatment of COVID-19 requiring hospitalization. Consistent with 
our longstanding policy, we consider the newness period to begin on 
October 22, 2020, when the NDA for VEKLURY[supreg] was approved by the 
FDA. We refer the reader to section II.F.7. of this final rule for a 
discussion of the comment solicitation regarding the newness period for 
products available through an EUA for COVID-19 including a summary of 
the comments received from the applicant and other commenters regarding 
this solicitation.
    With regard to the cost criterion, the applicant used the FY 2019 
MedPAR LDS and the February through June 2020 Electronic Data 
Interchange (EDI) transaction data to identify applicable cases. The 
applicant used the FY 2022 thresholds and the FY 2019 NPRM IPPS/LTCH 
impact file to standardize charges. As COVID-19 is an emergent disease, 
the applicant asserted that FY 2019 MedPAR claims may not be reflective 
of actual cases. Accordingly, and as summarized below, the applicant 
identified the FY 2019 MedPAR cases as proxy COVID-19 cases in its cost 
analysis. To supplement and confirm its MedPAR findings, the applicant 
used EDI data that includes actual COVID-19 cases from February through 
June 2020 to capture what the applicant described as true COVID-19 MS-
DRG mapping and charges.
    For the MedPAR LDS cases, the applicant used B97.29 with a 
manifestation code (J12.89 or J20.8 or J40 or J22 or J98.8 or J80). 
According to the applicant, this is based on the CDC guidance which 
specifies use of B97.29 with additional coding to identify the 
manifestation prior to the April 1, 2020 COVID-19 code. The applicant 
developed 3 sensitivity scenarios to further differentiate the MedPAR 
cases; Scenario 1: All Proxy COVID-19, Scenario 2: Proxy COVID-19 
without ventilation, and Scenario 3: Proxy COVID19 with ventilation. 
Next, the applicant analyzed linked 837 and 835 inpatient EDI 
transaction sets that were processed February through June of 2020. The 
837 and 835 transaction sets are updated daily and stored in the 
Inovalon provider research datasets, accounting for approximately 5-7% 
of the total Medicare FFS volume nationally on average. For cases prior 
to April 1, the applicant used the same coding as the MedPAR analysis. 
For claims on or after April 1, 2020, the applicant used the actual 
COVID-19 code U07.1. The applicant then identified cases using the 3 
sensitivity scenarios; Scenario 4: All COVID-19, Scenario 5: COVID-19 
without ventilation, and Scenario 6: COVID-19 with ventilation.
    The claim search conducted by the applicant identified 1,726 cases 
mapping to 25 MS-DRGs for scenario one, 274 cases mapping to eight MS-
DRGs for scenario two, 1,393 cases mapping to 21 MS-DRGs for scenario 
three, 3,826 cases mapping to 21 MS-DRGs for scenario four, 859 cases 
mapping to seven MS-DRGs for scenario five, and 2,917 cases mapping to 
14 MS-DRGs for scenario six. The MS-DRGs identified in each scenario 
are listed in the following tables.
BILLING CODE 4120-01-P

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BILLING CODE 4120-01-C
    The applicant determined an average unstandardized case weighted 
charge per case of $56,643 for Scenario 1; $82,733 for Scenario 2; 
$51,100 for Scenario 3; $75,891 for Scenario 4; $131,004 for Scenario 
5; and $59,393 for Scenario 6.
    The applicant stated that 33 percent of the length of stay charges 
from relevant cases were removed as charges for and related to the 
prior technologies in order to estimate the potential decrease in 
length of stay achieved by use of VEKLURY[supreg]. The applicant stated 
that these length of stay charges were removed from relevant cases to 
conservatively estimate the potential reduction in charges due to 
decreased length of stay through use of VEKLURY[supreg]. The applicant 
asserted that this offset was determined based on findings from the 
Adaptive COVID-19 Treatment Trial (ACTT-1), which found those treated 
with VEKLURY[supreg] had a median recovery time of 10 days, as compared 
with 15 days for those who received placebo.
    After calculating the average standardized charge per case for all 
scenarios, the applicant calculated the standardized charge per case 
for each MS-DRG. Next, for the analysis involving MedPAR, the applicant 
indicated that it applied the 2-year inflation factor used in the FY 
2021 IPPS/LTCH PPS final rule to calculate outlier threshold charges of 
13.1 percent. We note that the inflation factor used in the FY 2021 
IPPS/LTCH PPS final rule was 13.2 percent (1.13218) (85 FR 59039), 
which would have increased the inflated charges. For the analysis 
involving the EDI, the applicant used an inflation factor of 1.06353 or 
6.4%, which it indicated was the same inflation factor used in the FY 
2021 IPPS/LTCH PPS final rule (85 FR 59039). We note that the inflation 
factor used in the FY 2021 IPPS/LTCH PPS final rule was 6.4% (1.06404) 
(85 FR 59039), but this does not affect the cost analysis. To calculate 
the charges for the technology, the applicant used the

[[Page 45113]]

national average CCR for the Drugs cost center of 0.187 from the FY 
2021 Final IPPS rule. Lastly, the applicant calculated the case-
weighted threshold amount and the final inflated average case-weighted 
standardized charge per case for each scenario.
    The applicant stated that for Scenario 1, the final inflated 
average case-weighted standardized charge per case of $69,741 exceeded 
the average case-weighted threshold amount of $56,643 by $13,098. For 
Scenario 2, the final inflated average case-weighted standardized 
charge per case of $107,860 exceeded the average case-weighted 
threshold amount of $82,733 by $25,127. For Scenario 3, the final 
inflated average case-weighted standardized charge per case of $60,749 
exceeded the average case-weighted threshold amount of $51,100 by 
$9,649. For Scenario 4, the final inflated average case-weighted 
standardized charge per case of $110,553 exceeded the average case-
weighted threshold amount of $75,891 by $34,662. For Scenario 5, the 
final inflated average case-weighted standardized charge per case of 
$203,406 exceeded the average case-weighted threshold amount of 
$131,004 by $72,402. For Scenario 6, the final inflated average case-
weighted standardized charge per case of $63,915 exceeded the average 
case-weighted threshold amount of $59,393 by $4,522.
    The applicant stated that because the final inflated average case-
weighted standardized charge per case exceeded the average case-
weighted threshold amount, VEKLURY[supreg] meets the cost criterion.
    We invited public comment on whether VEKLURY[supreg] meets the cost 
criterion.
    Response: We did not receive comments regarding whether 
VEKLURY[supreg] meets the cost criterion. Based on the information 
included in the applicant's new technology add-on payment application, 
we believe that the VEKLURY[supreg] meets the cost criterion.
    With respect to the substantial clinical improvement criterion, the 
applicant asserted that VEKLURY[supreg] represents a substantial 
clinical improvement over existing technologies because it shortens 
time to recovery in patients hospitalized with severe COVID-19. The 
applicant also asserted that it represents a substantial clinical 
improvement because the technology results in improved clinical status 
and a trend toward reduced mortality, with the most significant 
reduction seen in a post-hoc analysis of patients with COVID-19 on low-
flow oxygen treated with VEKLURY[supreg]. The applicant further 
asserted VEKLURY[supreg] results in better clinical status for patients 
hospitalized with moderate COVID-19.
    As stated previously, the applicant asserted that VEKLURY[supreg] 
represents a substantial clinical improvement over existing 
technologies because it shortens time to recovery in patients 
hospitalized with severe COVID-19. To support this claim, the applicant 
referenced published, peer-reviewed results from the ACTT-1 study, a 
multi-center, multi-country adaptive, double-blinded, placebo-
controlled, randomized clinical trial. Patients with confirmed COVID-19 
and evidence of lung involvement were randomly assigned to receive 
either VEKLURY[supreg] (n=532; 200 mg loading dose on day 1, followed 
by 100 mg daily for up to 9 additional days) or placebo (n=516) for up 
to 10 days. Patients could receive other treatments if a participating 
hospital had a written policy or guideline for treating COVID-19. The 
study was conducted in 60 trial sites across the world with a majority 
of trial sites within the United States (45 trial sites plus 13 sub-
sites within the United States). The other sites were in Denmark (8), 
the United Kingdom (5), Greece (4), Germany (3), Korea (2), Mexico (2), 
Spain (2), Japan (1), and Singapore (1). The primary outcome measure of 
the ACTT-1 study was time to recovery, defined as the first day, from 
the time of enrollment into the study, that patients exhibited 
improvement in conditions based on hospitalization activity limitation, 
oxygen requirement, and medical care requirement.\612\
---------------------------------------------------------------------------

    \612\ Beigel JH, Tomashek KM, Dodd LE, et al. Remdesivir for the 
Treatment of Covid-19--Final Report. N Engl J Med. 2020.
---------------------------------------------------------------------------

    According to the applicant, as part of the trial design, an interim 
analysis was planned to determine if the study should be stopped early 
for futility, efficacy, or safety, if there was clear and substantial 
evidence of a treatment difference between study drug and placebo. An 
independent data and safety monitoring board met to review interim data 
and determined VEKLURY[supreg] was better than a placebo for the 
primary endpoint, time to recovery.\613\ The applicant stated those 
treated with VEKLURY[supreg] had a median recovery time of 10 days, as 
compared with 15 days for those who received placebo (rate ratio for 
recovery, 1.29; 95% confidence interval [CI], 1.12 to 1.49; P <0.001), 
and the number of serious adverse events was lower in the 
VEKLURY[supreg] treated group.\614\
---------------------------------------------------------------------------

    \613\ The National Institutes of Health (NIH). NIH clinical 
trial shows Remdesivir accelerates recovery from advanced COVID-19, 
published April 29, 2020. https://www.nih.gov/news-events/news-releases/nih-clinical-trial-shows-remdesivir-accelerates-recovery-advanced-covid-19.
    \614\ Beigel JH, Tomashek KM, Dodd LE, et al. Remdesivir for the 
Treatment of Covid-19--Final Report. N Engl J Med. 2020.
---------------------------------------------------------------------------

    As stated previously, the applicant asserted VEKLURY[supreg] 
represents a substantial clinical improvement over existing 
technologies because use of VEKLURY[supreg] results in improved 
clinical status and reduced mortality in patients with COVID-19 on low-
flow oxygen. According to the applicant, the pivotal ACTT-1 study 
showed an overall trend toward reduction in mortality with the most 
significant reduction observed in a post-hoc analysis of patients on 
low-flow oxyen treated with VEKLURY[supreg]. The overall mortality 
effect was not statistically significant. The applicant stated those 
treated with VEKLURY[supreg] continued to receive oxygen for fewer days 
(median, 13 days vs. 21 days) and the incidence of new oxygen use was 
lower in the VEKLURY[supreg] group (incidence, 36%; 95% CI, 26% to 47%) 
compared with the placebo group (incidence, 44%; 95% CI, 33% to 57%). 
In the post-hoc analysis, those receiving low-flow supplemental oxygen 
(that is, not those receiving noninvasive ventilation or high-flow 
oxygen, nor those receiving invasive mechanical ventilation or ECMO) 
treated with VEKLURY[supreg] had the largest reduction in mortality 
compared to the same cohort receiving the placebo (hazard ratio, 0.30; 
95% CI, 0.14 to 0.64).\615\
---------------------------------------------------------------------------

    \615\ Ibid.
---------------------------------------------------------------------------

    As stated previously, the applicant asserted VEKLURY[supreg] 
results in better clinical status for patients hospitalized with 
moderate COVID-19. To support this claim, the applicant referenced 
published, peer-reviewed results from an open label, placebo 
controlled, randomized clinical trial. Patients with moderately severe 
COVID-19 (pulmonary infiltrates on imaging but oxygen saturation >94 
percent on room air) were randomly assigned to receive either 
VEKLURY[supreg] plus continued standard of care for 10 days (n=197), 
VEKLURY[supreg] plus continued standard of care for 5 days (n=199), or 
continued standard of care (n=200). Standard of care could include use 
of concomitant medications such as steroids, hydroxychloroquine/
chloroquine, lopinavir-ritonavir, tocilizumab, and azithromycin. The 
median time to start VEKLURY[supreg] treatment was 8 days after start 
of symptoms. The median length of treatment in the 10-day group was 
actually 6 days. Patients who improved could be discharged from the 
hospital before completing their assigned course of treatment. The 
study was conducted

[[Page 45114]]

in 105 trial sites in the United States, Europe and Asia. The primary 
end point was assessment of clinical status on day 11 after initiation 
of treatment. Clinical status was assessed on a 7-point ordinal scale 
ranging from death (category 1) to discharged (category 7).\616\
---------------------------------------------------------------------------

    \616\ Spinner CD, Gottlieb RL, Criner GJ, et al. Effect of 
Remdesivir vs Standard Care on Clinical Status at 11 Days in 
Patients With Moderate COVID-19 A Randomized Clinical Trial. JAMA. 
2020; 342(11):1048-1057.
---------------------------------------------------------------------------

    According to the applicant, on day 11, patients with moderate 
COVID-19 treated with VEKLURY[supreg] for 5 days had a better clinical 
status compared with the standard of care (odds ratio 1.65; 95% CI, 
1.09 to 2.48, P=0.02). The applicant stated the difference was not 
statistically significant between those treated with VEKLURY[supreg] 
for 10 days compared with the standard of care (P=0.18 by Wilcoxon rank 
sum test; the proportional odds assumption was not met for this 
comparison). The applicant asserted that post hoc analyses demonstrated 
improved clinical status in both the 5- and 10-day treated cohorts at 
14 days (P=.03 for both groups). The applicant stated there were no 
significant differences in adverse events for those treated with 
Veklury for 5 days.\617\
---------------------------------------------------------------------------

    \617\ Ibid. Spinner CD, Gottlieb RL, Criner GJ, et al. Effect of 
Remdesivir vs Standard Care on Clinical Status at 11 Days in 
Patients With Moderate COVID-19 A Randomized Clinical Trial. JAMA. 
2020; 342(11):1048-1057.
---------------------------------------------------------------------------

    In the proposed rule, we noted that the articles submitted by the 
applicant in support of substantial clinical improvement used study 
designs that may be subject to bias, such as the adaptive and open 
label design. The ACTT-1 study included a prespecified interim analysis 
as part of its adaptive design but no changes were made to the placebo 
arm. We were unclear whether this may suggest that VEKLURY[supreg] did 
not demonstrate superiority over the control. We also noted the ACTT-1 
study showed considerable differences between geographic regions in 
median time to recovery for patients assigned to VEKLURY[supreg] 
compared to those assigned to placebo. For example, for the patient 
population studied at U.S. sites, the median time to recovery in the 
VEKLURY[supreg] group (n=310) vs. the placebo group (n=271) was 11 days 
vs. 16 days, respectively, whereas at non-US sites, patients treated 
with VEKLURY[supreg] (n=89) vs. placebo (n=81) experienced a median 
time to recovery of 8 vs. 12 days, respectively.\618\ Furthermore, the 
ACTT-1 study allowed other simultaneous treatments based on individual 
hospital policies or guidelines, which we stated may have potentially 
confounded the results of the trial.
---------------------------------------------------------------------------

    \618\ Beigel JH, Tomashek KM, Dodd LE, et al. Remdesivir for the 
Treatment of Covid-19--Final Report. N Engl J Med. 2020. See 
Supplementary Table S6.
---------------------------------------------------------------------------

    We invited public comments on whether VEKLURY[supreg] meets the 
substantial clinical improvement criterion.
    Comment: We received comments in support of approval of the new 
technology add-on payment for VEKLURY[supreg] with the commenters 
stating that this technology is used as standard of care for the 
treatment of hospitalized patients with COVID-19.
    Response: We appreciate these comments and will have considered 
them in our determination of substantial clinical improvement, which is 
discussed later in this section.
    Comment: The applicant submitted comments in response to CMS' 
concerns regarding the substantial clinical improvement criterion. In 
response to the concern that the articles submitted used study designs 
that may be subject to bias, such as the adaptive and open label 
design, the applicant stated that the ACTT-1 study was the first stage 
of the ACTT program and in this first stage, the only treatment 
evaluated was VEKLURY[supreg] versus placebo. The applicant stated that 
this comparison was done in a randomized, double-blinded manner and 
that this addressed potential biases and mitigated potential 
confounding. The applicant also stated that the term ``adaptive'' 
applies to the entire ACTT program as a whole, rather than any 
individual stage and that based on the superiority of VEKLURY[supreg] 
over placebo demonstrated in ACTT-1, subsequent stages of the study 
(ACTT-2, ACTT-3, ACTT-4) evaluated the efficacy of the addition of 
other treatments (for example, baricitinib, interferon-[beta], 
dexamethasone) to VEKLURY[supreg].
    The applicant also responded to CMS' concern that the ACTT-1 study 
included a prespecified interim analysis as part of its adaptive 
design, but no changes were made to the placebo arm making it unclear 
whether VEKLURY[supreg] demonstrated superiority over the control. The 
applicant noted the final report on ACTT-1,\619\ which stated that due 
to the rapid enrollment of the study, the planned interim analysis was 
conducted after enrollment of the study was completed and while follow-
up of enrolled patients was ongoing. The applicant stated that at the 
recommendation of the independent Data and Safety Monitoring Board, the 
interim results were shared with the study team and then made public. 
The applicant stated that no changes were made in the randomization 
scheme; however, treating physicians could request to be made aware of 
the treatment assignment of patients who had not completed day 29 if 
clinically indicated (for example, because of worsening clinical 
status), and patients originally in the placebo group could be given 
VEKLURY[supreg]. Lastly, the applicant stated that analyses of the 
impact of this crossover were evaluated in sensitivity analyses and 
found to produce results similar to those of the prespecified primary 
analysis, which demonstrated superiority of VEKLURY[supreg] over 
placebo.
---------------------------------------------------------------------------

    \619\ Beigel, JH, et al. Remdesivir for the Treatment of COVID-
19--Final Report. New Engl J Med 2020; 282: 1813-26. DOI: 10.1056/
NEJMoa2007764.
---------------------------------------------------------------------------

    In response to CMS' concern that the ACTT-1 study showed 
considerable differences between geographic regions in median time to 
recovery for patients assigned to VEKLURY[supreg] compared to those 
assigned to placebo, the applicant stated that ACTT-1 was conducted 
early in the course of the COVID-19 pandemic and enrolled a diverse 
population of patients across the globe. The applicant also stated that 
at the time of the ACTT-1 study, the impact of COVID-19 was 
particularly great in Italy \620\ and other parts of Europe, with 
hospital resources stretched to the point that healthcare resources 
were being reserved for those most likely to recover.\621\ The 
applicant stated that at the time, there were no known effective 
treatments for COVID-19 and ventilators were in short supply and were 
being rationed or shared between multiple patients. The applicant noted 
that despite these regional differences, VEKLURY[supreg] remained 
superior to placebo across the entire study population, even within 
these subgroups. The applicant also noted that the study was designed a 
priori to evaluate the efficacy of VEKLURY[supreg] over placebo in the 
entire enrolled population, rather than individual subgroups, including 
those defined by region. Therefore, the applicant concluded, the 
geographic variation in time to recovery was likely due to differential 
impact of pandemic at the time, and different characteristics of 
patients in each region.
---------------------------------------------------------------------------

    \620\ Odone A, Delmonte D, Scognamiglio, T, Signorelli C. COVID-
19 deaths in Lombardy, Italy: Data in context. Lancet Public Health. 
2020; 6: E310. https://www.thelancet.com/journals/lanpub/article/PIIS2468-2667(20)30099-/fulltext.
    \621\ Doldi M, Moscatelli A, Ravelli A, Spiazzi R, Petralia P. 
Medicine and humanism in the time of COVID-19. Ethical choices. Acta 
Biomed [internet]. 2020 Nov. 10 [cited 2021 Jun. 3];91(4):e2020167. 
Available from: https://mattioli1885journals.com/index.php/actabiomedica/article/view/10569.

---------------------------------------------------------------------------

[[Page 45115]]

    The applicant also referenced three additional studies presented at 
the World Microbe Forum in June 2021 that provided real-world data that 
demonstrated that effectiveness of VEKLURY[supreg] by baseline oxygen 
requirement subgroup and for mortality. The first study was an open 
label trial of 5 vs 10 days of treatment with VEKLURY[supreg] among 
patients hospitalized with severe COVID-19 compared to a real-world 
cohort of patients with severe COVID-19 who were not treated with 
VEKLURY[supreg] during the same time period, that is, through end of 
May 2020.\622\ According to the applicant, in this analysis, among 
1,974 patients treated with VEKLURY[supreg] for up to 10 days and 1,426 
propensity score weighted control patients, VEKLURY[supreg] was 
associated with reduced mortality by day 28 both overall (Hazard Ratio 
[HR]: 0.46, 95% CI: 0.39-0.54) and in subgroups of baseline oxygen 
requirement (low flow, HR: 0.35, 95% CI: 0.26-0.46; high-flow/non-
invasive ventilation, HR: 0.54, 95% CI: 0.42-0.69; invasive mechanical 
ventilation[IMV]/extracorporeal membrane oxygenation [ECMO], HR: 0.43, 
95% CI: 0.39-0.54). In addition, after the 10-day treatment course of 
the trial extension, VEKLURY[supreg] was associated with an increased 
likelihood of hospital discharge by day 28 overall (HR: 1.64, 95% CI: 
1.43-1.87) and in patients requiring low flow oxygen and high-flow/non-
invasive ventilation at baseline (HR: 1.85, 95% CI: 1.56-2.20; and HR: 
1.82, 95% CI: 1.40-2.37, respectively). No discharge benefit was 
observed in patients on IMV/ECMO at baseline.
---------------------------------------------------------------------------

    \622\ Go et al, WMF, 2021
---------------------------------------------------------------------------

    The second study was a comparative analysis of real-world U.S. 
hospital chargemaster data from Premier Healthcare. In the study, 
27,559 patients treated with VEKLURY[supreg] within 2 days of 
hospitalization and not requiring IMV/ECMO were propensity-score 
matched to 27,559 patients not treated with VEKLURY[supreg] in the same 
time period (August-November 2020).\623\ According to the applicant, in 
patients not requiring oxygen, treatment with VEKLURY[supreg] was 
associated with a statistically significant reduction in mortality at 
both day 14 (HR: 0.69, 95%CI: 0.57-0.83) and day 28 (HR: 0.80, 95% CI: 
0.68-0.94). Similarly, in patients requiring low-flow oxygen, treatment 
with VEKLURY[supreg] was associated with a statistically significant 
reduction mortality at both day 14 (HR: 0.67, 95% CI:0.59-0.77) and day 
28 (HR: 0.76, 95% CI:0.68-0.86). Among patients requiring high-flow 
oxygen/non-invasive ventilation (NIV), treatment with VEKLURY[supreg] 
was associated with a statistically significant reduction in mortality 
at day 14 (HR: 0.81, 95% CI: 0.70--0.93); however, there was no 
statistically significant difference between the VEKLURY[supreg] and 
control groups at day 28.
---------------------------------------------------------------------------

    \623\ Mozaffari et al, WMF, 2021.
---------------------------------------------------------------------------

    The third study was a comparative analysis of integrated US 
hospital chargemaster and medical/pharmacy claims from HealthVerity 
that examined patients newly diagnosed with COVID-19 between May 1, 
2020 (the date of Emergency Use Authorization from FDA) and May 3, 
2021.\624\ In this analysis, 24,856 patients treated with 
VEKLURY[supreg] were matched to 24,856 referent patients using risk set 
sampling and propensity score matching. In this data analysis, 
VEKLURY[supreg] was associated with reduced all-cause mortality by day 
28 overall (HR: 0.77, 95% CI: 0.73-0.81) and in each subgroup of 
baseline oxygen requirement: Room air (HR: 0.87, 95% CI: 0.80-0.94), 
low flow oxygen (HR: 0.78, 95% CI: 0.69-0.87), high-flow oxygen/NIV 
(HR: 0.73, 95% CI: 0.66-0.80), and IMV/ECMO (HR: 0.76, 95% CI: 0.66-
0.88). In addition, after completion of the 5-day treatment course, 
VEKLURY[supreg] was associated with a statistically significantly 
increased likelihood of hospital discharge overall (HR: 1.19, 95% CI: 
1.14, 1.25). This improvement in hospital discharge was statistically 
significant for patients on room air at baseline (HR: 1.24, 95% CI: 
1.16-1.32) and on low-flow oxygen at baseline (HR: 1.10, 95% CI: 1.00-
1.22), and suggestive for patients high-flow/NIV at baseline (HR: 1.14, 
95% CI: 0.98-1.33); no association was observed for hospital discharge 
among patients on ECMO/IMV.
---------------------------------------------------------------------------

    \624\ Chokkalingam et al, WMF, 2021.
---------------------------------------------------------------------------

    In response to CMS' concerns that the ACTT-1 study allowed other 
simultaneous treatments based on individual hospital policies or 
guidelines, which may have potentially confounded the results of the 
trial, the applicant stated that although the study allowed 
simultaneous treatment with other drugs according to local guidelines 
or practices, the randomized, placebo-controlled, double-blinded design 
of the study guarded against bias and minimized potential confounding. 
The applicant also stated that despite the added noise of other 
simultaneous treatments, VEKLURY[supreg] was demonstrated to be 
effective at both the interim and final analyses. The applicant also 
noted that at the time of ACTT-1, no other treatments had demonstrated 
efficacy against COVID-19, and many, including hydroxychloroquine and 
lopinavir/ritonavir, were later found to be ineffective. According to 
the applicant, the RECOVERY trial first reported results demonstrating 
a benefit of glucocorticoids in June 2020, after ACTT-1 enrollment was 
complete.\625\ Lastly, the applicant stated that the sensitivity 
analyses of ACTT-1 in which data were censored at earliest reported use 
of glucocorticoids or hydroxychloroquine still showed efficacy of 
VEKLURY[supreg].\626\
---------------------------------------------------------------------------

    \625\ University of Oxford. Low-cost dexamethasone reduces death 
by up to one third in hospitalised patients with severe respiratory 
complications of COVID-19. 16 June 2020. https://www.recoverytrial.net/news/low-costdexamethasone-reduces-death-by-up-to-one-third-in-hospitalised-patients-with-severe-respiratory-complications-ofcovid-19.
    \626\ Beigel, JH, et al. Remdesivir for the Treatment of COVID-
19--Final Report. New Engl J Med 2020; 282: 1813-26. DOI: 10.1056/
NEJMoa2007764.
---------------------------------------------------------------------------

    Response: We thank the applicant for the additional data it 
provided and for its comment. We believe that the clarifications 
provided by the applicant addressed the concerns we noted in the FY 
2022 IPPS/LTCH PPS proposed rule regarding the differences between 
geographic regions in median time to recovery between VEKLURY[supreg] 
patients and placebo patients. Although we note that controlling for 
the effect of geographic area would result in more robust analyses, we 
agree with the applicant that the geographic variation in time to 
recovery could be due to differential impact of pandemic at the time, 
and different characteristics of patients in each region. Lastly, we 
believe that the additional information from the applicant has 
addressed our concerns regarding the potential for bias in the study 
design and the prespecified interim analysis. Therefore, based on the 
data submitted by the applicant, we believe that VEKLURY[supreg] meets 
the substantial clinical improvement criterion because it because it 
has been shown to shorten time to recovery in patients hospitalized 
with severe COVID-19 by five days compared to patients treated with 
placebo and reduce mortality among patients receiving low-flow 
supplemental oxygen compared to the same cohort receiving the placebo.
    After consideration of the public comments we received, we have 
determined that VEKLURY[supreg] meets all of the criteria for approval 
of new technology add-on payments, and we are approving new technology 
add-on payments for VEKLURY[supreg] for FY 2022 when used for adults 
and pediatric patients (12 years of age and older and

[[Page 45116]]

weighing at least 40 kg) for the treatment of COVID-19 requiring 
hospitalization. Cases involving VEKLURY[supreg] that are eligible for 
new technology add-on payments will be identified by ICD-10-PCS codes 
XW033E5 (Introduction of remdesivir anti-infective into peripheral 
vein, percutaneous approach, new technology group 5) or XW043E5 
(Introduction of remdesivir anti-infective into central vein, 
percutaneous approach, new technology group 5).
    In its application, the applicant stated that the cost per case for 
VEKLURY[supreg] is $3,120 per case. Under Sec.  412.88(a)(2), we limit 
new technology add-on payments to the lesser of 65 percent of the costs 
of the new medical service or technology, or 65 percent of the amount 
by which the costs of the case exceed the MS-DRG payment. As a result, 
the maximum new technology add-on payment for a case involving the use 
of VEKLURY[supreg] is $2,028 for FY 2022. In addition, as discussed in 
section II.F.8, we established the NCTAP to pay hospitals the lesser 
of: (1) 65 percent of the operating outlier threshold for the claim; or 
(2) 65 percent of the amount by which the costs of the case exceed the 
standard DRG payment, including the adjustment to the relative weight 
under section 3710 of the Coronavirus Aid, Relief, and Economic 
Security (CARES) Act, for certain cases that include the use of a drug 
or biological product currently authorized for emergency use or 
approved for treating COVID-19. As discussed in section II.F.8, we are 
finalizing to extend the NCTAP through the end of the fiscal year in 
which the PHE ends for all eligible products. We are also finalizing 
that we will reduce the NCTAP for an eligible case by the amount of any 
new technology add-on payments. Therefore, cases involving the use of 
VEKLURY[supreg] in FY 2022 are eligible for new technology add-on 
payments and NCTAP, with the NCTAP to be reduced by a maximum of $2,028 
for the same treatment.
p. ZEPZELCATM (lurbinectedin)
    Jazz Pharmaceuticals submitted an application for new technology 
add-on payments for ZEPZELCATM for FY 2022. According to the 
applicant, ZEPZELCATM is an alkylating drug indicated for 
the treatment of adult patients with metastatic small cell lung cancer 
(SCLC) with disease progression on or after platinum-based 
chemotherapy. ZEPZELCATM is a marine-derived, synthetic 
antineoplastic compound that inhibits transcription-dependent 
replication stress and genome instability in tumor cells.
    According to the applicant, small cell lung cancer (SCLC) is an 
aggressive type of lung cancer where patients that progress after 
first-line chemotherapy have a poor prognosis due to limited clinical 
benefit from currently available second-line chemotherapy. Patients 
relapsing or progressing more than 90 days after completion of first-
line treatment are considered platinum sensitive and may be 
rechallenged with platinum-based chemotherapy.\627\ The majority of 
SCLC treated patients show disease relapse and are eligible for second-
line therapy; however, few second-line treatment options exist.\628\
---------------------------------------------------------------------------

    \627\ Garassino MC, et al. Outcomes of small-cell lung cancer 
patients treated with second-line chemotherapy: A multi-
institutional retrospective analysis. Lung Cancer 72 (2011) 378-383.
    \628\ Trigo J, et al. Lurbinectedin as second-line treatment for 
patients with small-cell lung cancer: A single-arm, open-label, 
phase 2 basket trial. Lancet Oncology. www.thelancet.com/oncology, 
Published online March 27, 2020. https://doi.org/10.1016/S1470-2045.
---------------------------------------------------------------------------

    According to the applicant, lung cancer overall is the second most 
common malignancy in the United States with 234,030 new cases and 
154,050 deaths estimated in 2018.\629\ Per the applicant, where most 
lung cancers are classified as non-SCLC, SCLC now comprises 
approximately 15% of all lung cancers. According to the applicant, SCLC 
is the most aggressive form of lung cancer characterized by rapid 
disease progression and early metastatic spread 
630 631 632--doubling in cell number about every 30 days and 
spreading quickly to lymph nodes and other organs.\633\ The applicant 
stated that the Veterans Lung Cancer Study Group used a two-stage 
system for describing SCLC, with a limited-stage (30% of cases) which 
is confined to a smaller portion of the body, and an extensive-stage 
(70% of cases) where the tumor was widespread.634 635 Many 
patients with SCLC have substantial comorbidities that may affect 
performance status and treatment options.\636\ A retrospective review 
analysis of Extensive-stage SCLC (ES-SCLC) patients found that when 
compared to patients at diagnosis, patients receiving second-line 
therapy were more likely to have congestive heart failure (67% vs 49%), 
thromboembolism (9% vs 2%), and depression (11% vs 7%).\637\ Further, 
these patients receiving second-line therapy were more likely to have 
infectious disease (57% vs 43%), electrolyte disorders (50% vs 22%), 
anemia (45% vs 19%), neutropenia (17% vs <0.2%), thrombocytopenia (12% 
vs 2%), and diarrhea (7% vs 3%) compared to the incidence of these 
comorbidities at diagnosis of ES-SCLC.\638\
---------------------------------------------------------------------------

    \629\ Tan WT, et al. Small Cell Lung Cancer (SCLC), Medscape, 
Oncology. Updated June 19, 2020. Emedicine.medscape.com.
    \630\ Ibid.
    \631\ Naito Y, et al. Rechallenge treatment with a platinum-
based regimen in patients with sensitive relapsed small-cell lung 
cancer. Medical Oncology (2018) 35:61.
    \632\ Von Pawel J, et al. Randomized phase III trial of 
amrubicin versus topotecan as second-line treatment for patients 
with small-cell lung cancer. J Clin Oncol. (2014) 32:35.
    \633\ Surveillance, Epidemiology, and End Results Program 
(SEER). Cancer stat facts: lung and bronchus cancer. https://seer.cancer.gov/statfacts/html/lungb.html. Accessed September 2020.
    \634\ Ibid.
    \635\ PDQ Adult Treatment Editorial Board. PDQ small cell lung 
cancer treatment. Bethesda, MD: National Cancer Institute. Updated 
March 20, 2020. https://www.cancer.gov/types/lung/hp/small-cell-lung-treatment-pdq. Accessed March 22, 2020. [PMID: 26389347].
    \636\ Kalemkerian GP. Small cell lung cancer. Semin Respir Crit 
Care Med. 2016;6(37):783-796.
    \637\ Danese M, et al. Comorbidity in patients with extensive 
disease small cell lung cancer. Presented at the AMCP Managed Care & 
Specialty Pharmacy Annual Meeting; March 27-30, 2017; Denver, CO.
    \638\ Ibid. Danese M, et al. Comorbidity in patients with 
extensive disease small cell lung cancer. Presented at the AMCP 
Managed Care & Specialty Pharmacy Annual Meeting; March 27-30, 2017; 
Denver, CO.
---------------------------------------------------------------------------

    According to the applicant, the standard of care for first-line 
chemotherapy for both limited-stage SCLC and ES-SCLC is platinum 
doublet and, in the case of ES-SCLC, platinum doublet in combination 
with a checkpoint inhibitor. SCLC is sensitive to platinum-based 
chemotherapy in the first-line setting but almost universally relapses, 
requiring subsequent lines of therapy.639 640 641 Once a 
patient relapses, the likelihood of response is highly dependent on 
time from initial therapy to relapse,\642\ with survival based on the 
duration of remission.\643\ According to the applicant, ES-SCLC is 
incurable; patients are treated with palliative intent, with a median 
survival of 7 to 11 months after diagnosis and with less than 5% 
survival at 2

[[Page 45117]]

years.644 645 Even limited-stage disease is rarely cured 
with radical local therapy (surgery or radiotherapy), and systemic 
chemotherapy (platinum plus etoposide) remains the cornerstone of 
first-line treatment in SCLC.\646\ Despite best management, the 5-year 
overall survival (OS) of even limited-stage SCLC is still only 15% to 
25%.647 648
---------------------------------------------------------------------------

    \639\ Shao C, et al. Chemotherapy treatments, costs of care, and 
survival for patients diagnosed with small cell lung cancer: a SEER-
Medicare study. Cancer Med. 2019;8:7613-7622.
    \640\ He J, et al. Survival, chemotherapy treatments, and health 
care utilization among patients with advanced small cell lung 
cancer: an observational study. Adv Ther. 2020;37:552-565.
    \641\ Karve SJ, et al. Comparison of demographics, treatment 
patterns, health care utilization, and costs among elderly patients 
with extensive-stage small cell and metastatic non-small cell lung 
cancers. BMC Health Serv Res. 2014;14:555.
    \642\ Shao C, et al. Chemotherapy treatments, costs of care, and 
survival for patients diagnosed with small cell lung cancer: a SEER-
Medicare study. Cancer Med. 2019;8:7613-7622.
    \643\ Pietanza MC, et al. Small cell lung cancer: will recent 
progress lead to improved outcomes? Clin Cancer Res. 
2015;21(10):2244-2255.
    \644\ Simos D, et al. Third-line chemotherapy in small-cell lung 
cancer: an international analysis. Clin Lung Cancer (2014) 15 (2): 
110-8.
    \645\ Pelayo AM, et al. Chemotherapy versus best supportive care 
for extensive small cell lung cancer. Cochrane Database Syst Rev 
(2013) 11: CD001990.
    \646\ Trigo J, et al. Lurbinectedin as second-line treatment for 
patients with small-cell lung cancer: a single-arm, open-label, 
phase 2 basket trial. Lancet Oncology. www.thelancet.com/oncology, 
Published online March 27, 2020. https://doi.org/10.1016/S1470-2045.
    \647\ Simos D, et al. Third-line chemotherapy in small-cell lung 
cancer: an international analysis. Clin Lung Cancer (2014) 15 (2): 
110-8.
    \648\ Pelayo AM, et al. Chemotherapy versus best supportive care 
for extensive small cell lung cancer. Cochrane Database Syst Rev 
(2013) 11: CD001990.
---------------------------------------------------------------------------

    The applicant asserted that while SCLC shows high sensitivity to 
first-line chemotherapy and radiotherapy, most patients develop disease 
relapse or progression within one year of 
treatment.649 650 651 It is reported that about 80% of 
limited-disease SCLC patients and almost all patients with ES-SCLC will 
develop relapse or progression after first-line treatment. Without 
second-line chemotherapy, the median survival time is 2 to 4 
months.652 653 The applicant stated that for patients 
classified as sensitive to first line treatment, due to remaining 
relapse-free for at least 3 months after treatment, rechallenge with 
the same chemotherapy regimen given as first line treatment is 
reasonable. For those classified as refractory (disease progression 
through first line treatment) and resistant (patients who show initial 
response to treatment but whose disease progresses within 3 months of 
completing chemotherapy), the second line treatment is Hycamtin 
(topotecan). According to the applicant, topotecan was the only 
preferred agent in the National Comprehensive Cancer Network (NCCN) 
Clinical Practice Guidelines for second-line treatment of patients with 
a Chemotherapy-free Interval (CTFI) <6 months. In summarizing the 
evidence of topotecan efficacy, the applicant stated that studies 
showed a median survival of 6.8 to 7.8 months,654 655 656 
progression free survival of 2.7 to 3.5 months,657 658 659 
and a median time to progression of 13.3 weeks.\660\ Furthermore, the 
applicant asserted that topotecan is associated with hematological 
toxicities such as anemia, neutropenia, thrombocytopenia, and febrile 
neutropenia.661 662 663
---------------------------------------------------------------------------

    \649\ Naito Y, et al. Rechallenge treatment with a platinum-
based regimen in patients with sensitive relapsed small-cell lung 
cancer. Medical Oncology (2018) 35:61.
     15437.
    \650\ Shiozawa, T. Rechallenge with first-line platinum 
chemotherapy for sensitive-relapsed small-cell lung cancer. Case Rep 
Oncol. 2018;11:622-632.
    \651\ Horita N, et al. Topotecan for relapsed small-cell lung 
cancer: systematic review and meta-analysis of 1347 patients. Sci 
Rep 2015;5: 15437.
    \652\ Shiozawa, T. Rechallenge with first-line platinum 
chemotherapy for sensitive-relapsed small-cell lung cancer. Case Rep 
Oncol. 2018;11:622-632.
    \653\ Wakuda K et al. Efficacy of second-line chemotherapy in 
patients with sensitive relapsed small-cell lung cancer. In vivo. 
33:2229-2234 (2019).
    \654\ Evans TL, et al. Cabazitaxel versus topotecan in patients 
with small-cell lung cancer with progressive disease during or after 
first-line platinum-based chemotherapy. J Thorac Oncol. 2015;10: 
1221-1228. Monnet I, et al. Carboplatin-etoposide versus topotecan 
as second-line treatment for sensitive relapsed small-cell lung 
cancer: phase 3 trial (ID 546) IASLC. 2019 World Conference on Lung 
Cancer; Barcelona, Spain; September 7-10, 2019 (abstr OA15.02). von 
Pawel JTopotecanTopotecancyclophosphamidecyclophosphamide, 
doxorubicin, and vincristine for the treatment of recurrent. J 
ClinVolVol 17, No 2, 1999: 658-667.
    \655\ Von Pawel J, et al. Randomized phase III trial of 
amrubicin versus topotecan as second-line treatment for patients 
with small-cell lung cancer. J Clin Oncol. (2014) 32:35.
    \656\ Von Pawel J, et al. Topotecan versus cyclophosphamide, 
doxorubicin, and vincristine for the treatment of recurrent small-
cell lung cancer. J Clin Oncol. Vol 17, No 2, 1999: 658-667.
    \657\ vonVon Pawel J, et al. Randomized phase III trial of 
amrubicin versus topotecan as second-line treatment for patients 
with small-cell lung cancer. J Clin Oncol. (2014) 32:35. Evans TL, 
et al. Cabazitaxel versus topotecan in patients with small-cell lung 
cancer with progressive disease during or after first-line platinum-
based chemotherapy. J Thorac Oncol. 2015;10: 1221-1228. Monnet I, et 
al. Carboplatin-etoposide versus topotecan as second-line treatment 
for sensitive relapsed small-cell lung cancer: phase 3 trial (ID 
546) IASLC. 2019 World Conference on Lung Cancer; Barcelona, Spain; 
September 7-10, 2019 (abstr OA15.02).
    \658\ Evans TL, et al. Cabazitaxel versus topotecan in patients 
with small-cell lung cancer with progressive disease during or after 
first-line platinum-based chemotherapy. J Thorac Oncol. 2015;10: 
1221-1228.
    \659\ von Pawel J, et al. Randomized phase III trial of 
amrubicin versus topotecan as second-line treatment for patients 
with small-cell lung cancer. J Clin Oncol. (2014) 32:35. Evans TL, 
et al. Cabazitaxel versus topotecan in patients with small-cell lung 
cancer with progressive disease during or after first-line platinum-
based chemotherapy. J Thorac Oncol. 2015;10: 1221-1228. Monnet I, et 
al. Carboplatin-etoposide versus topotecan as second-line treatment 
for sensitive relapsed small-cell lung cancer: phase 3 trial (ID 
546) IASLC. 2019 World Conference on Lung Cancer; Barcelona, Spain; 
September 7-10, 2019 (abstr OA15.02).
    \660\ vonVvon Pawel J, et al. Topotecan versus cyclophosphamide, 
doxorubicin, and vincristine for the treatment of recurrent small-
cell lung cancer. J Clin Oncol. Vol 17, No 2, 1999: 658-667.
    \661\ vonvVon Pawel JEvans TL, et al. CabazitaxelRandomized 
phase III trial of amrubicinCabazitaxel versus topotecan in patients 
with small-cell lung cancer with progressive disease during or after 
first-line platinum-based chemotherapy. J Thorac Oncol. 2015;10: 
1221-1228. Monnet I, et al. Carboplatin-etoposide versus topotecan 
as second-line treatment for patients with small-cell lung cancer. J 
Clin Oncol. (2014) 32:35. sensitive relapsed small-cell lung cancer: 
phase 3 trial (ID 546) IASLC. 2019 World Conference on Lung Cancer; 
Barcelona, Spain; September 7-10, 2019 (abstr OA15.02).
    \662\ Evans TL, et al. Cabazitaxel versus topotecan in patients 
with small-cell lung cancer with progressive disease during or after 
first-line platinum-based chemotherapy. J Thorac Oncol. 2015;10: 
1221-1228.
    \663\ Monnet I, et al. Carboplatin-etoposide versus topotecan as 
second-line treatment for sensitive relapsed small-cell lung cancer: 
phase 3 trial (ID 546) IASLC. 2019 World Conference on Lung Cancer; 
Barcelona, Spain; September 7-10, 2019 (abstr OA15.02).
---------------------------------------------------------------------------

    The applicant stated that since topotecan's approval in 1998, no 
other second-line SCLC treatment option had been approved until 
ZEPZELCATM gained approval in June 2020. According to the 
applicant, ZEPZELCATM is the first second-line treatment 
option for SCLC since 1998.
    According to the applicant, the FDA approved ZEPZELCATM 
on June 15, 2020 under the FDA's Accelerated Approval Program with 
Priority Review. ZEPZELCATM was also granted Orphan Drug 
Designation by the FDA. ZEPZELCATM is administered 
intravenously as a 3.2 mg/m\2\ dose over one hour, repeated every 21 
days until disease progression or unacceptable toxicity. 
ZEPZELCATM will typically be administered in an outpatient 
clinic. However, per the applicant, because many patients with SCLC 
have substantial comorbidities that may necessitate hospitalization and 
initiation of treatment, the first infusion and possibly some 
additional infusions will be administered in the inpatient hospital 
setting.\664\ The applicant submitted a request for a unique ICD-10-PCS 
code to identify the technology beginning FY 2022 and was granted 
approval for the following codes effective October 1, 2022: XW03387 
(Introduction of lurbinectedin into peripheral vein, percutaneous 
approach, new technology group 7) and XW04387 (Introduction of 
lurbinectedin into central vein, percutaneous approach, new technology 
group 7).
---------------------------------------------------------------------------

    \664\ Danese M, et al. Comorbidity in patients with extensive 
disease small cell lung cancer. Presented at the AMCP Managed Care & 
Specialty Pharmacy Annual Meeting; March 27-30, 2017; Denver, CO.
---------------------------------------------------------------------------

    As previously discussed, if a technology meets all three of the 
substantial similarity criteria, it would be considered substantially 
similar to an existing technology and, therefore, would not be 
considered ``new'' for purposes of new technology add-on payments.
    With respect to the first criterion, whether a product uses the 
same or a

[[Page 45118]]

similar mechanism of action to achieve a therapeutic outcome, the 
applicant asserted that the mechanism of action of 
ZEPZELCATM is not the same or similar to the mechanism of 
action of currently available products used in the treatment of 
patients with metastatic SCLC with disease progression on or after 
platinum-based chemotherapy. Per the applicant, ZEPZELCATM 
is a novel synthetic antineoplastic marine derived compound with a 
unique mode of action and chemical structure, with a terminal half-life 
of 51 hours and total plasma clearance of 11 L/h 
(50%).665 666 According to the applicant, 
ZEPZELCATM is a transcription inhibitor that binds DNA 
preferentially in quinine-rich sequences located within gene regulatory 
elements and induces a rapid degradation of transcribing RNA polymerase 
II that induces the eviction of oncogenic transcription factors and the 
silencing of their transcription program. The applicant states that 
ZEPZELCATM has preclinical data which suggests that 
oncogenic transcription of DNA to RNA was selectively inhibited via the 
dual actions of RNA polymerase II degradation and the formation of DNA 
breaks, which leads to apoptosis.\667\ The applicant further states 
that ZEPZELCATM has been shown to induce immunogenic cell 
death,\668\ and based on preclinical data, impacts the tumor 
microenvironment by altering the survival of tumor-associated 
macrophages (TAMs) and the production and function of key oncogenic 
inflammatory and growth factors.\669\
---------------------------------------------------------------------------

    \665\ ZEPZELCA website, ZEPZELCATM prescribing 
information., Rev. 6/2020:. https://www.zepzelcapro.com/.
    \666\ Romano M. et al. Travectedin and lurbinectedin are 
effective against leukemic cells derived from patients affected by 
chronic and juvenile myelomonocytic leukemia. European Journal of 
Cancer. 50 (6 Suppl):48.
    \667\ Santamaria G, et al. Lurbinectedin reverses platinum 
dependent IRFI overexpression and nuclear localization, partially 
responsible for resistance to platinum drugs in ovarian cancer. 
Proceedings of the American Association for Cancer Research (2017) 
58:311.
    \668\ Xie W, et al. Lurbinectedin synergizes with immune 
checkpoint blockade to generate anticancer immunity. Oncoimmunology. 
2019;5;8(11):e1656502.
    \669\ Farago AF, et al. ATLANTIS: A phase III study of 
lurbinectedin/doxorubicin versus topotecan or cyclophosphamide/
doxorubicin/vincristine in patients with small-cell lung cancer who 
have failed one prior platinum-containing line. Future Oncol. 
2019;15(3):231-239.
---------------------------------------------------------------------------

    According to the applicant, topotecan is a semi-synthetic 
derivative of camptothecin with topoisomerase I-inhibitory activity 
that relieves torsional strain in DNA by inducing reversible single 
strand breaks. The pharmacokinetics of topotecan have been evaluated in 
cancer patients following doses of 0.5 to 1.5 mg/m\2\ administered as a 
30-minute infusion. Topotecan exhibits multiexponential 
pharmacokinetics with a terminal half-life of 2 to 3 hours. Total 
exposure area under the curve (AUC) is approximately dose 
proportional.\670\ The applicant asserts that a clinical differentiator 
of ZEPZELCATM from topotecan is the rate of hematologic 
adverse reactions including neutropenia, anemia, thrombocytopenia, and 
febrile neutropenia.671 672 673
---------------------------------------------------------------------------

    \670\ FDA website, Hycamtin (topotecan) prescribing 
information., Rev. 2/2014: https://www.accessdata.fda.gov/drugsatfda_docs/label/2014/022453s002lbl.pdf.
    \671\ Von Pawel J, et al. Randomized phase III trial of 
amrubicin versus topotecan as second-line treatment for patients 
with small-cell lung cancer. J Clin Oncol. (2014) 32:35.
    \672\ Evans TL, et al. Cabazitaxel versus topotecan in patients 
with small-cell lung cancer with progressive disease during or after 
first-line platinum-based chemotherapy. J Thorac Oncol. 2015;10: 
1221-1228.
    \673\ Monnet I, et al. Carboplatin-etoposide versus topotecan as 
second-line treatment for sensitive relapsed small-cell lung cancer: 
phase 3 trial (ID 546) IASLC. 2019 World Conference on Lung Cancer; 
Barcelona, Spain; September 7-10, 2019 (abstr OA15.02).
---------------------------------------------------------------------------

    Lastly, the applicant asserted that ZEPZELCATM is not 
substantially similar to the more recently approved first-line 
treatments for ES-SCLC, TECENTRIQ[supreg] (atezolizumab) and 
IMFINZI[supreg] (durvalumab), both of which are PD-L1 blocking 
antibodies.
    With respect to the second criterion, whether a product is assigned 
to the same or a different MS-DRG, the applicant stated that 
ZEPZELCATM will not map to MS-DRGs distinct from other 
treatments for SCLC.
    With respect to the third criterion, whether the new use of the 
technology involves the treatment of the same or similar type of 
disease and the same or similar patient population when compared to an 
existing technology, the applicant stated that there have been no 
approved treatments for second-line treatment of SCLC since 1998 when 
topotecan was approved. Topotecan is indicated for the treatment of 
small cell lung cancers in patients with chemotherapy-sensitive disease 
after failure of first-line chemotherapy.\674\ The applicant states 
that topotecan is approved for relapses at least 60 days after 
initiation of a platinum-containing first-line regimen. 
ZEPZELCATM is indicated for the treatment of adult patients 
with metastatic small cell lung cancer (SCLC) with disease progression 
on or after platinum-based chemotherapy.\675\ The applicant also stated 
that ZEPZELCA was listed as a preferred regimen by the NCCN Clinical 
Practice Guidelines for second-line treatment of patients with a 
chemotherapy free interval (CTFI) <=6 months and recommended for 
patients with a CTFI >6 months.\676\
---------------------------------------------------------------------------

    \674\ FDA website, Hycamtin (topotecan) prescribing 
information., Rev. 2/2014: https://www.accessdata.fda.gov/drugsatfda_docs/label/2014/022453s002lbl.pdf .
    \675\ ZEPZELCA website, ZEPZELCATM prescribing 
information., Rev. 6/2020:. https://www.zepzelcapro.com/.
    \676\ NCCN Clinical Practice Guidelines in Oncology, Small Cell 
Lung Cancer. Version 4.2020, July 7, 2020. https://nccn.org.
---------------------------------------------------------------------------

    The applicant repeated results concerning the efficacy of topotecan 
and asserted that the efficacy results were achieved with a high rate 
of grade three and four hematologic Treatment Emergent Adverse Events 
(TEAEs).
    In summary, the applicant asserted that ZEPZELCATM meets 
the newness criterion because its mechanism of action is not the same 
or similar to the mechanism of action of currently available products 
used in the treatment of adult patients with metastatic SCLC and 
because it is indicated in patients with disease progression on or 
after platinum-based chemotherapy.
    We invited public comments on whether ZEPZELCATM is 
substantially similar to an existing technology and whether it meets 
the newness criterion.
    Comment: The applicant submitted comments reiterating its belief 
that ZEPZELCATM meets the newness criterion. First, the 
applicant stated that ZEPZELCATM's mechanism of action is 
not the same or similar to that of existing technology approved for 
treatment of the same patient population. Per the applicant, SCLC is a 
difficult to treat, extraordinarily lethal malignancy \677\ and that 
misregulated oncogenic transcriptions seem to direct SCLC initation and 
evolution, with transcription addiction being a feasible therapeutic 
target to treat the disease.678 679 Per the applicant, 
ZEPZELCATM represents an innovative approach to conventional 
anti-cancer drugs, with an elegant mechanism of action that has been 
well characterized in peer-reviewed, scientific journals and is based 
on the inhibition of transcription-dependent replication stress and 
genome instability of tumor cells.\680\ The applicant reiterated that

[[Page 45119]]

ZEPZELCATM is a novel synthetic antineoplastic compound, a 
marine-derived agent,\681\ with a unique mode of action and chemical 
structure. The applicant stated that ZEPZELCATM is not 
substantially similar to topotecan (brand name: Hycamtin), the only 
drug approved in over 20 years for patients with disease sensitive to 
treatment. The applicant further noted that topotecan is approved for 
relapses at least 60 days after initiation of a platinum containing 
first-line regimen.\682\ The applicant also stated that ZEPZELCA is 
also not substantially similar to the more recently approved first-line 
treatments for ES-SCLC: TECENTRIQ[supreg] (atezolizumab) and 
IMFINZI[supreg] (durvalumab), both of which are PD-L1 blocking 
antibodies.
---------------------------------------------------------------------------

    \677\ Gazdar AF, et al. Small-cell lung cancer: What we now, 
what we need to know and the path forward. Nat Rev Cancer (2017) 17 
(12): 725-37.
    \678\ Rudin CM, et al. Molecular subtypes of small cell lung 
cancer: a synthesis of human and mouse model data. Nat Rev Cancer. 
(2019) 19 (5): 289-97
    \679\ Christensen CL, et al. Targeting transcriptional 
addictions in small cell lung cancer with a covalent CDK7 inhibitor. 
Cancer Cell. (2014) 26 (6): 909.22.
    \680\ Arrieta O, et al. New opportunities in a challenging 
disease: lurbinectedin for relapsed small-cell lung cancer. Comment 
in Lancet Oncology. www.thelancet.com/oncology, Published online 
March 27, 2020.https://doi.org/10.1016/S1470-2045(20)30097-8.
    \681\ Romano M. et al. Travectedin and lurbinectedin are 
effective against leukemic cells derived from patients affected by 
chronic and juvenile myelomonocytic leukemia. European Journal of 
Cancer. 50 (6 Suppl):48.
    \682\ Trigo J, et al. Lurbinectedin as second-line treatment for 
patients with small-cell lung cancer: a single-arm, open-label, 
phase 2 basket trial. Lancet Oncology. www.thelancet.com/oncology, 
Published online March 27, 2020. https://doi.org/10.1016/S1470-2045.
---------------------------------------------------------------------------

    The applicant also stated that patient cases receiving intravenous 
infusion of ZEPZELCATM will be discretely identified by 
unique ICD-10-PCS procedure codes for ZEPZELCATM 
administration. The applicant stated that Jazz Pharmaceuticals' request 
for ZEPZELCATM-specific ICD-10-PCS codes was reviewed during 
the March 2021 ICD-10 Coordination and Maintenance (C&M) Committee 
meeting and that the effective date of these codes will be October 1, 
2021.
    Response: We thank the applicant for its comment. Based on our 
review of comments received and information submitted by the applicant 
as part of its FY 2022 new technology add-on payment application for 
ZEPZELCATM, as discussed in the proposed rule (86 FR 25353) 
and previously summarized, we agree with the applicant that 
ZEPZELCATM has a unique mechanism of action as a 
transcription inhibitor in the treatment of metastatic SCLC.\683\ 
Therefore, we believe ZEPZELCATM is not substantially 
similar to existing treatment options and meets the newness criterion. 
We consider the beginning of the newness period to commence when 
ZEPZELCATM was approved by FDA for the indication of adult 
patients with metastatic SCLC with disease progression on or after 
platinum-based chemotherapy, on June 15, 2020.
---------------------------------------------------------------------------

    \683\ Farago AF, et al. ATLANTIS: a phase III study of 
lurbinectedin/doxorubicin versus topotecan or cyclophosphamide/
doxorubicin/vincristine in patients with small-cell lung cancer who 
have failed one prior platinum-containing line. Future Oncol. 
2019;15(3):231-239.
---------------------------------------------------------------------------

    With respect to the cost criterion, the applicant conducted the 
following analysis to demonstrate that ZEPZELCATM meets the 
cost criterion. For the primary cost analysis cohort the applicant used 
the selection criteria of the presence of a lung cancer code as defined 
by ICD-10-CM family C34 (Malignant neoplasm of bronchus and lung) as 
the principal diagnosis and the presence of any chemotherapy code as 
defined by ICD_10-CM Z51.11 (Encounter for antineoplastic 
chemotherapy), ICD-10-CM Z51.12 (Encounter for antineoplastic 
immunotherapy), or any ICD-10-PCS chemotherapy code. Additionally, the 
applicant performed three sensitivity analyses for the cost criterion. 
The first is a broad cohort with the selection criteria of the presence 
of at least one lung cancer code (C34xx) and the presence of any 
chemotherapy code as defined by ICD-10-CM code Z51.11 (Encounter for 
antineoplastic chemotherapy), Z51.12 (Encounter for antineoplastic 
immunotherapy), or any ICD-10-PCS chemotherapy code. The second and 
third analyses involved TECENTRIQ[supreg] and IMFINZI[supreg] which are 
both immunotherapy drugs that have FDA approval for use as part of the 
first-line treatment in patients with SCLC. These drugs are to be used 
along with chemotherapy. The second analysis is the 
``TECENTRIQ[supreg]'' cohort with the selection criteria of the 
presence of at least one lung cancer code (C34xx) as either the 
principal or admitting diagnosis, and excluding cases with any ES-SCLC 
surgical codes. The final analysis, the ``IMFINZI[supreg]'' cohort, has 
the selection criteria of at least one of the following: (1) Presence 
of at least one lung cancer code (C34xx) and presence of any platinum-
based chemotherapy code as defined by ICD-10-CM Z51.11 (Encounter for 
antineoplastic chemotherapy) or Z51.12 (Encounter for antineoplastic 
immunotherapy); (2) Presence of at least one lung cancer code (C34xx) 
and assigned to MS-DRGs for respiratory neoplasms (180-182). The 
applicant stated that ZEPZELCATM is supplied in 4 mg single-
dose vials with the recommended dose of 3.2 mg/m\2\ by intravenous 
infusion over 60 minutes every 21 days until disease progression or 
unacceptable toxicity. Based on clinical study, the applicant stated 
that a single dose of ZEPZELCATM ranged from 4.05 mg to 6.4 
mg. To identify cases that may be eligible for the use of 
ZEPZELCATM, the applicant searched the FY 2019 MedPAR LDS 
file using these cohort selection criteria. The applicant stated that 
in all analyses, they imputed a case count of 11 for MS-DRGs with fewer 
than 11 cases and calculated the weighted average standardized charges 
across all MS-DRGs.
    Based on the FY 2019 MedPAR LDS file, the applicant identified a 
total of 1,100 cases in the primary cohort (mapped to 17 MS-DRGs), 
4,034 cases in the first sensitivity cohort (mapped to 195 MS-DRGs), 
34,437 cases in the second sensitivity cohort (mapped to 253 MS-DRGs), 
and 24,209 cases in the third sensitivity cohort (mapped to 128 MS-
DRGs). The applicant utilized the FY 2019 Final Rule with Correction 
Notice IPPS Impact File. Using the cases identified, the applicant then 
calculated the unstandardized average charges per case for each MS-DRG. 
The applicant expects that ES-SCLC patients will receive their initial 
dose of ZEPZELCATM in the inpatient setting. The applicant 
then standardized the charges and inflated the charges by 1.13218 or 
13.2 percent, the same inflation factor used by CMS to update the 
outlier threshold in the FY 2021 IPPS/LTCH PPS final rule. The 
applicant removed charges associated with chemotherapy since treatment 
with ZEPZELCATM would replace chemotherapy. To do so the 
applicant found the ratio of chemotherapy charges to radiology charges 
(0.14470075) from claims in the FY 2019 inpatient standard analytic 
file with a primary diagnosis of lung cancer (ICD-10-CM C34xx) and 
chemotherapy charges greater than zero. The applicant then added the 
charges for ZEPZELCATM by converting the costs of a single 
treatment (two single-dose vials) to a charge by dividing the cost by 
the national average cost-to-charge ratio of 0.187 for pharmacy from 
the FY 2021 IPPS/LTCH PPS final rule. The applicant calculated a final 
inflated average case weighted standardized charge per case for the 
primary cohort as $206,030, and $182,895, $146,174, and $130,975 for 
sensitivity cohorts 1, 2 and 3, respectively. The applicant referred to 
the FY 2022 New Technology Thresholds data file to determine the 
average case-weighted threshold amount for the primary cohort as 
$79,420, and $70,499, $70,226, and $57,383 for sensitivity cohorts 1, 2 
and 3, respectively. The final inflated average case-weighted 
standardized charge per case in the primary cohort and three

[[Page 45120]]

sensitivity cohorts exceeded the average case-weighted threshold amount 
by $126,610, $112,396, $75,948, and $73,592 respectively. Because the 
final inflated average case-weighted standardized charge per case 
exceeds in all scenarios the average case-weighted threshold amount, 
the applicant maintained that the technology meets the cost criterion.
    While we would not expect a significant difference, we noted in the 
proposed rule that instead of referring to the correction notice tab 
within the FY 2022 New Technology Thresholds data file, the applicant 
referred to the final rule tab. The FY 2022 New Technology Thresholds 
data file is available on the CMS IPPS home page at: https://www.cms.gov/medicare/acute-inpatient-pps/fy-2021-ipps-final-rule-home-page#Data.
    We also noted that the analysis provided by the applicant includes 
many MS-DRGs that are defined by factors that may or may not be related 
to ZEPZELCATM's indication for metastatic SCLC. For example, 
it is not clear that MS-DRG 004 Trach w MV >96 Hrs or Pdx Exc Face, 
Mouth & Neck w/o Maj O.R has a direct connection to small cell lung 
cancer though it may be related.
    We invited public comment on whether ZEPZELCATM meets 
the cost criterion.
    Comment: The applicant submitted a comment in response to these 
concerns. First, with respect to the MS-DRGs that were selected, the 
applicant clarified that in conducting the cost criterion analysis for 
the primary cohort, it identified patients that would best represent 
candidates for ZEPZELCATM, without regard to MS-DRG 
assignment. The applicant further stated that there is no ICD-10-CM 
diagnosis code specific to SCLC, only C34--malignant neoplasm of 
bronchus and lung and as such, the applicant believes that 
ZEPZELCATM candidates would have a principal diagnosis of 
Malignant Neoplasm of Bronchus and Lung and receive chemotherapy during 
the hospital stay. Per the applicant, the top 4 MS-DRGs within the 
primary cohort were DRG 180 RESPIRATORY NEOPLASMS WITH MCC, DRG 181 
RESPIRATORY NEOPLASMS WITH CC, DRG 166--OTHER RESPIRATORY SYSTEM O.R. 
PROCEDURES WITH MCC, and DRG 167--OTHER RESPIRATORY SYSTEM O.R. 
PROCEDURES WITH CC. The applicant stated that these 4 MS-DRGs represent 
almost 81 percent of all cases in the ZEPZELCATM primary 
cohort but acknowledges that some of the MS-DRGs are atypical MS-DRGs 
for SCLC patients. Per the applicant, all cases had a principal 
diagnosis of Malignant Neoplasm of Bronchus and Lung and received 
chemotherapy during the hospital stay. The applicant stated that these 
atypical MS-DRGs may have appeared because of complications and other 
factors that drive MS-DRG assignment but that these complications alone 
would not render the inclusion of these MS-DRGs inappropriate. The 
applicant further noted that the MS-DRGs referenced by CMS represent a 
small share of all cases (for example, MS-DRG 004 accounts for 1 
percent of the full primary cohort) and that if deemed appropriate, 
excluding certain MS-DRGs from the cost analysis would not impact the 
cost criterion results as virtually all individual MS-DRGs have 
standardized charges that exceed the cost criterion threshold. The 
applicant concluded by stating that ZEPZELCATM meets the 
cost criterion in the primary and three sensitivity cohort analyses.
    Next, the applicant indicated that it performed an analysis on a 
primary cohort and three sensitivity cohorts. Per the applicant, the 
primary cohort included inpatient hospital stays with the principal 
diagnosis code Malignant neoplasm of bronchus and lung (ICD-10-CM 
C34xx) and the patient received chemotherapy, as determined by presence 
of an ICD-10-CM Z51.11 (Encounter for antineoplastic chemotherapy), 
ICD-10-CM Z51.12 (Encounter for antineoplastic immunotherapy), or any 
ICD-10-PCS chemotherapy code on the claim. The applicant also reported 
its results from the three sensitivity cohorts.
    Finally, with respect to referencing the correction notice tab 
within the FY 2022 New Technology Threshold data file, the applicant 
stated that it re-evaluated the cost criterion for the primary and 3 
sensitivity cohorts using the correction notice thresholds and did not 
find material difference in the threshold or cost criterion findings. 
Specifically, the applicant identified the average case-weighted 
threshold amount for the primary cohort as $79,439, and $70,505, 
$70,245, and $57,384 for sensitivity cohorts 1, 2 and 3, respectively. 
The applicant stated the final inflated average case-weighted 
standardized charge per case in the primary cohort and three 
sensitivity cohorts exceeded the average case-weighted threshold amount 
by $126,591, $112,390, $75,929, and $73,591 respectively.
    Response: We appreciate the applicant's clarification regarding the 
MS-DRGs included in the analysis and agree that atypical DRGs represent 
a small share of all cases. Because virtually all individual MS-DRGs 
have standardized charges that exceed the cost criterion threshold we 
believe that the applicant has sufficiently addressed this concern. 
Based on the information submitted by the applicant as part of its FY 
2022 new technology add-on payment application for 
ZEPZELCATM, as discussed in the proposed rule (86 FR 25355 
through 25356) and previously summarized, and consideration of the 
comment received, we agree the final inflated average case-weighted 
standardized charge per case exceeded the average case-weighted 
threshold amount in each of the primary and 3 sensitivity cohorts. 
Therefore, ZEPZELCATM meets the cost criterion.
    With respect to the substantial clinical improvement criterion, the 
applicant asserted that ZEPZELCATM significantly improves 
clinical outcomes over existing treatment options for adult patients 
with metastatic SCLC with disease progression on or after platinum-
based chemotherapy in five ways. First, ZEPZELCATM offers an 
improved treatment option from both a safety and efficacy standpoint. 
Second, ZEPZELCATM offers safety improvement for treatment 
of patients with metastatic SCLC with disease progression on or after 
platinum-based chemotherapy over safety results previously reported in 
the literature for a comparable patient population. Third, patients 
with metastatic SCLC whose disease progresses on or after platinum-
based chemotherapy achieved higher overall response rates (ORRs) 
following treatment with ZEPZELCATM than ORR that had been 
previously reported in the literature for a comparable patient 
population. Fourth, overall survival (OS) rates achieved with 
ZEPZELCATM are clinically meaningful and are the highest 
rates reported for patients with metastatic SCLC whose disease 
progresses on or after platinum-based chemotherapy in more than 2 
decades. Fifth, the applicant asserted that ZEPZELCATM may 
represent a valuable treatment alternative to platinum rechallenge. The 
applicant submitted (or in some cases, referred to) multiple sources in 
support of these claims including retrospective analyses and other 
studies, a meta-analysis, data abstracts, literature reviews, 
prescribing information, FDA approved cancer therapies, practice 
guidelines, workgroup deliberations, a commentary, and an opinion 
regarding survival outcomes.
    With regard to the first claim, the applicant stated that 
ZEPZELCATM is the first second-line treatment option 
approved for SCLC since 1998 and is indicated for the treatment of 
adult

[[Page 45121]]

patients with metastatic SCLC with disease progression on or after 
platinum-based chemotherapy, a patient population with dismal outcomes. 
The applicant also stated that ZEPZELCATM offers an improved 
treatment option from both a safety and efficacy standpoint. The 
applicant outlined the nature of small cell lung cancer, patient 
treatment and prognosis. The applicant also stated that 
ZEPZELCATM could represent a valuable option for a patient 
population with high unmet medical need.\684\ Specifically, the 
applicant referred to four analyses, an epidemiology review, 
prescribing information, practice guidelines, a literature review 
inclusive of four articles, and one ZEPZELCATM study.
---------------------------------------------------------------------------

    \684\ Trigo J, et al. Lurbinectedin as second-line treatment for 
patients with small-cell lung cancer: a single-arm, open-label, 
phase 2 basket trial. Lancet Oncology. www.thelancet.com/oncology, 
Published online March 27, 2020. https://doi.org/10.1016/S1470-2045.
---------------------------------------------------------------------------

    First, an analysis stated that although small cell lung cancer 
shows high sensitivity to first-line chemotherapy and radiotherapy, 
most patients develop disease relapse or progression.\685\ Another 
analysis stated that most patients experience relapse of small cell 
lung cancer within 1 year of treatment.\686\ A separate analysis 
indicated that most patients who have initially responded to 
chemotherapy and radiotherapy eventually experience recurrence of the 
cancer in a few months.\687\ The fourth analysis indicated that almost 
all patients with extended disease will develop disease relapse or 
progression after first-line treatment and that without second-line 
chemotherapy, the median survival time is 2 to 4 months.\688\
---------------------------------------------------------------------------

    \685\ Shiozawa, T. Rechallenge with first-line platinum 
chemotherapy for sensitive-relapsed small-cell lung cancer. Case Rep 
Oncol. 2018;11:622-632.
    \686\ Naito Y, et al. Rechallenge treatment with a platinum-
based regimen in patients with sensitive relapsed small-cell lung 
cancer. Medical Oncology (2018) 35:61.
    \687\ Horita N, et al. Topotecan for relapsed small-cell lung 
cancer: systematic review and meta-analysis of 1347 patients. Sci 
Rep 2015;5: 15437.
    \688\ Wakuda K et al. Efficacy of second-line chemotherapy in 
patients with sensitive relapsed small-cell lung cancer. In vivo. 
33:2229-2234 (2019).
---------------------------------------------------------------------------

    Next, in referring to the epidemiology review, the applicant stated 
that most cases of small cell lung cancer occur in individuals aged 60-
80.\689\ In referring to prescribing information, the applicant stated 
that in 1998, Hycamtin (topotecan) was approved for patients with SCLC 
sensitive disease after failure of first-line chemotherapy. The 
applicant further stated that in the topotecan Phase 3 clinical study, 
sensitive disease was defined as disease responding to chemotherapy, 
but subsequently progressing at least 60 days after chemotherapy.\690\
---------------------------------------------------------------------------

    \689\ Tan WT, et al. Small Cell Lung Cancer (SCLC), Medscape, 
Oncology. Updated June 19, 2020. Emedicine.medscape.com.
    \690\ FDA website, Hycamtin (topotecan) prescribing 
information., Rev. 2/2014: https://www.accessdata.fda.gov/drugsatfda_docs/label/2014/022453s002lbl.pdf .
---------------------------------------------------------------------------

    Next, in referring to practice guidelines, the applicant stated 
that ZEPZELCA was studied in a broader (resistant disease and sensitive 
disease) population of SCLC patients and that prespecified subgroup 
analyses of ZEPZELCA results were done for patients with SCLC by CTFI 
in patients with resistant disease (CTFI <90 days) and sensitive 
disease (CTFI interval >=90 days). The applicant further noted that 
NCCN guidelines list ZEPZELCA as a preferred regimen for second-line 
treatment of patients with a CTFI <=6 months and recommended ZEPZELCA 
for patients with a CTFI >6 months.\691\
---------------------------------------------------------------------------

    \691\ NCCN Clinical Practice Guidelines in Oncology, Small Cell 
Lung Cancer. Version 4.2020, July 7, 2020. https://nccn.org.
---------------------------------------------------------------------------

    Next, the applicant referred to a literature review and submitted 
four sources. First, per the applicant, Iams et. al. describes 
available data on clinical efficacy, the emerging evidence regarding 
biomarkers and ongoing clinical trials using immune checkpoint 
inhibitors and other immunotherapies in patients with SCLC. The article 
included a discussion of the significant unmet needs in second-line 
therapy for SCLC.\692\ Second, per the applicant, Tsiouprou et. al. 
reported on a literature review of immunotherapy in treatment of ES-
SCLC and included a discussion of the significant unmet needs in 
second-line therapy for SCLC.\693\ Third, per the applicant, Wang et. 
al. presented a review of SCLC development, current therapy and 
included a discussion of the significant unmet needs in second-line 
therapy for SCLC.\694\ Fourth, per the applicant, Taniguchi et. al., is 
an opinion article discussing recent developments in the treatment of 
SCLC and includes a discussion of the significant unmet needs in 
second-line therapy for SCLC.\695\
---------------------------------------------------------------------------

    \692\ Iams WT, et al. Immunotherapeutic approaches for small-
cell lung cancer. Nat Rev Clin Oncol. 2020 May; 17(5):300-312. doi: 
10.1038/s41571-019-0316-z. Epub 2020 Feb 13.
    \693\ Tsiouprou I, et al. The r[ocirc]le of immunotherapy in 
extensive stage small-cell lung cancer: a review of the literature. 
Can Respir J. 2019 Nov 3;2019:6860432. doi: 10.1155/2019/6860432. 
eCollection 2019.
    \694\ Wang Y, et al. New insights into small-cell lung cancer 
development and therapy. Cell Biol Int. 2020 Aug;44(8):1564-1576. 
doi: 10.1002/cbin.11359. Epub 2020 Apr 18.
    \695\ Taniguchi H, et al. Targeted therapies and biomarkers in 
small cell lung cancer. Front Oncol. 2020 May 20;10:741. doi: 
10.3389/fonc.2020.00741. eCollection 2020.
---------------------------------------------------------------------------

    Finally, the applicant referred to Trigo, et. al., and stated that 
authors expressed that ZEPZELCA could present a valuable potential new 
treatment option after first-line platinum-based chemotherapy.\696\
---------------------------------------------------------------------------

    \696\ Trigo J, et al. Lurbinectedin as second-line treatment for 
patients with small-cell lung cancer: a single-arm, open-label, 
phase 2 basket trial. Lancet Oncology. www.thelancet.com/oncology, 
Published online March 27, 2020. https://doi.org/10.1016/S1470-2045.
---------------------------------------------------------------------------

    With regard to the second claim, the applicant asserted that 
ZEPZELCATM offers safety improvement for treatment of 
patients with metastatic SCLC with disease progression on or after 
platinum-based chemotherapy over safety results previously reported in 
the literature for a comparable patient population. The applicant 
asserted that safety is of particular importance for patients 
 65 with age being a major patient-related risk factor.\697\ 
The applicant also referred to a meeting abstract stating that several 
acute comorbidities were more common in Medicare patients initiating 
second-line chemotherapy than in all patients at diagnosis: infectious 
disease (57% versus 43%), electrolyte disorder (50% versus 22%), anemia 
(45% versus 19%), neutropenia (17% versus 0.1%), thrombocytopenia (12% 
versus 2%), and diarrhea (7% versus 3%).\698\
---------------------------------------------------------------------------

    \697\ Simeone E, et al. Nivolumab for the treatment of small 
cell lung cancer. Exp Rev Resp Med. 2020;14(1):5-13.
    \698\ Danese M, et al. Comorbidity in patients with extensive 
disease small cell lung cancer. Presented at the AMCP Managed Care & 
Specialty Pharmacy Annual Meeting; March 27-30, 2017; Denver, CO.
---------------------------------------------------------------------------

    The applicant also referred to six studies to support this claim. 
First, the applicant submitted Trigo et. al., that was based on Study 
B-005 (NCT01454972), a single-arm, open label, phase II basket trial to 
evaluate the activity and safety of lurbinectedin in patients with SCLC 
after failure of platinum-based chemotherapy. One hundred five patients 
with a diagnosis of SCLC and pre-treated with only one previous 
chemotherapy-containing line of treatment were included. Treatment 
consisted of 3.2mg/m2 lurbinectedin intravenously every 3 weeks until 
disease progression or unacceptable toxicity. The safety-related 
outcomes demonstrated the following adverse events: anemia 9%, 
leucopenia 29%, neutropenia 46%, and thrombocytopenia 7%. Serious 
treatment-related adverse events occurred in 10% of patients, of which 
neutropenia and febrile neutropenia

[[Page 45122]]

were the most common with 5% of patients for each.\699\
---------------------------------------------------------------------------

    \699\ Trigo J, et al. Lurbinectedin as second-line treatment for 
patients with small-cell lung cancer: a single-arm, open-label, 
phase 2 basket trial. Lancet Oncology. www.thelancet.com/oncology, 
Published online March 27, 2020. https://doi.org/10.1016/S1470-2045.
---------------------------------------------------------------------------

    Second, the applicant submitted an article from Von Pawel, et. al., 
of a randomized phase 3 study of a total of 637 patients with 
refractory or sensitive SCLC treated with topotecan and reported 
hematologic toxicities of grade >=3 anemia, 30.5%; neutropenia, 53.8%; 
thrombocytopenia, 54.3%; febrile neutropenia, 3%.\700\
---------------------------------------------------------------------------

    \700\ Von Pawel J, et al. Randomized phase III trial of 
amrubicin versus topotecan as second-line treatment for patients 
with small-cell lung cancer. J Clin Oncol. (2014) 32:35.
---------------------------------------------------------------------------

    Third, the applicant submitted an open label phase 2 study of 179 
patients with SCLC who relapsed after initial platinum-based 
chemotherapy, treated with topotecan and reported hematologic 
toxicities of neutropenia, 78.4%; thrombocytopenia, 45.5%; and febrile 
neutropenia/neutropenic infection/neutropenic sepsis, 18%.\701\
---------------------------------------------------------------------------

    \701\ Evans TL, et al. Cabazitaxel versus topotecan in patients 
with small-cell lung cancer with progressive disease during or after 
first-line platinum-based chemotherapy. J Thorac Oncol. 2015;10: 
1221-1228.
---------------------------------------------------------------------------

    Fourth, the applicant submitted an abstract from Monnet, et. al. of 
an open-label, multicenter, phase 3 trial that randomized patients with 
SCLC that responded to first-line platin-etoposide doublet treatment 
but showed evidence of disease relapse or progression at least 90 days 
after completion of the first-line treatment. Eighty-two patients were 
assigned to each treatment group: Those receiving combination 
chemotherapy (carboplatin and etoposide) versus those receiving oral 
topotecan. The abstract indicated that grade \3/4\ neutropenia was 
significantly more common in the topotecan group at 35.8% versus 19.7%; 
insignificantly more febrile neutropenia in the topotecan arm at 13.6% 
versus 6.2%; no difference for grade \3/4\ thrombocytopenia, 35.8% 
versus 30.9%; and anemia, 24.6% versus 21%.\702\
---------------------------------------------------------------------------

    \702\ Monnet, 2 L., et. al. Carboplatin-Etoposide Versus 
Topotecan as Second-Line Treatment for Sensitive Relapsed Small-Cell 
Lung Cancer: Phase 3 Trial. Journal of Thoracic Oncology Vol. 14 No. 
10S.
---------------------------------------------------------------------------

    Fifth, the applicant submitted an abstract from Leary, et. al., 
that is described as a pooled safety analysis with data from the phase 
II, single arm basket study by Trigo, et. al. (discussed previously), 
and a phase III RCT, the CORAIL study. The pooled analysis included a 
total of 554 patients treated with lurbinectedin. Of the 554, 335 were 
from the phase II basket study with selected solid tumors (9 
indications including 105 patients with small cell lung cancer) and 219 
were from the phase III CORAIL study with platinum resistant ovarian 
cancer. Authors presented an indirect exploratory comparison (pooled 
data from CORAIL + basket) and a direct comparison (data from CORAIL) 
of lurbinectedin vs. topotecan. Authors reported adverse events with 
lurbinectedin were grade \1/2\ fatigue, nausea and vomiting. Treatment-
related lurbinectedin/topotecan outcomes showed: dose reductions: 22.9/
48.3%; delays: 25.8/52.9%; grade >=3 serious adverse events: 15.0/
32.2%; discontinuations: 3.2/5.7%; deaths: 1.3/1.5%; granulocyte colony 
stimulating factor (G-CSF) use: 23.8/70.1%; and transfusions: 15.9/
52.9%. Authors concluded by stating that a significant safety advantage 
was observed when lurbinectedin was compared with topotecan in the 
CORAIL trial in terms of hematological toxicities. Authors also noted 
that with the limitations of indirect comparisons, in the pooled safety 
analysis, fewer lurbinectedin-treated patients had severe hematological 
toxicities, severe adverse events, dose adjustments, treatment 
discontinuations and use of supportive treatments than topotecan-
treated patients.\703\
---------------------------------------------------------------------------

    \703\ Leary A, et al. Pooled safety analysis of single-agent 
lurbinectedin versus topotecan (Results from a randomized phase III 
trial CORAIL and a phase II basket trial). ASCO2020 (American 
Society of Oncology); May 29-31, 2020. Abstract and poster.
---------------------------------------------------------------------------

    Sixth, the applicant provided a presentation summarizing results 
from the randomized phase 3 CORAIL study. The patient population was 
comprised of platinum resistant ovarian, fallopian or primary 
peritoneal cancer. Enrolled patients were randomly assigned to receive 
lurbinectedin or investigator choice of pegylated liposomal doxorubicin 
(PLD) or topotecan. The applicant stated that ZEPZELCATM was 
better tolerated than the control arm and that, overall, the data 
support a favorable safety profile for ZEPZELCATM.\704\
---------------------------------------------------------------------------

    \704\ Gaillard S, et al. Phase III trial of lurbinectedin versus 
PLD or topotecan in platinum-resistant ovarian cancer patients: 
results of the CORAIL trial. 2018 ESMO Presentation
---------------------------------------------------------------------------

    With regard to the third claim, the applicant stated that patients 
with metastatic SCLC whose disease progresses on or after platinum-
based chemotherapy achieved higher ORRs following treatment with 
ZEPZELCATM than ORR that had been previously reported in the 
literature for a comparable patient population. The applicant referred 
to four primary resources in support of ZEPZELCATM. First, 
as described previously, the applicant submitted Trigo, et. al., in 
which the primary endpoint is described as lurbinectedin anti-tumor 
activity in terms of investigator-assessed overall response (OR) and 
duration of response (DOR) as a secondary endpoint.\705\ The OR rate 
was identified as 35.2% and the mean DOR as 5.3 months. Second, the 
applicant submitted an abstract from Subbiah, et. al., a sub-study from 
Study B-005, that concluded that time from randomization to response 
was similar regardless of prior resistance or sensitivity to platinum-
based chemotherapy, and clinically meaningful DOR was noted in both 
subgroups of responders. \706\ Third, the applicant submitted an 
abstract from a second sub-study from Study B-005, indicating that ORR 
was similar across baseline characteristics: Age <65 = 36.8%; age >65 = 
32.4%; female = 31%; male = 38.1%; 1 prior line of therapy = 34.7%; >2 
prior lines of therapy = 42.9%; BSA 1.8m2 = 34.5%; and BSA >1.8m2 = 
36%. The authors concluded by noting that response to lurbinectedin 
appeared consistent regardless of baseline patient 
characteristics.\707\ Fourth, the applicant submitted a commentary from 
Arrieta, et. al., and stated that ZEPZELCATM outperformed 
all previously reported results for topotecan.\708\
---------------------------------------------------------------------------

    \705\ Additional secondary endpoints are discussed with the 
overall survival claim.
    \706\ Subbiah V, et al. Phase 2 basket trial of lurbinectedin in 
second-line SCLC: Characteristics and outcomes in treatment 
responders. IASLC 2020 North American Conference on Lung Cancer. 
Accepted for presentation October 16-17, 2020.
    \707\ Sands J, et al. Phase 2 basket trial of lurbinectedin in 
small-cell lung cancer (SCLC): Analysis of efficacy by baseline 
characteristics. IASLC 2020 North American Conference on Lung 
Cancer. Accepted for presentation October 16-17, 2020.
    \708\ Arrieta O, et al. New opportunities in a challenging 
disease: lurbinectedin for relapsed small-cell lung cancer. Comment 
in Lancet Oncology. www.thelancet.com/oncology, Published online 
March 27, 2020..https://doi.org/10.1016/S1470-2045(20)30097-8.
---------------------------------------------------------------------------

    The applicant also referred to three additional sources reflecting 
ORRs following treatment with topotecan. The Phase 3 trial of a total 
of 637 patients with refractory or sensitive SCLC treated with 
topotecan demonstrated an ORR of 16.9% and DOR of 4.2 months.\709\ In 
the open-label, multicenter, phase 3 trial of 164 patients with 
sensitive relapsed SCLC that responded to first-line platin etoposide 
doublet treatment but showed evidence of disease relapse or progression 
at least 90 days after completion of the first-line treatment,

[[Page 45123]]

patients randomized to the topotecan group demonstrated an ORR of 
25%.\710\ Lastly, a randomized, multi-center phase 3 trial of 107 
patients treated with topotecan reported an ORR of 24.3%.\711\
---------------------------------------------------------------------------

    \709\ Von Pawel J, et al. Randomized phase III trial of 
amrubicin versus topotecan as second-line treatment for patients 
with small-cell lung cancer. J Clin Oncol. (2014) 32:35.
    \710\ Monnet, 2 L., et. al. Carboplatin-Etoposide Versus 
Topotecan as Second-Line Treatment for Sensitive Relapsed Small-Cell 
Lung Cancer: Phase 3 Trial. Journal of Thoracic Oncology Vol. 14 No. 
10S
    \711\ Von Pawel J, et al. Topotecan versus cyclophosphamide, 
doxorubicin, and vincristine for the treatment of recurrent small-
cell lung cancer. J Clin Oncol. Vol 17, No 2, 1999: 658-667.
---------------------------------------------------------------------------

    With regard to the fourth claim, the applicant stated that the OS 
rates achieved with ZEPZELCATM are clinically meaningful and 
are the highest rates reported for patients with metastatic SCLC whose 
disease progresses on or after platinum-based chemotherapy in more than 
2 decades. The applicant submitted two studies in support of its claim 
of improved survival rates in patients treated with 
ZEPZELCATM. First, as described previously, the applicant 
submitted Trigo, et. al. and highlighted secondary endpoints including 
progression-free survival, progression-free survival at 4 and 6 months, 
overall survival and overall survival at 6 and 12 months. The mean 
progression free survival was identified as 3.5 months, mean overall 
survival 9.3 months in the overall population, 11.9 months in patients 
with a CTFI >=90 days and 5.0 months in those with CTFI <90 days.\712\
---------------------------------------------------------------------------

    \712\ Trigo J, et al. Lurbinectedin as second-line treatment for 
patients with small-cell lung cancer: a single-arm, open-label, 
phase 2 basket trial. Lancet Oncology. www.thelancet.com/oncology, 
Published online March 27, 2020. https://doi.org/10.1016/S1470-2045.
---------------------------------------------------------------------------

    Second, the applicant submitted an abstract from Subbiah, et. al., 
that summarized a sub-study from Study B-005 in which overall survival 
was a secondary endpoint. Authors report that patients treated with 
lurbinectedin had CTFI >=180 days and form the basis for their 
analysis. Sixty percent of patients were male, had ECOG PS 0-1, and had 
a median age of 57 years. Extensive stage disease at initial diagnosis 
was present in 35% of patients. All 20 patients had received prior 
platinum/etoposide, with no prior immunotherapy. Authors also reported 
that with a censoring of 55.0%, the median overall survival was 16.2 
months. Per the abstract, eleven patients (55.0%) were censored for 
survival analysis: Eight were on follow-up after disease progression, 
two were ongoing lurbinectedin treatment, and one had treatment 
discontinuation because of a treatment-related adverse event (worsening 
of prior peripheral neuropathy). Median follow-up was 15.6 months. 
Authors concluded time from randomization to response was similar 
regardless of prior resistance or sensitivity to platinum-based 
chemotherapy.\713\
---------------------------------------------------------------------------

    \713\ Subbiah V, et al. Activity of lurbinectedin in second-line 
SCLC patients who are candidates for platinum rechallenge IASLC 2020 
North American Conference on Lung Cancer. Accepted for presentation 
October 16-17, 2020.
---------------------------------------------------------------------------

    The applicant also referred to several randomized phase I and II 
studies of patients undergoing alternate therapies and highlighted 
those OS rates. The applicant provided an abstract from Monnet, et. 
al., (as mentioned previously with respect to applicant's second and 
third claims) summarizing results from a study that investigated 
whether the doublet carboplatin-etoposide was superior to topotecan 
monotherapy as second-line treatment in patients with sensitive 
relapsed SCLC. Authors reported patients treated with topotecan had 
progression free survival (PFS) of 2.7 months and OS of 7.4 
months.\714\ The applicant also referred to Evans, et. al., summarizing 
results from a study of patients with SCLC who relapsed after initial 
platinum-based chemotherapy who were divided into subgroups, 
chemosensitive vs. chemo-resistant/refractory disease. Patients were 
treated with topotecan. Authors reported topotecan PFS of 3.0 months 
and OS of 6.8 months.\715\ The applicant referred to Von Pawel, et. 
al., summarizing the results of a phase 3 trial of a total of 637 
patients with refractory or sensitive SCLC, including topotecan PFS of 
3.5 months and OS of 7.8 months (5.7 months for refractory).\716\ 
Lastly, the applicant referred to Von Pawel, et. al., that reported 
randomized, multi-center phase 3 results for topotecan with time to 
progression of 13.3 weeks and median OS of 25 weeks.\717\
---------------------------------------------------------------------------

    \714\ Monnet, 2 L., et. al. Carboplatin-Etoposide Versus 
Topotecan as Second-Line Treatment for Sensitive Relapsed Small-Cell 
Lung Cancer: Phase 3 Trial. Journal of Thoracic Oncology Vol. 14 No. 
10S
    \715\ Evans TL, et al. Cabazitaxel versus topotecan in patients 
with small-cell lung cancer with progressive disease during or after 
first-line platinum-based chemotherapy. J Thorac Oncol. 2015;10: 
1221-1228.
    \716\ Von Pawel J, et al. Randomized phase III trial of 
amrubicin versus topotecan as second-line treatment for patients 
with small-cell lung cancer. J Clin Oncol. (2014) 32:35.
    \717\ Von Pawel J, et al. Topotecan versus cyclophosphamide, 
doxorubicin, and vincristine for the treatment of recurrent small-
cell lung cancer. J Clin Oncol. Vol 17, No 2, 1999: 658-667.
---------------------------------------------------------------------------

    The applicant explained that a statement from an American Society 
of Clinical Oncology (ASCO) workgroup indicated that relative 
improvements in median OS of at least 20% are necessary to define a 
clinically meaningful improvement in outcome.\718\ The applicant 
summarized oncology literature reviews between 2014 and 2016 asserting 
that ASCO's threshold for OS was met in only 12% of studies (6 of 49) 
and 19% of therapies.719 720
---------------------------------------------------------------------------

    \718\ Ellis LM, et al. American Society of Clinical Oncology 
perspective: raising the bar for clinical trials by defining 
clinically meaningful outcomes. J Clin Oncol. 2014;32(12:1277-1280.
    \719\ Dreicer JJ, et al. Clinically meaningful benefit: real 
world use compared against the American and European guidelines. 
Blood Cancer Journal. 7,10.1038/s41408-017-0009-8.
    \720\ Kumar H, et al. An appraisal of clinically meaningful 
outcomes guidelines for oncology clinical trials, JAMA Oncology. 
Published online: Vol 2, No 9, 1238-1240.
---------------------------------------------------------------------------

    The applicant further stated that ZEPZELCATM's median OS 
for the overall population compared to the literature, meets the ASCO 
threshold and, for subsets of patient groups, median OS exceeds the 
ASCO threshold for clinically meaningful.
    The applicant concluded by stating that there is an urgent need for 
new treatment options for the SCLC population.\721\ The applicant 
asserted that CMS's new technology add-on payment approval of 
TECENTRIQ[supreg] for the treatment of patients with ES-SCLC effective 
for FY 2021 (85 FR 58684) further supports the urgency, referring to 
its 2 month improvement in survival.
---------------------------------------------------------------------------

    \721\ NCI Staff. For small cell lung cancer, immunotherapy drug 
finally brings improved survival. National Cancer Institute. October 
3, 2018. https://www.cancer.gov/news-events/cancer-currents-blog/2018/small-cell-lung-cancer-atezolizumab-survival.
---------------------------------------------------------------------------

    The applicant also referred to comments from specialists in the 
field of lung cancer stating that despite small trial sizes, 
improvement in overall survival is a major achievement and that any 
advance in survival is important given that few patients diagnosed with 
SCLC survive for even a year despite treatment.\722\
---------------------------------------------------------------------------

    \722\ NCI Staff. For small cell lung cancer, immunotherapy drug 
finally brings improved survival. National Cancer Institute. October 
3, 2018. https://www.cancer.gov/news-events/cancer-currents-blog/2018/small-cell-lung-cancer-atezolizumab-survival.
---------------------------------------------------------------------------

    With regard to the fifth claim, that ZEPZELCATM may 
represent a valuable treatment alternative to platinum rechallenge, the 
applicant submitted several sources pertaining to 
ZEPZELCATM. First, the applicant submitted two sub-analyses 
from Subbiah, et al., that were based on Study B-005 as its primary 
support for ZEPZELCATM. In both of these sub-analyses, 
patients had been pre-treated with one prior platinum-containing line. 
The first analysis included 20 patients from a subset of patients with 
CTFI >180 and authors report that patients treated with lurbinectedin 
had an ORR

[[Page 45124]]

at 60.0% and a median DoR of 5.5 months. The second analysis included 
60 patients from a SCLC cohort of the basket trial, with CTFI >90 d (20 
pts with CTFI >180 d). The applicant states that ZEPZELCATM 
was shown to be effective and well-tolerated in the platinum-sensitive 
relapsed SCLC population especially when CTFI >180 days. From these 
results, the authors concluded that ZEPZELCATM may represent 
a valuable alternative to platinum rechallenge.723 724 The 
applicant also referenced Arrieta et al., stating that 
ZEPZELCATM data outperformed less established treatment 
schemes including platinum rechallenge.\725\ The applicant stated that 
the July 7, 2020 NCCN Clinical Practice Guidelines in Oncology indicate 
that lurbinectedin is identified as a Preferred Regimen in relapse <=6 
months and a Recommended Regimen in relapse >6 months.\726\ The 
applicant referred to the authors' conclusion in Genestreti et al., 
stating that the outcome for second line chemotherapy for SCLC is poor 
and that rechallenge platinum/etoposide is a reasonable option with 
potentially better outcomes than standard chemotherapy.\727\
---------------------------------------------------------------------------

    \723\ Subbiah V, et al. Activity of lurbinectedin in second-line 
SCLC patients who are candidates for platinum rechallenge IASLC 2020 
North American Conference on Lung Cancer. Accepted for presentation 
October 16-17, 2020.
    \724\ Subbiah V, et al. Activity in second-line SCLC patient 
candidates for platinum rechallenge. ESMO (European Society for 
Medical Oncology) 2020 Congress; September 19-21, 2020. Poster 
1784P.
    \725\ Arrieta O, et al. New opportunities in a challenging 
disease: lurbinectedin for relapsed small-cell lung cancer. Comment 
in Lancet Oncology. www.thelancet.com/oncology, Published online 
March 27, 2020 . . . https://doi.org/10.1016/S1470-2045(20)30097-8.
    \726\ NCCN Clinical Practice Guidelines in Oncology, Small Cell 
Lung Cancer. Version 4.2020, July 7, 2020. https://nccn.org.
    \727\ Genestreti G, et al. Outcomes of platinum-sensitive small-
cell lung cancer patients treated with platinum/etoposide 
rechallenge: a multi-institutional retrospective analysis. Clinical 
Lung Cancer, Vol. 16, No. 6, e223-8.
---------------------------------------------------------------------------

    Finally, the applicant referred to Monnet, et al., stating that 
patients treated with combination therapy, carboplatin and etoposide, 
achieved a median OS of 7.4 months and ORR of 49%.\728\
---------------------------------------------------------------------------

    \728\ Monnet, 2 L., et al. Carboplatin-Etoposide Versus 
Topotecan as Second-Line Treatment for Sensitive Relapsed Small-Cell 
Lung Cancer: Phase 3 Trial. Journal of Thoracic Oncology Vol. 14 No. 
10S
---------------------------------------------------------------------------

    In the proposed rule (86 FR 25360), we noted the following 
concerns. The evidence submitted by the applicant in support of 
ZEPZELCATM's improvement in overall response and survival 
rates was based on one single-arm, open label, phase II basket study 
(Study B-005 (NCT01454972)) and several smaller subsetted analyses that 
were based on the basket study, and we noted that without a direct 
comparison arm it may be more difficult to draw definitive 
conclusions.729 730 731 732 We noted the following 
differences between the historical control patients and patients 
treated with ZEPZELCATM in these studies, which may confound 
the comparisons: First, patients with central nervous system 
involvement (brain metastases) were excluded from ZEPZELCATM 
treatment, and we noted that Arrieta, et al., noted that this criterion 
is of particular interest when translating results to the clinical 
setting, since patients with SCLC are known to be prone to develop 
brain metastases, and up to 50% do so throughout the disease 
course.\733\ Second, patients treated with ZEPZELCATM had 
access to immunotherapy during first line treatment, which may support 
patients' immune systems in fighting cancer. Third, the CTFI used in 
the single arm basket trial differed from those used in the historical 
controls of topotecan studies, and we noted that CTFIs can impact 
treatment response and outcome. As, per the applicant, 
ZEPZELCATM was listed as a preferred regimen by the NCCN 
Clinical Practice Guidelines for second-line treatment of patients with 
a CTFI <=6 months and recommended for patients with a CTFI >6 months, 
while topotecan is only FDA approved for chemotherapy-sensitive cases, 
defined using a 60 day CTFI, we noted that the appropriate comparator 
treatment for ZEPZELCATM would differ depending on the CTFI 
subset. However, the historical controls relied on an overall topotecan 
population with CTFI >60. To the extent that this group was more 
heavily weighted with patients in the lower CTFI group, it was unclear 
whether this may partially explain the poorer outcomes of patients in 
the historical control groups. We also noted that, while the claim of 
improved hematological outcomes using ZEPZELCATM appeared to 
be mostly supported by the female-only arm of the CORAIL study, results 
from the pooled sample of the basket trial still appeared to 
demonstrate an improvement over the topotecan arm. We believed that 
this may suggest that the inclusion of male patients did not alter the 
conclusion that patients treated with ZEPZELCATM appeared 
more favorable than those treated with topotecan. We further noted that 
bone marrow stimulating drugs were allowed in the topotecan arm of the 
CORAIL study so the observed adverse hematologic effects may have been 
the best case for that arm of the study. Finally, we noted that the 
subsetted analyses generated from the primary basket study had small 
sample sizes and the authors of these studies stated that further 
research on larger populations is required to draw firm 
conclusions.734 735
---------------------------------------------------------------------------

    \729\ Sands J, et al. Phase 2 basket trial of lurbinectedin in 
small-cell lung cancer (SCLC): Analysis of efficacy by baseline 
characteristics. IASLC 2020 North American Conference on Lung 
Cancer. Accepted for presentation October 16-17, 2020.
    \730\ Subbiah V, et al. Phase 2 basket trial of lurbinectedin in 
second-line SCLC: Characteristics and outcomes in treatment 
responders. IASLC 2020 North American Conference on Lung Cancer. 
Accepted for presentation October 16-17, 2020.
    \731\ Subbiah V, et al. Activity of lurbinectedin in second-line 
SCLC patients who are candidates for platinum rechallenge IASLC 2020 
North American Conference on Lung Cancer. Accepted for presentation 
October 16-17, 2020.
    \732\ Subbiah V, et al. Activity in second-line SCLC patient 
candidates for platinum rechallenge. ESMO (European Society for 
Medical Oncology) 2020 Congress; September 19-21, 2020. Poster 
1784P.
    \733\ Arrieta O, et al. New opportunities in a challenging 
disease: lurbinectedin for relapsed small-cell lung cancer. Comment 
in Lancet Oncology. www.thelancet.com/oncology, Published online 
March 27, 2020 . . . https://doi.org/10.1016/S1470-2045(20)30097-8.
    \734\ Subbiah V, et al. Activity in second-line SCLC patient 
candidates for platinum rechallenge. ESMO (European Society for 
Medical Oncology) 2020 Congress; September 19-21, 2020. Poster 
1784P.
    \735\ Sands J, et al. Phase 2 basket trial of lurbinectedin in 
small-cell lung cancer (SCLC): Analysis of efficacy by baseline 
characteristics. IASLC 2020 North American Conference on Lung 
Cancer. Accepted for presentation October 16-17, 2020.
---------------------------------------------------------------------------

    We invited public comments on whether ZEPZELCATM meets 
the substantial clinical improvement criterion.
    Comment: The applicant submitted comments in response to CMS' 
concerns pertaining to substantial clinical improvement. First, with 
respect to the concern that the evidence submitted by the applicant was 
based on one single-arm, open label, phase II basket study (Study B-005 
(NCT01454972) and several smaller subsetted analyses, the applicant 
stated that the basket study evaluated ZEPZELCATM as a 
single-agent in patient cohorts across 9 different tumor types (a 
basket trial design), including a cohort of patients with SCLC with 
disease progression on or after platinum-based chemotherapy (n=105) 
(NCT02454972), conducted at 26 investigational sites in the European 
Union, United Kingdom and U.S. The applicant stated that the study was 
originally intended to be a signal-finding study, was designed as a 
single-arm trial, and the overall response rate (ORR) in the SCLC 
cohort, which consisted of patients who had received a prior line of 
chemotherapy, was

[[Page 45125]]

notable at 35 percent.\736\ The applicant further noted that based on 
the study ORR and duration of response in the SCLC cohort, the FDA 
granted accelerated approval of ZEPZELCATM to allow for 
earlier approval of drugs that treat serious conditions and that fill 
an unmet medical need based on a surrogate endpoint (ORR and duration 
of response) that is thought to predict clinical benefit. The applicant 
stated that continued approval may be contingent upon verification and 
description of clinical benefit in a confirmatory trial(s). Per the 
applicant, accelerated approval of ZEPZELCATM is of 
paramount importance to metastatic SCLC patients given the high relapse 
and disease progression rates in SCLC2-5 and because no second-line 
therapy options had been approved in over 20 years (that is, topotecan 
in 1998). The applicant stated that because most cases of SCLC occur in 
individuals aged 60-80 years,\737\ this is a risk-benefit profile that 
warrants additional second-line treatment options and that 
ZEPZELCATM fulfills a high unmet need for patients with 
metastatic SCLC, with a majority being Medicare beneficiaries.
---------------------------------------------------------------------------

    \736\ Naito Y, et al. Rechallenge treatment with a platinum-
based regimen in patients with sensitive relapsed small-cell lung 
cancer. Medical Oncology (2018) 35:61.
    \737\ Tan WT, et al. Small Cell Lung Cancer (SCLC), Medscape, 
Oncology. Updated June 19, 2020. Emedicine.medscape.com
---------------------------------------------------------------------------

    Next, with respect to the differences between the historical 
control patients and patients treated with ZEPZELCATM in 
these studies, the applicant stated that while SCLC patients often 
develop brain metastases, it is common for clinical trials in SCLC to 
exclude patients with central nervous system (CNS) involvement, 
including the Phase 3 trial for amrubicin versus topotecan, where 
patients with prior brain metastasis and symptomatic CNS metastases 
were excluded.\738\ Per the applicant, such exclusions are in part due 
to the poor clinical status of these patients. The applicant stated 
that in Study B-005, there were 4 patients that had CNS involvement (3 
patients had a history of CNS involvement, and 1 patient had CNS 
involvement at baseline (protocol deviation)). The applicant also 
stated that among these 4 patients treated with ZEPZELCATM, 
there were 2 partial responses, 1 stable disease, and 1 progressive 
disease (data on file).
---------------------------------------------------------------------------

    \738\ von Pawel J, et al. Randomized phase III trial of 
amrubicin versus topotecan as second-line therapy in small cell lung 
cancer. J Clin Oncol. Vol 32, No 35, 2014: 4012-4020.
---------------------------------------------------------------------------

    With respect to the concern that patients treated with 
ZEPZELCATM had access to immunotherapy during first line 
treatment, the applicant stated that Study B-005 was initiated prior to 
the FDA approval of immunotherapy agents such as atezolizumab, 
nivolumab, and durvalumab. The applicant also stated that in total, 
only 8 of the 105 patients enrolled were previously treated with 
immunotherapy. Per the applicant, in reviewing the data in the small 
number of patients that fell into this category, it could not determine 
that these patients were driving the median overall response. The 
applicant stated that the median OS 95% confidence interval of the 105 
patients is overlapping with the 95% confidence interval of the 97 
patients who were not treated with immunotherapy (data on file).
    With respect to the concern that the CTFI used in the single arm 
basket trial differs from those used in the historical controls of 
topotecan studies, the applicant stated that while it is possible that 
grouping by CTFI may affect efficacy measures, it is important to 
understand that the clinical community uses different CTFI groups with 
no singular convention. Per the applicant, some in the oncology 
community use 90 days as a cutoff (concordant with European Society for 
Medical Oncology (ESMO)), and others use 180 days (concordant with NCCN 
guidelines). The applicant stated that the study that led to the FDA 
approval of topotecan used 60 days as a CTFI cutoff; \739\ Study B-005 
used 90 days. Per the applicant, Study B-005 also included a population 
that was actually sicker than populations in several SCLC studies 
because of the inclusion of patients who had CTFI <30 days (n=21 of 105 
patients). In order to demonstrate a more specific comparison with the 
topotecan trial that led to its FDA approval, an exploratory analysis 
was conducted excluding patients with CTFI <60 from the Study B-005 
results. The applicant stated that this analysis supports that when 
matching CTFI groupings for comparison purposes, the efficacy profile 
of ZEPZELCATM is substantially improved over study results 
that Van Pawel et. al.\740\ reported for topotecan.
---------------------------------------------------------------------------

    \739\ von Pawel J, et al. Randomized phase III trial of 
amrubicin versus topotecan as second-line therapy in small cell lung 
cancer. J Clin Oncol. Vol 32, No 35, 2014: 4012-4020
    \740\ von Pawel J, et al. Topotecan versus cyclophosphamide, 
doxorubicin, and vincristine for the treatment of recurrent small-
cell lung cancer. J Clin Oncol. Vol 17, No 2, 1999: 658-667.
---------------------------------------------------------------------------

    With respect to the concern that improved hematological outcomes 
using ZEPZELCATM appears to be mostly supported by the 
female-only arm of the CORAIL study, the applicant stated that a 
significant safety advantage was observed when ZEPZELCATM 
was compared with topotecan in the CORAIL trial in terms of 
hematological toxicities. Per the applicant, this finding was based on 
an indirect exploratory comparison (pooled data from CORAIL + Study B-
005) and a direct comparison (data from CORAIL).\741\ The applicant 
stated that the inclusion of male patients in the pooled safety 
analysis did not alter the conclusion that patients treated with 
ZEPZELCATM appeared more favorable than those treated with 
topotecan.
---------------------------------------------------------------------------

    \741\ Leary A, et al. Pooled safety analysis of single-agent 
lurbinectedin versus topotecan (Results from a randomized phase III 
trial CORAIL and a phase II Basket trial). ASCO2020 (American 
Society of Oncology); May 29-31, 2020. Abstract and poster.
---------------------------------------------------------------------------

    With respect to the concern regarding bone marrow stimulating 
drugs, the applicant stated that bone marrow stimulating drugs were 
allowed in the topotecan arm of the CORAIL study so the observed 
adverse hematologic effects may have been the best case for that arm of 
the study, concurring with CMS' observations. The applicant reiterated 
that a significant safety advantage was observed when 
ZEPZELCATM was compared with topotecan in the CORAIL trial 
and in terms of hematological toxicities based on indirect exploratory 
comparison (pooled data from CORAIL + Study B-005) and a direct 
comparison (data from CORAIL).\742\ Per the applicant, inclusion of 
male patients in the pooled safety analysis did not alter the 
conclusion that patients treated with ZEPZELCATM appeared 
more favorable than those treated with topotecan.
---------------------------------------------------------------------------

    \742\ Ibid
---------------------------------------------------------------------------

    Finally, with respect to the concern that the subsetted analyses 
generated from the primary basket study have small sample sizes, the 
applicant stated that while the subset sizes are small in number, these 
are actually sizable for a rare disease such as SCLC. Per the 
applicant, it is standard practice for study investigators and authors 
to conclude that further research is needed when presenting study 
results but that subset analyses can provide extremely meaningful 
clinical findings for consideration when clinicians evaluate and make 
real-world treatment decisions. The applicant stated that 
ZEPZELCATM may represent a valuable clinical option to 
platinum rechallenge. Per the applicant, the results of this post-hoc 
analysis were recently published in December 2020 by Subbiah et. al. in 
the peer-reviewed journal, Lung Cancer,\743\ showing that Study B-

[[Page 45126]]

005 patients with CTFI >180 days (n=20) achieved a 60% ORR (Table 23 of 
the New Technology Add-on Payment application), which compares 
favorably to the ORR of 46% (n=11) in a previous platinum-rechallenge 
study sub-group analysis reported by Wakuda et. al.\744\ Per the 
applicant, overall survival in the Study B-005 post-hoc analysis in 
patients with CTFI <180 days was 16.2 months (Table 23), which compares 
favorably to that reported by Wakuda et al, 15.7 months (n=11).\745\ 
The applicant stated that while the CTFI >180 days cohort was small, it 
represented nearly 20% of the Study B-005 SCLC trial population and 
demonstrated high ORR and overall survival that appears in line with 
clinical efficacy of platinum rechallenge. The applicant concluded by 
stating that these findings are now informing clinical practice in the 
treatment of SCLC.
---------------------------------------------------------------------------

    \743\ von Pawel J, et al. Topotecan versus cyclophosphamide, 
doxorubicin, and vincristine for the treatment of recurrent small-
cell lung cancer. J Clin Oncol. Vol 17, No 2, 1999: 658-667
    \744\ Wakuda K, et al. Efficacy of rechallenge chemotherapy in 
patients with sensitive relapsed small cell lung cancer. Am J Clin 
Oncol 38(1) (2015) 28-32.
    \745\ Ibid.
---------------------------------------------------------------------------

    We also received several comments from clinicians in the fields of 
oncology and pharmacy, stating that the rapid spread of SCLC and early 
relapse after first-line treatment make management of this disease very 
challenging. The commenters stated that ZEPZELCATM is 
effective in the treatment of relapsed SCLC, fills an unmet need in 
second line treatment, is easy to administer and is well tolerated. 
Commenters stated that approving ZEPZELCATM for new 
technology add-on payments would expedite care and offer an added 
treatment option for eligible patients.
    Response: We thank the applicant and other commenters for their 
comments regarding the substantial clinical improvement criterion. 
After consideration of the comments received and the information 
provided, we agree with the applicant and other commenters that 
ZEPZELCATM represents a substantial clinical improvement 
because it fills an unmet need in second-line treatment for ES-SCLC. 
Because existing treatments are indicated for patients with platinum-
sensitive disease, ZEPZELCATM treats a disease for which 
there are no existing treatments. We also believe that, given the 
context of those patients who were treated, we believe the improvement 
seen in the matched comparison between topotecan and 
ZEPZELCATM in overall survival (25 weeks vs. 11.8 months) 
and ORR (26% vs. 32%) represents a substantial clinical improvement 
over existing technologies in the second line treatment of patients 
with metastatic SCLC with disease progression on or after platinum-
based chemotherapy.
    Based on the information received to date and comments received, we 
have determined that ZEPZELCATM meets all of the criteria 
for approval for new technology add-on payments for the reasons stated 
previously. Therefore, we are approving new technology add-on payments 
for ZEPZELCATM for FY 2022. Cases involving the use of 
ZEPZELCATM that are eligible for new technology add-on 
payments will be identified by ICD-10-PCS procedure codes: XW03387 
(Introduction of lurbinectedin into peripheral vein, percutaneous 
approach, new technology group 7) or XW04387 (Introduction of 
lurbinectedin into central vein, percutaneous approach, new technology 
group 7).
    In its application, the applicant estimated that the cost of 
ZEPZELCATM is $13,266 per patient. Under Sec.  412.88(a)(2), 
we limit new technology add-on payments to the lesser of 65 percent of 
the average cost of the technology, or 65 percent of the costs in 
excess of the MS-DRG payment for the case. As a result, the maximum new 
technology add-on payment for a case involving the use of 
ZEPZELCATM is $8,622.90 for FY 2022.
6. FY 2022 Applications for New Technology Add-On Payments (Alternative 
Pathways)
    As discussed previously, beginning with applications for FY 2021, a 
medical device that is part of FDA's Breakthrough Devices Program and 
has received marketing authorization for the indication covered by the 
Breakthrough Device designation may qualify for the new technology add-
on payment under an alternative pathway. Additionally, beginning with 
FY 2021, a medical product that is designated by the FDA as a Qualified 
Infectious Disease Product (QIDP) and has received marketing 
authorization for the indication covered by the QIDP designation, and, 
beginning with FY 2022, a medical product that is a new medical product 
approved under FDA's Limited Population Pathway for Antibacterial and 
Antifungal Drugs (LPAD) and used for the indication approved under the 
LPAD pathway, may also qualify for the new technology add-on payment 
under an alternative pathway. Under an alternative pathway, a 
technology will be considered new and not substantially similar to an 
existing technology for purposes of the new technology add-on payment 
under the IPPS and will not need to meet the requirement that it 
represents an advance that substantially improves, relative to 
technologies previously available, the diagnosis or treatment of 
Medicare beneficiaries. These technologies must still meet the cost 
criterion.
    We note, section 1886(d)(5)(K)(ii)(II) of the Act provides for the 
collection of data with respect to the costs of a new medical service 
or technology described in subclause (I) for a period of not less than 
2 years and not more than 3 years beginning on the date on which an 
inpatient hospital code is issued with respect to the service or 
technology. Our regulations in Sec.  412.87(c)(2) for breakthrough 
devices and Sec.  412.87(d)(2) for certain antimicrobial products state 
that a medical device/product that meets the condition in paragraph 
(c)(1) or (d)(1) of Sec.  412.87 will be considered new for not less 
than 2 years and not more than 3 years after the point at which data 
begin to become available reflecting the inpatient hospital code (as 
defined in section 1886(d)(5)(K)(iii) of the Act) assigned to the new 
technology (depending on when a new code is assigned and data on the 
new technology become available for DRG recalibration). After CMS has 
recalibrated the DRGs, based on available data, to reflect the costs of 
an otherwise new medical technology, the medical technology will no 
longer be considered ``new'' under the criterion of this section.
    We received 17 applications for new technology add-on payments for 
FY 2022 under the alternative new technology add-on payment pathway. In 
accordance with the regulations under Sec.  412.87(e)(2), applicants 
for new technology add-on payments, including Breakthrough Devices, 
must have FDA marketing authorization by July 1 of the year prior to 
the beginning of the fiscal year for which the application is being 
considered. We first determine whether a new technology meets the 
newness criterion, and only if so, do we make a determination as to 
whether the technology meets the cost threshold. One applicant withdrew 
its application prior to the issuance of the proposed rule. Of the 
remaining 16 applications, 13 of the technologies received a 
Breakthrough Device designation from FDA and three were designated as a 
QIDP by FDA. We did not receive any applications for technologies 
approved through the LPAD pathway. Subsequently, two applicants 
withdrew their applications for the Neovasc ReducerTM and 
ThoraflexTM Hybrid Device prior to the issuance of this 
final rule. Two applicants, BONESUPPORT Inc. (the applicant for 
CERAMENT[supreg] G)

[[Page 45127]]

and Phagenesis Ltd. (the applicant for the Phagenyx[supreg] System), 
did not meet the deadline of July 1, 2021 for FDA approval or clearance 
of the technology and, therefore, the technologies are not eligible for 
consideration for new technology add-on payments for FY 2022. We note 
that we did receive some comments requesting that CMS extend the policy 
that allows for conditional approval for certain antimicrobials to 
Breakthrough Devices that have not received FDA marketing authorization 
by July 1 to facilitate timely access to these technologies for 
beneficiaries. As discussed in the FY 2021 IPPS/LTCH final rule (85 FR 
58742), we may consider this for future rulemaking as we gain more 
experience with this conditional approval process for certain 
antimicrobial products, but the July 1 deadline for FDA approval or 
clearance for consideration of new technology add-on payment 
applications, as set forth in the regulations at Sec.  412.87(e), 
continues to apply to applications for new technology add-on payments 
for Breakthrough Devices for FY 2022. A discussion of the remaining 12 
applications is presented in this final rule, including 9 technologies 
that have received a Breakthrough Device designation from FDA and three 
that were designated as a QIDP by FDA.
    Under the policy finalized in the FY 2021 IPPS/LTCH PPS final rule 
(85 FR 58742), we revised the regulations at Sec.  412.87(e) by adding 
a new paragraph (3) which provides for conditional approval for a 
technology for which an application is submitted under the alternative 
pathway for certain antimicrobial products (QIDPs and LPADs) at Sec.  
412.87(d) that does not receive FDA marketing authorization by the July 
1 deadline specified in Sec.  412.87(e)(2), provided that the 
technology receives FDA marketing authorization by July 1 of the 
particular fiscal year for which the applicant applied for new 
technology add-on payments. We refer the reader to the FY 2021 IPPS/
LTCH PPS final rule for a complete discussion of this policy (85 FR 
58737 through 58742).
    As we did in the FY 2021 IPPS/LTCH PPS proposed rule, for 
applications under the alternative new technology add-on payment 
pathway, in the FY 2022 IPPS/LTCH PPS proposed rule, we proposed to 
approve or disapprove each of these 12 applications for FY 2022 new 
technology add-on payments. Therefore, in this section of the preamble 
of this final rule, we provide background information on each of these 
12 alternative pathway applications and discuss whether or not each 
technology is eligible for the new technology add-on payment for FY 
2022. As previously noted, the applications for the Neovasc 
ReducerTM and ThoraflexTM Hybrid Device were 
withdrawn prior to the issuance of this final rule, and the remaining 
two technologies, CERAMENT[supreg] G and the Phagenyx[supreg] System, 
did not meet the deadline of July 1, 2021 for FDA approval or clearance 
of the technology and, therefore, these technologies are not eligible 
for consideration for new technology add-on payments for FY 2022. We 
refer readers to the FY 2020 IPPS/LTCH PPS final rule (84 FR 42292 
through 42297) and FY 2021 IPPS/LTCH PPS final rule (85 FR 58715 
through 58733) for a complete discussion of the alternative new 
technology add-on payment pathways for these technologies.
a. Alternative Pathway for Breakthrough Devices
(1) AprevoTM Intervertebral Body Fusion Device
    Carlsmed, Inc. submitted an application for new technology-add on 
payments for the aprevoTM Intervertebral Fusion Device 
(aprevoTM) for FY 2022. Per the applicant, the device is an 
interbody fusion implant that stabilizes the lumbar spinal column and 
facilitates fusion during lumbar fusion procedures indicated for the 
treatment of spinal deformity. The applicant states that the implant 
device is custom made for patient-specific features, by using patient 
CT scans to create 3D virtual models of the deformity. The device is 
used during anterior lumbar interbody fusion, lateral lumbar interbody 
fusion, transforaminal lumbar interbody fusion, or standalone anterior 
lumbar interbody fusion procedures. According to the applicant, the 
aprevoTM device is additively manufactured and made from 
Titanium Alloy (Ti-6Al-4V) per ASTM F3001, and has a cavity intended 
for the packing of bone graft. In addition, the applicant explained 
that aprevoTM is used with supplemental fixation devices and 
bone graft packing. Per the applicant, the device was formerly known as 
``CorraTM.''
    The aprevoTM device received FDA Breakthrough Device 
designation under the name ``Corra'' on July 1, 2020 for the Corra 
Anterior, Corra Transforaminal and Corra Lateral Lumbar Fusion System 
interbody device which is intended for use in anterior lumbar interbody 
fusion (ALIF), lateral lumbar interbody fusion (LLIF), and 
transforaminal lumbar interbody fusion (TLIF) under this designation. 
The applicant was granted FDA 510(k) clearance as a Class II medical 
device for the anterior lumbar interbody fusion and lateral lumbar 
interbody fusion indications on December 3, 2020. We stated in the 
proposed rule that the applicant anticipated that the 
aprevoTM device would receive FDA marketing authorization by 
May 2021 for the additional indications of transforaminal interbody 
fusion and standalone anterior lumbar interbody fusion (which 
incorporates supplemental fixation), and was granted 510(k) clearance 
for the TLIF indication on June 30, 2021. Since the anterior and 
lateral lumbar fusion indications that received marketing authorization 
on December 3, 2020 correspond to the indications that received 
Breakthrough Device designation, we stated that we believed the newness 
date for these indications would be December 3, 2020. The 
transforaminal interbody fusion indication, which also corresponds to 
the indication that received Breakthrough Device designation, received 
marketing authorization on June 30, 2021, and we therefore believe the 
newness date for this indication would be June 30, 2021. We noted that 
under the eligibility criteria for approval under the alternative 
pathway for certain transformative new devices, only the use of 
aprevoTM for the ALIF, LLIF, and TLIF indications, and the 
FDA Breakthrough Device designations it received for these uses, are 
relevant for purposes of the new technology add-on payment application 
for FY 2022. As the use of aprevoTM for the standalone 
indication is not included in the Breakthrough Device designation 
indications, it is not eligible for new technology add-on payments.
    The applicant submitted a request to the ICD-10 Coordination and 
Maintenance Committee for approval of a code for FY 2022 to uniquely 
identify the technology and was granted approval for the following 
procedure codes effective October 1, 2021:
BILLING CODE 4120-01-P

[[Page 45128]]

[GRAPHIC] [TIFF OMITTED] TR13AU21.205

    With respect to the cost criterion, the applicant provided the 
following analysis. The applicant used the MS-DRG grouping function 
within FindACode software in conjunction with the online MS-DRG v37.0 
Definitions Manual to identify the appropriate MS-DRGs to which 
potential cases that may be eligible for treatment involving 
aprevoTM patient-specific interbody cages would most likely 
map. The applicant identified the following six relevant MS-DRGs:
[GRAPHIC] [TIFF OMITTED] TR13AU21.206

    The applicant conducted a review of ICD-10-PCS codes for procedures 
in which the aprevoTM patient-specific intervertebral body 
fusion cases might be placed into the lumbar spine of an adult patient 
diagnosed with spinal curvature. For MS-DRGs 453, 454, and 455, the 
applicant searched the FY 2019 MedPAR dataset for cases with any of the 
following procedure codes:

[[Page 45129]]

[GRAPHIC] [TIFF OMITTED] TR13AU21.207

    For MS-DRGs 456, 457, and 458, the applicant searched the FY 2019 
MedPAR dataset for cases reporting a procedure code in Table A in 
combination with a primary diagnosis code in Table B or a secondary 
diagnosis code in Table C.
[GRAPHIC] [TIFF OMITTED] TR13AU21.208


[[Page 45130]]


[GRAPHIC] [TIFF OMITTED] TR13AU21.209


[[Page 45131]]


[GRAPHIC] [TIFF OMITTED] TR13AU21.210

[GRAPHIC] [TIFF OMITTED] TR13AU21.211


[[Page 45132]]


BILLING CODE 4120-01-C
    The applicant identified 45,331 cases across all six MS-DRGs. The 
applicant first removed charges to account for the two types of prior 
technology devices that the applicant asserted are most likely to be 
replaced by aprevoTM Intervertebral Body Fusion Device. 
Specifically, the applicant calculated an average cost for the top five 
selling devices in each category of prior technology, which include 
standalone ALIF and LLIF lateral expandable cages.\746\ The applicant 
then multiplied the cost of the technology being replaced by three, 
which, per the applicant, is the number of lumbar cages implanted for 
the correction of spinal curvature, to arrive at an estimated hospital 
cost per case.\747\ The applicant converted costs to charges by 
weighting the operating cost-to-charge ratios for each of the 3,315 
hospitals in the FY 2021 IPPS/LTCH final rule and correction notice 
impact file by each hospital's share of the 9,235,824 submitted claims 
to obtain a national average CCR of 0.2546, of which the inverse is a 
national-average hospital markup of 393 percent. The applicant then 
standardized the charges and applied an inflation factor of 13.1 
percent, which, per the applicant, is the outlier charge inflation 
factor used in the FY 2021 IPPS/LTCH final rule (85 FR 59038), to 
update the charges from FY 2019 to FY 2021. We note that the applicant 
appears to have used the FY 2021 IPPS/LTCH PPS proposed rule inflation 
factor rather than the 2-year inflation factor from the FY 2021 IPPS/
LTCH PPS final rule of 13.2 percent (85 FR 59039), which would have 
resulted in a higher inflated charge figure. The applicant then added 
charges for the new technology by multiplying the estimated average 
cost for the aprevoTM Intervertebral Body Fusion Device by 
three devices per case and converting the cost to charges using the 393 
percent hospital charge markup.
---------------------------------------------------------------------------

    \746\ Orthopedic Network News. ``2019 Spinal Surgery update.'' 
Volume 30, No. 4. October 2019.
    \747\ Ibid.
---------------------------------------------------------------------------

    The applicant calculated a final inflated case-weighted average 
standardized charge per case of $247,648 and an average case-weighted 
threshold of $157,600. Because the final inflated average case-weighted 
standardized charge per case exceeded the average case-weighted 
threshold amount, the applicant asserted that the technology meets the 
cost criterion.
    In the FY 2022 IPPS/LTCH PPS proposed rule (86 FR 25364), we agreed 
with the applicant that the aprevoTM Intervertebral Body 
Fusion meets the cost criterion and therefore proposed to approve the 
aprevoTM Intervertebral Body Fusion device for the 
indications of ALIF and LLIF, and for the indication of TLIF, subject 
to the technology receiving FDA marketing authorization for that 
indication by July 1, 2021, as these indications correspond to the 
Breakthrough Device designation, for new technology add-on payments for 
FY 2022.
    Based on preliminary information from the applicant at the time of 
the proposed rule, the cost of the aprevoTM Intervertebral 
Body Fusion is $31,500, or an estimated average cost of $10,500 per 
device multiplied by three, which, according to the applicant, is the 
average number of devices used per procedure. We noted that the cost 
information for this technology may be updated in the final rule based 
on revised or additional information CMS receives prior to the final 
rule. Under Sec.  412.88(a)(2), we limit new technology add-on payments 
to the lesser of 65 percent of the average cost of the technology, or 
65 percent of the costs in excess of the MS-DRG payment for the case. 
As a result, we proposed that the maximum new technology add-on payment 
for a case involving the use of the aprevoTM Intervertebral 
Body Fusion Device would be $20,475 for FY 2022 (that is 65 percent of 
the average cost of the technology).
    We invited public comments on whether the aprevoTM 
Intervertebral Body Fusion Device meets the cost criterion and our 
proposal to approve new technology add-on payments for 
aprevoTM Intervertebral Body Fusion Device for FY 2022 for 
ALIF and LLIF, and for TLIF, subject to the technology receiving 
marketing authorization for that indication by July 1, 2021.
    Comment: We received several comments expressing support for the 
approval of the aprevoTM Intervertebral Body Fusion Device 
for the new technology add-on payment for FY 2022. The commenters 
stated that aprevoTM provides a more effective treatment for 
surgeries for adult spinal deformities and improves patient care by 
reducing complications. Also, a commenter expressed general support for 
the approval of the aprevoTM Intervertebral Body Fusion 
Device as an orthopaedic device which advances the care of 
musculoskeletal disorders and improves patients' quality of life.
    Response: We appreciate the commenters' support.
    Comment: The applicant submitted a comment noting that CMS 
determines eligibility for the new technology add-on payment based on 
the newness of the technology, which has been established in regulation 
as being measured from the first date upon which data become available 
reflecting inpatient use of the technology. The applicant requested 
that CMS adjust the beginning of the newness period for the 
aprevoTM Intervertebral Body Fusion Device from the date of 
FDA clearance on December 3, 2020, to the date the device was first 
used commercially on February 23, 2021. Per the applicant, using the 
date of FDA approval or clearance as the basis for the start of the 
newness period does not account for situations where a product may be 
approved by the FDA for distribution and use but is not yet being 
distributed to or used by hospitals in caring for patients.
    Response: We thank the applicant for its comment. As we have 
discussed in prior rulemaking (77 FR 53348), generally, our policy is 
to begin the newness period on the date of FDA approval or clearance 
or, if later, the date of availability of the product on the U.S. 
market. The applicant states that the aprevoTM 
Intervertebral Body Fusion Device was first used commercially on 
February 23, 2021, but it is unclear from the information provided when 
the technology first became available for sale and, absent additional 
information from the applicant, we cannot determine a newness date 
based on a documented delay in the technology's availability on the 
U.S. market. However, we note that using either the FDA clearance date 
of December 3, 2020, or the date suggested by manufacturer of February 
23, 2021, aprevoTM is still considered new for FY 2022 
because the 3-year anniversary date (December 3, 2023 or February 23, 
2024, respectively) would occur after FY 2022.
    Based on the information provided in the application for new 
technology add-on payments, and after consideration of the public 
comments we received, we believe the aprevoTM Intervertebral 
Body Fusion meets the cost criterion. The aprevoTM 
Intervertebral Body Fusion received marketing authorization from the 
FDA on December 3, 2020 for the indications for ALIF and LLIF and on 
June 30, 2021 for the indication for TLIF, that are covered by its 
Breakthrough Device designation. Therefore, we are finalizing our 
proposal to approve new technology add-on payments for the 
aprevoTM Intervertebral Body Fusion for FY 2022, and we 
consider the beginning of the newness period to commence on December 3, 
2020 for the indications for ALIF and LLIF and June 30, 2021 for the 
indication for TLIF, which is when the technology received FDA 
marketing authorization for the indications

[[Page 45133]]

covered by its Breakthrough Device designation. Based on the 
information at the time of this final rule, the cost per case is 
$31,500 or an estimated average cost of $10,500 per device multiplied 
by three, which, according to the applicant, is the average number of 
devices used per procedure. Under Sec.  412.88(a)(2), we limit new 
technology add-on payments to the lesser of 65 percent of the average 
cost of the technology, or 65 percent of the costs in excess of the MS-
DRG payment for the case. As a result, we are finalizing that the 
maximum new technology add-on payment for a case involving the use of 
the aprevoTM Intervertebral Body Fusion Device would be 
$20,475 for FY 2022 (that is 65 percent of the average cost of the 
technology). Cases involving the use of the aprevoTM 
Intervertebral Body Fusion Device that are eligible for new technology 
add-on payments will be identified by any of the following ICD-10-PCS 
codes:
[GRAPHIC] [TIFF OMITTED] TR13AU21.212

(2) aScopeTM Duodeno
    Ambu, Inc. submitted an application for new technology add on 
payments for the aScopeTM Duodeno for FY 2022. The device is 
a sterile, single-use endoscope for endoscopy and endoscopic surgery 
indicated for treatment of the upper gastrointestinal (GI) tract. Per 
the applicant, the device includes a flexible insertion tube with a 
bendable tip equipped with lighting and camera. According to the 
applicant, the aScopeTM Duodeno is inserted into the mouth 
of the patient and steered via the esophagus and stomach to the 
duodenum. The applicant states that single-use scopes eliminate the 
risk of patient-to-patient transmission of infection related to 
reprocessing. The applicant also states the device is designed to be 
used with aBox Duodeno, which is a video processor that outputs video 
imaging for observation and recording. Per the applicant, the device 
may also be used with existing external video monitors for image 
display as well as other endoscopic accessories and equipment.
    The aScopeTM Duodeno (formerly aScope 1 Duo) was 
designated as a Breakthrough Device, indicated for use with the aScope 
Base (now aBox Duodeno), endo-therapy accessories (for example, biopsy 
forceps) and other ancillary equipment (for example, video monitor) for 
endoscopy and endoscopic surgery within the duodenum, and received FDA 
510(k) clearance as a Class II medical device on July 17, 2020 for the 
same indication. Per the applicant, the device was available on the 
market immediately after FDA clearance.
    The applicant stated that the applicant for EXALTTM 
Model D, another technology discussed in this section, submitted a 
request to the ICD-10 Coordination and Maintenance Committee for FY 
2022 for a unique code to identify use of single-use duodenoscopes. The 
applicant further stated that since this code would describe and 
identify use of aScope, they did not submit a request for approval of a 
code to uniquely identify the technology. The applicant for 
aScopeTM Duodeno was granted approval for the following 
procedure codes effective October 1, 2021: XFJB8A7 (Inspection of 
hepatobiliary duct using single-use duodenoscope, new technology group 
7) and XFJD8A7 (Inspection of pancreatic duct using single-use 
duodenoscope, new technology group 7).
    To demonstrate that the technology meets the cost criterion, the 
applicant searched the FY 2019 MedPAR Limited Data Set (LDS) for cases 
reporting one of the following ICD-10-PCS codes commonly used to report 
endoscopic retrograde cholangiopancreatography (ERCP) and use of 
duodenoscopes:
BILLING CODE 4120-01-P

[[Page 45134]]

[GRAPHIC] [TIFF OMITTED] TR13AU21.213

BILLING CODE 4120-01-C
    The applicant excluded MS-DRGs that had fewer than 100 cases from 
the analysis. The applicant did not say how many cases it excluded 
based on this criterion.
    In total, the applicant identified 54,848 cases across 40 unique 
MS-DRGs. The applicant then removed charges for prior technology by 
dividing the per use cost for reusable duodenoscopes and related 
components \748\ by the hospital-specific cost-to-charge ratio from the 
FY 2021 IPPS/LTCH Proposed Rule Impact File at the claims level and 
averaging the resulting estimated charges by MS-DRG. The applicant then 
standardized the charges and applied an inflation factor of 13.2 
percent, or the 2-year inflation factor used to update the outlier 
threshold in the FY 2021 IPPS/LTCH final rule (85 FR 59039), to update 
the charges from FY 2019 to FY 2021. The applicant added charges for 
the aScopeTM Duodeno and related components by dividing the 
cost per use by the national cost-to-charge ratio of 0.2970 for 
Supplies and Equipment (85 FR 58601).
---------------------------------------------------------------------------

    \748\ Derived from Travis, et al. minus the 20 percent overhead 
cost.
---------------------------------------------------------------------------

    The applicant calculated a final inflated average case-weighted 
standardized charge per case of $89,945 and an average case-weighted 
threshold of $64,894. Because the final inflated average case-weighted 
standardized charge per case exceeded the average case-weighted 
threshold amount, the applicant asserted that the technology meets the 
cost criterion.
    In the FY 2022 IPPS/LTCH PPS proposed rule (86 FR 25366), we agreed 
with the applicant that the aScopeTM Duodeno meets the cost 
criterion; and therefore, we proposed to approve the 
aScopeTM Duodeno for new technology add-on payments for FY 
2022.
    Based on preliminary information from the applicant at the time of 
the proposed rule, the cost of the aScopeTM Duodeno is 
$2,184.27. However, the applicant noted in its application that this 
cost is broken down into three components, including the disposable 
sleeve, the aBox Duodeno (a video processor and light source), and 
other endoscopic accessories and equipment. We stated that we believed 
it is appropriate to only consider the cost of the disposable sleeve as 
the cost of the technology, as the other two components, which include 
the aBox Duodeno and an external monitor that, per the applicant, do 
not incur new costs per use, would thus be paid for under the IPPS for 
capital-related costs. As noted previously, because section 
1886(d)(5)(K)(i) of the Act requires that the Secretary establish a 
mechanism to recognize the costs of new medical services or 
technologies under the payment system established under that 
subsection, which establishes the system for paying for the operating 
costs of inpatient hospital services, we do not include capital costs 
in the add-on payments for a new medical service or technology or make 
new technology add on payments under the IPPS for capital-related 
costs. Thus, we stated that we believe the operating cost of the 
aScopeTM Duodeno is $1,995.
    Based on the information available at the time of the proposed 
rule, we stated that it appeared that both aScopeTM Duodeno 
and EXALTTM Model D will be identified by the same ICD-10-
PCS code and share the same indication for endoscopy and endoscopic 
surgery within the duodenum. We stated that as we are unable to 
separately identify these cases to apply two separate payment amounts 
for these technologies, we were proposing to use a case-weighted 
average to calculate a single cost that would be used to

[[Page 45135]]

determine the new technology add-on payment amount for both 
technologies. To compute the weighted average cost, we summed the total 
number of projected cases for each of the applicants, which equaled 
12,064 (3,750 plus 8,314). Then we divided the number of projected 
cases for each of the applicants by the total number of cases, which 
resulted in the following case-weighted percentages: 31 percent for 
aScopeTM Duodeno and 69 percent for EXALTTM Model 
D. We multiplied the cost per case for the manufacturer specific 
technology by the case-weighted percentage (0.31 * $1,995 = $620.13 for 
aScopeTM Duodeno and 0.69 * $2,930 = $2,019.23 for 
EXALTTM Model D). This resulted in a case-weighted average 
cost of $2,639.36 for both technologies. We invited public comments on 
the proposed case-weighted average, as well as any alternative 
approaches for determining and applying the new technology add-on 
payment amount for cases involving these technologies, for FY 2022.
    We noted that the cost information for this technology may be 
updated in the final rule based on revised or additional information 
CMS receives prior to the final rule. Under Sec.  412.88(a)(2), we 
limit new technology add-on payments to the lesser of 65 percent of the 
average cost of the technology, or 65 percent of the costs in excess of 
the MS-DRG payment for the case. As a result, we proposed that the 
maximum new technology add-on payment for a case involving the use of 
aScopeTM Duodeno or EXALTTM Model D would be 
$1,715.59 for FY 2022 (that is, 65 percent of the case-weighted average 
cost of both technologies).
    We invited public comments on whether aScopeTM Duodeno 
meets the cost criterion and our proposal to approve new technology 
add-on payments for aScopeTM Duodeno for FY 2022. We further 
invited public comments on the calculation of the maximum new 
technology add-on payment amount for the aScopeTM Duodeno.
    We did not receive comments on our proposals for the 
aScopeTM Duodeno for the new technology add-on payment for 
FY 2022. As we discuss later in this section, we separately received 
comments from the applicant for the EXALTTM Model D 
supporting CMS' proposal to use a case-weighted average to calculate a 
single cost that would be used to determine the new technology add-on 
payment amount.
    Based on the information provided in the application for new 
technology add-on payments we believe aScopeTM Duodeno meets 
the cost criterion. Also, aScopeTM Duodeno received 
marketing authorization from the FDA on July 17, 2020 for the 
indication covered by its Breakthrough Device designation. Therefore, 
we are finalizing our proposal to approve new technology add-on 
payments for aScopeTM Duodeno for FY 2022, and we consider 
the beginning of the newness period to commence on July 17, 2020 which 
is when the technology received FDA marketing authorization for the 
indication covered by its Breakthrough Device designation. Based on the 
information at the time of this final rule, and using the case-weighted 
average cost as described in the proposed rule and earlier in this 
final rule, the cost per case is $2,639.36. Under Sec.  412.88(a)(2), 
we limit new technology add-on payments to the lesser of 65 percent of 
the average cost of the technology, or 65 percent of the costs in 
excess of the MS DRG payment for the case. As a result, we are 
finalizing that the maximum new technology add-on payment for a case 
involving the use of the aScopeTM Duodeno or 
EXALTTM Model D would be $ 1,715.59 for FY 2022 (that is 65 
percent of the case-weighted average cost of both technologies). Cases 
involving the use of the aScopeTM Duodeno eligible for new 
technology add-on payments will be identified by ICD-10- PCS codes: 
XFJB8A7 (Inspection of hepatobiliary duct using single-use 
duodenoscope, new technology group 7) or XFJD8A7 (Inspection of 
pancreatic duct using single-use duodenoscope, new technology group).
(3) Caption GuidanceTM
    Caption Health, Inc. submitted an application for new technology-
add on payments for Caption GuidanceTM for FY 2022. Per the 
applicant, Caption GuidanceTM is an artificial intelligence 
(AI) guided medical imaging acquisition software system indicated for 
the acquisition of cardiac ultrasound images. The applicant explained 
that the system provides real-time guidance during transthoracic 
echocardiography (2D-TTE) to assist in obtaining anatomically correct 
and optimized images that represent standard 2D echocardiographic 
diagnostic views and orientations. The applicant also states that the 
technology is classified by FDA as software as a medical device (SaMD), 
so in order to use the software, the Caption GuidanceTM 
system must be installed on a compatible third-party ultrasound system.
    Caption GuidanceTM is designated as a Breakthrough 
Device, indicated to assist medical professionals in the acquisition of 
cardiac ultrasound images, and received FDA De Novo approval on 
February 7, 2020 for the same indication. The applicant stated that an 
updated version of the system subsequently received 510(k) clearance 
under 510(k) number K200755 on April 16, 2020 on an expedited basis due 
to COVID-19. Per the applicant, an interim version of the software 
became available on March 17, 2020, though not sold, on an emergency 
basis to assist sites in responding to the COVID-19 pandemic. According 
to the applicant, the first version of the technology was released 
commercially on September 15, 2020 with a first date of sale of 
September 29, 2020. Therefore, we stated that we believe that the 
newness date for this technology is the date on which Caption 
GuidanceTM became available on the market, September 15, 
2020. The item is a Class II medical device assigned to product code 
QJU with descriptor Image Acquisition And/Or Optimization Guided By 
Artificial Intelligence. The applicant submitted a request to the ICD-
10 Coordination and Maintenance Committee for a new code to uniquely 
identify the technology and was granted approval to identify Caption 
GuidanceTM using the following procedure code effective 
October 1, 2021: X2JAX47 (Inspection of heart using transthoracic 
echocardiography, computer-aided guidance, new technology group 7).
    Comment: Several commenters, including the applicant, supported the 
proposal to consider September 15, 2020, as the date on which Caption 
GuidanceTM became available for purposes of evaluating the 
newness period for new technology add-on payments. The applicant stated 
that the proposed newness date is appropriate given that, during FY 
2019, which is the time period of the data CMS proposed to use for 
recalibrating the MS-DRGs, Caption Guidance was not yet commercially 
available and as a result, the claims do not adequately reflect the 
cost of technology. In addition, the applicant stated that CMS has 
defaulted to the FDA approval date despite other reasons being provided 
by applicants regarding the date of first commercial availability. 
Another commenter also stated that requiring a manufacturer to submit 
information rebutting a presumption that the date of first availability 
is the date of FDA marketing authorization adds unnecessary burden and 
complexity to the new technology add-on payments application and review 
process. The commenter believes that a more efficient and appropriate 
policy would be for the new technology add-on payment newness period to

[[Page 45136]]

begin with the date of the first claim, which is consistent with the 
definition of newness used in determining the period of eligibility for 
Transitional Pass-through status in the Hospital Outpatient Prospective 
Payment System (OPPS).
    Response: We thank the commenters for their support and feedback 
and agree that the newness date for this technology is the date on 
which Caption GuidanceTM became available on the market, 
September 15, 2020, and that Caption GuidanceTM meets the 
newness criterion for FY 2022. We note that though, generally, our 
policy is to begin the newness period on the date of FDA approval or 
clearance, we may consider a documented delay in the technology's 
market availability in our determination of newness (77 FR 53348 and 70 
FR 47341).
    Regarding the commenter's belief that beginning the newness period 
on the date of first claim would be a more efficient and appropriate 
policy, as well as consistent with the definition of newness used in 
determining the period of eligibility for Transitional Pass-through 
status in OPPS, we note that ``newness'' for purposes of the OPPS pass-
through policy refers to a drug, biological, or device's eligibility 
for pass-through status. In particular, for pass-through drugs and 
biologicals, ``newness'' means that the drug or biological was first 
payable as an outpatient hospital service after December 31, 1996. For 
pass-through devices, ``newness'' means that CMS received the 
applicant's pass-through application within 3 years of the date of FDA 
approval for the device. It appears the commenter is referring not to 
newness in terms of eligibility for OPPS pass-through status, but 
rather to the two-to-three-year period for pass-through status can be 
in effect. Under Sec. Sec.  419.64(c)(2) and 419.66(g), the pass-
through period begins on the date on which CMS makes its first pass-
through payment for a drug, biological, or device. For new technology 
add-on payments, as we have discussed in prior rulemaking (77 FR 53348) 
and noted above, generally, our policy is to begin the newness period 
on the date of FDA approval or clearance or, if later, the date of 
availability of the product on the U.S. market.
    With respect to the cost criterion, the applicant searched the CY 
2019 Limited Data Set (LDS)--Carrier Standard Analytic File (SAF), 5 
percent sample, for beneficiaries receiving limited echocardiography, 
as described by Current Procedural Terminology (CPT[supreg]) code 93308 
(Echocardiography, transthoracic, real-time with image documentation 
(2D), includes M-mode recording, when performed, follow-up or limited 
study) with a place of service code 21 (inpatient hospital) or 23 
(emergency department) and the associated inpatient stays. Per the 
applicant, limited echocardiography, the procedure most likely to 
include Caption Guidance, is not reliably reported in the inpatient 
setting. As a result, the applicant used a multi-step approach where 
corresponding inpatient stays were identified in the CY 2019 LDS--
Inpatient SAF for the beneficiaries identified in the Carrier SAF. 
Inpatient stays were identified by matching on the unique beneficiary 
ID and by matching the carrier claim date of service against the 
inpatient admission and discharge dates. The applicant counted an 
inpatient stay if the date of service for CPT code 93308 occurred on or 
after the inpatient admission date (or during the three days preceding 
the date of admission), but was also on or before the discharge date of 
the hospital stay. The applicant eliminated non-inpatient claims and 
claims with a payment amount less than or equal to zero, as well as 
claims from hospitals that are not used in the ratesetting process.
    The applicant summarized the remaining claims by MS-DRG, and by 
principal diagnosis and MS-DRG. The applicant cross-walked the MS-DRG 
codes to FY 2021 MS-DRG definitions using the MS-DRG grouper for FY 
2021 and identified a list of 461 unique MS-DRGs to which cases 
representing patients who may be eligible for use of Caption 
GuidanceTM mapped. The applicant also utilized data from 
current Caption GuidanceTM customers to obtain a list of 
principal diagnoses associated with each MS-DRG. The applicant noted 
that, because this analysis began with the CY 2019 LDS Carrier SAF, 5 
percent sample, the inpatient claims captured underrepresent the total 
number of inpatient stays in which CPT code 93308 is expected to be 
performed. The applicant applied the unique MS-DRG and principal 
diagnosis combinations to all inpatient claims in the CY 2018 and CY 
2019 LDS SAF with a discharge date in FY 2019. The applicant then 
removed any claims where there were no billed charges in revenue 
centers 0480 (Cardiology-General) and 0483 (Cardiology-Echocardiology). 
The applicant explained that MS-DRG and principal diagnosis alone are 
unlikely to be a good proxy for performance of CPT code 93308. The 
applicant noted that there are charges to revenue centers 0480 and 0483 
among nearly 100 percent of cases identified, and that no other revenue 
centers were billed at such high frequency. The applicant explained 
that it did not use the FY 2021 MedPAR LDS for this reason, as the 
dataset does not report charges by revenue center.
    The applicant identified 1,932,386 cases mapping to 461 MS-DRGs. 
Then the applicant standardized the charges and applied the 2-year 
charge inflation factor used to adjust the outlier threshold 
determination, which the applicant stated was 10.22 percent. We note 
that the applicant appears to have used an inflation factor lower than 
the FY 2021 IPPS/LTCH PPS final rule of 13.2 percent (85 FR 59039), 
which would have resulted in a higher inflated charge figure. The 
applicant did not remove charges for prior technology as the applicant 
maintained that no existing technology is comparable to Caption 
GuidanceTM.
    The applicant then added charges for the new technology. The 
applicant calculated the technology's cost per case in a multi-step 
process. First, the applicant multiplied the cost of Caption 
GuidanceTM by the number of devices under the CCN of each 
subscribing provider to obtain a provider-specific total device cost. 
Next, for each subscribing provider, the applicant identified Medicare 
inpatient cases that would be eligible for Caption 
GuidanceTM using the criteria and methodology described 
previously. The applicant then multiplied the number of inpatient cases 
by 15 percent, which per the applicant is consistent with published 
evidence that the percent of limited echocardiography cases ranged from 
12 to 15 percent of all inpatient echocardiography services.\749\ The 
applicant then added the number of Medicare hospital outpatient cases 
for CPT code 93308 for each subscribing provider to the estimated 
inpatient limited echocardiography utilization to estimate total 
Medicare limited echocardiography by provider. The applicant divided 
the total Medicare inpatient and outpatient cases receiving limited 
echocardiogram by an average Medicare share of 63 percent, which the 
applicant estimated by analyzing discharges reporting three ICD-10-PCS 
codes: B244ZZZ (Ultrasonography of right heart), B245ZZZ 
(Ultrasonography of left heart), and B246ZZZ (Ultrasonography of right 
and left heart) from HCUPnet's Nationwide Inpatient

[[Page 45137]]

Sample, 2017, to obtain the total limited echocardiography cases. The 
applicant then divided the total device cost by the total limited 
echocardiography cases to obtain a provider-specific cost per case, 
which it then averaged across all subscriber hospitals. Finally, the 
applicant converted the cost per case to charges per case by dividing 
the cost per case by the national average cost-to-charge ratio for the 
cardiology cost center of 0.094 (85 FR 58601).
---------------------------------------------------------------------------

    \749\ Ward RP, Lee L, Ward TJ, Lang RM. Utilization and 
Appropriateness of Transthoracic Echocardiography in Response to he 
COVID-19 Pandemic. J Am Soc Echoardiogr. 2020 June;33(6):690-691. 
doi: 101.1016/j.echo.2020.04.006. Epub 2020 April 10.
---------------------------------------------------------------------------

    The applicant calculated a final inflated case-weighted average 
standardized charge per case of $113,435 and an average case-weighted 
threshold of $69,197. Because the final inflated average case-weighted 
standardized charge per case exceeded the average case-weighted 
threshold amount, the applicant asserted that the technology meets the 
cost criterion.
    We agreed with the applicant that, using the cost per case provided 
by the applicant, the Caption GuidanceTM system would meet 
the cost criterion and therefore proposed to approve the Caption 
GuidanceTM system for new technology add-on payments for FY 
2022.
    We stated that based on preliminary information from the applicant 
at the time of proposed rule, the cost per case of the Caption 
Guidance\TM\ system is $2,874. We noted that the cost information for 
this technology may be updated in the final rule based on revised or 
additional information CMS receives prior to the final rule. Under 
Sec.  412.88(a)(2), we limit new technology add-on payments to the 
lesser of 65 percent of the average cost of the technology, or 65 
percent of the costs in excess of the MS-DRG payment for the case. As a 
result, we proposed that the maximum new technology add-on payment for 
a case involving the use of the Caption GuidanceTM system 
would be $1,868.10 for FY 2022 (that is 65 percent of the average cost 
of the technology).
    In the proposed rule, we stated our concern that the applicant 
appears to have used a single list price of Caption 
GuidanceTM per hospital with a cost per patient that can 
vary based on the volume of cases. We stated that we were interested in 
information about whether the cost per patient varies based on the 
utilization of the technology by the hospitals. We stated that the cost 
per patient could be skewed by the small number of hospitals utilizing 
the technology and their low case volumes. It is possible, if hospitals 
with large patient populations adopt Caption GuidanceTM, the 
cost per patient would be significantly lower.
    In the FY 2021 IPPS/LTCH PPS final rule (85 FR 58628), in a similar 
instance, we stated our understanding that there are unique 
circumstances to determining a cost per case for a technology that 
utilizes a subscription for its cost. We invited comments from the 
public as to the appropriate method to determine a cost per case for 
such technologies, including comments on whether the cost per case 
should be estimated based on subscriber hospital data as described 
previously, and if so, whether the cost analysis should be updated 
based on the most recent subscriber data for each year for which the 
technology may be eligible for the new technology add-on payment.
    We invited public comments on whether the Caption 
GuidanceTM system meets the cost criterion and our proposal 
to approve new technology add-on payments for Caption 
GuidanceTM system for FY 2022, including on whether the 
newness period for this technology would begin on September 15, 2020.
    Comment: We received a few comments on our request for comment 
regarding technologies sold on a subscription basis and whether the 
cost per case should be estimated based on subscriber hospital data, 
and if so, whether the cost analysis should be updated based on the 
most recent subscriber data for each year for which the technology may 
be eligible for the new technology add-on payment. Most commenters 
agreed that in determining the cost per case for technologies seeking 
new technology add-on payment that utilize a subscription model, we 
should limit our analysis to subscriber hospitals and update the cost 
analysis on an annual basis. A commenter noted that alternative 
methodologies involving estimating the number of patients who would be 
eligible to receive treatment utilizing a technology sold on a 
subscription basis would be likely to result in a payment amount that 
does not adequately reflect the estimated average cost of such service 
or technology as required by the statute. The commenter believes that 
given the direct impact of utilization changes on cost per case when 
using a subscription model, it is reasonable for CMS to annually update 
the payment amount using the most recent subscriber utilization data.
    We also received a comment from the applicant stating that Caption 
GuidanceTM had been commercially available for less than 30 
days prior to the application deadline and that the first sale was 
completed within two weeks of this deadline. The applicant stated as 
there were too few subscriber hospitals to limit the cost per case 
analysis to just subscribers, they calculated the anticipated cost per 
case across all IPPS hospitals. The applicant explained that each 
hospital's anticipated total cost was determined based on the estimated 
number of devices multiplied by the list price per device. The 
applicant then explained that the cost per case was calculated using 
the anticipated total device costs and the estimated number of Medicare 
and non-Medicare cases. The applicant stated that an average of these 
unique costs per case was taken to derive the average cost per case 
across all IPPS hospitals, which the applicant then converted to 
charges using the national average cost-to-charge ratio of 0.094 for 
cardiology cost centers (85 FR 58601). The applicant also noted that it 
updated its cost analysis with the correct inflation factor of 13.22 
percent as advised in the FY 2022 IPPS proposed rule and stated that 
with the change, the technology still meets the cost criterion.
    Response: We thank the commenters for the support and feedback and 
agree that Caption GuidanceTM meets the cost criterion. We 
also thank the commenters for their feedback on determining a cost per 
case for technologies sold on a subscription basis. CMS will continue 
to consider the issues relating to calculation of the cost per unit of 
technologies sold on a subscription basis, including the merits of 
calculating the cost per case across all IPPS hospitals versus limiting 
the cost per case analysis to current users and whether the cost 
analysis should be updated based on the most recent subscriber data for 
each year for which the technology may be eligible for the new 
technology add-on payment, as we gain more experience in this area.
    Based on the information provided in the application for new 
technology add-on payments, and after consideration of the public 
comments we received, we believe Caption GuidanceTM system 
meets the cost criterion. Therefore, we are finalizing our proposal to 
approve new technology add-on payments for the Caption 
GuidanceTM system for FY 2022, and we consider the beginning 
of the newness period to commence on September 15, 2020 which is when 
the technology became commercially available for the indication covered 
by its Breakthrough Device designation. Based on the information at the 
time of this final rule, the cost per case of the Caption 
GuidanceTM system is $2,874. Under Sec.  412.88(a)(2), we 
limit new technology add-on payments to the lesser of 65 percent of the 
average cost of the technology, or 65 percent of the costs in excess of 
the MS DRG payment

[[Page 45138]]

for the case. As a result, we are finalizing that the maximum new 
technology add-on payment for a case involving the use of the Caption 
GuidanceTM system would be $1,868.10 for FY 2022 (that is 65 
percent of the average cost of the technology). Cases involving the use 
of the Caption GuidanceTM system that are eligible for new 
technology add-on payments will be identified by ICD-10-PCS code: 
X2JAX47 (Inspection of heart using transthoracic echocardiography, 
computer-aided guidance, new technology group 7).
(5) EXALTTM Model D Single-Use Duodenoscope
    Boston Scientific Corporation applied for new technology-add on 
payments for EXALTTM Model D Single-Use Duodenoscope 
(EXALTTM) for FY 2022. Per the applicant, EXALTTM 
is a single-use, flexible duodenoscope indicated for diagnostic and 
therapeutic treatment of the pancreaticobiliary system during 
endoscopic retrograde cholangiopancreatography (ERCP) procedures. 
According to the applicant, the scope is most commonly used to 
facilitate therapeutic maneuvers such as removal of gallstones from the 
bile ducts, dilation of strictures in the bile or pancreatic ducts, or 
to relieve an obstruction by inserting a plastic or metal stent. The 
applicant states that EXALTTM is intended to eliminate the 
risk of patient-to-patient transmission of infection related to 
reprocessing of reusable duodenoscopes.
    EXALTTM is designated as a Breakthrough Device, 
indicated for intended use with a Boston Scientific endoscopic video 
imaging system for endoscopy and endoscopic surgery within the 
duodenum, and received FDA 510(k) clearance as a Class II medical 
device on December 13, 2019 for the same indication. The applicant 
indicates that this device is the first FDA-cleared single-use 
duodenoscope in the U.S. According to the applicant, EXALTTM 
was available on the market immediately after FDA approval. The 
applicant listed 50 ICD-10-PCS codes that describe ERCP and other 
procedures in which EXALTTM and other duodenoscopes are 
used. The applicant submitted a request to the ICD-10 Coordination and 
Maintenance Committee for approval of a code to uniquely identify the 
technology and was granted approval to identify the EXALTTM 
using the following procedure codes effective October 1, 2021: XFJB8A7 
(Inspection of hepatobiliary duct using single-use duodenoscope, new 
technology group 7) and XFJD8A7 (Inspection of pancreatic duct using 
single-use duodenoscope, new technology group 7).
    With respect to the cost criterion, the applicant conducted two 
analyses based on 100 percent of identified claims and 76 percent of 
identified claims, both of which are further described later in this 
section. To identify potential cases where EXALTTM could be 
utilized, the applicant searched the FY 2019 MedPAR file for the 
following ICD-10-PCS codes:
BILLING CODE 4120-01-P
[GRAPHIC] [TIFF OMITTED] TR13AU21.214


[[Page 45139]]


[GRAPHIC] [TIFF OMITTED] TR13AU21.215

    For the analysis using 100 percent of cases, the applicant 
identified a total of 59,966 cases spanning 440 MS-DRGs. The applicant 
then removed 100 percent of charges associated with the service 
Medical/Surgical Supplies and Devices for the prior technology. The 
applicant stated that it does not believe use of EXALTTM 
will replace any other medical supplies but removed 100 percent of 
charges associated with service category Medical/Surgical Supply Charge 
Amount, which included the revenue center code 027x, to be as 
conservative as possible. The applicant then standardized the charges 
and applied an inflation factor of 13.2 percent, which is the same 
inflation factor used by CMS to update the outlier threshold in the FY 
2021 IPPS/LTCH PPS final rule, to update the charges from FY 2019 to FY 
2021 (85 FR 59039). The applicant added charges for the new technology 
by multiplying the cost of the technology by the national CCR for 
implantable devices from the FY 2021 IPPS/LTCH PPS final rule. Under 
the analysis based on 100 percent of claims, the applicant determined 
an average case-weighted threshold amount of $66,588 and a final 
inflated case weighted average standardized charge per case of $96,079.
    For the analysis using 76 percent of cases, which the applicant 
conducted due to these cases mapping to just 14 MS-DRGs, the applicant 
used the same methodology, which identified 45,530 cases across 14 MS-
DRGs. The applicant determined an average case-weighted threshold 
amount of $63,762 and a final inflated case weighted average 
standardized charge per case of $84,631. Because the final inflated 
case-weighted average standardized charge per case exceeded the average 
case-weighted threshold amount for both analyses, the applicant 
asserted that the technology meets the cost criterion.
    We stated in the proposed rule that we are concerned that the 
applicant used the national CCR for implantable devices from the FY 
2021 IPPS/LTCH PPS final rule, as a duodenoscope is not an implantable 
device. We noted that the cost analysis for another duodenoscope that 
is the subject of an application for new technology add-on payments for 
FY 2022, the aScopeTM Duodeno, used the national CCR for 
supplies and equipment to convert the cost of the technology to 
charges, and that we believe that the same CCR should apply for 
purposes of the cost analysis for EXALTTM Model D Single-Use 
Duodenoscope.
    We stated that we agreed with the applicant that EXALTTM 
Model D Single-Use Duodenoscope meets the cost criterion and therefore 
proposed to approve EXALTTM Model D Single-Use Duodenoscope 
for new technology add on payments for FY 2022.
    As discussed previously, based on the information available at the 
time of the proposed rule, it appeared that both aScopeTM 
Duodeno and EXALTTM Model D will be identified by the same 
ICD-10-PCS code and share the same indication for endoscopy and 
endoscopic surgery within the duodenum. We stated that thus, as we are 
unable to separately identify these cases to apply two separate payment 
amounts for these technologies, we were proposing to use a case-
weighted average to calculate a single cost that would be used to 
determine the new technology add-on payment amount for both 
technologies. To compute the weighted average cost, we summed the total 
number of projected cases for each of the applicants, which equaled 
12,064 (3,750 plus 8,314). Then we divided the number of projected 
cases for each of the applicants by the total number of cases, which 
resulted in the following case-weighted percentages: 31 Percent for 
aScopeTM Duodeno and 69 percent for EXALTTM Model 
D. We then multiplied the cost per case for the manufacturer specific 
technology by the case-weighted percentage (0.31 * $1,995 = $620.13 for 
aScopeTM Duodeno and 0.69 * $2,930 = $2,019.23 for 
EXALTTM Model D). This resulted in a case-weighted average 
cost of $2,639.36 for both technologies. We invited public comments on 
the proposed case-weighted average, as well as any alternative 
approaches for determining and applying the new technology add-on 
payment amount for cases involving these technologies, for FY 2022.
    We noted that the cost information for this technology may be 
updated in the final rule based on revised or additional information 
CMS receives prior to the final rule. Under Sec.  412.88(a)(2), we 
limit new technology add-on payments to the

[[Page 45140]]

lesser of 65 percent of the average cost of the technology, or 65 
percent of the costs in excess of the MS-DRG payment for the case. As a 
result, we proposed that the maximum new technology add-on payment for 
a case involving the use of the product EXALTTM Model D 
Single-Use Duodenoscope or aScopeTM Duodeno would be 
$1,715.59 for FY 2022 (that is 65 percent of the case-weighted average 
cost of both technologies).
    We invited public comments on whether EXALTTM Model D 
Single-Use Duodenoscope meets the cost criterion and our proposal to 
approve new technology add-on payments for EXALTTM Model D 
Single-Use Duodenoscope for FY 2022. We further invited public comments 
on our calculation of the maximum new technology add-on payment amount 
for the EXALTTM Model D.
    Comment: A commenter, the applicant, submitted a public comment 
urging CMS to finalize its proposal to approve an add-on payment for 
EXALTTM Model D Single-Use Duodenoscope. The commenter 
agreed that EXALT Model D meets the cost criterion and therefore 
satisfies the criteria under the alternative new technology pathway for 
certain transformative new devices finalized by CMS in the FY 2020 IPPS 
Final Rule. The commenter also supported CMS' proposal to use a case-
weighted average to calculate a single cost that would be used to 
determine the new technology add-on payment amount.
    Response: We thank the commenter for its support and feedback.
    Based on the information provided in the application for new 
technology add-on payments, and after consideration of the public 
comments we received, we believe EXALTTM Model D meets the 
cost criterion. Also, EXALTTM Model D received marketing 
authorization from the FDA on December 13, 2019 for the indication 
covered by its Breakthrough Device designation. Therefore, we are 
finalizing our proposal to approve new technology add-on payments for 
the EXALTTM Model D for FY 2022, and we consider the 
beginning of the newness period to commence on December 13, 2019 which 
is when the technology received FDA marketing authorization for the 
indication covered by its Breakthrough Device designation. Based on the 
information at the time of this final rule, and using the case-weighted 
average cost as described in the proposed rule and earlier in this 
final rule, the cost per case of the EXALTTM Model D is 
$2,639.36. Under Sec.  412.88(a)(2), we limit new technology add-on 
payments to the lesser of 65 percent of the average cost of the 
technology, or 65 percent of the costs in excess of the MS DRG payment 
for the case. As a result, we are finalizing that the maximum new 
technology add-on payment for a case involving the use of the 
EXALTTM Model D Single-Use Duodenoscope or 
aScopeTM Duodeno would be $1,715.59 for FY 2022 (that is 65 
percent of the case-weighted average cost of both technologies). Cases 
involving the use of the EXALTTM Model D eligible for new 
technology add-on payments will be identified by ICD-10- PCS codes: 
XFJB8A7 (Inspection of hepatobiliary duct using single-use 
duodenoscope, new technology group 7) or XFJD8A7 (Inspection of 
pancreatic duct using single-use duodenoscope, new technology group 7).
(6) FUJIFILM EP-7000X System
    Fujifilm Corporation submitted an application for new technology-
add on payments for FUJIFILM EP-7000X System for FY 2022. The FUJIFILM 
EP-7000X system is an endoscopic video imaging system used for 
endoscopic observation, diagnosis, treatment, and image recording in 
minimally invasive surgeries of abdominal gynecologic and thoracic 
areas. Per the applicant, this system allows for the visualization of 
hemoglobin oxygen saturation levels of blood in superficial tissue 
under a 2D endoscopic image, which helps physicians identify tissue 
that is not appropriately oxygenated and thus potentially ischemic. The 
applicant further explains that the technology consists of four 
components: Video Laparoscope EL-R740M, Processor VP-7000, Light Source 
BL-7000X, and Image Processing Unit EX-0.
    The FUJIFILM EP-7000X system received Breakthrough Device 
designation for endoscopic observation, diagnosis, treatment, and image 
recording in patients requiring such procedures on September 17, 2020 
and was granted FDA 510(k) clearance on June 30, 2021. The applicant 
submitted a request to the ICD-10 Coordination and Maintenance 
Committee for approval of a unique code for FY 2022 to identify the 
technology and was granted approval to identify the FUJIFILM EP-7000X 
system using the following procedure codes effective October 1, 2021:
[GRAPHIC] [TIFF OMITTED] TR13AU21.216

    With respect to the cost criterion, the applicant searched the FY 
2019 MedPAR claims data file to identify potential cases representing 
patients who may be eligible for treatment with the EP-7000X System. 
The applicant identified claims that reported an ICD-10-PCS procedure 
code for gastrointestinal bypass or hernia repair, which the applicant 
listed in the following table:

[[Page 45141]]

[GRAPHIC] [TIFF OMITTED] TR13AU21.217


[[Page 45142]]


[GRAPHIC] [TIFF OMITTED] TR13AU21.218


[[Page 45143]]


[GRAPHIC] [TIFF OMITTED] TR13AU21.219


[[Page 45144]]


[GRAPHIC] [TIFF OMITTED] TR13AU21.220


[[Page 45145]]


[GRAPHIC] [TIFF OMITTED] TR13AU21.221

BILLING CODE 4120-01-C
    Per the applicant, oxygen saturation endoscopic imaging would not 
be necessary, as both imaging procedures are used to evaluate vascular 
perfusion and therefore the applicant excluded cases with the ICD-10-
PCS procedure code 4A1BXSH (Monitoring of Gastrointestinal Vascular 
Perfusion using Indocyanine Green Dye, External Approach). In addition, 
the applicant compared cases with procedure code 4A1BXSH to cases 
without procedure code 4A1BXSH and found that cases with the procedure 
code have higher total standardized charges. The applicant further 
limited the cases to MS-DRGs with at least one percent of case volume, 
leaving 12,020 cases spread across 16 MS-DRGs, or 83 percent of the 
14,522 cases initially identified. The applicant standardized the 
charges and applied an inflation factor of 13.2 percent, which is the 
same inflation factor used by CMS to update the outlier threshold in 
the FY 2021 IPPS/LTCH PPS final rule, to update the charges from FY 
2019 to FY 2021 (85 FR 59039). The applicant did not remove charges for 
the current technology as the applicant believed the use of EP-87000X 
System would not replace any other therapies except for the vascular 
perfusion monitoring procedure for which cases were already excluded.
    The applicant then added charges for the new technology. The 
applicant explained that the total cost of the EP-87000X System 
consists of the capital equipment as well as a service contract for the 
equipment and a calibration fee required to perform a calibration 
between a video laparoscope and light source every 6 months. The 
applicant stated that it calculated the equipment cost per minute using 
the Medicare physician fee schedule formula used for calculating 
practice expense relative value units (RVUs). The applicant stated that 
it also assumed a 3 percent usage rate, a 5.5 percent interest rate, a 
0 percent maintenance factor (as the maintenance fee is built into the 
cost of the equipment), and a 5-year useful life. The applicant 
multiplied the machine cost per minute by the number of minutes of 
procedure time, which the applicant estimated to be 4.5 hours or 270 
minutes, to obtain the per patient cost. The applicant then converted 
the cost to charges by dividing the cost per patient by the national 
average cost-to-charge ratio for supplies and equipment (0.297).
    Based on the cost information, the applicant calculated a final 
inflated case-weighted average standardized charge per case of $106,603 
and an average case-weighted threshold of $80,392. Because the final 
inflated case-weighted average standardized charge per case exceeded 
the average case-weighted threshold amount, the applicant asserted that 
the technology meets the cost criterion.
    In the FY 2022 IPPS/LTCH PPS proposed rule (86 FR 25380), we stated 
that because section 1886(d)(5)(K)(i) of the Act requires that the 
Secretary establish a mechanism to recognize the costs of new medical 
services or technologies under the payment system established under 
that subsection, which establishes the system for paying for the 
operating costs of inpatient hospital services, we do not include 
capital costs in the add-on payments for a new medical service or 
technology or make new technology add-on payments under the IPPS for 
capital-related costs. We stated that based on preliminary information 
from the applicant, it appeared that the costs of the FUJIFILM EP-7000X 
System did not include any operating costs. Therefore, we stated that 
even if the technology meets the cost criterion, it appeared that no 
new technology add-on payment would be made for the FUJIFILM EP-7000X 
System because, as discussed in prior rulemaking and noted previously, 
we only make new technology add-on payments for operating costs (72 FR 
47307 through 47308). We invited public comments on whether the

[[Page 45146]]

FUJIFILM EP-7000X System has any operating costs. We proposed to 
approve new technology add-on payments for only the operating costs of 
FUJIFILM EP-7000X System for FY 2022 if it was determined that the 
technology does have operating costs, since it appears to meet the cost 
criterion as previously noted, subject to the technology receiving FDA 
marketing authorization for endoscopic observation, diagnosis, 
treatment, and image recording in patients requiring such procedures by 
July 1, 2021.
    Comment: We received one comment from the applicant supporting the 
FUJIFILM EP-7000X System be approved for new technology add-on payment 
for FY 2022. The commenter stated that by virtue of the 510(k) 
clearance (K203717) the FDA marketing authorization is expected by July 
15, 2021. Also, the applicant provided updated cost information and 
stated that the EP-7000X System contains both capital and operating 
costs. Per the applicant, the capital costs include those associated 
with the processor, light source, and imaging processing unit, and the 
operating costs include (1) the flexible endoscope/video laparoscope, 
which are types of minor equipment treatable as operating costs by 
hospitals, and (2) the maintenance cost associated with reprocessing 
and calibration, which are treated as operating expenses by CMS. The 
commenter asserted that the video laparoscope and flexible endoscope 
are ``minor equipment'' and, therefore, treatable as an operating cost 
and not a capital cost. The applicant stated that CMS has a multi-
factored test for determining whether a device is minor equipment: (a) 
In general it has no fixed location and is subject to use by various 
departments of the provider's facility; (b) it is comparatively small 
in size and unit cost; (c) it is subject to inventory control; (d) 
there is a fairly large quantity in use; and, (e) generally, it has a 
useful life of approximately 3 years or less.\750\ Per the applicant, 
the video laparoscope and flexible endoscope are minor equipment 
because they are relatively small in size (the video laparoscope is 
only 330 mm in length), are mobile and not in a fixed location, and may 
be inventoried separately from other components of the device because 
they are reprocessed between uses. The applicant further stated that 
the useful life of the video laparoscope and flexible endoscope is one 
year, as evidenced by the product warranty of that length of time. Per 
the applicant, because the video laparoscope and flexible endoscope are 
integral to the EP-7000X and are treatable as operating costs by virtue 
of being minor equipment, there are operating costs associated with the 
technology.
---------------------------------------------------------------------------

    \750\ Provider Reimbursement Manual (PRM) Part 1, ch. 1, Sec.  
104.5.
---------------------------------------------------------------------------

    The applicant further stated that the fees and costs associated 
with reprocessing, sterilization, and maintenance of the device are 
maintenance fees due to the use of the video laparoscope and flexible 
endoscope for more than one patient and are also not considered to be 
capital costs.\751\
---------------------------------------------------------------------------

    \751\ Provider Reimbursement Manual (PRM), Part 1, ch. 28 Sec.  
2806.2.
---------------------------------------------------------------------------

    Response: We thank the applicant for their comment. However, we 
remain concerned that the cost for FUJIFILM EP-7000X System includes 
only capital-related costs and does not include operating costs. We 
note that the flexible endoscope is not included on the Breakthrough 
Device designation and is therefore ineligible for new technology add-
on payments under the alternative pathway, and the remainder of our 
response refers only to the video laparoscope listed on the 
Breakthrough Device designation. We agree that minor equipment, as 
determined by the multi-factor test described in the Provider 
Reimbursement Manual (PRM) above, can be considered to be operating 
costs in some cases. Though the applicant asserts that the technology 
meets the criteria to be considered minor equipment, we disagree that 
the useful life of a technology is evidenced by its warranty, and 
believe that the useful life described in the criteria would extend for 
many years past that, particularly in the case of scopes. Since we 
believe that the video laparoscope would have a useful life extending 
past 3 years, we cannot consider it to be treatable as operating costs 
as it is not minor equipment. We further note that the PRM states that 
items that have a standalone functional capability may be considered on 
an item-by-item basis, but items purchased as in integrated system must 
be considered as a single asset when applying the capitalization 
threshold.\752\ Since the video laparoscope does not have a standalone 
functional capacity as it requires connections to the capital 
components of the system (that is, light source, processor) to 
function, we consider the FUJIFILM EP-7000x System to be capital as it 
is an integrated system and believe we should not separate individual 
components of the system for the purposes of determining whether it 
includes operating costs.
---------------------------------------------------------------------------

    \752\ PRM, Part1, ch. 1, Sec.  108.1.
---------------------------------------------------------------------------

    In addition, while we agree with the applicant's assertion that 
maintenance and processing fees are considered operating expenses, when 
determining a new technology add-on payment, we provide payment based 
on the cost of the actual technology (such as the drug or device 
itself) and not for additional costs related to the use of the device, 
such as the ongoing use of the device including maintenance and 
processing fees. For example, if a technology required an extra hour of 
operating room time, or reduced the amount of procedure time, we would 
neither add nor deduct costs based on this, and would only consider the 
actual cost of the technology at the time of purchase in our 
determination of the add-on payment. Therefore, the maintenance and 
processing fees described by the applicant are not eligible to be 
included in new technology add-on payments.
    Based on the above, we continue to believe that there are no 
operating costs with the use of the FUJIFILM EP-7000X System. 
Therefore, we are not approving new technology add-on payments for the 
FUJIFILM EP-7000X System for FY 2022.
(7) HarmonyTM Transcatheter Pulmonary Valve (TPV) System
    Medtronic submitted an application for new technology-add on 
payments for HarmonyTM Transcatheter Pulmonary Valve (TPV) 
System (``HarmonyTM'') for FY 2022. The system consists of a 
bioprosthetic heart valve developed from porcine pericardial tissue 
mounted on self-expanding nitinol struts sewn to a polyester fabric. 
According to the applicant, HarmonyTM is implanted in the 
patient's heart between the right ventricle and the bifurcation of the 
pulmonary arteries to treat patients with congenital heart disease who 
are indicated for a pulmonary valve replacement. The applicant states 
that HarmonyTM is the first transcatheter pulmonary valve 
that is designed to treat the patient's condition at the native site of 
the pulmonary valve without a pre-existing valve conduit or pre-
existing bioprosthetic valve.
    The HarmonyTM TPV System received designation as a 
Breakthrough Device on May 1, 2019, with the indication for the 
treatment of symptomatic severe pulmonary regurgitation in patients 
with a surgically-repaired right ventricular outflow tract. In the 
proposed rule, we stated that the applicant noted that the proposed 
indication for the FDA marketing authorization would be more expansive 
than the indication for the FDA

[[Page 45147]]

Breakthrough Device status, to include patients who have had a prior 
transcatheter intervention. We noted that under the eligibility 
criteria for approval under the alternative pathway for certain 
transformative new devices, only the use of the HarmonyTM 
TPV System for the treatment of symptomatic severe pulmonary 
regurgitation in patients with a surgically-repaired RVOT, and the FDA 
Breakthrough Device designation it received for that use, are relevant 
for purposes of the new technology add-on payment application for FY 
2022. Subsequently, the applicant received Premarket Approval (PMA) as 
a Class III medical device on March 26, 2021 with an indication for use 
in the management of pediatric and adult patients with severe pulmonary 
regurgitation (that is, severe pulmonary regurgitation as determined by 
echocardiography and/or pulmonary regurgitant fraction >=30% as 
determined by cardiac magnetic resonance imaging) who have a native or 
surgically-repaired right ventricular outflow tract and are clinically 
indicated for surgical pulmonary valve replacement. Since the 
Breakthrough Device designation is indicated for use in patients with a 
surgically-repaired RVOT, and does not include patients with a native 
RVOT, we note that only the Breakthrough Device indication is eligible 
for new technology add-on payments.
    The applicant noted that the HarmonyTM TPV System is 
currently reported within table 02R of the ICD-10 PCS tabular list 
(body part value Pulmonary Valve, approach value Percutaneous, device 
value as appropriate, and qualifier value No Qualifier). Per the 
applicant, this same code also applies to existing technology for 
transcatheter valve replacement within a conduit or a pre-existing 
prosthetic valve. The applicant submitted a request to the ICD-10 
Coordination and Maintenance Committee for approval of a unique code 
for FY 2022 to identify the technology and was granted approval to 
identify the HarmonyTM Transcatheter Pulmonary Valve (TPV) 
using the following procedure code effective October 1, 2021: 02RH38M 
(Replacement of pulmonary valve with zooplastic tissue, native site, 
percutaneous approach).
    With respect to the cost criterion, the applicant searched the FY 
2019 MedPAR dataset for claims representing patients with congenital 
diagnoses who received a surgical valve or a transcatheter procedure. 
The applicant identified claims across five MS-DRGs after excluding 
cases with outlier payments. Per the applicant, 6 percent of cases were 
in MS-DRG 216, 24 percent of cases were in MS-DRG 219, 12 percent of 
cases were in MS-DRG 220, 26 percent of cases were in MS-DRG 266, and 
32 percent of cases were in MS-DRG 267. The applicant did not provide 
case counts because the volume in each MS-DRG was fewer than 11 cases.
    Next, the applicant removed charges for the prior technology and 
standardized the charges. The applicant described the charges for the 
technology that would be replaced as ``the sum of the medical-surgical 
pacemaker amount, the intraocular lens amount, the other implants 
amount, and the investigational device amount.'' The applicant also 
removed charges related to the prior technology, which it described as 
``the sum of the medical surgical supplies amount, the durable medical 
equipment amount, and the used durable medical amount minus the prior 
technology charges.'' The applicant then applied an inflation factor of 
13.1 percent, which per the applicant is the same inflation factor used 
by CMS to update the outlier threshold in the FY 2021 IPPS/LTCH PPS 
final rule, to update the charges from FY 2019 to FY 2021. We note that 
the applicant appears to have used the FY 2021 IPPS/LTCH PPS proposed 
rule inflation factor rather than the 2-year inflation factor from the 
FY 2021 IPPS/LTCH PPS final rule of 13.2 percent (85 FR 59039), which 
would have resulted in a higher inflated charge figure. The applicant 
added charges for the new technology by dividing the cost of the 
HarmonyTM TPV by the national CCR for implantable devices, 
which is 0.293 (85 FR 58601). The applicant also added charges related 
to the new technology, which the applicant estimated to be similar to 
the charges related to transcatheter procedures within MS-DRGs 266-267.
    The applicant calculated a final inflated case-weighted average 
standardized charge per case of $257,970 and an average case-weighted 
threshold of $202,037. Because the final inflated case-weighted average 
standardized charge per case exceeded the average case-weighted 
threshold amount, the applicant asserted that the technology meets the 
cost criterion.
    In the FY 2022 IPPS/LTCH PPS proposed rule (86 FR 25381), we 
expressed our concern that the applicant's charge threshold analysis 
utilized a small sample of 55 cases, given that the applicant projected 
a case volume of over 1,000 cases for FY 2022. Subject to the applicant 
adequately addressing this concern, we stated that we would agree that 
the technology meets the cost criterion and therefore are proposing to 
approve HarmonyTM Transcatheter Pulmonary Valve (TPV) System 
for new technology add-on payments for FY 2022, subject to the 
technology receiving FDA marketing authorization for the treatment of 
symptomatic severe pulmonary regurgitation in patients with a 
surgically-repaired right ventricular outflow tract by July 1, 2021. We 
stated that, as noted previously, only the use of the 
HarmonyTM TPV System for the treatment of symptomatic severe 
pulmonary regurgitation in patients with a surgically-repaired right 
ventricular outflow tract, and the FDA Breakthrough Device designation 
it received for that use, are relevant for purposes of the new 
technology add-on payment application for FY 2022.
    Based on preliminary information from the applicant at the time of 
the proposed rule, the cost of the HarmonyTM Transcatheter 
Pulmonary Valve (TPV) System is $41,500. Per the applicant, this cost 
is comprised of $33,000 for the HarmonyTM TPV and $8,500 for 
the HarmonyTM transcatheter pulmonary valve delivery and 
loading system. We stated that it was not clear to us whether these 
costs reflect the use of capital equipment. We noted that the cost 
information for this technology may be updated in the final rule based 
on revised or additional information CMS receives prior to the final 
rule. Under Sec.  412.88(a)(2), we limit new technology add-on payments 
to the lesser of 65 percent of the average cost of the technology, or 
65 percent of the costs in excess of the MS-DRG payment for the case. 
We stated as a result, if both components of the HarmonyTM 
Transcatheter Pulmonary Valve (TPV) System are operating costs, we were 
proposing that the maximum new technology add-on payment for a case 
involving the use of the HarmonyTM Transcatheter Pulmonary 
Valve (TPV) System would be $26,975 for FY 2022 (that is 65 percent of 
the average cost of the technology).
    We invited public comments on whether the HarmonyTM 
Transcatheter Pulmonary Valve (TPV) System meets the cost criterion and 
our proposal to approve new technology add-on payments for 
HarmonyTM Transcatheter Pulmonary Valve (TPV) System for FY 
2022, subject to FDA marketing authorization of HarmonyTM 
Transcatheter Pulmonary Valve (TPV) System by July 1, 2021 for the 
treatment of patients with severe pulmonary regurgitation who have had 
prior intervention on the right ventricular outflow tract and are 
clinically indicated for a pulmonary valve

[[Page 45148]]

replacement. We also invited public comment on whether the costs of the 
HarmonyTM TPV and HarmonyTM transcatheter 
pulmonary valve delivery and loading system reflect use of capital 
equipment.
    Comment: The applicant submitted a public comment urging CMS to 
finalize its proposal to approve a new technology add-on payment for 
HarmonyTM Transcatheter Pulmonary Valve (TPV) System. The 
commenter noted that the proposed rule referred to the anticipated FDA 
approval of the technology as 510(k) clearance instead of premarket 
approval application (PMA). The commenter also requested that CMS 
consider that because FDA grants Breakthrough Device designation early 
in the product development process, the final indication for a product 
may evolve based on clinical research findings, and therefore may not 
be identical to the proposed indication wording at the time the 
designation is granted. In the specific case of the 
HarmonyTM TPV System, the applicant stated that the final 
commercial indication differs from the Breakthrough Device designation 
in that it also includes use in native right ventricular outflow tracts 
in addition to surgically-repaired right ventricular outflow tracts. 
The applicant further stated that the final approval reflects a single, 
ongoing development and review process, which is distinct from 
scenarios in which a manufacturer may submit additional indications for 
separate reviews and approvals/clearances that are not encompassed by 
the single process arising from the Breakthrough Device designation. 
Accordingly, it requested that the new technology add-on payment 
eligibility apply to the full FDA-approved indication for the 
HarmonyTM TPV System.
    With respect to the concerns for the cost criterion that the charge 
threshold analysis conducted for the HarmonyTM TPV System 
utilized a small sample of 55 cases, while their projected case volume 
was over 1,000 cases for FY 2022 (86 FR 25381) the applicant clarified 
that the projected sales volume of 1,054 that was included in the 
application included patients across payer types, while the cost 
criterion analysis was based on Medicare claims data only. The 
applicant stated that it was indicated in the application, based on 
analysis of the Nationwide Inpatient Sample (NIS) dataset, which is 
part of the Healthcare Cost and Utilization Project sponsored by the 
Agency for Healthcare Research and Quality, that approximately 16 
percent of the total number of patients with the relevant congenital 
heart disease diagnosis codes (selected based on the patients enrolled 
in the HarmonyTM feasibility and IDE studies) were Medicare 
beneficiaries. The commenter applied this percentage to the projected 
sales volume of 1,054 to project the anticipated Medicare volume to be 
171 patients. While the projected Medicare volume of 171 still exceeds 
the cases found in the historical claims data for the target patient 
population, the applicant stated it is directionally more consistent 
than the figure of over 1,000 cases, about which CMS expressed concern 
in the proposed rule. The applicant further stated that because 
HarmonyTM represents a new, less invasive treatment option 
for patients, it is reasonable to expect that more interventions may be 
performed in the future than what is currently reflected by the number 
of cases in the historical claims data.
    With respect to the concern that the costs of HarmonyTM 
TPV may include capital costs, the applicant stated that they can 
confirm that neither of the components listed are considered capital 
equipment, as both the bioprosthetic heart valve and the delivery 
system are single-use products. The applicant stated that specifically, 
the bioprosthetic valve is implanted in the patient's heart where it 
remains, and the delivery system delivers the valve to the heart and is 
then discarded after a single use.
    Response: We thank the commenter for the additional information and 
feedback. We agree that the FDA approval of the technology should be 
listed as a premarket approval application (PMA) and in this final 
rule, have revised the description of the relevant approval to indicate 
that the applicant received Premarket Approval (PMA) as a Class III 
medical device on March 26, 2021. With regard to the differences 
between the Breakthrough Device designation indication and the PMA 
indication, under Sec.  412.87(c)(1), a new medical device under the 
alternative pathway must receive marketing authorization for the 
indication covered by the Breakthrough Devices Program designation (85 
FR 58736). Since the PMA indication is broader than the Breakthrough 
Device indication in that it includes native outflow tracts in addition 
to surgically-repaired outflow tracts, only the Breakthrough Device 
indication is applicable for purposes of new technology add-on 
payments.
    Regarding the cost criterion, we thank the applicant for its 
explanation of the discrepancy between the projected sales volume and 
the anticipated Medicare volume. We also agree with the applicant that 
both the bioprosthetic heart valve and the delivery system are single-
use products and that these components are not capital costs.
    Based on the information provided in the application for new 
technology add-on payments, and after consideration of the public 
comment we received, we believe HarmonyTM Transcatheter 
Pulmonary Valve (TPV) System meets the cost criterion. Therefore, we 
are finalizing our proposal to approve new technology add-on payments 
for the HarmonyTM Transcatheter Pulmonary Valve (TPV) System 
for FY 2022, and we consider the beginning of the newness period to 
commence on March 26, 2021, which is when the technology received FDA 
marketing authorization for use in the management of pediatric and 
adult patients with severe pulmonary regurgitation (that is, severe 
pulmonary regurgitation as determined by echocardiography and/or 
pulmonary regurgitant fraction >=30% as determined by cardiac magnetic 
resonance imaging) who have a native or surgically-repaired right 
ventricular outflow tract and are clinically indicated for surgical 
pulmonary valve replacement. As previously discussed, under the 
eligibility criteria for approval under the alternative pathway for 
certain transformative new devices, only the use of the 
HarmonyTM TPV System for the treatment of symptomatic severe 
pulmonary regurgitation in patients with a surgically-repaired RVOT, 
and the FDA Breakthrough Device designation it received for that use, 
are relevant for purposes of the new technology add-on payment 
application for FY 2022. Since the Breakthrough Device designation is 
indicated for use in patients with a surgically-repaired RVOT, and does 
not include patients with a native RVOT, only cases involving the 
Breakthrough Device indication for use in patients with a surgically-
repaired RVOT are eligible for new technology add-on payments.
    Based on the information at the time of this final rule, the cost 
per case of the HarmonyTM Transcatheter Pulmonary Valve 
(TPV) System is $41,500. Under Sec.  412.88(a)(2), we limit new 
technology add-on payments to the lesser of 65 percent of the average 
cost of the technology, or 65 percent of the costs in excess of the MS 
DRG payment for the case. As a result, we are finalizing that the 
maximum new technology add-on payment for a case involving the use of 
the HarmonyTM Transcatheter Pulmonary Valve (TPV) System 
would be $26,975 for FY 2022 (that is 65 percent of the average cost of 
the technology). Cases involving the use of the HarmonyTM 
Transcatheter Pulmonary Valve (TPV) System that are

[[Page 45149]]

eligible for new technology add-on payments will be identified by ICD-
10- PCS code 02RH38M (Replacement of pulmonary valve with zooplastic 
tissue, native site, percutaneous approach).
(10) INTERCEPT Fibrinogen Complex (PRCFC)
    Cerus Corporation applied for new technology-add on payments for 
INTERCEPT Fibrinogen Complex (pathogen reduced cryoprecipitated 
fibrinogen complex), for FY 2022. INTERCEPT Fibrinogen Complex is a 
blood product indicated for the treatment for fibrinogen deficiency-
related bleeding, including massive hemorrhage. Per the applicant, this 
blood product is useful in emergency departments and operating rooms 
due to its 5-day shelf life at room temperature. The applicant stated 
that the 5-day shelf life of the blood product makes it immediately 
available in a ready-to-transfuse form as a fibrinogen source and 
thereby provides a significant benefit for patients with massive 
hemorrhage in a real time-critical fashion that is not achievable with 
other existing fibrinogen replacement products.
    INTERCEPT Fibrinogen Complex is designated as a Breakthrough 
Device, indicated for control of massive bleeding associated with 
fibrinogen (Fg) deficiency, and received FDA premarket approval (PMA) 
on November 24, 2020 for the following indications: (1) Treatment and 
control of bleeding, including massive hemorrhage, associated with 
fibrinogen deficiency; (2) control of bleeding when recombinant and/or 
specific virally inactivated preparations of factor XIII or von 
Willebrand factor (vWF) are not available; (3) second-line therapy for 
von Willebrand disease (vWD); and (4) control of uremic bleeding after 
other treatment modalities have failed. The applicant provided 
information stating that the product was not available for sale until 
May 5, 2021 due to manufacturing lead time for system components as 
well as validations and quality control analyses that needed to be 
completed by the manufacturing facilities and delayed production of 
commercially available product. We note that, under the eligibility 
criteria for approval under the alternative pathway for certain 
transformative new devices, only the use of INTERCEPT Fibrinogen 
Complex for the control of massive bleeding associated with fibrinogen 
(Fg) deficiency, and the FDA Breakthrough Device designation it 
received for that use, are relevant for purposes of the new technology 
add-on payment application for FY 2022.
    The applicant submitted a request to the ICD-10 Coordination and 
Maintenance Committee for approval of a unique code for FY 2022 to 
identify the technology and was granted approval to identify INTERCEPT 
Fibrinogen Complex using the following procedure codes effective 
October 1, 2021: 30233D1 (Transfusion of nonautologous pathogen reduced 
cryoprecipitated fibrinogen complex into peripheral vein, percutaneous 
approach) and 30243D1 (Transfusion of nonautologous pathogen reduced 
cryoprecipitated fibrinogen complex into central vein, percutaneous 
approach).
    With respect to the cost criterion, the applicant searched the FY 
2019 MedPAR dataset for cases reporting an ICD-10-PCS procedure code 
for nonautologous plasma cryoprecipitate. The applicant identified 
8,553 cases spanning over 369 MS-DRGs.
[GRAPHIC] [TIFF OMITTED] TR13AU21.222

    Per the applicant, the top 5 MS-DRGs were 219 (Cardiac Valve and 
Other Major Cardiothoracic Procedures Without Cardiac Catheterization 
with MCC), 220 (Cardiac Valve and Other Major Cardiothoracic Procedures 
Without Cardiac Catheterization with CC), 871 (Septicemia or Severe 
Sepsis Without Mv >96 Hours with MCC), 003 (ECMO or Tracheostomy with 
Mv >96 Hours Or Principal Diagnosis Except Face, Mouth And Neck With 
Major O.R. Procedure), and 216 (Cardiac Valve and Other Major 
Cardiothoracic Procedures with Cardiac Catheterization with MCC) and 
accounted for 34 percent of all cases. The applicant then removed 
charges for the technology being replaced. Per the applicant, INTERCEPT 
Fibrinogen Complex would replace the current nonautologous plasma 
cryoprecipitate billed with a blood revenue code. The applicant 
explained that it could not separate nonautologous plasma 
cryoprecipitate from other blood charges and therefore removed all 
charges from the blood department. The applicant then standardized the 
charges and applied the 2-year outlier inflation factor of 13.2 percent 
used to update the outlier threshold in the FY 2021 IPPS/LTCH final 
rule (85 FR 59039). To estimate the cost of the technology, the 
applicant multiplied the sale price of INTERCEPT Fibrinogen Complex by 
an average of 12.9 units of cryoprecipitate required per patient, which 
the applicant asserted as equivalent to 5.2 grams of fibrinogen based 
on a recent study in adult cardiac surgery patients with clinically 
significant bleeding and fibrinogen deficiency.\753\ The applicant 
estimated an average per-patient cost of $3,900, which the applicant 
converted to charges using the national cost-to-charge ratio for blood 
and blood products (0.271) from the FY 2021 IPPS/LTCH PPS final rule 
(85 FR 58601). The applicant indicated that the outlier inflation 
factor was not applied to charges for INTERCEPT Fibrinogen Complex.
---------------------------------------------------------------------------

    \753\ Callum J. et al. (2019). Effect of fibrinogen concentrate 
vs cryoprecipitate on blood component transfusion after cardiac 
surgery: The FIBRES randomized clinical trial. JAMA, 322(20), 1-11.
---------------------------------------------------------------------------

    The applicant calculated a final inflated case-weighted average 
standardized charge per case of $299,895 and an average case-weighted 
threshold of $183,897. Because the final inflated case-weighted average 
standardized charge per case exceeded the average case-weighted 
threshold amount, the applicant asserted that the technology meets the 
cost criterion.
    In the FY 2022 IPPS/LTCH PPS proposed rule (86 FR 25385), we agreed 
with the applicant that INTERCEPT Fibrinogen Complex meets the cost 
criterion and therefore proposed to approve INTERCEPT Fibrinogen

[[Page 45150]]

Complex for new technology add-on payments for FY 2022 when used for 
the control of massive bleeding associated with fibrinogen (Fg) 
deficiency. Based on preliminary information from the applicant at the 
time of the proposed rule, the cost of INTERCEPT Fibrinogen Complex is 
$750 per gram x 5.2 grams for the amount of $3,900 per patient. Under 
Sec.  412.88(a)(2), we limit new technology add-on payments to the 
lesser of 65 percent of the average cost of the technology, or 65 
percent of the costs in excess of the MS-DRG payment for the case. As a 
result, we proposed that the maximum new technology add-on payment for 
a case involving the use of INTERCEPT Fibrinogen Complex would be 
$2,535 per patient for FY 2022 (that is, 65 percent of the average cost 
of the technology).
    We invited public comments on whether INTERCEPT Fibrinogen Complex 
meets the cost criterion and our proposal to approve new technology 
add-on payments for INTERCEPT Fibrinogen Complex for FY 2022 when used 
for the control of massive bleeding associated with fibrinogen (Fg) 
deficiency.
    Comment: Several commenters, including the applicant, urged CMS to 
finalize our proposal to approve a new technology add-on payment for 
INTERCEPT Fibrinogen Complex. The applicant also requested that CMS 
include the commercial name for the technology, INTERCEPT Fibrinogen 
Complex, in the final rule so that providers understand that pathogen 
reduced cryoprecipitated fibrinogen complex (PRCFC) and INTERCEPT 
Fibrinogen Complex are the same product.
    Response: We thank the commenters for their support and feedback 
and note that we have included the commercial name for INTERCEPT 
Fibrinogen Complex in this final rule.
    Based on the information provided in the application for new 
technology add-on payments, and after consideration of the public 
comments we received, we believe INTERCEPT Fibrinogen Complex meets the 
cost criterion. Also, the applicant received FDA marketing 
authorization on November 24, 2020 for the following indications: (1) 
Treatment and control of bleeding, including massive hemorrhage, 
associated with fibrinogen deficiency; (2) control of bleeding when 
recombinant and/or specific virally inactivated preparations of factor 
XIII or von Willebrand factor (vWF) are not available; (3) second-line 
therapy for von Willebrand disease (vWD); and (4) control of uremic 
bleeding after other treatment modalities have failed. Therefore, we 
are finalizing our proposal to approve new technology add-on payments 
for INTERCEPT Fibrinogen Complex for FY 2022, and we consider the 
beginning of the newness period to commence on May 5, 2021, based on 
information provided by the applicant that the product first became 
available for sale on that date. We note that, under the eligibility 
criteria for approval under the alternative pathway for certain 
transformative new devices, only the use of INTERCEPT Fibrinogen 
Complex for the treatment of massive bleeding associated with 
fibrinogen (Fg) deficiency, and the FDA Breakthrough Device designation 
it received for that use, are relevant for purposes of the new 
technology add-on payment application for FY 2022. Since the 
Breakthrough Device designation is indicated for use in the treatment 
of massive bleeding associated with fibrinogen (Fg) deficiency, and not 
for the other uses under the FDA marketing authorization, only cases 
involving the use of INTERCEPT Fibrinogen Complex for the Breakthrough 
Device indication for use in the treatment of massive bleeding 
associated with fibrinogen (Fg) deficiency are eligible for new 
technology add-on payments.
    Based on the information at the time of this final rule, the cost 
per case of the INTERCEPT Fibrinogen Complex is $3,900. Under Sec.  
412.88(a)(2), we limit new technology add-on payments to the lesser of 
65 percent of the average cost of the technology, or 65 percent of the 
costs in excess of the MS DRG payment for the case. As a result, we are 
finalizing that the maximum new technology add-on payment for a case 
involving the use of INTERCEPT Fibrinogen Complex, is $2,535 for FY 
2022 (that is 65 percent of the average cost of the technology). Cases 
involving the use of the INTERCEPT Fibrinogen Complex that would be 
eligible for new technology add-on payments will be identified by ICD-
10-PCS codes: 30233D1 (Transfusion of nonautologous pathogen reduced 
cryoprecipitated fibrinogen complex into peripheral vein, percutaneous 
approach) or 30243D1 (Transfusion of nonautologous pathogen reduced 
cryoprecipitated fibrinogen complex into central vein, percutaneous 
approach), in combination with one of the following ICD-10-CM codes: 
D65 (Disseminated intravascular coagulation) or D68.2 (Hereditary 
deficiency of other clotting factors).
(11) RECELL[supreg] Autologous Cell Harvesting Device
    Avita Medical submitted an application for new technology-add on 
payments for RECELL[supreg] Autologous Cell Harvesting Device 
(RECELL[supreg]). The device is a standalone, single-use, battery-
powered device used to process an autologous skin cell suspension for 
the treatment of acute thermal burn wounds. Per the applicant, the 
purpose of the device is to assist with harvesting a small graft from 
the patient's healthy skin and immediate processing into an autologous 
skin cell suspension which is then immediately applied to the patient's 
burn wound following surgical preparation of the acute thermal burn 
wound. The applicant describes the device components as including a 
mechanical scraping tray, wells for incubating the donor graft with a 
proprietary enzyme solution, a rinsing well, a cell strainer, a spray 
applicator as well as buttons for ``self-test'', and ``run.''
    RECELL[supreg] was granted Expedited Access Pathway (EAP) by FDA 
(and is therefore considered part of the Breakthrough Devices Program 
by FDA \754\ on December 10, 2015 with the indication for use at the 
patient's point-of care for preparation of an autologous epithelial 
cell suspension to be applied to a prepared wound bed; under the 
supervision of a healthcare professional, the suspension is used to 
achieve epithelial regeneration for definitive closure of burn 
injuries, particularly in patients having limited availability of donor 
skin for autografting. RECELL[supreg] received FDA premarket approval 
(PMA) on September 20, 2018 with the indication for use listed as 
indicated for the treatment of acute thermal burn wounds in patients 18 
years of age and older. We stated in the proposed rule that since the 
narrower indication for which the technology received PMA is included 
within the scope of the EAP indication, it appears that the PMA 
indication is appropriate for new technology add-on payment under the 
alternative pathway criteria. Per the applicant, RECELL[supreg] was 
available for sale upon FDA approval, albeit on a very limited basis 
primarily to burn centers involved with the clinical trials. According 
to the applicant, new ICD-10-PCS codes that are specific to 
RECELL[supreg] were created effective October 1, 2019. Per the 
applicant, the first three characters of these codes are ``0HR,'' 
followed by a fourth character signifying which body part is impacted, 
then ``X72'' for the final three characters.
---------------------------------------------------------------------------

    \754\ https://www.fda.gov/regulatory-information/search-fida-guidance-documents/breakthrough-devices-program.
---------------------------------------------------------------------------

    With regard to the newness criterion, we stated that we believe 
that the beginning of the newness period for RECELL[supreg] commences 
from the date of

[[Page 45151]]

approval by the FDA on September 20, 2018, as the applicant indicated 
the technology was available for sale from that date. Because the 3-
year anniversary date of the entry of RECELL[supreg] onto the U.S. 
market (September 20, 2021) will occur in FY 2021, we stated that we do 
not believe that the device is eligible for new technology add on 
payments for FY 2022. Accordingly, we proposed to disapprove 
RECELL[supreg] Autologous Cell Harvesting Device for new technology add 
on payments for FY 2022. We invited public comments on our proposal to 
disapprove new technology add-on payments for the RECELL Autologous 
Cell Harvesting Device for FY 2022, including on whether the technology 
meets the newness criterion.
    Comment: The applicant submitted a comment in response to our 
concerns. The applicant asserted that the eligibility date for the 
newness criterion for RECELL[supreg] should be the date on which 
inpatient coding was available for the technology. Since the unique 
Cell Suspension Technique ICD-10 code qualifier describing 
RECELL[supreg] did not go into effect until October 1, 2019, the 
applicant asserts that should be the date considered for new technology 
add-on payment eligibility purposes and not the date of FDA approval on 
September 20, 2018. The applicant explains that the regulation at 42 
CFR 412.87(c) states that under the alternative pathway, the newness 
period begins after the point at which data begin to become available 
reflecting the inpatient hospital code (as defined in section 
1886(d)(5)(K)(iii) of the Social Security Act) assigned to the new 
technology (depending on when a new code is assigned and data on the 
new technology become available for DRG recalibration). The applicant 
emphasized that the regulatory section does not reference the FDA 
approval date, which it stated is appropriate because there is 
typically a lag between FDA approval and assignment of codes for the 
technology. Additionally, the applicant stated that our policy is that 
a medical service or technology may continue to be considered ``new'' 
for purposes of new technology add-on payments within 2 or 3 years 
after the point at which data begin to become available reflecting the 
inpatient hospital code assigned to the new service or technology (88 
FR 25211). Also, the applicant stated CMS proposed to extend new 
technology add-on payment status for numerous technologies that were 
cleared by FDA on dates earlier than the RECELL approval date. The 
applicant believes it would be inconsistent and arbitrary for CMS to 
deny new technology add-on payments for RECELL in FY 2022 on the basis 
of the FDA clearance date while extending new technology add-on payment 
status to technologies that are less ``new'' than RECELL[supreg]. 
Therefore the applicant believes RECELL[supreg] should qualify for new 
technology add-on payment in FY 2022.
    We also received several comments reiterating the applicant's 
comments. The commenters also added that they are requesting approval 
of new technology add-on payment for RECELL due to the clinically 
meaningful improvements in healing they observed in their patients, in 
order to make it financially viable to provide to patients.
    Response: We thank the applicant and the other commenters for their 
comments. However, we disagree that the newness date should begin with 
the date that the unique ICD-10-PCS code describing RECELL[supreg] was 
effective on October 1, 2019 and not with the date of FDA approval, 
September 20, 2018. We note that in the FY 2005 final rule (69 FR 
49002), we provided a detailed explanation for why using the date on 
which a specific code is assigned to a technology is not an appropriate 
test of newness. In that rule, we noted that, in many instances, a 
technology may have been in use for several years, or even several 
decades, prior to the assignment of a new code (69 FR 49003). Thus, we 
continue to believe it is appropriate to determine newness based on the 
date on which a product becomes available for use in the Medicare 
population and the date when hospitals can begin to use either an 
existing or new code to bill for the new service or technology. 
Consistent with the statute and our implementing regulations, a 
technology is no longer considered as ``new'' once it is more than 2 to 
3 years old, irrespective of how frequently the medical service or 
technology has been used in the Medicare population (70 FR 47349). As 
such, in this case, because RECELL has been available on the U.S. 
market for more than 2 to 3 years, we consider the costs to have been 
included in the MS-DRG relative weights. In addition, although we are 
finalizing our proposal to extend new technology add-on payments for 
technologies with a newness date prior to RECELL[supreg], this policy 
does not extend to technologies that were not approved for new 
technology add-on payments for FY 2021. We note that our process 
requires applicants to submit their application for new technology add-
on payments by the appropriate deadlines for the fiscal year in which 
they wish to be granted new technology status. We further note that the 
applicant received FDA approval on September 20, 2018 and could have 
submitted an application for new technology add on payments for earlier 
fiscal years under either the traditional or alternative pathways. The 
applicant did not apply for and was not approved for new technology add 
on payments for FY 2021. Our proposal was limited to an extension of 
new technology add-on payments for previously approved technologies and 
not to grant a new approval for add-on payments, and therefore 
RECELL[supreg] does not fit within the parameters of this proposal. We 
do not believe it would be appropriate to grant RECELL[supreg] a new 
technology add-on payment when it is not new for the fiscal year for 
which it is applying.
    Therefore, for the reasons stated in the proposed rule and in this 
final rule, because the RECELL[supreg] Autologous Cell Harvesting 
Device will not be within the newness period for FY 2022 and is 
therefore ineligible to receive new technology add-on payments, we are 
not approving new technology add-on payments for the RECELL[supreg] 
Autologous Cell Harvesting Device for FY 2022. As discussed previously, 
our past and present practice is to analyze the new technology add-on 
payment criteria in a sequential fashion, beginning with newness. We 
note that the applicant submitted a comment in regard to the cost 
criterion. However, as RECELL[supreg] does not meet the criterion for 
newness, we will not be making a determination in regard to cost or 
summarizing comments on the cost criterion in this final rule.
(12) Shockwave C2 Intravascular Lithotripsy (IVL) System
    Shockwave Medical Inc. submitted an application for new technology-
add on payments for Shockwave C2 Intravascular Lithotripsy (IVL) System 
for FY 2022. Per the applicant, the IVL Catheter is intended for 
lithotripsy-enabled, low-pressure dilation of calcified, stenotic de 
novo coronary arteries prior to stenting. The applicant explained that 
the device is delivered through the coronary arterial system, and it 
generates intermittent sonic waves within the target treatment site 
that disrupt calcium within the lesion, allowing subsequent dilation of 
a coronary artery stenosis using low balloon pressure. The applicant 
also noted that the procedure can be used for otherwise difficult to 
treat calcified stenosis, including calcified stenosis that are 
anticipated to exhibit resistance to full balloon dilation or 
subsequent uniform coronary stent expansion.

[[Page 45152]]

    Shockwave C2 Intravascular Lithotripsy (IVL) System was designated 
as a Breakthrough Device in August 2019, indicated for lithotripsy-
enabled, low-pressure dilation of calcified, stenotic de novo coronary 
arteries prior to stenting.
    The applicant received Pre-Market Approval as a Class III device 
from the FDA on February 12, 2021 for the same proposed indication. The 
applicant stated that though they expected market availability by April 
2021, the device became available immediately after FDA approval. The 
applicant submitted a request to the ICD-10 Coordination and 
Maintenance Committee for approval of a unique code for FY 2022 to 
identify the technology and was granted approval to identify the 
Shockwave C2 Intravascular Lithotripsy (IVL) System using the following 
procedure codes effective October 1, 2021:
[GRAPHIC] [TIFF OMITTED] TR13AU21.223

    With regard to the cost criterion, the applicant conducted two 
analyses based on 100 percent of identified claims and 81 percent of 
identified claims. To identify potential cases where Coronary IVL could 
be utilized, the applicant searched the FY 2019 MedPAR file for ICD-10-
PCS codes for the placement of a coronary stent, consistent with the 
anticipated FDA indication for Shockwave C2 Intravascular Lithotripsy 
(IVL). The applicant included all codes beginning with ``027'' and 
ending with ``6'' or Z'' in its search. The applicant highlighted the 
potential codes in between using the table that follows:
[GRAPHIC] [TIFF OMITTED] TR13AU21.224


[[Page 45153]]


    For the analysis using 100 percent of cases, the applicant 
identified 160,901 cases mapping to 209 MS-DRGs. Per the applicant, 
Shockwave C2 Intravascular Lithotripsy (IVL) does not replace any 
current devices used for indicated patients. However, to be 
conservative, the applicant removed 50 percent of charges associated 
with revenue center 0278--other implants. The applicant then 
standardized the charges and applied the 2-year outlier inflation 
factor of 13.2 percent used to update the outlier threshold in the FY 
2021 IPPS/LTCH PPS final rule (85 FR 59039), to update the charges from 
FY 2019 to FY 2021. The applicant added charges for the new technology 
by multiplying the cost of the technology by the estimated number of 
devices per patient and then dividing by the national CCR for 
implantable devices (0.293) from the FY 2021 IPPS/LTCH PPS final rule. 
Under the analysis based on 100 percent of identified claims, the 
applicant calculated a final inflated case-weighted average 
standardized charge per case of $143,805 and an average case-weighted 
threshold of $115,693.
    For the analysis using 81 percent of cases, the applicant 
identified 130,907 cases mapping to MS-DRGs 246 and 247. The applicant 
conducted the same analysis noted previously and determined a final 
inflated case-weighted average standardized charge per case of $122,020 
and an average case-weighted threshold of $104,783. Because the final 
inflated case-weighted average standardized charge per case exceeded 
the average case-weighted threshold amount under both analyses, the 
applicant asserted that the technology meets the cost criterion.
    In the FY 2022 IPPS/LTCH PPS proposed rule (86 FR 25389), we agreed 
with the applicant that Shockwave C2 Intravascular Lithotripsy (IVL) 
System meets the cost criterion and therefore proposed to approve 
Shockwave C2 Intravascular Lithotripsy (IVL) System for new technology 
add on payments for FY 2022, subject to the technology receiving FDA 
marketing authorization for lithotripsy-enabled, low-pressure dilation 
of calcified, stenotic de novo coronary arteries prior to stenting by 
July 1, 2021.
    Based on preliminary information from the applicant at the time of 
the proposed rule, the cost of the Shockwave C2 Intravascular 
Lithotripsy (IVL) System is $4,700 per device x 1.2 devices required 
per case for an amount of $5,640. Under Sec.  412.88(a)(2), we limit 
new technology add-on payments to the lesser of 65 percent of the 
average cost of the technology, or 65 percent of the costs in excess of 
the MS-DRG payment for the case. As a result, we proposed that the 
maximum new technology add-on payment for a case involving the use of 
the Shockwave C2 Intravascular Lithotripsy (IVL) System would be $3,666 
for FY 2022 (that is, 65 percent of the average cost of the 
technology).
    We invited public comments on whether the Shockwave C2 
Intravascular Lithotripsy (IVL) System meets the cost criterion and our 
proposal to approve new technology add-on payments for the Shockwave C2 
Intravascular Lithotripsy (IVL) System for FY 2022, subject to 
Shockwave C2 Intravascular Lithotripsy (IVL) System receiving FDA 
marketing authorization by July 1, 2021 for lithotripsy-enabled, low-
pressure dilation of calcified, stenotic de novo coronary arteries 
prior to stenting.
    Comment: The applicant submitted a public comment expressing 
support for the approval of the Shockwave C2 Intravascular Lithotripsy 
(IVL) System for the new technology add-on payment for FY 2022. The 
applicant further stated that the device became commercially available 
approximately two weeks after the date of FDA approval.
    Response: We thank the commenter for their support and for 
providing additional information. We note that we had previously 
received communication from the applicant stating that the device was 
commercially available immediately after FDA approval and therefore, 
absent additional information, it is unclear which is the date of 
commercial availability. However, we note that, using either date as 
the beginning of the newness period, the technology would be considered 
new for FY 2022.
    Based on the information provided in the application for new 
technology add-on payments, and after consideration of the public 
comments we received, we believe Shockwave C2 Intravascular Lithotripsy 
(IVL) System meets the cost criterion. Shockwave C2 Intravascular 
Lithotripsy (IVL) System received marketing authorization from the FDA 
on February 12, 2021 for the indications covered by its Breakthrough 
Device designation for lithotripsy-enabled, low-pressure dilation of 
calcified, stenotic de novo coronary arteries prior to stenting. 
Therefore, we are finalizing our proposal to approve new technology 
add-on payments for the Shockwave C2 Intravascular Lithotripsy (IVL) 
System for FY 2022, and we consider the beginning of the newness period 
to commence on February 12, 2021 which is the date on which the 
technology received FDA marketing authorization for the indication 
covered by its Breakthrough Device designation.
    Based on the information at the time of this final rule, the cost 
per case of the Shockwave C2 Intravascular Lithotripsy (IVL) System is 
$4,700 per device x 1.2 devices required per case for an amount of 
$5,640. Under Sec.  412.88(a)(2), we limit new technology add-on 
payments to the lesser of 65 percent of the average cost of the 
technology, or 65 percent of the costs in excess of the MS DRG payment 
for the case. As a result, we are finalizing that the maximum new 
technology add-on payment for a case involving the use of the Shockwave 
C2 Intravascular Lithotripsy (IVL) System is $3,666 for FY 2022 (that 
is 65 percent of the average cost of the technology). Cases involving 
the use of the Shockwave C2 Intravascular Lithotripsy (IVL) System that 
are eligible for new technology add-on payments will be identified by 
ICD-10- PCS codes:
[GRAPHIC] [TIFF OMITTED] TR13AU21.225


[[Page 45154]]


b. Alternative Pathways for Qualified Infectious Disease Products 
(QIDPs)
(1) CONTEPOTM (fosfomycin)
    Nabriva Therapeutics US, Inc. submitted an application for new 
technology-add on payments for CONTEPOTM (fosfomycin) for FY 
2022. CONTEPOTM is an intravenously administered epoxide 
antibiotic intended for the treatment of complicated urinary tract 
infections (cUTI) including acute pyelonephritis (AP) caused by 
designated susceptible bacteria. Per the applicant, the drug inhibits 
cell wall synthesis at an earlier stage and provides new treatment for 
patients with cUTIs including acute pyelonephritis caused by 
Escherichia coli and Klebsiella pneumonia that have failed to respond 
to other first-line therapies.
    CONTEPOTM is designated as a QIDP. The applicant 
initially applied for FDA approval when submitting a New Drug 
Application (NDA) in October 2018 seeking marketing approval of IV 
fosfomycin for injection (ZTI-01) for the treatment of patients 18 
years and older with cUTI including acute pyelonephritis caused by 
designated susceptible bacteria. According to the applicant, on June 
19, 2020, the FDA rejected the applicant's resubmitted NDA due to 
unresolved manufacturing issues that required an in-person inspection, 
which the FDA was not able to conduct due to travel restrictions. The 
applicant stated that it planned to resubmit an NDA after discussing 
next steps with the FDA and hoped to receive FDA approval prior to July 
1, 2021.
    The applicant previously applied for a new technology add-on 
payment for the same indication for FY 2021 and received conditional 
approval for new technology add-on payments for FY 2021, subject to 
CONTEPOTM receiving FDA marketing authorization before July 
1, 2021 (85 FR 58724). In the FY 2022 IPPS/LTCH PPS proposed rule (86 
FR 25391), we explained that if CONTEPO\TM\ receives FDA marketing 
authorization before July 1, 2021, the new technology add-on payment 
for cases involving the use of this technology would be made effective 
for discharges beginning in the first quarter after FDA marketing 
authorization is granted. We stated that if the FDA marketing 
authorization is received on or after July 1, 2021, no new technology 
add-on payments will be made for cases involving the use of CONTEPO\TM\ 
for FY 2021.
    We further stated that if CONTEPOTM receives FDA 
marketing authorization before July 1, 2021, the applicant has 
indicated that it would withdraw its application for FY 2022 and would 
instead seek new technology add-on payments for CONTEPOTM 
for FY 2022 as a continuation of the conditional approval for FY 2021. 
The applicant requested in its application for FY 2022 that if the 
technology does not receive FDA marketing authorization by July 1, 
2021, CMS conditionally approve CONTEPOTM for new technology 
add-on payments for FY 2022. We note that CONTEPOTM did not 
receive FDA marketing authorization by July 1, 2021.
    The applicant applied for and received a unique ICD-10-PCS 
procedure code to identify cases involving the administration of 
CONTEPOTM in 2019. Effective October 1, 2019, 
CONTEPOTM administration can be identified by ICD-10-PCS 
procedure codes XW033K5 (Introduction of fosfomycin anti-infective into 
peripheral vein, percutaneous approach, new technology group 5) and 
XW043K5 (Introduction of fosfomycin anti-infective into central vein, 
percutaneous approach, new technology group 5), which the applicant 
states are unique to CONTEPOTM administration.
    With regard to the cost criterion, the applicant used the FY 2019 
MedPAR Limited Data Set (LDS) to assess the MS-DRGs to which potential 
cases representing hospitalized patients who may be eligible for 
treatment involving CONTEPOTM would most likely be mapped. 
According to the applicant, CONTEPOTM is anticipated to be 
indicated for the treatment of hospitalized patients who have been 
diagnosed with complicated urinary tract infections (cUTIs). The 
applicant identified 199 ICD-10-CM diagnosis code combinations that 
identify hospitalized patients who have been diagnosed with a cUTI. 
Searching the FY 2019 MedPAR data file for these ICD-10-CM diagnosis 
codes resulted in a total of 525,876 potential cases that span 507 
unique MS-DRGs. The applicant noted that the cases identified are fewer 
than in the FY 2021 new technology add-on payment application. Per the 
applicant, this change occurred because the applicant excluded 
additional claims for Medicare Advantage and inpatient ``full-
encounter'' claims from all cohorts. The applicant maintained that 
while cohorts are smaller, the effects on the results were minimal.
    The applicant examined associated charges per MS-DRG and removed 
charges for potential antibiotics that may be replaced by the use of 
CONTEPOTM. Specifically, the applicant identified 5 
antibiotics currently used for the treatment of patients who have been 
diagnosed with a cUTI and calculated the cost of each of these drugs 
for administration over 14-day inpatient hospitalization. Because 
patients who have been diagnosed with a cUTI would typically only be 
treated with one of these antibiotics at a time, the applicant 
estimated an average of the 14-day cost for the 5 antibiotics. The 
applicant then converted the cost to charges by dividing the costs by 
the national average CCR of 0.187 for drugs from the FY 2021 IPPS/LTCH 
PPS final rule (85 FR 58601). The applicant then standardized the 
charges for each case and inflated each case's charges by applying the 
FY 2021 IPPS/LTCH PPS final rule outlier charge inflation factor of 
13.2 percent (85 FR 59039).
    The applicant then added the charges for the new technology by 
calculating the per-day cost per patient. The applicant noted that the 
duration of therapy of up to 14 days (patients that had a cUTI with 
concurrent bacteremia) is consistent with the prospective prescribing 
information, and that it used this 14-day duration of therapy to 
calculate total inpatient cost. The applicant then converted these 
costs to charges by dividing the costs per patient by the national 
average cost-to charge ratio of 0.187 for drugs from the FY 2021 IPPS/
LTCH PPS final rule (85 FR 58601). The applicant calculated a final 
inflated case-weighted average standardized charge per case of $79,619 
and a case weighted threshold of $59,237. Because the final inflated 
case-weighted average standardized charge per case for 
CONTEPOTM exceeded the average case-weighted threshold 
amount, the applicant maintained it meets the cost criterion.
    As summarized, the applicant used a 14-day duration of therapy to 
calculate total inpatient cost for purposes of its cost analysis. 
However, the applicant noted that the average number of days a patient 
would be administered CONTEPOTM will most likely fall 
between 10 to 14 days of therapy given the current guideline 
recommendations. Of these treatment days, the applicant noted that 
nearly all would occur during the inpatient hospital stay. Consistent 
with our historical practice, and as stated in the FY 2021 IPPS/LTCH 
PPS final rule, we believe the new technology add-on payment for 
CONTEPOTM, if approved, would be based on the average cost 
of the technology and not the maximum (85 FR 58724). Without further 
information from the applicant regarding the average number of days 
CONTEPOTM is administered, we continue to believe using the 
middle ground of 12.5 days,

[[Page 45155]]

based on the 10-14 day period indicated by the applicant, is 
appropriate for this analysis to determine the average number of days 
CONTEPOTM is administered in the hospital. To assess whether 
the technology would meet the cost criterion using an average cost for 
the technology based on this 12.5-day period for CONTEPOTM 
administration, we converted the costs to charges by dividing the costs 
per patient by the national average cost-to charge ratio of 0.187 for 
drugs from the FY 2021 IPPS/LTCH PPS final rule (85 FR 58601). Based on 
data from the applicant, this resulted in a final inflated average 
case-weighted standardized charge per case of $77,613, which exceeds 
the case weighted threshold of $59,237.
    Because of the large number of cases included in this cost 
analysis, the applicant supplemented the analysis as described 
previously with additional sensitivity analyses. In these analyses, the 
previous cost analysis was repeated using only the top 75 percent of 
cases and the top 20 MS-DRGs. In these two additional sensitivity 
analyses, the final inflated case-weighted average standardized charge 
per case for CONTEPOTM of $70,718 and $70,046 exceeded the 
average case-weighted threshold amount of $55,388 and $55,468, 
respectively. Because the final inflated case-weighted average 
standardized charge per case for CONTEPOTM exceeded the 
average case-weighted threshold amount, the applicant asserts that 
CONTEPOTM meets the cost criterion.
    In the FY 2022 IPPS/LTCH PPS proposed rule (86 FR 25391), we agreed 
with the applicant that CONTEPOTM (fosfomycin) meets the 
cost criterion. We stated that therefore, if CONTEPOTM does 
not receive FDA approval by July 1, 2021 to receive new technology add-
on payments beginning with FY 2021, for FY 2022, per the policy 
finalized in the FY 2021 IPPS/LTCH PPS final rule (85 FR 58739 through 
58742), we proposed to conditionally approve CONTEPOTM for 
new technology add-on payments, subject to the technology receiving FDA 
marketing authorization by July 1, 2022 (that is, by July 1 of the 
fiscal year for which the applicant applied for new technology add-on 
payments (2022)). If CONTEPOTM receives FDA marketing 
authorization before July 1, 2022, the new technology add-on payment 
for cases involving the use of this technology would be made effective 
for discharges beginning in the first quarter after FDA marketing 
authorization is granted. If the FDA marketing authorization is 
received on or after July 1, 2022, no new technology add-on payments 
would be made for cases involving the use of CONTEPOTM for 
FY 2022. As previously noted, the applicant has received a unique ICD-
10-PCS procedure code to identify cases involving the administration of 
CONTEPOTM. We stated that if CONTEPOTM receives 
FDA marketing authorization prior to July 1, 2021, we were proposing to 
continue making new technology add-on payments for CONTEPOTM 
in FY 2022.
    As discussed previously, without further information from the 
applicant regarding the average number of days CONTEPOTM is 
administered, and consistent with our approach for the FY 2021 IPPS/
LTCH PPS final rule, we believe using a 12.5-day duration of therapy is 
a reasonable approach for estimating the average cost of the 
technology. Based on preliminary information from the applicant at the 
time of the proposed rule, the cost of CONTEPOTM 
administered over 12.5 days is $3,500. We noted that the cost 
information for this technology may be updated in the final rule based 
on revised or additional information CMS receives prior to the final 
rule. Under Sec.  412.88(a)(2), we limit new technology add-on payments 
for QIDPs to the lesser of 75 percent of the average cost of the 
technology, or 75 percent of the costs in excess of the MS-DRG payment 
for the case. As a result, we proposed that if CONTEPOTM 
receives FDA marketing authorization prior to July 1, 2022, the maximum 
new technology add-on payment for a case involving the use of 
CONTEPOTM (fosfomycin) would be $2,625 for FY 2022 (that is, 
75 percent of the average cost of the technology). Cases involving the 
use of CONTEPOTM that would be eligible for new technology 
add-on payments will be identified by ICD-10-PCS procedure codes 
XW033K5 (Introduction of fosfomycin anti-infective into peripheral 
vein, percutaneous approach, new technology group 5) or XW043K5 
(Introduction of fosfomycin anti-infective into central vein, 
percutaneous approach, new technology group 5).
    We invited public comments on whether CONTEPOTM 
(fosfomycin) meets the cost criterion and our proposal to approve new 
technology add-on payments for CONTEPOTM (fosfomycin) for FY 
2022.
    Comment: A commenter, the applicant, supported CMS' proposal to 
approve new technology add-on payments for FY 2022 for 
CONTEPOTM. The applicant also voiced support for CMS' 
proposal to grant conditional approval for new technology add-on 
payments for CONTEPOTM for FY 2022 in the event that it did 
not receive marketing approval by July 1, 2021, subject to 
CONTEPOTM receiving marketing approval by July 1, 2022. Per 
the applicant, in light of delays with FDA onsite inspections due to 
ongoing FDA travel restrictions, CONTEPOTM did not receive 
FDA approval by the July 1, 2021 deadline, and it will keep CMS 
informed with regard to the status of its NDA once a new PDUFA date is 
confirmed.
    Response: We thank the applicant for their comment and update.
    Based on the information provided in the application for new 
technology add-on payments, and after consideration of the public 
comment we received, we believe CONTEPOTM meets the cost 
criterion. Therefore, because CONTEPOTM otherwise meets the 
new technology add-on payment criteria under the alternative pathway 
for products designated as QIDPs, we are granting a conditional 
approval for CONTEPOTM for new technology add-on payments, 
subject to the technology receiving FDA marketing authorization by July 
1, 2022 (that is, by July 1 of the fiscal year for which the applicant 
applied for new technology add-on payments (2022)). If 
CONTEPOTM receives FDA marketing authorization before July 
1, 2022, the new technology add-on payment for cases involving the use 
of this technology would be made effective for discharges beginning in 
the first quarter after FDA marketing authorization is granted. If the 
FDA marketing authorization is received on or after July 1, 2022, no 
new technology add-on payments will be made for cases involving the use 
of CONTEPOTM for FY 2022.
    Based on the information at the time of this final rule, the cost 
per case of CONTEPOTM is $3,500. Under Sec.  412.88(a)(2), 
we limit new technology add-on payments for QIDPs to the lesser of 75 
percent of the average cost of the technology, or 75 percent of the 
costs in excess of the MS DRG payment for the case. As a result, we are 
finalizing that, subject to CONTEPO receiving marketing authorization 
by July 1, 2022, the maximum new technology add-on payment for a case 
involving the use of CONTEPOTM will be for $2,625 for FY 
2022 (that is 75 percent of the average cost of the technology). Cases 
involving the use of CONTEPOTM that would be eligible for 
new technology add-on payments will be identified by ICD-10- PCS codes: 
XW033K5 (Introduction of fosfomycin anti-infective into peripheral 
vein, percutaneous approach, new technology group 5) or XW043K5 
(Introduction of fosfomycin anti-infective into central vein, 
percutaneous approach, new technology group 5).

[[Page 45156]]

(2) FETROJA[supreg] (cefiderocol)
    Shionogi & Co., Ltd submitted an application for new technology-add 
on payments for FETROJA[supreg] (cefiderocol) for FY 2022. 
FETROJA[supreg] is an injectable siderophore cephalosporin indicated 
for the treatment of hospital-acquired bacterial pneumonia (HABP)/
ventilator-associated bacterial pneumonia (VABP) on September 25, 2020. 
Per the applicant, FETROJA[supreg] should be used to treat infections 
where limited or no alternative treatment options are available and 
where FETROJA[supreg] (cefiderocol) is likely to be an appropriate 
treatment option, which may include use in patients with infections 
caused by documented or highly suspected carbapenem-resistant and/or 
multidrug-resistant gram-negative (GN) pathogens. The applicant asserts 
that the principal antibacterial/bactericidal activity of 
FETROJA[supreg] occurs with inhibiting GN bacterial cell wall synthesis 
by binding to penicillin-binding proteins.
    FETROJA[supreg] was designated as a QIDP for HABP/VABP and received 
FDA marketing approval for this indication on September 25, 2020. 
FETROJA[supreg] became available on the market for the treatment of 
HABP/VABP after FDA approval for this indication. FETROJA[supreg] also 
has a QIDP designation and is FDA approved for cUTI, and was granted a 
new technology add-on payment under the alternative new technology add-
on payment pathway for certain antimicrobials for this indication in 
the FY 2021 IPPS/LTCH final rule (85 FR 58721). The current new 
technology add-on payment application for FY 2022 is specific to the 
indication of HABP/VABP. According to the applicant, the ICD-10 
Coordination and Maintenance Committee approved the following ICD-10-
PCS codes to specifically describe the IV administration of FETROJA, 
effective October 1, 2020: XW033A6 (Introduction of cefiderocol anti-
infective into peripheral vein, percutaneous approach, new technology 
group 6) and XW043A6 (Introduction of cefiderocol anti-infective into 
central vein, percutaneous approach, new technology group 6).
    With regard to the cost criterion, the applicant conducted two 
analyses based on 100 percent and 75 percent of identified claims. For 
both scenarios, the applicant used the FY 2019 MedPAR Limited Data Set 
(LDS) to assess the MS-DRGs to which potential cases representing 
hospitalized patients who may be eligible for FETROJA[supreg] treatment 
would be mapped. The applicant identified eligible cases by searching 
the FY 2019 MedPAR for cases reporting ICD-10-CM codes for pneumonia 
and for resistance to antimicrobial drugs.
    Under the first scenario of 100 percent of cases, the applicant 
identified 9,595 cases mapping to 203 MS-DRGs. Under the second 
scenario of 75 percent of cases, the applicant identified 7,218 cases 
mapping to 19 MS-DRGs. The applicant standardized the charges after 
calculating the average case-weighted unstandardized charge per case 
for both scenarios and removing 50 percent of charges associated with 
the drug revenue centers 025x, 026x, and 063x under both scenarios. Per 
the applicant, FETROJA[supreg] is expected to replace some of the drugs 
that would otherwise be utilized to treat these patients. The applicant 
stated that it believes 50 percent of these total charges to be a 
conservative estimate as other drugs will still be required for these 
patients during their hospital stay. The applicant then applied an 
inflation factor of 13.2 percent, which was the 2-year outlier charge 
inflation factor used in the FY 2021 IPPS/LTCH PPS final rule (85 FR 
59039), to update the charges from FY 2019 to FY 2021. The applicant 
then added charges for FETROJA[supreg] by dividing the total average 
hospital cost of FETROJA[supreg] by the national average cost-to-charge 
ratio (0.187) for drugs published in the FY 2021 IPPS/LTCH PPS final 
rule (85 FR 58601).
    The applicant calculated a final inflated case-weighted average 
standardized charge per case of $164,825 for the first scenario and 
$148,821 for the second scenario and an average case-weighted threshold 
amount of $78,296 for the first scenario and $73,607 for the second 
scenario. Because the final inflated case-weighted average standardized 
charge per case for each scenario exceeds the average case-weighted 
threshold amount for each scenario, the applicant asserted that the 
technology meets the cost criterion.
    In the FY 2022 IPPS/LTCH PPS proposed rule (86 FR 25392), we agreed 
with the applicant that FETROJA[supreg] (cefiderocol) meets the cost 
criterion and therefore proposed to approve FETROJA[supreg] for new 
technology add-on payments for FY 2022 when used for the treatment of 
HABP/VABP. Cases involving the use of FETROJA[supreg] that are eligible 
for new technology add-on payments will be identified by ICD-10-PCS 
procedure codes XW033A6 or XW043A6.
    Based on preliminary information from the applicant at the time of 
the proposed rule, the cost of FETROJA[supreg] administered over an 
average of 10.4 days is $11,439.79. We noted that the cost information 
for this technology may be updated in the final rule based on revised 
or additional information CMS receives prior to the final rule. Under 
Sec.  412.88(a)(2), we limit new technology add-on payments for QIDPs 
to the lesser of 75 percent of the average cost of the technology, or 
75 percent of the costs in excess of the MS-DRG payment for the case. 
As a result, we proposed that the maximum new technology add-on payment 
for a case involving the use of FETROJA[supreg] when used for the 
treatment of HABP/VABP would be $8,579.84 for FY 2022 (that is, 75 
percent of the average cost of the technology).
    We invited public comments on whether FETROJA[supreg] (cefiderocol) 
meets the cost criterion and our proposal to approve new technology 
add-on payments for FETROJA[supreg] for FY 2022 for the treatment of 
HABP/VABP.
    Comment: A commenter, the applicant, supported CMS' proposal to 
approve new technology add-on payments for FY 2022 for FETROJA[supreg]. 
The applicant also noted two incorrect codes in the list of ICD-10-PCS 
codes for the administration of FETROJA in the proposed rule (86 FR 
25392) and requested that we correct the list to include XW033A6 and 
XW043A6.
    Response: We thank the applicant for its comment. We appreciate the 
clarification and note that in this final rule, as noted below, cases 
involving the use of FETROJA[supreg] eligible for new technology add-on 
payments will be identified by the ICD-10-PCS codes listed by the 
commenter.
    Based on the information provided in the application for new 
technology add-on payments, and after consideration of the public 
comments we received, we believe FETROJA[supreg] meets the cost 
criterion. Also, FETROJA[supreg] was designated as a QIDP for HABP/VABP 
and received FDA marketing approval for this indication on September 
25, 2020. Therefore, we are finalizing our proposal to approve new 
technology add-on payments for FETROJA[supreg] for FY 2022. We consider 
the beginning of the newness period to commence on September 25, 2020 
which is when the technology received FDA marketing authorization for 
this indication. Based on the information at the time of this final 
rule, the cost per case of FETROJA[supreg] is $11,439.79. Under Sec.  
412.88(a)(2), we limit new technology add-on payments to the lesser of 
75 percent of the average cost of the technology, or 75 percent of the 
costs in excess of the MS DRG payment for the case. As a result, we are 
finalizing that the maximum new technology add-on payment for a case 
involving the use of FETROJA[supreg] for the HABP/VABP indication is 
$8,579.84 for FY 2022 (that

[[Page 45157]]

is 75 percent of the average cost of the technology). Cases involving 
the use of FETROJA[supreg] eligible for new technology add-on payments 
will be identified by ICD-10- PCS codes: XW033A6 (Introduction of 
cefiderocol anti-infective into peripheral vein, percutaneous approach, 
new technology group 6) or XW043A6 (Introduction of cefiderocol anti-
infective into central vein, percutaneous approach, new technology 
group 6).
(3) RECARBRIOTM (imipenem, cilastatin, and relebactam)
    Merck & Co. submitted an application for new technology add-on 
payments for RECARBRIOTM for FY 2022. RECARBRIOTM 
is a fixed-dose combination of imipenem, a penem antibacterial; 
cilastatin, a renal dehydropeptidase inhibitor; and relebactam, a novel 
b-lactamase inhibitor (BLI) administered via intravenous infusion. Per 
the applicant, RECARBRIOTM is indicated for the treatment of 
hospital-acquired bacterial pneumonia (HABP) and ventilator-associated 
bacterial pneumonia (VABP) caused by susceptible Gram-negative 
bacteria. RECARBRIOTM is also indicated for complicated 
urinary tract infections (cUTI) and complicated intra-abdominal 
infections (cIAI) and was approved for new technology add-on payment 
for these indications in the FY 2021 IPPS/LTCH PPS final rule (85 FR 
58728).
    The applicant explained that the recommended dose of 
RECARBRIOTM is 1.25 grams administered by intravenous 
infusion over 30 minutes every 6 hours in patients 18 years of age and 
older with creatinine clearance (CrCl) 90 mL/min or greater. Per the 
applicant, the recommended treatment course suggests that a patient 
will receive 1 vial per dose and 4 doses per day. Per 
RECARBRIOTM's prescribing information, the recommended 
duration of treatment is 4 days to 14 days.
    RECARBRIOTM is designated as a QIDP indicated for the 
treatment of HABP/VABP and received FDA approval through a supplemental 
NDA on June 4, 2020 for this indication. According to the applicant, 
RECARBRIOTM originally submitted an NDA for the cUTI and 
cIAI indications and received FDA approval on July 16, 2019. The 
applicant previously applied for the new technology add-on payment for 
the cUTI and cIAI indications, which CMS approved in the FY 2021 IPPS/
LTCH PPS final rule (85 FR 58728). The application for new technology 
add-on payments for FY 2022 is specific to the HABP and VABP 
indications. The applicant noted that RECARBRIOTM can be 
identified with ICD-10-PCS codes XW033U5 (Introduction of imipenem-
cilastatin-relebactam anti-infective into peripheral vein, percutaneous 
approach, new technology group 5) or XW043U5 (Introduction of imipenem-
cilastatin-relebactam anti-infective into central vein, percutaneous 
approach, new technology group 5).
    To demonstrate that the technology meets the cost criterion, the 
applicant searched the FY 2019 MedPAR Limited Data Set (LDS) for cases 
reporting ICD-10-CM diagnosis code J95.851 (Ventilator assisted 
pneumonia) for VABP, and the following list of codes for HABP:
[GRAPHIC] [TIFF OMITTED] TR13AU21.226

    Additionally, for HABP, the applicant identified cases that 
included present on admission indicators of N (Diagnosis was not 
present at time of inpatient admission), U (Documentation insufficient 
to determine if condition was present at the time of inpatient 
admission), W (Clinically undetermined), or 1 (Unreported/not used).
    The applicant identified a total 106,964 cases, which were mapped 
to 355 unique MS-DRGs. The applicant removed 88 MS-DRGs with minimal 
frequencies (fewer than 11 cases), leaving 106,655 cases mapping to 267 
MS-DRGs. Per the applicant, the top 10 MS-DRGs covered approximately 
34.1 percent of all patients. The applicant examined associated charges 
per MS-DRG and removed all pharmacy charges to be replaced using 
RECARBRIOTM. The applicant then standardized and inflated 
the charges by applying the FY 2021 IPPS/LTCH PPS final rule outlier 
charge inflation factor of 1.13218 (85 FR 59039).
    The applicant estimated an average cost of RECARBRIOTM 
for the treatment of HABP and VABP in the inpatient setting based on 
the recommended dose of 1.25 grams (imipenem 500 mg, cilastatin 500 mg, 
relebactam 250 mg) administered by intravenous infusion over 30 minutes 
every 6 hours in patients 18 years of age and older with creatinine 
clearance (CLcr) 90 mL/min or greater. As stated previously, according 
to the applicant, the recommended treatment course suggests that a 
patient will receive 1 vial per dose, 4 doses per day within a 
recommended treatment duration of 4 to 14 days. To determine the cost 
per patient, the applicant stated it used the FY 2019 MedPAR analysis 
of total cases representing hospitalized patients who may be eligible 
for treatment involving RECARBRIOTM to identify a percentage 
of total cases per indication: HABP 94.07 percent of cases and VABP 
5.93

[[Page 45158]]

percent. According to the applicant, it next identified the average 
length of stay per indication: HABP 14.2 days and VABP 24.2 days. The 
applicant also assumed that 70 percent of patients would receive 
RECARBRIOTM beginning on the fourth day after admission 
while the remaining 30 percent of these patients would receive 
RECARBRIOTM beginning on the second day of their 
hospitalization. The applicant then multiplied the daily dose cost by 
the two scenarios for each HABP and VABP indication to determine the 
cost per stay for each indication by days of drug use. Next it 
multiplied the cost per stay for each indication by the share of cases 
by days in use (70/30 percent split) to determine the weighted cost for 
days in use estimation. The applicant then summed the 70/30 percent 
case breakdown (weighted cost) for patients initiating on day 2 and 4 
to determine the average cost per indication for HABP and VABP. 
Finally, the applicant multiplied the average cost per indication by 
the percent of total cases for HABP and VABP, then summed them to get 
the overall average cost. The applicant converted this cost to a charge 
by dividing the costs by the national average cost-to-charge ratio of 
0.187 for drugs published in the FY 2021 IPPS/LTCH PPS final rule (85 
FR 58601) and added the resulting charges to determine the final 
inflated case-weighted average standardized charge per case.
    The applicant calculated a final inflated case-weighted average 
standardized charge per case of $258,946 and an average case-weighted 
threshold amount of $123,172. The applicant also calculated an average 
case-weighted standardized charge per case for HABP and VABP separately 
using the same methodology previously described and determined final 
inflated case-weighted average standardized charges per case of 
$249,992 for HABP and $394,992 for VABP and average case-weighted 
thresholds of $117,466 for HABP and $214,869 for VABP.
    In addition, because RECARBRIOTM was previously approved 
for a new technology add-on payment for the cUTI and cIAI indications, 
the applicant modified the added amount of the charge for 
RECARBRIOTM based on the cost calculation of the technology 
using all four indications. Using the same methodology previously 
described, the applicant determined final inflated case-weighted 
average standardized charges per case of $250,209 for HABP and VABP, 
$241,255 for HABP, and $386,255 for VABP and average case-weighted 
thresholds of $123,172 for HABP and VABP, $117,466 for HABP, and 
$214,869 for VABP. Because the final inflated case-weighted average 
standardized charge per case exceeded the average case-weighted 
threshold amount in each scenario, the applicant maintained that the 
technology met the cost criterion.
    In the FY 2022 IPPS/LTCH PPS proposed rule (86 FR 25394), we agreed 
with the applicant that RECARBRIOTM meets the cost criterion 
and therefore proposed to approve RECARBRIOTM for new 
technology add-on payments for FY 2022 when used for treatment of HABP 
and VABP. Based on preliminary information from the applicant at the 
time of the proposed rule, the cost of RECARBRIOTM is 
$12,768.68 when used for the treatment of HABP and VABP. We noted that 
the cost information for this technology may be updated in the final 
rule based on revised or additional information CMS receives prior to 
the final rule. Under Sec.  412.88(a)(2), we limit new technology add-
on payments for QIDPs to the lesser of 75 percent of the costs of the 
new medical service or technology, or 75 percent of the amount by which 
the costs of the case exceed the MS-DRG payment. As a result, we 
proposed that the maximum new technology add-on payment for a case 
involving the use of RECARBRIOTM would be $9,576.51 for FY 
2022 (that is, 75 percent of the average cost of the technology) when 
used for treatment of HABP and VABP.
    We invited public comments on whether RECARBRIOTM 
(imipenem, cilastatin, and relebactam) meets the cost criterion and our 
proposal to approve new technology add-on payments for the 
RECARBRIOTM (imipenem, cilastatin, and relebactam) for the 
indications of HABP and VABP for FY 2022.
    We did not receive any comments on our proposal to approve 
RECARBRIOTM for new technology add-on payments for FY 2022.
    Based on the information provided in the application for new 
technology add-on payments, we believe RECARBRIOTM meets the 
cost criterion. Also, RECARBRIOTM is designated as a QIDP 
indicated for the treatment of HABP/VABP and received FDA approval 
through a supplemental NDA on June 4, 2020 for this indication. 
Therefore, we are finalizing our proposal to approve new technology 
add-on payments for RECARBRIOTM for FY 2022, and we consider 
the beginning of the newness period to commence on June 4, 2020 for the 
treatment of HABP/VABP, which is when the technology received FDA 
marketing authorization for this indication. Based on the information 
at the time of this final rule, the cost per case of 
RECARBRIOTM is $12,769. Under Sec.  412.88(a)(2), we limit 
new technology add-on payments for QIDPs to the lesser of 75 percent of 
the average cost of the technology, or 75 percent of the costs in 
excess of the MS DRG payment for the case. As a result, we are 
finalizing that the maximum new technology add-on payment for a case 
involving the use of the RECARBRIOTM for the treatment of 
HABP/VABP is $9,577 for FY 2022 (that is 75 percent of the average cost 
of the technology). Cases involving the use of RECARBRIOTM 
that are eligible for new technology add-on payments will be identified 
by ICD-10-PCS codes: XW033U5 (Introduction of imipenem-cilastatin-
relebactam anti-infective into peripheral vein, percutaneous approach, 
new technology group 5) or XW043U5 (Introduction of imipenem-
cilastatin-relebactam anti-infective into central vein, percutaneous 
approach, new technology group 5).
c. Other Comments
    Comment: We received multiple comments regarding payment for QIDPs 
and new technology add-on payment policies, including that Medicare 
should pay QIDP antibiotics separately from DRGs, make payment for QIDP 
products at 100%, and reduce the new technology add-on payment approval 
timeframes to shorten application cycles to streamline access to 
coverage, coding, and payment for new technologies. Also, several 
commenters recommended CMS initiate accelerated antibacterial and 
antifungal guideline updates to facilitate clinician education and 
correspond with the new technology add-on payment pathway for 
antimicrobials. Another commenter recommended that CMS extend the new 
technology add- on payment pathway to microbiome therapeutics that also 
treat urgent antimicrobial threats, such as Clostridioides difficile 
infection (CDI). Similarly, several commenters recommended that CMS 
establish an additional new technology add-on payment pathway for 
Breakthrough and Regenerative Medicine Advanced Therapies (RMAT) 
designated products to enhance payment for these products that have 
received FDA marketing authorization and for Breakthrough gene therapy 
products, similar to the pathway developed for QIDPs. Furthermore, the 
commenters recommended the add-on payment amount for products that 
qualify for new technology add-on payment pathways should be similar to 
products qualifying for the QIDP and LPAD pathway which pursuant to 
Sec.  412.88(a)(2)(ii)(B) is the lesser of: (1)

[[Page 45159]]

Seventy-five percent of the costs of the new medical service or 
technology; or (2) seventy-five percent of the amount by which the 
costs of the case exceed the standard DRG payment.
    Response: We appreciate the commenters' recommendations for 
potential changes to the new technology add-on payment program and 
recognize the importance of addressing these critical issues. We will 
take these comments into consideration for future rulemaking.
    Comment: A commenter stated that CMS should not extend the 20% 
adjustment codified in section 3710 of the CARES Act for discharges 
involving a patient diagnosed with COVID-19 beyond the duration of the 
PHE. A commenter recommended that CMS use its exceptions and 
adjustments authority under 42 U.S.C. 1886(d)(5)(I) to adopt a parallel 
policy that continues the 20 percent increase in the MS-DRG weight for 
discharges of patients diagnosed with COVID-19 through the end of the 
fiscal year in which the COVID-19 emergency period ends.
    Response: Per the statute in section 3710 of the CARES Act, the 20% 
payment adjustment is scheduled to end at the end the PHE. Unless 
Congress extends the end date of the 20% payment adjustment beyond the 
end of the PHE, we expect to discontinue these payments at the time 
specified by the statute.
7. Comment Solicitation on the New Technology Add-On Payment Newness 
Period for Products Available Through an Emergency Use Authorization 
(EUA) for COVID-19
    As noted previously, and explained in the FY 2005 IPPS final rule 
(69 FR 49002), the intent of section 1886(d)(5)(K) of the Act and 
regulations under Sec.  412.87(b)(2) is to pay for new medical services 
and technologies for the first 2 to 3 years that a product comes on the 
market, during the period when the costs of the new technology are not 
yet fully reflected in the DRG weights.
    As we have discussed in prior rulemaking (77 FR 53348), generally, 
our policy is to begin the newness period on the date of FDA approval 
or clearance or, if later, the date of availability of the product on 
the U.S. market, when data reflecting the costs of the technology begin 
to become available for recalibration of the DRGs. In some specific 
circumstances, we have recognized a date later than FDA approval as the 
appropriate starting point for the 2-year to 3-year newness period for 
new technologies approved for add-on payments (85 FR 58734).
    As discussed previously, in the FY 2009 IPPS final rule (73 FR 
48561 through 48563), we revised our regulations at Sec.  412.87 to 
codify our longstanding practice of how CMS evaluates the eligibility 
criteria for new medical service or technology add-on payment 
applications. We stated that new technologies that have not received 
FDA approval do not meet the newness criterion. In addition, we stated 
we do not believe it is appropriate for CMS to determine whether a 
medical service or technology represents a substantial clinical 
improvement over existing technologies before the FDA makes a 
determination as to whether the medical service or technology is safe 
and effective. For these reasons, we first determine whether a new 
technology meets the newness criterion, and only if so, do we make a 
determination as to whether the technology meets the cost threshold and 
represents a substantial clinical improvement over existing medical 
services or technologies. We also finalized at 42 CFR 412.87(c) 
(subsequently redesignated as 412.87(e)) that all applicants for new 
technology add-on payments must have FDA approval or clearance by July 
1 of the year prior to the beginning of the fiscal year for which the 
application is being considered.
    In the FY 2021 IPPS/LTCH PPS final rule, to more precisely describe 
the various types of FDA approvals, clearances, licensures, and 
classifications that we consider under our new technology add-on 
payment policy, we finalized a technical clarification to Sec.  
412.87(e)(2) to indicate that new technologies must receive FDA 
marketing authorization (for example, pre-market approval (PMA); 510(k) 
clearance; the granting of a De Novo classification request; approval 
of a New Drug Application (NDA); or Biologics License Application (BLA) 
licensure) by July 1 of the year prior to the beginning of the fiscal 
year for which the application is being considered. As noted in the FY 
2021 IPPS/LTCH PPS final rule, this technical clarification did not 
change our longstanding policy for evaluating whether a technology is 
eligible for new technology add-on payment for a given fiscal year, and 
we continue to consider FDA marketing authorization as representing 
that a product has received FDA approval or clearance for purposes of 
eligibility for the new technology add-on payment under Sec.  
412.87(e)(2) (85 FR 58742).
    An EUA by the FDA allows a product to be used for emergency use, 
but under our longstanding policy, we believe it would not be 
considered an FDA marketing authorization for the purpose of new 
technology add-on payments, as a product that is available only through 
an EUA is not considered to have an FDA approval or clearance. 
Therefore, under the current regulations at 42 CFR 412.87(e)(2) and 
consistent with our longstanding policy of not considering eligibility 
for new technology add-on payments prior to a product receiving FDA 
approval or clearance, we believe a product available only through an 
EUA would not be eligible for new technology add-on payments.
    Although an EUA is not an FDA approval or clearance that would be 
considered FDA marketing authorization within the meaning of Sec.  
412.87(e)(2), data reflecting the costs of products that have received 
an EUA could become available as soon as the date of the EUA issuance 
and prior to receiving FDA approval or clearance. CMS also recognizes 
that the manufacturers of products with EUAs (such as some COVID-19 
treatments) might further engage with FDA to seek approval or 
clearance, and may be eligible for new technology add-on payments in 
the future. We sought comment on how data reflecting the costs of a 
product with an EUA, which may become available upon authorization of 
the product for emergency use (but prior to FDA approval or clearance), 
should be considered for purposes of the 2-year to 3-year period of 
newness for new technology add-on payments for a product with or 
expected to receive an EUA, including whether the newness period should 
begin with the date of the EUA.
    Comment: We received multiple comments in response to our request 
for comment. Commenters recommended that CMS use the date of FDA 
approval, and not the date of the EUA, as the beginning of the 2-year 
to 3-year newness period. The commenters stated that a full FDA review 
process is in the interest of patient safety and clinical efficacy 
rather than expanding eligibility to include products under the 
expedited EUA process; and that data collected during the EUA period 
may reflect high variability in estimates of costs due to challenges 
associated with variable treatment practices in the context of the 
global pandemic and a novel disease. The commenters further stated that 
the data collected may not reflect government price subsidies provided 
for products during the EUA period. These factors may distort estimates 
of the cost of treatment and not appropriately reflect the total cost 
of care for patients who receive treatment using new COVID-19 
therapeutics. A commenter also stated that while data

[[Page 45160]]

reflecting the costs of EUA products may become available from the date 
of the EUA, CMS should not base the newness period on data gathered 
during the EUA period, but rather, should monitor how pricing may have 
changed once the product receives full marketing authorization. Some 
commenters recommended that CMS allow EUAs as an appropriate form of 
FDA authorization as required under the new technology add-on payment 
process. A commenter stated that CMS' belief that an EUA should not be 
considered an FDA marketing authorization for the purpose of new 
technology add-on payments as a product that is available only through 
an EUA is not considered to have FDA approval or clearance, is highly 
problematic since an EUA is an authorization to allow products on the 
US market within the limitations established under the letter of 
authorization which contemplates marketing actions including 
advertising and promotional activities. The commenter further stated 
that it is clear from the text of the proposed rule that market 
authorization, not approval, is the criterion for add-on payment 
eligibility and that an EUA is a formal FDA authorization to market.
    Response: We thank the commenters for their feedback and we will 
consider these comments for future rulemaking where applicable. With 
regard to the commenter who asserted that CMS should allow EUAs as an 
appropriate form of FDA authorization for new technology add-on 
payments as an EUA is a formal authorization to market, we note that 
there are distinct eligibility criteria for new technology add-on 
payments. As noted previously, historically, CMS has stated that for 
the purposes of new technology add-on payments, new technologies that 
have not received FDA approval do not meet the newness criterion. As 
noted in section F.1.a.3 of this final rule, in addition to the newness 
criterion, a technology must meet the substantial improvement criterion 
to qualify for new technology add-on payment. We have previously stated 
(73 FR 48561 through 48563) that we do not believe it is appropriate 
for CMS to determine whether a medical service or technology represents 
a substantial clinical improvement over existing technologies before 
the FDA makes a determination as to whether the medical service or 
technology is safe and effective. For these reasons, we first determine 
whether a new technology meets the newness criterion, and only if so, 
do we make a determination as to whether the technology meets the cost 
threshold and represents a substantial clinical improvement over 
existing medical services or technologies. An EUA authorizes a product 
for emergency use when it is determined that it is reasonable to 
believe that a product is effective in treating a condition, and, when 
used under the conditions described in the EUA, the known and potential 
benefits outweigh the known and potential risks for the product.\755\ 
As the safety and effectiveness of therapies under an EUA continue to 
be evaluated, \756\ we are therefore unable to consider EUA as FDA 
marketing authorization for the purposes of new technology add-on 
payments.
---------------------------------------------------------------------------

    \755\ U.S. Food and Drug Administration. (2020, November 19). 
Coronavirus (COVID-19) Update: FDA Authorizes Drug Combination for 
Treatment of COVID-19. U.S. Food and Drug Administration. https://www.fda.gov/news-events/press-announcements/coronavirus-covid-19-update-fda-authorizes-drug-combination-treatment-covid-19.
    \756\ Ibid.
---------------------------------------------------------------------------

8. Extension of the New COVID-19 Treatments Add-On Payment (NCTAP) 
Through the End of the FY in Which the PHE Ends
    In response to the COVID-19 PHE, we established the New COVID-19 
Treatments Add-on Payment (NCTAP) under the IPPS for COVID-19 cases 
that meet certain criteria (85 FR 71157-71158). We believe that as 
drugs and biological products become available and are authorized for 
emergency use or approved by FDA for the treatment of COVID-19 in the 
inpatient setting, it is appropriate to increase the current IPPS 
payment amounts to mitigate any potential financial disincentives for 
hospitals to provide new COVID-19 treatments during the PHE. Therefore, 
effective for discharges occurring on or after November 2, 2020 and 
until the end of the PHE for COVID-19, we established the NCTAP to pay 
hospitals the lesser of: (1) 65 percent of the operating outlier 
threshold for the claim; or (2) 65 percent of the amount by which the 
costs of the case exceed the standard DRG payment, including the 
adjustment to the relative weight under section 3710 of the Coronavirus 
Aid, Relief, and Economic Security (CARES) Act, for certain cases that 
include the use of a drug or biological product currently authorized 
for emergency use or approved for treating COVID-19.
    We stated in the proposed rule that we anticipated that there might 
be inpatient cases of COVID-19, beyond the end of the PHE, for which 
payment based on the assigned MS-DRG may not adequately reflect the 
additional cost of new COVID-19 treatments. In order to continue to 
mitigate potential financial disincentives for hospitals to provide 
these new treatments, and to minimize any potential payment disruption 
immediately following the end of the PHE, we stated that we believed 
that the NCTAP should remain available for cases involving eligible 
treatments for the remainder of the fiscal year in which the PHE ends 
(for example, if the PHE were to end in FY 2022, until September 30, 
2022).\757\ At the same time, we stated that we also believed that any 
new technology add-on payments that may be approved for a COVID-19 
treatment would also serve to mitigate any potential financial 
disincentives for hospitals to provide that new COVID-19 treatment, 
such that the NCTAP would no longer be needed for that same product. We 
noted that a COVID-19 treatment that is the subject of an application 
for FY 2022 new technology add-on payments and which receives FDA 
approval or clearance by July 1, 2021 would be eligible for 
consideration for new technology add-on payments for FY 2022.
---------------------------------------------------------------------------

    \757\ On January 22, 2021, former Acting HHS Secretary Norris 
Cochran sent a letter to governors announcing that HHS has 
determined that the public health emergency will likely remain in 
place for the entirety of 2021, and when a decision is made to 
terminate the declaration or let it expire, HHS will provide states 
with 60 days' notice prior to termination.
---------------------------------------------------------------------------

    Therefore, we proposed to extend the NCTAP for eligible products 
that are not approved for new technology add-on payments through the 
end of the fiscal year in which the PHE ends (for example, September 
30, 2022). We also proposed to discontinue the NCTAP for discharges on 
or after October 1, 2021 for a product that is approved for new 
technology add-on payments beginning FY 2022.
    We stated that we believed the proposal to extend NCTAP for 
eligible products would allow some form of add-on payment (that is, 
NCTAP or new technology add-on payment) to continue uninterrupted for 
some period of time following the conclusion of the COVID-19 PHE, as we 
anticipated that there will continue to be inpatient cases of COVID-19 
after the PHE ends. For example, if a drug or biological product with 
an EUA to treat COVID-19 does not receive FDA approval by July 1, 2021, 
and the PHE ends on December 31, 2021, the proposal would allow 
discharges involving that product to continue to be eligible for the 
NCTAP through September 30, 2022 (the end of FY 2022). We stated that 
if that same product receives FDA approval by July 1, 2022, it would be 
eligible for consideration of new technology add-on

[[Page 45161]]

payments beginning FY 2023, and new technology add-on payments, if 
approved, would begin on October 1, 2022 (the beginning of FY 2023).
    We invited public comment on our proposals to continue the NCTAP 
for eligible products that are not approved for new technology add-on 
payments through the end of the fiscal year in which the PHE ends and 
to discontinue the NCTAP for products that are approved for new 
technology add-on payments.
    Comment: Commenters overwhelmingly supported our proposal to 
continue the NCTAP for eligible products that are not approved for new 
technology add-on payments through the end of the fiscal year in which 
the PHE ends. Commenters stated that extending NCTAPs through the end 
of the fiscal year in which the PHE ends will enable providers to 
continue to treat COVID-19 patients without incurring excess losses.
    Many commenters recommended that CMS remain flexible and consider 
further extending NCTAP to ensure the payment serves its intended 
purposes of supporting providers treating COVID-19 patients, even after 
the PHE, until such a time as the data used to establish payment for 
the applicable MS-DRGs reflects the cost of new COVID-19 treatments. A 
commenter specifically requested that if the PHE were to end less than 
three months prior to the end of the current fiscal year, CMS would 
allow NCTAP to continue for the remainder of the calendar year.
    Some commenters supported our proposal to discontinue the NCTAP for 
products that are approved for new technology add-on payments beginning 
FY 2022. Another commenter recommended that CMS should not extend the 
NCTAP beyond its current expiration date for the existing treatments 
that had an opportunity to apply for new technology add-on payments. 
The commenter also stated that CMS should consider whether any 
treatments for which authorization is newly granted this calendar year 
should receive the NCTAP until the treatment may apply for and be 
granted new technology add-on payment status. The commenter asserted 
that CMS should evaluate safety, cost, and utilization data gathered 
since the NCTAP's inception to assess the financial impact and clinical 
outcomes of this policy to inform the decision on whether to grant new 
technology add-on payment status.
    A commenter, the applicant for Veklury, supported paying NCTAP 
until it expires and then paying the new technology add-on payment once 
the NCTAP is no longer paid. The commenter provided the following table 
demonstrating that the NCTAP is more effective than a potential new 
technology add-on payment at mitigating the potential financial 
disincentives for a hospital to provide new COVID-19 treatments. The 
commenter identified relevant MS-DRGs using Veklury ICD-10 codes from 
FY 2020 MedPAR data and modeled estimated average payment rates using 
FY 2019 MedPAR data across a variety of scenarios.
BILLING CODE 4120-01-P
[GRAPHIC] [TIFF OMITTED] TR13AU21.227

BILLING CODE 4120-01-C
    The commenter stated that the NCTAP provides appropriate levels of 
support to reduce disincentives to use COVID-19 therapeutics, 
particularly when compared to new technology add-on payments. The 
commenter also stated that the NCTAP may be particularly useful to 
hospitals as a means to smooth the transition in payment once the 20% 
COVID-19 DRG add-on payment ends at the conclusion of the PHE, as 
mandated by the CARES Act. Therefore, the commenter suggested that 
instead of discontinuing the NCTAP when a new technology add-on payment 
is approved as we proposed, that CMS grant a conditional new technology 
add-on payment that would not take effect until the expiration of the 
NCTAP. They believed that this approach would be similar to the 
conditional new technology add-on payment established for certain 
antimicrobial products and would provide clear guidance for providers 
and more consistent access to NCTAP across COVID-19 treatment options. 
They suggested that once the NCTAP period has expired at the end of the 
fiscal year, the new technology add-on payment would immediately 
initiate and extend through the remainder of the new technology add-on 
payment's 2-3-year newness period, with the beginning of the newness 
period tied to the FDA approval date of the new technology and 
inclusive of the period where a conditional new technology add-on 
payment was in place and a product was eligible for NCTAP.

[[Page 45162]]

    A commenter noted that in many instances, NCTAP would result in 
higher payment than the new technology add-on payment for the same 
product. The commenter recommended that CMS provide the add-on payment, 
either NCTAP or new technology add-on payment, whichever results in the 
highest total case-level Medicare payment for current NCTAP products 
that are approved for new technology add-on payment status. The 
commenter believes that this policy would encourage the use of these 
treatments and mitigate sudden declines in payment and should remain in 
effect through the fiscal year in which the PHE ends. Another commenter 
stated that it was concerned that for a product currently eligible for 
NCTAP that is approved for new technology add-on payment, Medicare 
payment may be inadequate if the NCTAP is discontinued, making it more 
difficult for providers to sustainably care for patients in the same 
manner as when the NCTAP was in place. The commenter encouraged CMS to 
consider allowing the payment structure for the NCTAP to continue even 
if a product has been approved for new technology add-on payments 
beginning in FY 2022.
    A commenter recommended that CMS should consider NCTAP and new 
technology add-on payments to run consecutively and not concurrently so 
that these payment statuses do not overlap. Another commenter supported 
paying both NCTAP and new technology add-on payments for a single 
technology if the technology is eligible for both add on payments.
    Response: We appreciate the commenters' feedback and support for 
the proposed extension of the NCTAP. After consideration of the 
comments received, and for the reasons discussed previously, we are 
finalizing our proposed extension of the NCTAP through the end of the 
fiscal year in which the PHE ends. We also appreciate the commenters' 
recommendations to further extend the NCTAP beyond this timeframe. 
Since we cannot predict the timing or circumstances around the end of 
the PHE, we will consider these for future rulemaking.
    After consideration of the comments, we believe technologies 
eligible for new technology add-on payments should also be eligible for 
NCTAP. While we received some comments supporting our proposal to 
discontinue NCTAP for a product that is approved for new technology 
add-on payments, we agree with the other commenters that the NCTAP is 
more effective than a potential new technology add-on payment at 
mitigating the potential financial disincentives for a hospital to 
provide new COVID-19 treatments. By making an NCTAP for technologies 
also eligible for new technology add-on payment, we believe this will 
mitigate any financial disincentives for treatments for COVID-19 
depending on whether the treatment is eligible for new technology add-
on payment or NCTAP only. Specifically, as demonstrated by the 
commenter above, the NCTAP without new technology add-on payment can 
result in a higher add-on payment than the new technology add-on 
payment without NCTAP. We do not believe technologies approved for new 
technology add-on payment should be disadvantaged and receive a lower 
add-on payment than those technologies eligible for NCTAP. Allowing for 
both NCTAP and new technology add-on payments for technologies eligible 
to receive both will result in the products receiving an equivalent 
payment in the amount of the NCTAP.
    Therefore, after review of the comments received, we are not 
finalizing our proposal to discontinue NCTAP for discharges on or after 
October 1, 2021 for a product that is approved for new technology add-
on payments beginning FY 2022, but are instead finalizing to extend 
NCTAP through the end of the FY in which the PHE ends for all eligible 
products, including those approved for new technology add-on payments 
for FY 2022. However, we are also finalizing that we will reduce the 
NCTAP for an eligible case by the amount of any new technology add-on 
payments so that we do not create a financial disincentive between 
technologies eligible for both the new technology add-on payment and 
NCTAP compared to technologies eligible for NCTAP only. This will 
ensure that the add-on payment for a technology eligible for both new 
technology add-on payments and NCTAP is equivalent to that of a 
technology only eligible for the NCTAP.
    As discussed in section F.5.t., we are approving Veklury for FY 
2022 new technology add on payments. Veklury is the only COVID-19 
treatment eligible for new technology add-on payments in FY 2022. 
Therefore, cases involving the use of Veklury in FY 2022 are eligible 
for both new technology add-on payments and NCTAP, with any new 
technology add-on payment reducing the amount of any NCTAP for the same 
treatment. Accordingly, cases of Veklury will receive a total add-on 
payment that will be equal to the payment it would receive if it were 
only eligible for NCTAP.
    As discussed above, we are finalizing our proposal to extend the 
NCTAP for eligible products through the end of the fiscal year in which 
the PHE ends, with modifications. Specifically, we are finalizing to 
extend the NCTAP through the end of the fiscal year in which the PHE 
ends for all eligible products, including those approved for new 
technology add-on payments for FY 2022. We are not finalizing our 
proposal to discontinue the NCTAP for discharges on or after October 1, 
2021 for a product that is approved for new technology add-on payments 
beginning FY 2022. Instead, we are finalizing that we will continue to 
allow NCTAP for cases eligible for the new technology add-on payment, 
through the end of the fiscal year in which the PHE ends, with the new 
technology add-on payment reducing the amount of the NCTAP, as 
discussed previously.

III. Changes to the Hospital Wage Index for Acute Care Hospitals

A. Background

1. Legislative Authority
    Section 1886(d)(3)(E) of the Act requires that, as part of the 
methodology for determining prospective payments to hospitals, the 
Secretary adjust the standardized amounts for area differences in 
hospital wage levels by a factor (established by the Secretary) 
reflecting the relative hospital wage level in the geographic area of 
the hospital compared to the national average hospital wage level. We 
currently define hospital labor market areas based on the delineations 
of statistical areas established by the Office of Management and Budget 
(OMB). A discussion of the FY 2022 hospital wage index based on the 
statistical areas appears under section III.A.2. of the preamble of 
this final rule.
    Section 1886(d)(3)(E) of the Act requires the Secretary to update 
the wage index annually and to base the update on a survey of wages and 
wage-related costs of short-term, acute care hospitals. (CMS collects 
these data on the Medicare cost report, CMS Form 2552-10, Worksheet S-
3, Parts II, III, and IV. The OMB control number for approved 
collection of this information is 0938-0050, which expires on March 31, 
2022.) This provision also requires that any updates or adjustments to 
the wage index be made in a manner that ensures that aggregate payments 
to hospitals are not affected by the change in the wage index. The 
adjustment for FY 2022 is discussed in section II.B. of the Addendum to 
this final rule.
    As discussed in section III.I. of the preamble of this final rule, 
we also take into account the geographic reclassification of hospitals 
in

[[Page 45163]]

accordance with sections 1886(d)(8)(B) and 1886(d)(10) of the Act when 
calculating IPPS payment amounts. Under section 1886(d)(8)(D) of the 
Act, the Secretary is required to adjust the standardized amounts so as 
to ensure that aggregate payments under the IPPS after implementation 
of the provisions of sections 1886(d)(8)(B), 1886(d)(8)(C), and 
1886(d)(10) of the Act are equal to the aggregate prospective payments 
that would have been made absent these provisions. The budget 
neutrality adjustment for FY 2022 is discussed in section II.A.4.b. of 
the Addendum to this final rule.
    Section 1886(d)(3)(E) of the Act also provides for the collection 
of data every 3 years on the occupational mix of employees for short-
term, acute care hospitals participating in the Medicare program, in 
order to construct an occupational mix adjustment to the wage index. A 
discussion of the occupational mix adjustment that we are applying to 
the FY 2022 wage index appears under sections III.E. and F. of the 
preamble of this final rule.
2. Core-Based Statistical Areas (CBSAs) for the FY 2022 Hospital Wage 
Index
    The wage index is calculated and assigned to hospitals on the basis 
of the labor market area in which the hospital is located. Under 
section 1886(d)(3)(E) of the Act, beginning with FY 2005, we delineate 
hospital labor market areas based on OMB-established Core-Based 
Statistical Areas (CBSAs). The current statistical areas (which were 
implemented beginning with FY 2015) are based on revised OMB 
delineations issued on February 28, 2013, in OMB Bulletin No. 13-01. 
OMB Bulletin No. 13-01 established revised delineations for 
Metropolitan Statistical Areas, Micropolitan Statistical Areas, and 
Combined Statistical Areas in the United States and Puerto Rico based 
on the 2010 Census, and provided guidance on the use of the 
delineations of these statistical areas using standards published in 
the June 28, 2010 Federal Register (75 FR 37246 through 37252). We 
refer readers to the FY 2015 IPPS/LTCH PPS final rule (79 FR 49951 
through 49963 and 49973 through 49982)) for a full discussion of our 
implementation of the OMB statistical area delineations beginning with 
the FY 2015 wage index. Generally, OMB issues major revisions to 
statistical areas every 10 years, based on the results of the decennial 
census. However, OMB occasionally issues minor updates and revisions to 
statistical areas in the years between the decennial censuses through 
OMB Bulletins. On July 15, 2015, OMB issued OMB Bulletin No. 15-01, 
which provided updates to and superseded OMB Bulletin No. 13-01 that 
was issued on February 28, 2013. The attachment to OMB Bulletin No. 15-
01 provided detailed information on the update to statistical areas 
since February 28, 2013. The updates provided in OMB Bulletin No. 15-01 
were based on the application of the 2010 Standards for Delineating 
Metropolitan and Micropolitan Statistical Areas to Census Bureau 
population estimates for July 1, 2012 and July 1, 2013. In the FY 2017 
IPPS/LTCH PPS final rule (81 FR 56913), we adopted the updates set 
forth in OMB Bulletin No. 15-01 effective October 1, 2016, beginning 
with the FY 2017 wage index. For a complete discussion of the adoption 
of the updates set forth in OMB Bulletin No. 15-01, we refer readers to 
the FY 2017 IPPS/LTCH PPS final rule. In the FY 2018 IPPS/LTCH PPS 
final rule (82 FR 38130), we continued to use the OMB delineations that 
were adopted beginning with FY 2015 to calculate the area wage indexes, 
with updates as reflected in OMB Bulletin No. 15-01 specified in the FY 
2017 IPPS/LTCH PPS final rule.
    On August 15, 2017, OMB issued OMB Bulletin No. 17-01, which 
provided updates to and superseded OMB Bulletin No. 15-01 that was 
issued on July 15, 2015. The attachments to OMB Bulletin No. 17-01 
provided detailed information on the update to statistical areas since 
July 15, 2015, and were based on the application of the 2010 Standards 
for Delineating Metropolitan and Micropolitan Statistical Areas to 
Census Bureau population estimates for July 1, 2014 and July 1, 2015. 
In the FY 2019 IPPS/LTCH PPS final rule (83 FR 41362 through 41363), we 
adopted the updates set forth in OMB Bulletin No. 17-01 effective 
October 1, 2018, beginning with the FY 2019 wage index. For a complete 
discussion of the adoption of the updates set forth in OMB Bulletin No. 
17-01, we refer readers to the FY 2019 IPPS/LTCH PPS final rule. In the 
FY 2020 IPPS/LTCH PPS final rule (84 FR 42300 through 42301), we 
continued to use the OMB delineations that were adopted beginning with 
FY 2015 (based on the revised delineations issued in OMB Bulletin No. 
13-01) to calculate the area wage indexes, with updates as reflected in 
OMB Bulletin Nos. 15-01 and 17-01.
    On April 10, 2018 OMB issued OMB Bulletin No. 18-03 which 
superseded the August 15, 2017 OMB Bulletin No. 17-01. On September 14, 
2018, OMB issued OMB Bulletin No. 18-04 which superseded the April 10, 
2018 OMB Bulletin No. 18-03. Historically OMB bulletins issued between 
decennial censuses have only contained minor modifications to CBSA 
delineations based on changes in population counts. However, OMB's 2010 
Standards for Delineating Metropolitan and Micropolitan Standards 
created a larger mid-decade redelineation that takes into account 
commuting data from the American Commuting Survey. As a result, the 
September 14, 2018 OMB Bulletin No. 18-04 included more modifications 
to the CBSAs than are typical for OMB bulletins issued between 
decennial censuses.
    In the FY 2021 IPPS/LTCH PPS final rule (85 FR 58743 through 58755) 
we adopted the updates set forth in OMB Bulletin No. 18-04 effective 
October 1, 2020, beginning with the FY 2021 wage index. For a complete 
discussion of the adoption of the updates set forth in OMB Bulletin No. 
18-04, we refer readers to the FY 2021 IPPS/LTCH PPS final rule.
    On March 6, 2020, OMB issued Bulletin No. 20-01, which provided 
updates to and superseded OMB Bulletin No. 18-04 that was issued on 
September 14, 2018. The attachments to OMB Bulletin No. 20-01 provided 
detailed information on the update to statistical areas since September 
14, 2018, and were based on the application of the 2010 Standards for 
Delineating Metropolitan and Micropolitan Statistical Areas to Census 
Bureau population estimates for July 1, 2017 and July 1, 2018. (For a 
copy of this bulletin, we refer readers to the following website: 
https://www.whitehouse.gov/wp-content/uploads/2020/03/Bulletin-20-01.pdf). In OMB Bulletin No. 20-01, OMB announced one new Micropolitan 
Statistical Area, one new component of an existing Combined Statistical 
Area and changes to New England City and Town Area (NECTA) 
delineations. In the FY 2021 IPPS/LTCH PPS final rule (85 FR 58744), we 
stated that if appropriate, we would propose any necessary wage area 
updates based on OMB Bulletin No. 20-01 in the FY 2022 IPPS/LTCH PPS 
proposed rule. After reviewing OMB Bulletin No. 20-01, we have 
determined that the changes in Bulletin 20-01 encompassed delineation 
changes that would not affect the Medicare wage index for FY 2022. 
Specifically, the updates consisted of changes to NECTA delineations 
and the creation of a new Micropolitan Statistical Area which was then 
added as a new component to an existing Micropolitan Statistical Area. 
The Medicare wage index does not utilize NECTA definitions, and, as 
most recently discussed in FY 2021 IPPS/

[[Page 45164]]

LTCH PPS final rule (85 FR 58746), we include hospitals located in 
Micropolitan Statistical areas in each State's rural wage index. 
Therefore, while we are adopting the updates set forth in OMB Bulletin 
No. 20-01 consistent with our general policy of adopting OMB 
delineation updates, we note that specific wage index updates would not 
be necessary for FY 2022 as a result of adopting these OMB updates. In 
other words, these OMB updates would not affect any hospital's 
geographic area for purposes of the wage index calculation for FY 2022.
    For FY 2022, we are continuing to use the OMB delineations that 
were adopted beginning with FY 2015 (based on the revised delineations 
issued in OMB Bulletin No. 13-01) to calculate the area wage indexes, 
with updates as reflected in OMB Bulletin Nos. 15-01, 17-01, 18-04 and 
20-01, although as noted above the latter Bulletin did not require any 
wage area updates.
    We note that, in connection with our adoption in FY 2021 of the 
updates in OMB Bulletin 18-04, we adopted a policy to place a 5 percent 
cap, for FY 2021, on any decrease in a hospital's wage index from the 
hospital's final wage index in FY 2020 so that a hospital's final wage 
index for FY 2021 would not be less than 95 percent of its final wage 
index for FY 2020. We refer the reader to the FY 2021 IPPS/LTCH PPS 
final rule (85 FR 58753 through 58755) for a complete discussion of 
this transition. As finalized in the FY 2021 IPPS/LTCH PPS final rule, 
this transition is set to expire at the end of FY 2021. However, given 
the unprecedented nature of the ongoing COVID-19 public health 
emergency (PHE), we also sought comment on whether it would be 
appropriate to continue to apply a transition to the FY 2022 wage index 
for hospitals negatively impacted by our adoption of the updates in OMB 
Bulletin 18-04. For example, such an extended transition could 
potentially take the form of holding the FY 2022 wage index for those 
hospitals harmless from any reduction relative to their FY 2021 wage 
index. If we were to apply a transition to the FY 2022 wage index for 
hospitals negatively impacted by our adoption of the updates in OMB 
Bulletin 18-04, we also sought comment on making this transition budget 
neutral, as is our usual practice, in the same manner that the FY 2021 
transition was made budget neutral as discussed in the FY 2021 IPPS/
LTCH PPS final rule (85 FR 58755).
    Comment: We received several comments strongly recommending CMS 
extend a transition policy similar to that implemented in FY 2020 and 
FY 2021. Several commenters, citing the severity and continuing impact 
of changes related to the OMB updates, the low wage index policy, and 
the lingering financial burden caused by the COVID-19 PHE, urged CMS to 
add an additional year of transition, applied in a budget neutral 
manner. These commenters stated that given the wide-ranging factors 
impacting wage index values, it would not be equitable to limit the 
transition adjustment only to the effects of the revised labor market 
delineations. The commenters requested the transition be implemented 
more broadly to all hospitals experiencing large declines in wage index 
values. Many of these commenters recommended CMS consider making a 
permanent 5 percent maximum reduction policy to protect hospitals from 
large year-to-year variations in wage index values as a means to reduce 
overall volatility.
    Other commenters requested that CMS extend a hold harmless policy 
for all hospitals negatively affected by CMS' adoption of revised 
delineations until OMB releases further revisions predicated on the 
results of the 2020 decennial census. A commenter recommended a hold-
harmless transition be applied specifically to hospitals in CBSAs that 
were negatively affected by the FY 2021 adoption of revised CBSAs, 
citing specific CBSAs they believed warranted an additional transition 
adjustment.
    Several commenters, while supporting some form of transition 
adjustment for negatively affected hospitals, requested any such 
adjustment be made in a non-budget neutral manner. These commenters 
expressed their preference that any such adjustment should not come at 
the expense of the providers themselves. Some commenters stated that 
such a budget neutrality adjustment would disadvantage providers who 
have increased their wage index values due to a variety of factors.
    Response: After consideration of the comments, we are applying an 
extended transition to the FY 2022 wage index for hospitals. 
Specifically, for hospitals that received the transition in FY 2021, we 
are continuing a wage index transition for FY 2022 under which we will 
apply a 5 percent cap on any decrease in the hospital's wage index 
compared to its wage index for FY 2021 to mitigate significant negative 
impacts of, and provide additional time for hospitals to adapt to, the 
CMS decision to adopt the revised OMB delineations. Also, as discussed 
in the FY 2021 IPPS/LTCH final rule, we believe applying a 5-percent 
cap on any decrease in a hospital's wage index from the hospital's 
final wage index from the prior fiscal year is an appropriate 
transition as it provides predictability in payment levels from FY 2021 
to the upcoming FY 2022 as well as effectively mitigating any 
significant decreases in the wage index for FY 2022.
    We considered comments requesting that we apply the transition 
adjustment in FY 2022 to all hospitals with significant reductions in 
wage index values (not just those that received the transition 
adjustment in FY 2021). Specifically, the policy commenters recommended 
would extend not only to specific changes in wage index policy (such as 
the introduction of the low wage policy or CMS's adoption of revised 
OMB labor market delineations), but would address any significant 
reductions in hospitals' wage index values, including changes in 
hospital average hourly wage values and changes in various 
reclassification statuses. We also considered comments recommending a 
5-percent cap become a permanent policy for future fiscal years. We 
considered how best to address these potential scenarios in a 
consistent and thoughtful manner, and we reiterate that our policy 
principles with regard to the wage index include generally using the 
most current data and information available and providing that data and 
information, as well as any approaches to addressing any significant 
effects on Medicare payments resulting from these potential scenarios, 
in notice and comment rulemaking. In FY 2020 and FY 2021, CMS 
implemented two separate transition policies limiting any hospital to a 
5 percent year-to-year reduction in wage index values. In FY 2020, the 
purpose of the transition was to address potential impacts due to 
implementation of the low wage policy. In FY 2021, the purpose was to 
address the impact of CMS's adoption of the revised OMB labor market 
delineations. Both the low wage policy and the adoption of revised OMB 
delineations had wide ranging wage index implications; some of which 
could not be readily isolated in order to target the negative impacts, 
such as individual hospital reclassification considerations. CMS 
determined it would be appropriate to apply the transition to all 
hospitals experiencing significant reductions in wage index values. 
There is no specific wage index policy finalized in FY 2022 that 
warrants a similar application of a transition cap to all hospitals. 
For FY 2022, we are limiting the transition policy only to hospitals 
that received a transition adjustment in FY 2021 in order to

[[Page 45165]]

provide additional time for these hospitals to adapt to the FY 2021 
changes.
    We considered the comments recommending we not apply this continued 
transition in a budget neutral manner. We believe limiting the 
transition in FY 2022 to a 5 percent cap on any decrease in the 
hospital's wage index compared to its wage index for FY 2021 rather 
than holding the hospital's FY 2022 wage index harmless from any 
reduction relative to its FY 2021 wage index balances the commenters' 
concerns by limiting the impact of the budget neutrality factor applied 
to the standardized amount while mitigating any continued significant 
decreases in the wage index for FY 2022. Therefore, for FY 2022, 
similar to FY 2021, we are applying a budget neutrality adjustment to 
the standardized amount so that our transition, as previously 
described, is implemented in a budget neutral manner under our 
authority in section 1886(d)(5)(I) of the Act. Implementing the 
transition wage index in a budget neutral manner is consistent with 
past practice (for example, 79 FR 50372 and 84 FR 42338) where CMS has 
used its exceptions and adjustments authority under section 
1886(d)(5)(I)(i) of the Act to budget neutralize transition wage index 
policies when such policies allow for the application of a transitional 
wage index only when it benefits the hospital. We believe, and continue 
to believe, that it would be appropriate to ensure that such policies 
do not increase estimated aggregate Medicare payments beyond the 
payments that would be made had we never applied these transition 
policies (79 FR 50372 and 84 FR 42337 through 42338).
3. Codes for Constituent Counties in CBSAs
    CBSAs are made up of one or more constituent counties. Each CBSA 
and constituent county has its own unique identifying codes. There are 
two different lists of codes associated with counties: Social Security 
Administration (SSA) codes and Federal Information Processing Standard 
(FIPS) codes. Historically, CMS has listed and used SSA and FIPS county 
codes to identify and crosswalk counties to CBSA codes for purposes of 
the hospital wage index. As we discussed in the FY 2018 IPPS/LTCH PPS 
final rule (82 FR 38129 through 38130), we have learned that SSA county 
codes are no longer being maintained and updated. However, the FIPS 
codes continue to be maintained by the U.S. Census Bureau. We believe 
that using the latest FIPS codes will allow us to maintain a more 
accurate and up-to-date payment system that reflects the reality of 
population shifts and labor market conditions.
    The Census Bureau's most current statistical area information is 
derived from ongoing census data received since 2010; the most recent 
data are from 2020. The Census Bureau maintains a complete list of 
changes to counties or county equivalent entities on the website at: 
https://www.census.gov/programs-surveys/geography/technical-documentation/county-changes.html. We believe that it is important to 
use the latest counties or county equivalent entities in order to 
properly crosswalk hospitals from a county to a CBSA for purposes of 
the hospital wage index used under the IPPS.
    In the FY 2018 IPPS/LTCH PPS final rule (82 FR 38129 through 
38130), we adopted a policy to discontinue the use of the SSA county 
codes and began using only the FIPS county codes for purposes of cross 
walking counties to CBSAs. In addition, in the same rule, we 
implemented the latest FIPS code updates, which were effective October 
1, 2017, beginning with the FY 2018 wage indexes. These updates have 
been used to calculate the wage indexes in a manner generally 
consistent with the CBSA-based methodologies finalized in the FY 2005 
IPPS final rule and the FY 2015 IPPS/LTCH PPS final rule.
    For FY 2022, we are continuing to use only the FIPS county codes 
for purposes of cross walking counties to CBSAs. For FY 2022, Tables 2 
and 3 associated with this final rule and the County to CBSA Crosswalk 
File and Urban CBSAs and Constituent Counties for Acute Care Hospitals 
File posted on the CMS website reflect the latest FIPS code updates.

B. Worksheet S-3 Wage Data for the FY 2022 Wage Index

    The FY 2022 wage index values are based on the data collected from 
the Medicare cost reports submitted by hospitals for cost reporting 
periods beginning in FY 2018 (the FY 2021 wage indexes were based on 
data from cost reporting periods beginning during FY 2017).
1. Included Categories of Costs
    The FY 2022 wage index includes all of the following categories of 
data associated with costs paid under the IPPS (as well as outpatient 
costs):
     Salaries and hours from short-term, acute care hospitals 
(including paid lunch hours and hours associated with military leave 
and jury duty);
     Home office costs and hours;
     Certain contract labor costs and hours, which include 
direct patient care, certain top management, pharmacy, laboratory, and 
nonteaching physician Part A services, and certain contract indirect 
patient care services (as discussed in the FY 2008 final rule with 
comment period (72 FR 47315 through 47317)); and
     Wage-related costs, including pension costs (based on 
policies adopted in the FY 2012 IPPS/LTCH PPS final rule (76 FR 51586 
through 51590)) and other deferred compensation costs.
2. Excluded Categories of Costs
    Consistent with the wage index methodology for FY 2021, the wage 
index for FY 2022 also excludes the direct and overhead salaries and 
hours for services not subject to IPPS payment, such as skilled nursing 
facility (SNF) services, home health services, costs related to GME 
(teaching physicians and residents) and certified registered nurse 
anesthetists (CRNAs), and other subprovider components that are not 
paid under the IPPS. The FY 2022 wage index also excludes the salaries, 
hours, and wage-related costs of hospital-based rural health clinics 
(RHCs), and Federally qualified health centers (FQHCs) because Medicare 
pays for these costs outside of the IPPS (68 FR 45395). In addition, 
salaries, hours, and wage-related costs of CAHs are excluded from the 
wage index for the reasons explained in the FY 2004 IPPS final rule (68 
FR 45397 through 45398). For FY 2020 and subsequent years, other wage-
related costs are also excluded from the calculation of the wage index. 
As discussed in the FY 2019 IPPS/LTCH final rule (83 FR 41365 through 
41369), other wage-related costs reported on Worksheet S-3, Part II, 
Line 18 and Worksheet S-3, Part IV, Line 25 and subscripts, as well as 
all other wage-related costs, such as contract labor costs, are 
excluded from the calculation of the wage index.
3. Use of Wage Index Data by Suppliers and Providers Other Than Acute 
Care Hospitals Under the IPPS
    Data collected for the IPPS wage index also are currently used to 
calculate wage indexes applicable to suppliers and other providers, 
such as SNFs, home health agencies (HHAs), ambulatory surgical centers 
(ASCs), and hospices. In addition, they are used for prospective 
payments to IRFs, IPFs, and LTCHs, and for hospital outpatient 
services. We note that, in the IPPS rules, we do not address comments 
pertaining to the wage indexes of any supplier or provider except IPPS 
providers and LTCHs. Such comments should be made in response to 
separate proposed rules for those suppliers and providers.

[[Page 45166]]

    We did not receive any comments on the discussion in this section.

C. Verification of Worksheet S-3 Wage Data

    The wage data for the FY 2022 wage index were obtained from 
Worksheet S-3, Parts II and III of the Medicare cost report (Form CMS-
2552-10, OMB Control Number 0938-0050 with expiration date March 31, 
2022) for cost reporting periods beginning on or after October 1, 2017, 
and before October 1, 2018. For wage index purposes, we refer to cost 
reports during this period as the ``FY 2018 cost report,'' the ``FY 
2018 wage data,'' or the ``FY 2018 data.'' Instructions for completing 
the wage index sections of Worksheet S-3 are included in the Provider 
Reimbursement Manual (PRM), Part 2 (Pub. 15-2), Chapter 40, Sections 
4005.2 through 4005.4. The data file used to construct the FY 2022 wage 
index includes FY 2018 data submitted to us as of the end of June 2021. 
As in past years, we performed an extensive review of the wage data, 
mostly through the use of edits designed to identify aberrant data.
    We suggested our MACs to revise or verify data elements that result 
in specific edit failures. For the proposed FY 2022 wage index, we 
identified and excluded 86 providers with aberrant data that should not 
be included in the wage index. However, we stated that if data elements 
for some of these providers are corrected, we intended to include data 
from those providers in the final FY 2022 wage index. We also adjusted 
certain aberrant data and included these data in the wage index. For 
example, in situations where a hospital did not have documentable 
salaries, wages, and hours for housekeeping and dietary services, we 
imputed estimates, in accordance with policies established in the FY 
2015 IPPS/LTCH PPS final rule (79 FR 49965 through 49967). We 
instructed MACs to complete their data verification of questionable 
data elements and to transmit any changes to the wage data no later 
than March 19, 2021. For the final FY 2022 wage index, we restored 28 
hospitals to the wage index because their data was either verified or 
improved, but we also removed the data of 5 hospital for the first time 
after the proposed rule due to its data being aberrant or due to 
conversion to CAH status. Thus, 63 hospitals with aberrant data remain 
excluded from the FY 2022 wage index (86-28 + 5 = 63).
    In constructing the proposed FY 2022 wage index, we included the 
wage data for facilities that were IPPS hospitals in FY 2018, inclusive 
of those facilities that have since terminated their participation in 
the program as hospitals, as long as those data did not fail any of our 
edits for reasonableness. We stated in the proposed rule (86 FR 25398) 
that we believe including the wage data for these hospitals is, in 
general, appropriate to reflect the economic conditions in the various 
labor market areas during the relevant past period and to ensure that 
the current wage index represents the labor market area's current wages 
as compared to the national average of wages. However, we excluded the 
wage data for CAHs as discussed in the FY 2004 IPPS final rule (68 FR 
45397 through 45398); that is, any hospital that is designated as a CAH 
by 7 days prior to the publication of the preliminary wage index public 
use file (PUF) is excluded from the calculation of the wage index.
    For the proposed FY 2022 wage index, we removed 3 hospitals that 
converted to CAH status on or after January 24, 2020, the cut-off date 
for CAH exclusion from the FY 2021 wage index, and through and 
including January 24, 2021, the cut-off date for CAH exclusion from the 
FY 2022 wage index. Since the proposed rule, we learned of 2 more 
hospital that converted to CAH status on or after January 24, 2020, and 
through and including January 24, 2021, the cut-off date for CAH 
exclusion from the FY 2022 wage index, for a total of 5 hospitals that 
were removed from the FY 2022 wage index due to conversion to CAH 
status. In summary, we calculated the FY 2022 wage index using the 
Worksheet S-3, Parts II and III wage data of 3,182 hospitals.
    For the FY 2022 wage index, we allotted the wages and hours data 
for a multicampus hospital among the different labor market areas where 
its campuses are located using campus full-time equivalent (FTE) 
percentages as originally finalized in the FY 2012 IPPS/LTCH PPS final 
rule (76 FR 51591). Table 2, which contains the FY 2022 wage index 
associated with this final rule (available via the internet on the CMS 
website), includes separate wage data for the campuses of 21 
multicampus hospitals. The following chart lists the multicampus 
hospitals by CSA certification number (CCN) and the FTE percentages on 
which the wages and hours of each campus were allotted to their 
respective labor market areas:
BILLING CODE 4120-01-P

[[Page 45167]]

[GRAPHIC] [TIFF OMITTED] TR13AU21.228

BILLING CODE 4120-01-C
    We note that, in past years, in Table 2, we have placed a ``B'' to 
designate the subordinate campus in the fourth position of the hospital 
CCN. However, for the FY 2019 IPPS/LTCH PPS proposed and final rules 
and subsequent rules, we have moved the ``B'' to the third position of 
the CCN. Because all IPPS hospitals have a ``0'' in the third position 
of the CCN, we believe that placement of the ``B'' in this third 
position, instead of the ``0'' for the subordinate campus, is the most 
efficient method of identification and interferes the least with the 
other, variable, digits in the CCN.
    Comment: Several commenters strongly opposed the exclusion of 
hospitals' wage data. These commenters stated that excluding accurate 
and verified data is inconsistent with the extensive process 
established by CMS to ensure the accuracy and reliability of hospital 
wage index data.
    A commenter stated that several of the 86 hospitals CMS identifies 
as having ``aberrant'' data are California hospitals whose wages are 
higher than their core-based statistical average (CBSA) average. The 
commenter stated that in the proposed rule CMS does not cite specific 
reasons why the agency believes the data from these hospitals are 
``aberrant.'' Therefore, the commenter stated that the excluded 
hospitals and other stakeholders are left to infer that CMS is 
excluding these hospitals because their wages are higher than those of 
other hospitals in the CBSA. The commenter explained that in the 
absence of explanation from the agency, stakeholders are left to make 
educated guesses as to why CMS has deemed the wage data aberrant, 
limiting their ability to fully comment on the exclusion of individual 
hospitals. The commenter alleged that CMS is using arbitrary and 
undisclosed criteria to exclude these hospitals.
    The commenter continued that the FFY 2022 wage data from worksheet 
S-3 of cost reports filed during FFY 2018 for the excluded hospitals 
with average hourly wages that are higher than the CBSA average have 
been reviewed by CMS and its MAC as part of the well-established 
Medicare wage index review process (just like all other hospitals). The 
commenter indicated that, in accordance with the wage index review 
process, as defined in CMS' Wage Index Development Timetable, at least 
one of the hospitals in question submitted corrected data in a timely 
manner that was reviewed and accepted by the MAC. The commenter stated 
that, in accordance with Medicare's wage index review process, the 
excluded hospitals' FFY 2018 worksheet S-3 wage data

[[Page 45168]]

were determined by the MAC to be accurate.
    Commenters specifically raised the following concerns about 
lawfulness of excluding wage data for these hospitals: Section 
1395ww(d)(3)(E) of the statute does not provide the authority for CMS 
to delete accurately-reported wage data; excluding hospitals without 
any definable standards is an abuse of discretion, creates uncertainty, 
and is arbitrary and capricious; the proposed exclusion is procedurally 
improper without notice-and-comment rulemaking in accordance with the 
Administrative Procedure Act (APA); excluding accurate wage data 
disregards labor costs and improperly substitutes CMS' judgment of 
reasonable wage levels for actual, free-market wage data; and singling 
out a health system due to its collective bargaining practices 
undermines the National Labor Relations Act (NLRA).
    Several commenters stated that high labor costs are a true 
reflection of the challenging labor markets in California and the fact 
that wages are influenced by labor negotiations does not render them 
any less valid.
    Commenters also expressed concern regarding the effects of 
excluding the hospitals' wage data. A few commenters stated that 
excluding the wage data for the hospitals will decrease payments to 
hospitals in those CBSAs significantly, jeopardizing access to care for 
Medicare beneficiaries across California. Many commenters stated that 
excluding the hospitals' wage data will also harm inpatient psychiatric 
facilities, inpatient rehabilitation facilities, skilled nursing 
facilities, and other provider types whose payments are impacted by the 
wage index, and noted that CMS did not identify the fiscal impacts of 
the exclusions in its respective regulatory impact analyses for the 
IPF, IRF, SNF, and the IPPS proposed rules.
    Response: We received similar comments in FY 2016 and reiterate the 
points we made in the FY 2016 IPPS/LTCH final rule (80 FR 49490-49491).
    Section 1886(d)(3)(E) of the Act requires the Secretary to adjust 
the proportion of hospitals' costs attributable to wages and wage-
related costs for area differences reflecting the relative hospital 
wage level in the geographic area of the hospital compared to the 
national average hospital wage level. We believe that, under this 
section of the Act, we have discretion to exclude aberrant hospital 
data from the wage index PUFs to help ensure that the costs 
attributable to wages and wage-related costs in fact reflect the 
relative hospital wage level in the hospitals' geographic area.
    Since the origin of the IPPS, the wage index has been subject to 
its own annual review process, first by the MACs, and then by CMS. 
Hospitals are aware that both the MACs (via instructions issued by CMS) 
and CMS evaluate the accuracy and reasonableness of hospitals' wage 
index data, and hospitals may appeal to CMS as part of the April and 
June appeals processes. As a standard practice, after each annual desk 
review, CMS reviews the results of the MACs' desk reviews and focuses 
on items flagged during the desk review, requiring that the MACs and, 
if necessary, hospitals provide additional documentation, adjustments, 
or corrections to the data. Each year in the IPPS/LTCH PPS proposed 
rule, we discuss the process wherein CMS suggested the MACs to ``revise 
or verify data elements that result in specific edit failures'' (86 FR 
25398). In the FY 2022 IPPS/LTCH PPS proposed rule, similar to the 
proposed rules of prior years, we stated that we included the wage data 
for facilities that were IPPS hospitals in FY 2012, inclusive of those 
facilities that have since terminated their participation in the 
program as hospitals, as long as those data did not fail any of our 
edits for reasonableness. We believe that including the wage data for 
these hospitals is appropriate, in general, to reflect the various 
labor market areas during the relevant past period and to ensure that 
the current wage index represents the labor market area's current wages 
as compared to the national average of wages (80 FR 24464). That is, a 
hospital is included in the wage index if its data are reasonable, 
regardless of whether the hospital is open or whether it has terminated 
after the relevant past period, because the wage index is constructed 
to represent the relative average hourly wage for each labor market 
area in that past period. Thus, reasonableness and relativity to each 
area's average hourly wages have been longstanding tenets of the wage 
index development process that CMS has articulated in rulemaking.
    We disagree with the commenters that removing hospitals from the FY 
2022 wage index PUFs was arbitrary and undermined the MAC desk review 
process because, as discussed above, as a standard part of the 
refinement of the annual wage index, CMS evaluates the wage data for 
both accuracy and reasonableness to ensure that the wage index is a 
relative measure of the labor value provided to a typical hospital in a 
particular labor market area. As part of this evaluation process, it is 
CMS, not the MACs, that makes the decisions to include or exclude a 
hospital's data from the wage index, and it would not be appropriate 
for CMS to make such decisions prior to a desk review being performed. 
The commenters seem to indicate that only hospitals with high average 
hourly wages were removed from the PUFs. In the FY 2022 IPPS/LTCH PPS 
proposed rule (86 FR 25398), we stated that ``For the proposed FY 2022 
wage index, we identified and excluded 86 providers with aberrant data 
that should not be included in the wage index. If data elements for 
some of these providers are corrected, we intend to include data from 
those providers in the final FY 2022 wage index''. We note that we 
never anticipated that the data of all 86 hospitals would be corrected; 
we only anticipated that the data of some of those hospitals would be 
corrected. This is because approximately 42 hospitals were deleted from 
the FY 2022 proposed wage index for reasons that would make their data 
unresolvable, including, but not limited to, termination (during or 
since the relevant past period), low/no Medicare utilization, being a 
CAH, or not reporting any wage data. Thus, ``aberrant'' hospitals are 
not limited to only hospitals that fail edits for reasonableness, but 
also include hospitals whose data are unresolvable. In fact, the number 
of hospitals deleted from the January or April 2021 PUFs due to having 
an extraordinarily high average hourly wage (and no other significant 
edit failures) was a small percentage of the 86 excluded hospitals 
(11.6 percent). Approximately 45 hospitals excluded from the January 
2022 PUF had the potential to improve their data and be included in the 
April 2015 PUF and/or the final rule wage index. As we stated earlier, 
we received corrected data or improved documentation for 28 hospitals. 
Therefore, we are including these 28 hospitals in the final FY 2022 
wage index. This demonstrates the effectiveness of our process--
hospitals were included in final wage index because these hospitals 
were responsive to the MACs' and CMS' requests for sufficient 
documentation to improve their data. Consequently, the majority of 
hospitals whose data were excluded from the proposed wage index but had 
the potential to improve their data are included in the FY 2022 final 
wage index. We believe the final wage index is all the more accurate as 
a result.
    Regarding the hospitals in California to which a commenter 
referred, without knowing the specific provider numbers we are left to 
assume which providers the commenter is referring to. In any case, we 
use the following example of

[[Page 45169]]

a hospital in California removed from the FY 2022 wage index. The 
hospital is located in CBSA 23420 (Fresno, California) and had a very 
high average hourly wage and was removed from the wage data even though 
the hospital's wage data was properly documented. However, the hospital 
does not merely have the highest average hourly wage in the CBSA; its 
average hourly wage is extremely and unusually high, significantly 
higher than the next highest average hourly wage in that CBSA and in 
the surrounding areas. While we believe this is a result of the unique 
salary structure and business model of the hospital's owner, not from a 
lack of reliability in its wage data, we believe the data is 
nonetheless aberrant and we therefore have authority to remove it. We 
do not believe that the average hourly wage of this particular hospital 
accurately reflects the economic conditions in its labor market area 
during the FY 2018 cost reporting period. Therefore, its inclusion in 
the wage index would not ensure that the FY 2022 wage index represents 
the labor market area's current wages as compared to the national 
average of wages. Rather, its inclusion would distort the average 
hourly wage of its labor market area. Accordingly, we have exercised 
our discretion to remove this hospital's wage data from the FY 2022 
wage index.
    Furthermore, just as CMS has excluded certain hospitals from the 
wage index with extraordinarily high average hourly wages relative to 
their labor market areas, CMS also has excluded hospitals with 
extraordinarily low average hourly wages relative to their labor market 
areas. An objective comparison of the hospitals included in the FY 2022 
preliminary PUF to the hospitals included in the January and April 2022 
PUFs demonstrates CMS' ``fairness'' in evaluating the appropriateness 
and relativity of the wage data of hospitals with both extraordinarily 
low and extraordinarily high average hourly wages. While some hospitals 
with high extraordinarily high average hourly wages remain excluded 
from the FY 2022 final wage index, some hospitals with extraordinarily 
low average hourly wages also remain excluded from the FY 2022 final 
wage index. Therefore, we disagree with commenters' assertions that we 
have been ``arbitrary and capricious'' and have ``abused'' our 
discretion in excluding hospitals from the wage index.
    We also note that each time a PUF is posted, CMS instructs the MACs 
to send letters to each of their hospitals notifying and instructing 
them to review their wage index data that were just posted. Hospitals 
that review each PUF and observe that they are excluded may then submit 
an April appeal to CMS, and/or contact CMS and the MAC to discuss 
possible ways to revise or verify their data for inclusion in the wage 
index. We believe the established annual wage index timetable grants 
sufficient time for hospitals to review, appeal, and/or correct their 
data. We also welcome State hospital associations to be more proactive 
in the process of urging their constituents to be responsive to the 
MACs' and CMS' requests for documentation and to become more involved 
in resolving issues related to aberrant data. We note that it has never 
been CMS' policy to disclose audit protocol. However, we may consider a 
limited proposal regarding criteria for excluding a hospital's data 
from the wage index due to its overall average hourly wage being either 
too high or too low, as well as utilizing additional methods of 
communicating with stakeholders regarding the adequacy of their wage 
data.
    Finally, we provide an impact of the overall impact of the wage 
index with regard to the IPPS. We do not provide an impact for each 
hospital excluded from the wage data. The cost report data of the 
providers deleted from the wage index is provided with each public use 
file and commenters can conduct an analysis of any change to the wage 
index if we were to restore the data of a hospital deleted from the 
wage index. With regard to the other PPSs, we refer commenters to the 
rulemaking of those PPSs for comments on the wage index and any impact 
analysis.
    Comment: Commenters expressed concern that the wage data collected 
during the PHE will be less reflective of regional wages. Commenters 
suggest CMS consider not using the 2020 and 2021 data to set future 
wage indices. A few commenters stated that additional responsibilities 
on hospital staff that were also due September 2020, such as the 
triennial Occupational Mix Survey, created opportunities for errors 
into the FY 2022 wage indexes.
    Response: FY 2022 uses wage data from 2018 which is not affected by 
the COVID-19 PHE. FYs 2023, 2024 and 2025 would typically use wage data 
from 2020 and 2021 since the wage index is on a four-year lag with 
regard to the data. We will consider comments on the 2020 and 2021 wage 
data in future rulemaking, as applicable.

D. Method for Computing the FY 2022 Unadjusted Wage Index

    As we stated in the proposed rule (86 FR 25400), the method used to 
compute the FY 2022 wage index without an occupational mix adjustment 
follows the same methodology that we used to compute the wage indexes 
without an occupational mix adjustment in the FY 2021 IPPS/LTCH PPS 
final rule (see 85 FR 58758 through 58761, September 18, 2020), and we 
did not propose any changes to this methodology. We have restated our 
methodology in this section of this rule.
    Step 1.--We gathered data from each of the non-Federal, short-term, 
acute care hospitals for which data were reported on the Worksheet S-3, 
Parts II and III of the Medicare cost report for the hospital's cost 
reporting period relevant to the wage index (in this case, for FY 2022, 
these were data from cost reports for cost reporting periods beginning 
on or after October 1, 2017, and before October 1, 2018). In addition, 
we included data from some hospitals that had cost reporting periods 
beginning before October 2017 and reported a cost reporting period 
covering all of FY 2018. These data were included because no other data 
from these hospitals would be available for the cost reporting period 
as previously described, and because particular labor market areas 
might be affected due to the omission of these hospitals. However, we 
generally describe these wage data as FY 2018 data. We note that, if a 
hospital had more than one cost reporting period beginning during FY 
2018 (for example, a hospital had two short cost reporting periods 
beginning on or after October 1, 2017, and before October 1, 2018), we 
include wage data from only one of the cost reporting periods, the 
longer, in the wage index calculation. If there was more than one cost 
reporting period and the periods were equal in length, we included the 
wage data from the later period in the wage index calculation.
    Step 2.--Salaries.--The method used to compute a hospital's average 
hourly wage excludes certain costs that are not paid under the IPPS. 
(We note that, beginning with FY 2008 (72 FR 47315), we included what 
were then Lines 22.01, 26.01, and 27.01 of Worksheet S-3, Part II of 
CMS Form 2552-96 for overhead services in the wage index. Currently, 
these lines are lines 28, 33, and 35 on CMS Form 2552-10. However, we 
note that the wages and hours on these lines are not incorporated into 
Line 101, Column 1 of Worksheet A, which, through the electronic cost 
reporting software, flows

[[Page 45170]]

directly to Line 1 of Worksheet S-3, Part II. Therefore, the first step 
in the wage index calculation is to compute a ``revised'' Line 1, by 
adding to the Line 1 on Worksheet S-3, Part II (for wages and hours 
respectively) the amounts on Lines 28, 33, and 35.) In calculating a 
hospital's Net Salaries (we note that we previously used the term 
``average'' salaries in the FY 2012 IPPS/LTCH PPS final rule (76 FR 
51592), but we now use the term ``net'' salaries) plus wage-related 
costs, we first compute the following: Subtract from Line 1 (total 
salaries) the GME and CRNA costs reported on CMS Form 2552-10, Lines 2, 
4.01, 7, and 7.01, the Part B salaries reported on Lines 3, 5 and 6, 
home office salaries reported on Line 8, and exclude salaries reported 
on Lines 9 and 10 (that is, direct salaries attributable to SNF 
services, home health services, and other subprovider components not 
subject to the IPPS). We also subtract from Line 1 the salaries for 
which no hours were reported. Therefore, the formula for Net Salaries 
(from Worksheet S-3, Part II) is the following:

((Line 1 + Line 28 + Line 33 + Line 35)-(Line 2 + Line 3 + Line 4.01 + 
Line 5 + Line 6 + Line 7 + Line 7.01 + Line 8 + Line 9 + Line 10)).

    To determine Total Salaries plus Wage-Related Costs, we add to the 
Net Salaries the costs of contract labor for direct patient care, 
certain top management, pharmacy, laboratory, and nonteaching physician 
Part A services (Lines 11, 12 and 13), home office salaries and wage-
related costs reported by the hospital on Lines 14.01, 14.02, and 15, 
and nonexcluded area wage-related costs (Lines 17, 22, 25.50, 25.51, 
and 25.52). We note that contract labor and home office salaries for 
which no corresponding hours are reported are not included. In 
addition, wage-related costs for nonteaching physician Part A employees 
(Line 22) are excluded if no corresponding salaries are reported for 
those employees on Line 4. The formula for Total Salaries plus Wage-
Related Costs (from Worksheet S-3, Part II) is the following: ((Line 1 
+ Line 28 + Line 33 + Line 35)-(Line 2 + Line 3 + Line 4.01 + Line 5 + 
Line 6 + Line 7 + Line 7.01 + Line 8 + Line 9 + Line 10)) + (Line 11 + 
Line 12 + Line 13 + Line 14.01 + 14.02 + Line 15) + (Line 17 + Line 22 
+ 25.50 + 25.51 + 25.52).
    Step 3.--Hours.--With the exception of wage-related costs, for 
which there are no associated hours, we compute total hours using the 
same methods as described for salaries in Step 2. The formula for Total 
Hours (from Worksheet S-3, Part II) is the following:

((Line 1 + Line 28 + Line 33 + Line 35)-(Line 2 + Line 3 + Line 4.01 + 
Line 5 + Line 6 + Line 7 + Line 7.01 + Line 8 + Line 9 + Line 10)) + 
(Line 11 + Line 12 + Line 13 + Line 14.01 + 14.02 + Line 15).

    Step 4.--For each hospital reporting both total overhead salaries 
and total overhead hours greater than zero, we then allocate overhead 
costs to areas of the hospital excluded from the wage index 
calculation. First, we determine the ``excluded rate'', which is the 
ratio of excluded area hours to Revised Total Hours (from Worksheet S-
3, Part II) with the following formula: (Line 9 + Line 10)/(Line 1 + 
Line 28 + Line 33 + Line 35)-(Lines 2, 3, 4.01, 5, 6, 7, 7.01, and 8 
and Lines 26 through 43). We then compute the amounts of overhead 
salaries and hours to be allocated to the excluded areas by 
multiplying, the previously discussed ratio, by the total overhead 
salaries and hours reported on Lines 26 through 43 of Worksheet S-3, 
Part II. Next, we compute the amounts of overhead wage-related costs to 
be allocated to the excluded areas using three steps:
     We determine the ``overhead rate'' (from Worksheet S-3, 
Part II), which is the ratio of overhead hours (Lines 26 through 43 
minus the sum of Lines 28, 33, and 35) to revised hours excluding the 
sum of lines 28, 33, and 35 (Line 1 minus the sum of Lines 2, 3, 4.01, 
5, 6, 7, 7.01, 8, 9, 10, 28, 33, and 35). We note that, for the FY 2008 
and subsequent wage index calculations, we have been excluding the 
overhead contract labor (Lines 28, 33, and 35) from the determination 
of the ratio of overhead hours to revised hours because hospitals 
typically do not provide fringe benefits (wage-related costs) to 
contract personnel. Therefore, it is not necessary for the wage index 
calculation to exclude overhead wage-related costs for contract 
personnel. Further, if a hospital does contribute to wage-related costs 
for contracted personnel, the instructions for Lines 28, 33, and 35 
require that associated wage-related costs be combined with wages on 
the respective contract labor lines. The formula for the Overhead Rate 
(from Worksheet S-3, Part II) is the following: (Lines 26 through 43-
Lines 28, 33 and 35)/((((Line 1 + Lines 28, 33, 35)-(Lines 2, 3, 4.01, 
5, 6, 7, 7.01, 8, and 26 through 43))-(Lines 9 and 10)) + (Lines 26 
through 43-Lines 28, 33, and 35)).
     We compute overhead wage-related costs by multiplying the 
overhead hours ratio by wage-related costs reported on Part II, Lines 
17, 22, 25.50, 25.51, and 25.52.
     We multiply the computed overhead wage-related costs by 
the previously described excluded area hours ratio.
    Finally, we subtract the computed overhead salaries, wage-related 
costs, and hours associated with excluded areas from the total salaries 
(plus wage-related costs) and hours derived in Steps 2 and 3.
    Step 5.--For each hospital, we adjust the total salaries plus wage-
related costs to a common period to determine total adjusted salaries 
plus wage-related costs. To make the wage adjustment, we estimate the 
percentage change in the employment cost index (ECI) for compensation 
for each 30-day increment from October 14, 2017 through April 15, 2019, 
for private industry hospital workers from the BLS' Compensation and 
Working Conditions. We use the ECI because it reflects the price 
increase associated with total compensation (salaries plus fringes) 
rather than just the increase in salaries. In addition, the ECI 
includes managers as well as other hospital workers. This methodology 
to compute the monthly update factors uses actual quarterly ECI data 
and assures that the update factors match the actual quarterly and 
annual percent changes. We also note that, since April 2006 with the 
publication of March 2006 data, the BLS' ECI uses a different 
classification system, the North American Industrial Classification 
System (NAICS), instead of the Standard Industrial Codes (SICs), which 
no longer exist. We have consistently used the ECI as the data source 
for our wages and salaries and other price proxies in the IPPS market 
basket, and we did not propose to make any changes to the usage of the 
ECI for FY 2022. The factors used to adjust the hospital's data are 
based on the midpoint of the cost reporting period, as indicated in 
this rule.
    Step 6.--Each hospital is assigned to its appropriate urban or 
rural labor market area before any reclassifications under section 
1886(d)(8)(B), 1886(d)(8)(E), or 1886(d)(10) of the Act. Within each 
urban or rural labor market area, we add the total adjusted salaries 
plus wage-related costs obtained in Step 5 for all hospitals in that 
area to determine the total adjusted salaries plus wage-related costs 
for the labor market area.
    Step 7.--We divide the total adjusted salaries plus wage-related 
costs obtained under Step 6 by the sum of the corresponding total hours 
(from Step 4) for all hospitals in each labor market area to determine 
an average hourly wage for the area.

[[Page 45171]]

    Step 8.--We add the total adjusted salaries plus wage-related costs 
obtained in Step 5 for all hospitals in the Nation and then divide the 
sum by the national sum of total hours from Step 4 to arrive at a 
national average hourly wage.
    Step 9.--For each urban or rural labor market area, we calculate 
the hospital wage index value, unadjusted for occupational mix, by 
dividing the area average hourly wage obtained in Step 7 by the 
national average hourly wage computed in Step 8.
    Step 10.--For each urban labor market area for which we do not have 
any hospital wage data (either because there are no IPPS hospitals in 
that labor market area, or there are IPPS hospitals in that area but 
their data are either too new to be reflected in the current year's 
wage index calculation, or their data are aberrant and are deleted from 
the wage index), we finalized in the FY 2020 IPPS/LTCH PPS final rule 
(84 FR 42305) that, for FY 2020 and subsequent years' wage index 
calculations, such CBSA's wage index would be equal to total urban 
salaries plus wage-related costs (from Step 5) in the State, divided by 
the total urban hours (from Step 4) in the State, divided by the 
national average hourly wage from Step 8 (see 84 FR 42305 and 42306) 
August 16, 2019). We stated that we believe that, in the absence of 
wage data for an urban labor market area, it is reasonable to use a 
statewide urban average, which is based on actual, acceptable wage data 
of hospitals in that State, rather than impute some other type of value 
using a different methodology. For calculation of the FY 2022 wage 
index, we note there is one urban CBSA for which we do not have IPPS 
hospital wage data. In Table 3 (which is available via the internet on 
the CMS website) which contains the area wage indexes, we include a 
footnote to indicate to which CBSAs this policy applies. These CBSAs' 
wage indexes would be equal to total urban salaries plus wage-related 
costs (from Step 5) in the respective State, divided by the total urban 
hours (from Step 4) in the respective State, divided by the national 
average hourly wage (from Step 8) (see 84 FR 42305 and 42306) August 
16, 2019). Under this step, we also apply our policy with regard to how 
dollar amounts, hours, and other numerical values in the wage index 
calculations are rounded, as discussed in this section of this rule.
    We refer readers to section II. of the Appendix of the final rule 
for the policy regarding rural areas that do not have IPPS hospitals.
    Step 11.--Section 4410 of Public Law 105-33 provides that, for 
discharges on or after October 1, 1997, the area wage index applicable 
to any hospital that is located in an urban area of a State may not be 
less than the area wage index applicable to hospitals located in rural 
areas in that State. The areas affected by this provision are 
identified in Table 2 listed in section VI. of the Addendum to the 
final rule and available via the internet on the CMS website.
    Following is our policy with regard to rounding of the wage data 
(dollar amounts, hours, and other numerical values) in the calculation 
of the unadjusted and adjusted wage index, as finalized in the FY 2020 
IPPS/LTCH final rule (84 FR 42306; August 16, 2019). For data that we 
consider to be ``raw data,'' such as the cost report data on Worksheets 
S-3, Parts II and III, and the occupational mix survey data, we use 
such data ``as is,'' and do not round any of the individual line items 
or fields. However, for any dollar amounts within the wage index 
calculations, including any type of summed wage amount, average hourly 
wages, and the national average hourly wage (both the unadjusted and 
adjusted for occupational mix), we round the dollar amounts to 2 
decimals. For any hour amounts within the wage index calculations, we 
round such hour amounts to the nearest whole number. For any numbers 
not expressed as dollars or hours within the wage index calculations, 
which could include ratios, percentages, or inflation factors, we round 
such numbers to 5 decimals. However, we continue rounding the actual 
unadjusted and adjusted wage indexes to 4 decimals, as we have done 
historically.
    As discussed in the FY 2012 IPPS/LTCH PPS final rule, in ``Step 
5,'' for each hospital, we adjust the total salaries plus wage-related 
costs to a common period to determine total adjusted salaries plus 
wage-related costs. To make the wage adjustment, we estimate the 
percentage change in the employment cost index (ECI) for compensation 
for each 30-day increment from October 14, 2017, through April 15, 
2019, for private industry hospital workers from the BLS' Compensation 
and Working Conditions. We have consistently used the ECI as the data 
source for our wages and salaries and other price proxies in the IPPS 
market basket, and we did not propose any changes to the usage of the 
ECI for FY 2022. The factors used to adjust the hospital's data were 
based on the midpoint of the cost reporting period, as indicated in the 
following table.

[[Page 45172]]

[GRAPHIC] [TIFF OMITTED] TR13AU21.229

    For example, the midpoint of a cost reporting period beginning 
January 1, 2018, and ending December 31, 2018, is June 30, 2018. An 
adjustment factor of 1.01780 was applied to the wages of a hospital 
with such a cost reporting period.
    Previously, we also would provide a Puerto Rico overall average 
hourly wage. As discussed in the FY 2017 IPPS/LTCH PPS final rule (81 
FR 56915), prior to January 1, 2017, Puerto Rico hospitals were paid 
based on 75 percent of the national standardized amount and 25 percent 
of the Puerto Rico-specific standardized amount. As a result, we 
calculated a Puerto Rico specific wage index that was applied to the 
labor-related share of the Puerto Rico-specific standardized amount. 
Section 601 of the Consolidated Appropriations Act, 2016 (Pub. L. 114-
113) amended section 1886(d)(9)(E) of the Act to specify that the 
payment calculation with respect to operating costs of inpatient 
hospital services of a subsection (d) Puerto Rico hospital for 
inpatient hospital discharges on or after January 1, 2016, shall use 
100 percent of the national standardized amount. As we stated in the FY 
2017 IPPS/LTCH PPS final rule (81 FR 56915 through 56916), because 
Puerto Rico hospitals are no longer paid with a Puerto Rico specific 
standardized amount as of January 1, 2016, under section 1886(d)(9)(E) 
of the Act, as amended by section 601 of the Consolidated 
Appropriations Act, 2016, there is no longer a need to calculate a 
Puerto Rico specific average hourly wage and wage index. Hospitals in 
Puerto Rico are now paid 100 percent of the national standardized 
amount and, therefore, are subject to the national average hourly wage 
(unadjusted for occupational mix) and the national wage index, which is 
applied to the national labor-related share of the national 
standardized amount. Therefore, for FY 2022, there is no Puerto Rico-
specific overall average hourly wage or wage index.
    Based on the methodology, as previously discussed, we stated in the 
proposed rule (86 FR 25402) that the proposed FY 2022 unadjusted 
national average hourly wage was $46.42.
    We did not receive any comments regarding the discussion of our 
method for computing the FY 2022 unadjusted wage index. Based on the 
previously described methodology, the final FY 2022 unadjusted national 
average hourly wage is the following:
[GRAPHIC] [TIFF OMITTED] TR13AU21.230

E. Occupational Mix Adjustment to the FY 2022 Wage Index

    As stated earlier, section 1886(d)(3)(E) of the Act provides for 
the collection of data every 3 years on the occupational mix of 
employees for each short-term, acute care hospital participating in the 
Medicare program, in order to construct an occupational mix adjustment 
to the wage index, for application beginning October 1, 2004 (the FY 
2005 wage index). The purpose of the occupational mix adjustment is to 
control for the effect of hospitals' employment choices on the wage 
index. For example, hospitals may choose to employ different 
combinations of registered nurses, licensed practical nurses, nursing 
aides, and medical assistants for the purpose of providing nursing care 
to their patients. The varying labor costs associated with these 
choices reflect hospital management decisions rather

[[Page 45173]]

than geographic differences in the costs of labor.
1. Use of 2019 Medicare Wage Index Occupational Mix Survey for the FY 
2022 Wage Index
    Section 304(c) of the Consolidated Appropriations Act, 2001 (Pub. 
L. 106- 554) amended section 1886(d)(3)(E) of the Act to require CMS to 
collect data every 3 years on the occupational mix of employees for 
each short-term, acute care hospital participating in the Medicare 
program. As discussed in the FY 2018 IPPS/LTCH PPS proposed rule (82 FR 
19903) and final rule (82 FR 38137), we collected data in 2016 to 
compute the occupational mix adjustment for the FY 2019, FY 2020, and 
FY 2021 wage indexes. A new measurement of occupational mix is required 
for FY 2022.
    The FY 2022 occupational mix adjustment is based on a new calendar 
year (CY) 2019 survey. Hospitals were required to submit their 
completed 2019 surveys (Form CMS-10079, OMB number 0938-0907, 
expiration date September 31, 2022) to their MACs by September 3, 2020. 
The preliminary, unaudited CY 2019 survey data were posted on the CMS 
website on September 8, 2020. As with the Worksheet S-3, Parts II and 
III cost report wage data, as part of the FY 2022 desk review process, 
the MACs revised or verified data elements in hospitals' occupational 
mix surveys that resulted in certain edit failures.
2. Calculation of the Occupational Mix Adjustment for FY 2022
    In the FY 2022 IPPS/LTCH PPS proposed rule (86 FR 25403), for FY 
2022, we proposed to calculate the occupational mix adjustment factor 
using the same methodology that we have used since the FY 2012 wage 
index (76 FR 51582 through 51586) and to apply the occupational mix 
adjustment to 100 percent of the FY 2022 wage index. In the FY 2020 
IPPS/LTCH PPS final rule (84 FR 42308), we modified our methodology 
with regard to how dollar amounts, hours, and other numerical values in 
the unadjusted and adjusted wage index calculation are rounded, in 
order to ensure consistency in the calculation. According to the policy 
finalized in the FY 2020 IPPS/LTCH PPS final rule (84 FR 42308 and 
42309), for data that we consider to be ``raw data,'' such as the cost 
report data on Worksheets S-3, Parts II and III, and the occupational 
mix survey data, we continue to use these data ``as is'', and not round 
any of the individual line items or fields. However, for any dollar 
amounts within the wage index calculations, including any type of 
summed wage amount, average hourly wages, and the national average 
hourly wage (both the unadjusted and adjusted for occupational mix), we 
round such dollar amounts to 2 decimals. We round any hour amounts 
within the wage index calculations to the nearest whole number. We 
round any numbers not expressed as dollars or hours in the wage index 
calculations, which could include ratios, percentages, or inflation 
factors, to 5 decimals. However, we continue rounding the actual 
unadjusted and adjusted wage indexes to 4 decimals, as we have done 
historically.
    Similar to the method we use for the calculation of the wage index 
without occupational mix, salaries and hours for a multicampus hospital 
are allotted among the different labor market areas where its campuses 
are located. Table 2 associated with this final rule (which is 
available via the internet on the CMS website), which contains the 
final FY 2022 occupational mix adjusted wage index, includes separate 
wage data for the campuses of multicampus hospitals. We refer readers 
to section III.C. of the preamble of this final rule for a chart 
listing the multicampus hospitals and the FTE percentages used to allot 
their occupational mix data.
    Because the statute requires that the Secretary measure the 
earnings and paid hours of employment by occupational category not less 
than once every 3 years, all hospitals that are subject to payments 
under the IPPS, or any hospital that would be subject to the IPPS if 
not granted a waiver, must complete the occupational mix survey, unless 
the hospital has no associated cost report wage data that are included 
in the FY 2022 wage index. For the proposed FY 2022 wage index, we used 
the Worksheet S-3, Parts II and III wage data of 3,159 hospitals, and 
we used the occupational mix surveys of 2,955 hospitals for which we 
also had Worksheet S-3 wage data, which represented a ``response'' rate 
of 94 percent (2,955/3,159). For the proposed FY 2022 wage index, we 
applied proxy data for noncompliant hospitals, new hospitals, or 
hospitals that submitted erroneous or aberrant data in the same manner 
that we applied proxy data for such hospitals in the FY 2012 wage index 
occupational mix adjustment (76 FR 51586). As a result of applying this 
methodology, the proposed FY 2022 occupational mix adjusted national 
average hourly wage was $46.37.
    We did not receive any comments on our proposed calculation of the 
occupational mix adjustment to the FY 2022 wage index. Thus, for the 
reasons discussed in this final rule and in the FY 2022 IPPS/LTCH PPS 
proposed rule, we are finalizing our proposal, without modification to 
calculate the occupational mix adjustment factor using the same 
methodology that we have used since the FY 2012 wage index and to apply 
the occupational mix adjustment to 100 percent of the FY 2022 wage 
index.
    For the final FY 2022 wage index, we are using the Worksheet S3, 
Parts II and III wage data of 3,182 hospitals, and we are using the 
occupational mix surveys of 3,028 hospitals for which we also have 
Worksheet S-3 wage data, which is a ``response'' rate of 95 percent 
(3,028/3,182). For the final FY 2022 wage index, we are applying proxy 
data for noncompliant hospitals, new hospitals, or hospitals that 
submitted erroneous or aberrant data in the same manner that we applied 
proxy data for such hospitals in the FY 2012 wage index occupational 
mix adjustment (76 FR 51586). As a result of applying this methodology, 
the final FY 2022 occupational mix adjusted national average hourly 
wage is the following:
[GRAPHIC] [TIFF OMITTED] TR13AU21.231


[[Page 45174]]



F. Analysis and Implementation of the Occupational Mix Adjustment and 
the FY 2022 Occupational Mix Adjusted Wage Index

    As discussed in section III.E. of the preamble of this final rule, 
for FY 2022, we are applying the occupational mix adjustment to 100 
percent of the FY 2022 wage index. We calculated the occupational mix 
adjustment using data from the 2019 occupational mix survey data, using 
the methodology described in the FY 2012 IPPS/LTCH PPS final rule (76 
FR 51582 through 51586).
    The FY 2022 national average hourly wages for each occupational mix 
nursing subcategory as calculated in Step 2 of the occupational mix 
calculation are as follows:
[GRAPHIC] [TIFF OMITTED] TR13AU21.232

The national average hourly wage for the entire nurse category is 
computed in Step 5 of the occupational mix calculation. Hospitals with 
a nurse category average hourly wage (as calculated in Step 4) of 
greater than the national nurse category average hourly wage receive an 
occupational mix adjustment factor (as calculated in Step 6) of less 
than 1.0. Hospitals with a nurse category average hourly wage (as 
calculated in Step 4) of less than the national nurse category average 
hourly wage receive an occupational mix adjustment factor (as 
calculated in Step 6) of greater than 1.0.
    Based on the 2019 occupational mix survey data, we determined (in 
Step 7 of the occupational mix calculation) the following:
[GRAPHIC] [TIFF OMITTED] TR13AU21.233

    We compared the FY 2022 occupational mix adjusted wage indexes for 
each CBSA to the unadjusted wage indexes for each CBSA. Applying the 
occupational mix adjustment to the wage data resulted in the following:
[GRAPHIC] [TIFF OMITTED] TR13AU21.234

    These results indicate that a smaller percentage of urban areas 
(53.6 percent) would benefit from the occupational mix adjustment than 
would rural areas (57.4 percent).

[[Page 45175]]

    We also compared the FY 2022 wage data adjusted for occupational 
mix from the 2019 survey to the FY 2022 wage data adjusted for 
occupational mix from the 2016 survey. This analysis illustrates the 
effect on area wage indexes of using the 2019 survey data compared to 
the 2016 survey data; that is, it shows whether hospitals' wage indexes 
will increase or decrease under the 2019 survey data as compared to the 
prior 2016 survey data. Applying the occupational mix adjustment to the 
wage data, based on the 2019 survey, resulted in the following:
[GRAPHIC] [TIFF OMITTED] TR13AU21.235

BILLING CODE 4120-01-C
    These results indicate that the wage indexes of 52.9 percent of 
CBSAs overall will decrease due to application of the 2019 occupational 
mix survey data as compared to the 2016 occupational mix survey data. 
Further, a larger percentage of urban areas (48.1 percent) will benefit 
from the use of the 2019 occupational mix survey data as compared to 
the 2016 occupational mix survey data than will rural areas (38.3 
percent).

G. Application of the Rural Floor, Application of the State Frontier 
Floor, Continuation of the Low Wage Index Hospital Policy, and Budget 
Neutrality Adjustment

1. Rural Floor
    Section 4410(a) of Public Law 105-33 provides that, for discharges 
on or after October 1, 1997, the area wage index applicable to any 
hospital that is located in an urban area of a State may not be less 
than the area wage index applicable to hospitals located in rural areas 
in that State. This provision is referred to as the rural floor. 
Section 3141 of Public Law 111-148 also requires that a national budget 
neutrality adjustment be applied in implementing the rural floor.
    In the FY 2020 IPPS/LTCH PPS final rule (84 FR 42332 through 
42336), we removed urban to rural reclassifications from the 
calculation of the rural floor to prevent inappropriate payment 
increases under the rural floor due to rural reclassifications, such 
that, beginning in FY 2020, the rural floor is calculated without 
including the wage data of hospitals that have reclassified as rural 
under section 1886(d)(8)(E) of the Act (as implemented in the 
regulations at Sec.  412.103). The rural floor for this FY 2022 
proposed rule continues to be calculated without the wage data of 
hospitals that have reclassified as rural under Sec.  412.103. We did 
not propose any changes to the rural floor policy for FY 2022. Also, 
for the purposes of applying the provisions of section 
1886(d)(8)(C)(iii) of the Act, effective beginning in FY 2020, we 
remove the data of hospitals reclassified from urban to rural under 
section 1886(d)(8)(E) of the Act (as implemented in the regulations at 
Sec.  412.103) from the calculation of ``the wage index for rural areas 
in the State in which the county is located'' as referred to in section 
1886(d)(8)(C)(iii) of the Act. We did not propose any changes to this 
policy for FY 2022.
    Based on the FY 2022 wage index associated with this final rule 
(which is available via the internet on the CMS website) and based on 
the calculation of the rural floor without the wage data of hospitals 
that have reclassified as rural under Sec.  412.103, we estimate that 
269 hospitals would receive an increase in their FY 2022 wage index due 
to the application of the rural floor.
    Comment: Some commenters expressed their support for the 
application of the rural floor policy which included support for the 
continued exclusion of the wage data of hospitals that have 
reclassified as rural under Sec.  412.103 when calculating the wage 
index for the rural floor.
    Response: We appreciate the commenters' support for the application 
of the rural floor policy.
    Comment: A commenter urged CMS to treat hospitals that classify as 
rural per the MGCRB, as rural for all instances including the rural 
floor calculation.
    Response: We thank the commenter for their comment about the MGCRB 
as it relates to the rural floor calculation. According to current 
policy, hospitals that classify as rural per the MGCRB, may be included 
in the rural floor calculation.
    Comment: Some commenters opposed the continued application of a 
nationwide rural floor budget neutrality adjustment, noting that the 
policy does nothing more than benefit a few hospitals and exacerbate a 
downward spiral of the wage index for low-wage-index hospitals.
    Response: We appreciate the commenters' concerns about application 
of the nationwide rural floor budget neutrality policy. However, as 
stated in the FY 2017 IPPS/LTCH PPS final rule (81 FR 56920), for 
discharges occurring on or after October 1, 2010, for purposes of 
applying the rural floor, section 3141 of the Affordable Care Act 
replaced the statewide budget neutrality adjustment policy with the 
national budget neutrality adjustment policy that was in

[[Page 45176]]

place during FY 2008. That is, section 3141 required that budget 
neutrality for the rural floor be applied ``through a uniform, national 
adjustment to the area wage index'' instead of within each State 
beginning in FY 2011 (75 FR 50160). Accordingly, we do not have the 
authority to calculate rural floor budget neutrality in a State-
specific manner.
2. Imputed Floor
    In the FY 2005 IPPS final rule (69 FR 49109 through 49111), we 
adopted the imputed floor policy as a temporary 3-year regulatory 
measure to address concerns from hospitals in all-urban States that 
have argued that they are disadvantaged by the absence of rural 
hospitals to set a wage index floor for those States. We extended the 
imputed floor policy eight times since its initial implementation, the 
last of which was adopted in the FY 2018 IPPS/LTCH PPS final rule and 
expired on September 30, 2018. (We refer readers to further discussions 
of the imputed floor in the IPPS/LTCH PPS final rules from FYs 2014 
through 2019 (78 FR 50589 through 50590, 79 FR 49969 through 49971, 80 
FR 49497 through 49498, 81 FR 56921 through 56922, 82 FR 38138 through 
38142, and 83 FR 41376 through 41380, respectively) and to the 
regulations at 42 CFR 412.64(h)(4).) For FYs 2019, 2020, and 2021, 
hospitals in all-urban states received a wage index that was calculated 
without applying an imputed floor, and we no longer included the 
imputed floor as a factor in the national budget neutrality adjustment.
    In computing the imputed floor for an all-urban State under the 
original methodology established beginning in FY 2005, we calculated 
the ratio of the lowest-to-highest CBSA wage index for each all-urban 
State as well as the average of the ratios of lowest-to-highest CBSA 
wage indexes of those all-urban States. We then compared the State's 
own ratio to the average ratio for all-urban States and whichever was 
higher was multiplied by the highest CBSA wage index value in the 
State--the product of which established the imputed floor for the 
State.
    We adopted a second, alternative methodology beginning in FY 2013 
(77 FR 53368 through 53369) to address the concern that the original 
imputed floor methodology guaranteed a benefit for one all-urban State 
with multiple wage indexes (New Jersey) but could not benefit another 
all-urban State, Rhode Island, which had only one CBSA. Under the 
alternative methodology, we first determined the average percentage 
difference between the post-reclassified, pre-floor area wage index and 
the post-reclassified, rural floor wage index (without rural floor 
budget neutrality applied) for all CBSAs receiving the rural floor. The 
lowest post-reclassified wage index assigned to a hospital in an all-
urban State having a range of such values then was increased by this 
factor, the result of which established the State's alternative imputed 
floor. Under the updated OMB labor market area delineations adopted by 
CMS beginning in FY 2015, Delaware became an all-urban State, along 
with New Jersey and Rhode Island, and was subject to an imputed floor 
as well. In addition, we adopted a policy, as reflected at Sec.  
412.64(h)(4)(vi), that, for discharges on or after October 1, 2012, and 
before October 1, 2018, the minimum wage index value for a State is the 
higher of the value determined under the original methodology or the 
value determined under the alternative methodology. The regulations 
implementing the imputed floor wage index, both the original 
methodology and the alternative methodology, were set forth at Sec.  
412.64(h)(4).
    Section 9831 of the American Rescue Plan Act of 2021 (Pub. L. 117-
2) enacted on March 11, 2021, amended section 1886(d)(3)(E)(i) of the 
Act (42 U.S.C. 1395ww(d)(3)(E)(i)) and added section 1886(d)(3)(E)(iv) 
of the Act to establish a minimum area wage index for hospitals in all-
urban States for discharges occurring on or after October 1, 2021. 
Specifically, section 1886(d)(3)(E)(iv)(I) and (II) of the Act provides 
that for discharges occurring on or after October 1, 2021, the area 
wage index applicable to any hospital in an all-urban State may not be 
less than the minimum area wage index for the fiscal year for hospitals 
in that State established using the methodology described in Sec.  
412.64(h)(4)(vi) as in effect for FY 2018. Thus, effective beginning 
October 1, 2021 (FY 2022), section 1886(d)(3)(E)(iv) of the Act 
reinstates the imputed floor wage index policy for all-urban States, 
with no expiration date, using the methodology described in 42 CFR 
412.64(h)(4)(vi) as in effect for FY 2018. As discussed previously, 
under Sec.  412.64(h)(4)(vi), the minimum wage index value for 
hospitals in an all-urban State is the higher of the value determined 
using the original methodology (as set forth at Sec.  412.64(h)(4)(i) 
through (v)) or the value determined using alternative methodology (as 
set forth at Sec.  412.64(h)(4)(vi)(A) and (B)) for calculating an 
imputed floor. Therefore, as provided in Sec.  412.64(h)(vi), we would 
apply the higher of the value determined under the original or 
alternative methodology for calculating a minimum wage index, or 
imputed floor, for all-urban States effective beginning with FY 2022. 
We note that the rural floor values used in the alternative methodology 
at Sec.  412.64(h)(4)(vi)(A) and (B) would not include the wage data of 
hospitals reclassified under Sec.  412.103, because we currently 
calculate the rural floor without the wage data of such hospitals.
    Unlike the imputed floor that was in effect from FYs 2005 through 
2018, section 1886(d)(3)(E)(iv)(III) of the Act provides that the 
imputed floor wage index shall not be applied in a budget neutral 
manner. Specifically, section 9831(b) of Public Law 117-2 amends 
section 1886(d)(3)(E)(i) of the Act to exclude the imputed floor from 
the budget neutrality requirement under section 1886(d)(3)(E)(i) of the 
Act. In other words, the budget neutrality requirement under section 
1886(d)(3)(E)(i) of the Act, as amended, must be applied without taking 
into account the imputed floor adjustment under section 
1886(d)(3)(E)(iv) of the Act. When the imputed floor was in effect from 
FY 2005 through FY 2018, to budget neutralize the increase in payments 
resulting from application of the imputed floor, we calculated the 
increase in payments resulting from the imputed floor together with the 
increase in payments resulting from the rural floor and applied an 
adjustment to reduce the wage index. By contrast, for FY 2022 and 
subsequent years, we proposed to apply the imputed floor after the 
application of the rural floor and to apply no reductions to the 
standardized amount or to the wage index to fund the increase in 
payments to hospitals in all-urban States resulting from the 
application of the imputed floor required under section 
1886(d)(3)(E)(iv) of the Act.
    We note, given the recent enactment of section 9831 of Public Law 
117-2 on March 11, 2021, there was not sufficient time available to 
incorporate the changes required by this statutory provision (which 
provides for the application of the imputed floor adjustment in a non-
budget neutral manner beginning in FY 2022) into the calculation of the 
provider wage index for the proposed rule. We will include the imputed 
floor adjustment in the calculation of the provider wage index in the 
FY 2022 final rule. We note that CMS has posted, concurrent with the 
issuance of the proposed rule, estimated imputed floor values by state 
in a separate data file on the FY 2022 IPPS Proposed Rule web page on 
the CMS website at https://www.cms.gov/Medicare/Medicare-Fee-for-
Service-

[[Page 45177]]

Payment/AcuteInpatientPPS/index, and an aggregate payment impact for 
the imputed floor in the Appendix to the proposed rule.
    The imputed floor under section 1886(d)(3)(E)(iv) of the Act 
applies to all-urban States, as defined in new subclause (IV). Section 
1886(d)(3)(E)(iv)(IV) provides that, for purposes of the imputed floor 
wage index under clause (iv), the term all-urban State means a State in 
which there are no rural areas (as defined in section 1886(d)(2)(D) of 
the Act) or a State in which there are no hospitals classified as rural 
under section 1886 of the Act. Under this definition, given that it 
applies for purposes of the imputed floor wage index, we believe it 
would be appropriate to consider a hospital to be classified as rural 
under section 1886 of the Act if it is assigned the State's rural area 
wage index value. Therefore, under the definition at section 
1886(d)(3)(E)(iv)(IV) of the Act, ``a State in which there are no 
hospitals classified as rural under this section'' would include a 
State that has a rural area but no hospitals that receive the rural 
area wage index under section 1886(d) of the Act. For purposes of this 
definition, hospitals redesignated as rural under section 1886(d)(8)(E) 
of the Act (412.103 rural reclassifications) would be considered 
classified as rural if they receive the rural wage index; however, 
hospitals that are deemed urban under section 1886(d)(8)(B) of the Act 
(in Lugar counties), or are reclassified to an urban area under section 
1886(d)(10) of the Act (MGCRB reclassifications) would not be 
considered classified as rural because they do not receive the rural 
wage index. In contrast, we note that in the imputed floor policy in 
effect from FY 2005 through FY 2018, we did not consider a State to 
qualify for ``all urban status'' if there were one or more hospitals 
geographically located in the rural area of the State, even if all such 
hospitals subsequently reclassified to receive an urban area wage 
index. There is currently one State, Connecticut, that would be 
eligible for the imputed floor under this aspect of the proposed rule 
because there are currently no hospitals in Connecticut that are 
classified as rural under section 1886(d) for purposes of the wage 
index--in other words, there are no hospitals that receive the rural 
wage index.
    There is currently one rural county in Connecticut. All hospitals 
in this county are either deemed urban under section 1886(d)(8)(B) of 
the Act or receive an MGCRB reclassification under section 1886(d)(10) 
of the Act. While several Connecticut hospitals were approved for rural 
reclassification under section 1886(d)(8)(E) of the Act, at this point 
all have received a subsequent urban reclassification under section 
1886(d)(10) of the Act.
    Additionally, under section 1861(x) of the Act, the term State has 
the meaning given to it in section 210(h) of the Act. Because section 
210(h) of the Act defines the word State to also include the District 
of Columbia and the Commonwealth of Puerto Rico, Washington, DC and 
Puerto Rico may also qualify as all-urban States for purposes of the 
imputed floor if the requirements of section 1886(d)(3)(E)(iv)(IV) of 
the Act are met. Based on data available for the proposed rule, the 
following States would be all-urban States as defined in section 
1886(d)(3)(E)(iv)(IV) of the Act, and thus hospitals in such States 
would be eligible to receive an increase in their wage index due to 
application of the imputed floor for FY 2022: New Jersey, Rhode Island, 
Delaware, Connecticut, and Washington, DC.
    We proposed to revise the regulations at Sec.  412.64(e)(1) and (4) 
and (h)(4) and (5) to implement the imputed floor required by section 
1886(d)(3)(E)(iv) of the Act for discharges occurring on or after 
October 1, 2021. First, we proposed to make the following revisions to 
the regulation text to specify that the imputed floor required under 
section 1886(d)(3)(E)(iv) of the Act would not be applied in a budget 
neutral manner:
     We proposed to revise the introductory language at Sec.  
412.64(e)(4) to state that the budget neutrality adjustment for the 
imputed floor under paragraph (h)(4) applies only to discharges on or 
after October 1, 2004 and before October 1, 2018.
     We proposed a conforming revision to Sec.  
412.64(e)(1)(ii) to refer to Sec.  412.64(h)(4)(vii) (proposed in the 
proposed rule) in the introductory phrase that excepts certain 
provisions from the budget neutrality requirement specified in 
paragraph (e)(1)(ii).
     We proposed to revise Sec.  412.64(h)(4) to add a new 
clause (vii) stating that, for discharges on or after October 1, 2021, 
the minimum wage index computed under this paragraph may not be applied 
in a budget neutral manner.
    In addition, we proposed to revise the introductory language at 
Sec.  412.64(h)(4) to specify that the minimum wage index and 
methodology described in that paragraph also apply for discharges on or 
after October 1, 2021. Further, we proposed to revise Sec.  
412.64(h)(4)(vi) to specify that this clause also applies to discharges 
on or after October 1, 2021.
    Finally, we proposed to make the following revisions to Sec.  
412.64(h)(5). First, we proposed to redesignate the current language at 
Sec.  412.64(h)(5) as Sec.  412.64(h)(5)(i) and to revise this language 
to reflect that it applies for purposes of applying the imputed floor 
for discharges on or after October 1, 2004 and before October 1, 2018. 
Second, we proposed to add a new clause (ii) to Sec.  412.64(h)(5) to 
reflect the proposed definition of all-urban State for purposes of 
applying the imputed floor for discharges on or after October 1, 2021, 
as previously discussed. Specifically, we proposed at Sec.  
412.64(h)(5)(ii) that, for purposes of applying the imputed floor for 
discharges on or after October 1, 2021, an all-urban State is a State 
with no rural areas, as defined in Sec.  412.64, or a State in which 
there are no hospitals classified as rural under section 1886 of the 
Act. We are further proposing at Sec.  412.64(h)(5)(ii) that a hospital 
would be considered classified as rural under section 1886 of the Act 
if it is assigned the State's rural area wage index value.
    Comment: Several commenters supported the proposed implementation 
of the imputed floor wage index policy to benefit all-urban states. A 
commenter opposed the reinstatement of the imputed floor, stating that 
it exacerbates wage index disparities, but acknowledged that CMS 
followed legislation enacted by Congress. This commenter requested CMS 
include details by state of the effects of the imputed rural floor. 
Commenters both in support and in opposition of the imputed floor 
policy applauded its implementation without the application of budget 
neutrality, per section 9831 of the American Rescue Plan Act of 2021. A 
commenter specifically concurred with CMS' interpretation that the 
definition of an all-urban state according to section 9831 of the 
American Rescue Plan Act of 2021 is one in which no hospital receives 
the rural area wage index.
    Response: We appreciate the commenters' support of our proposed 
implementation of the imputed floor. Responding to the commenter 
opposed to this policy, we underscore that, as the commenter itself 
pointed out, the imputed floor has been enacted into law via section 
9831 of the American Rescue Plan Act of 2021. Accordingly, CMS does not 
have discretion to not adopt this policy. In response this commenter's 
request for details by state of the effects of the imputed rural floor, 
we direct the commenter to the data file that CMS posted concurrent 
with the proposed rule with estimated imputed floor value by state at 
https://

[[Page 45178]]

www.cms.gov/files/zip/fy2022-ipps-nprm-imputed-state-floors.zip. 
Finally, we agree with the commenter that CMS' implementation of the 
imputed floor is consistent with the exemption from budget neutrality 
and the definition of an all-urban state according to section 9831 of 
the American Rescue Plan Act of 2021.
    Comment: A commenter requested that CMS clarify whether a hospital 
that is assigned the imputed floor wage index value would be treated as 
if the hospital is physically located in a geographically rural area. 
The commenter requested that CMS confirm that receipt of the imputed 
floor wage index would confer rural status for provisions such as RRC 
qualification, GME, DSH, and MGCRB reclassification.
    Response: A hospital that receives the imputed floor wage index is 
not considered rural. In fact, the imputed floor policy by definition 
applies only to all-urban states. The commenter might be referring to 
Sec.  412.103 urban to rural reclassifications, which does confer rural 
status for certain purposes; the imputed floor simply sets a minimum 
wage index in an all-urban state, but does not change the status of the 
hospital. Accordingly, the imputed floor wage index would not confer 
rural status for the aforementioned provisions.
    After consideration of the public comments, we are finalizing 
without modification our proposed revisions to the regulations at Sec.  
412.64(e)(1) and (4) and (h)(4) and (5) to implement the imputed floor 
required by section 1886(d)(3)(E)(iv) of the Act for discharges 
occurring on or after October 1, 2021.
3. State Frontier Floor for FY 2022
    Section 10324 of Public Law 111-148 requires that hospitals in 
frontier States cannot be assigned a wage index of less than 1.0000. 
(We refer readers to the regulations at 42 CFR 412.64(m) and to a 
discussion of the implementation of this provision in the FY 2011 IPPS/
LTCH PPS final rule (75 FR 50160 through 50161).) In the FY 2022 IPPS/
LTCH PPS proposed rule (86 FR 25407), we did not propose any changes to 
the frontier floor policy for FY 2022. In the proposed rule, we stated 
that 44 hospitals would receive the frontier floor value of 1.0000 for 
their FY 2022 proposed wage index. These hospitals are located in 
Montana, North Dakota, South Dakota, and Wyoming.
    We did not receive any public comments on the application of the 
State frontier floor for FY 2022. In this final rule, 44 hospitals will 
receive the frontier floor value of 1.0000 for their FY 2022 wage 
index. These hospitals are located in Montana, North Dakota, South 
Dakota, and Wyoming. We note that while Nevada meets the criteria of a 
frontier State, all hospitals within the State currently receive a wage 
index value greater than 1.0000.
    The areas affected by the rural and frontier floor policies for the 
final FY 2022 wage index are identified in Table 2 associated with this 
final rule, which is available via the internet on the CMS website.
4. Continuation of the Low Wage Index Hospital Policy; Budget 
Neutrality Adjustment
    To help mitigate wage index disparities, including those resulting 
from the inclusion of hospitals with rural reclassifications under 42 
CFR 412.103 in the rural floor, in the FY 2020 IPPS/LTCH PPS final rule 
(84 FR 42325 through 42339), we finalized policies to reduce the 
disparity between high and low wage index hospitals by increasing the 
wage index values for certain hospitals with low wage index values and 
doing so in a budget neutral manner through an adjustment applied to 
the standardized amounts for all hospitals, as well as by changing the 
calculation of the rural floor. We also provided for a transition in FY 
2020 for hospitals experiencing significant decreases in their wage 
index values as compared to their final FY 2019 wage index, and made 
these changes in a budget neutral manner.
    We increase the wage index for hospitals with a wage index value 
below the 25th percentile wage index value for a fiscal year by half 
the difference between the otherwise applicable final wage index value 
for a year for that hospital and the 25th percentile wage index value 
for that year across all hospitals (the low wage index hospital 
policy). We stated in the FY 2020 IPPS/LTCH PPS final rule (84 FR 42326 
through 42328) that this policy will be effective for at least 4 years, 
beginning in FY 2020, in order to allow employee compensation increases 
implemented by these hospitals sufficient time to be reflected in the 
wage index calculation. Therefore, the policy will continue in FY 2022. 
In order to offset the estimated increase in IPPS payments to hospitals 
with wage index values below the 25th percentile wage index value, for 
FY 2022 and for subsequent fiscal years during which the low wage index 
hospital policy is in effect, we proposed to apply a budget neutrality 
adjustment in the same manner as we applied it in FY 2021, as a uniform 
budget neutrality factor applied to the standardized amount. We refer 
readers to section II.A.4.b. of the addendum to this final rule for 
further discussion of the budget neutrality adjustment for FY 2022. For 
purposes of the low wage index hospital policy, based on the data for 
the final rule, the table displays the 25th percentile wage index value 
across all hospitals for FY 2022.

------------------------------------------------------------------------
 
------------------------------------------------------------------------
FY 2022 25th Percentile Wage Index Value................          0.8437
------------------------------------------------------------------------

    Comment: Many commenters thanked CMS for continuing the low wage 
index policy to significantly help struggling low-wage hospitals and 
promote equity among providers. These commenters specifically applauded 
CMS increasing the wage index values of low-wage hospitals. Several 
commenters requested that CMS extend the policy beyond four years as 
originally stated in the FY 2020 IPPS final rule when the policy was 
finalized, with a commenter specifically requesting the policy be 
finalized for a ten-year period. Other commenters similarly supported 
the policy but maintained that CMS needs to do more to address wage 
index disparities facing rural and low-wage providers, particularly 
considering the devastating effects of the COVID-19 pandemic on 
hospitals. Alternative solutions suggested by the commenters included a 
national rural wage index; an urban wage index floor of 1.0000; and 
wage data audits to verify local labor prices.
    Response: We appreciate the many comments received in support of 
our policy to provide an increase in the wage index for hospitals with 
wage index values below the 25th percentile wage index value for a year 
(referred to as the low wage index hospital policy). We note that we 
did not propose any changes to this policy in the FY 2022 IPPS/LTCH PPS 
proposed rule. We appreciate the commenters' requests to extend this 
policy beyond four years as well as other suggested alternatives. 
Because we consider these comments to be outside the scope of the FY 
2022 IPPS/LTCH PPS proposed rule, we are not addressing them in this 
final rule but may consider them in future rulemaking.
    Comment: We also received many comments opposing the continuation 
of the low wage index hospital policy. The commenters expressed that 
the policy fails to recognize legitimate differences in geographic 
labor markets. A commenter questioned CMS' statutory authority to 
promulgate this policy under 42 U.S.C. 1395ww(d)(3)(E) because 
inflating the wage index for the lowest quartile creates a wage index 
system not based on actual wages paid

[[Page 45179]]

by these hospitals. A few commenters maintained that the low wage 
policy is not well targeted and is ineffective. A commenter pointed to 
a recent OIG report that suggests a complicated set of issues in local 
labor markets determines hospital wages in addition to Medicare payment 
rates. The commenter requested that CMS repeal the low wage index 
policy for FY 2022 while it pursues the OIG's recommendation for CMS to 
study the reasons some hospitals in a particular area were able to pay 
higher wages than others in the same area prior to the implementation 
of the low wage index hospital policy.
    Response: We believe we addressed the commenters' concerns in our 
response to comments when we first promulgated the policy, and we refer 
readers to that discussion (84 FR 42325 through 42328). Specifically, 
in response to the commenters opposing our policy because they assert 
the policy fails to recognize differences in geographic labor markets, 
we continue to believe, for the reasons stated in the FY 2020 IPPS/LTCH 
PPS final rule (84 FR 42327-42328), that by preserving the rank order 
in wage index values, our policy continues to reflect meaningful 
distinctions between the employee compensation costs faced by hospitals 
in different geographic areas. Furthermore, as stated in the FY 2020 
IPPS/LTCH PPS final rule (84 FR 42327 through 42328), we believe that 
the low wage index hospital policy increases the accuracy of the wage 
index as a relative measure of wages across different geographic 
regions because it allows low wage index hospitals to increase their 
employee compensation in ways that we would expect if there were no lag 
in reflecting compensation adjustments in the wage index. Thus, under 
the low wage index hospital policy, we believe the wage index for low 
wage index hospitals appropriately reflects the relative hospital wage 
level in those areas compared to the national average hospital wage 
level. As explained in the FY 2020 IPPS/LTCH PPS final rule (84 FR 
42331), because the low wage index hospital policy results in a wage 
index that is based on the actual wage data we collect from hospitals, 
it falls within the scope of the authority in section 1886(d)(3)(E) of 
the Act, which requires that the wage index be constructed ``on the 
basis of'' that data.
    Relying in part on an OIG report about the policy, some commenters 
stated that our policy is mis-targeted and ineffective. We believe, 
however, that the numerous comments received in support of this policy 
indicate that many low wage hospitals are indeed helped by this policy. 
More importantly, refining our criteria to target a subset of low-wage 
hospitals as the commenter suggests, such as low-wage hospitals that 
are rural or that have negative profit margins, would not maintain the 
rank order in wage index values. As we stated earlier, we believe that 
maintaining the rank order of wage index values is important to reflect 
meaningful distinctions between the employee compensation costs faced 
by hospitals in different geographic areas. Even several commenters 
that disagreed with our policy stressed the need for the wage index to 
be an accurate measure of the relative level of wages in different 
areas. A highly targeted approach that selected individual hospitals 
for relief would not maintain the rank order of wage index values and 
thus would be inconsistent with the construction of a relative measure 
of area wage levels. While it might be possible to refine our criteria 
for a more targeted approach, we believe it is reasonable to conclude 
that our current policy will have the intended effect of providing the 
opportunity for low wage hospitals to increase compensation. As we 
stated in the FY 2020 IPPS/LTCH PPS final rule (84 FR 42327), the 
future wage data from those hospitals will help us assess our 
reasonable expectation that hospitals will increase their employee 
compensation as a result of wage index increases under this policy. 
Once the increased employee compensation is reflected in the wage data, 
there may be no need for the continuation of the policy, given that we 
would expect the resulting increases in the wage index to continue 
after the temporary policy is discontinued.
    Commenters that referenced the OIG report pointed out that the 
report indicates that Medicare payment is only one factor contributing 
to hospitals' low wages. While we recognize that Medicare payment is 
not the only factor driving hospital wages, Medicare payment is a 
contributing factor to hospital wage levels that is within the purview 
of CMS, unlike factors such as local housing markets. Therefore, we 
continue to believe it is appropriate to keep this policy in place 
while we evaluate its effectiveness. As we stated earlier in response 
to this comment, while the OIG report indicates that there may be ways 
to refine our policy, it does not show that our current policy approach 
is unreasonable or suggest the policy goal we are hoping to achieve is 
unworthy. Nor does the OIG report suggest we lack authority to pursue 
that goal. At most the OIG report suggests there might be alternative 
approaches to the problem. Therefore, we disagree with the commenter's 
suggestion that we repeal the low wage index hospital policy currently 
in place to study the OIG's recommendations. Due to the four year data 
lag until a hospital's wages are reflected in the wage index, we 
believe that keeping the policy in place for the full four year period 
that was finalized in the FY 2020 IPPS/LTCH PPS final rule will enable 
us to evaluate whether the policy achieved its intended effects. 
Prematurely pausing this policy, as the commenter suggests, could 
hamper the potential effectiveness of this policy in providing low wage 
hospitals an opportunity to increase compensation, which may in turn 
raise their wage index.
    In response to the comment suggesting that CMS study the reasons 
hospitals are able to pay higher wages, we note that CMS has 
extensively studied wage disparities and contributing factors to low 
wage indexes in the past. In the FY 2019 IPPS LTCH/PPS proposed rule 
(83 FR 20372), CMS issued a request for information engaging multiple 
stakeholders on wage index disparities. As summarized in the FY 2020 
IPPS/LTCH PPS proposed and final rules (84 FR 19394 and 84 FR 42326-
42332, respectively) many stakeholders expressed that circularity, 
where low wage hospitals remain locked in a downward spiral due to low 
wage indexes that prevent them from raising their wages, was the most 
important wage index issue facing the system and it needed to be 
addressed quickly. The low wage index hospital policy was developed as 
a result of extensive analysis and engagement with multiple 
stakeholders. We refer readers to the FY 2020 IPPS/LTCH PPS final rule 
(84 FR 42326-42332) for further discussion of the low wage index 
hospital policy and our responses to similar comments.
    Therefore, while the OIG report suggests that we do further study 
before implementing any policy regarding low wage hospitals, we note 
that we had already promulgated the policy by the time of the OIG 
report, and that we have been studying this issue for several years. We 
believe there was more than a sufficient basis on which to conclude 
that it was appropriate to take immediate action in the form of the 
policy we finalized and to continue to assess the results of that 
policy and to otherwise continue to analyze the issue. Doing further 
study might have resulted in a policy some might have preferred being 
implemented sometime in the future, but we concluded that the problem 
needed addressing now. Again, we believe the many comments we

[[Page 45180]]

received in favor of the policy support this judgment. We agree with 
the OIG that the issue deserves more study, and we will continue to 
engage in that, but we believe the best course was to implement our 
policy now while we engage in that study.
    Comment: Many commenters supported increasing the wage index values 
of low-wage hospitals, but urged CMS to do so in a non-budget-neutral 
manner. Commenters asserted that this redistribution forces high-wage, 
mostly urban hospitals to bear the cost of supporting lower-wage 
hospitals. Commenters who opposed the low wage index hospital policy 
also disagreed with the budget neutrality adjustment, stating that the 
budget neutrality adjustment penalizes many hospitals, including rural 
hospitals. Some commenters stated that 42 U.S.C. 1395ww(d)(5)(I) does 
not authorize budget neutrality adjustments to the national 
standardized amount, except for transfer cases. Other commenters 
requested that CMS ensure that the budget neutrality adjustment factor 
not apply to hospitals falling below the 25th percentile or revert to 
its FY 2020 proposal to decrease the wage index for hospitals with 
values above the 75th percentile. A few commenters stated that the wage 
index increase for hospitals between the 22nd and the 25th percentile 
is negated by the reduction to the standardized rate.
    Response: We disagree with the commenters that the low wage index 
hospital policy should be implemented in a non-budget neutral manner. 
As we stated in response to similar comments in the FY 2020 IPPS/LTCH 
PPS final rule, (84 FR 42331 and 42332), under section 1886(d)(3)(E) of 
the Act, the wage index adjustment is required to be implemented in a 
budget neutral manner. However, even if the wage index were not 
required to be budget neutral under section 1886(d)(3)(E) of the Act, 
we would consider it inappropriate to use the wage index to increase or 
decrease overall IPPS spending. As we stated in the FY 2020 IPPS/LTCH 
PPS final rule (84 FR 42331), the wage index is not a policy tool but 
rather a technical adjustment designed to be a relative measure of the 
wages and wage-related costs of subsection (d) hospitals. As a result, 
as we explained in the FY 2020 IPPS/LTCH PPS final rule, if it were 
determined that section 1886(d)(3)(E) of the Act does not require the 
wage index to be budget neutral, we invoke our authority at section 
1886(d)(5)(I) of the Act in support of such a budget neutrality 
adjustment. We have considered the commenters' suggestion that we do 
not have authority under section 1886(d)(5)(I) of the Act to implement 
a budget neutrality adjustment to the national standardized amount, 
including the argument that such authority exists only with respect to 
transfer cases. Contrary to the commenters' suggestion, and consistent 
with our response to a similar comment in the FY 2020 and FY 2021 IPPS/
LTCH PPS final rules, we believe that we have broad authority under 
section 1886(d)(5)(I) of the Act to promulgate a budget neutrality 
adjustment to the national standardized amount and that this authority 
is not limited to transfer cases. We refer readers to the full 
discussion of budget neutrality for the low wage index hospital policy 
in the FY 2020 IPPS/LTCH PPS final rule (84 FR 42328-42332).
    With regard to the commenter's assertion about a possible reduction 
to overall payment if the amount of benefit received from the wage 
index boost is less than the reduction to the standardized rate, we 
believe we have applied both the quartile policy and the budget 
neutrality policy appropriately. The quartile adjustment is applied to 
the wage index, which resulted in an increase to the wage index for 
hospitals below the 25th percentile. The budget neutrality adjustment 
is applied to the standardized amount in order to ensure that the low 
wage index hospital policy is implemented in a budget neutral manner. 
Thus, consistent with our current methodology for implementing wage 
index budget neutrality under section 1886(d)(3)(E) of the Act and with 
how we implemented budget neutrality for the low wage index hospital 
policy in FY 2020, we believe it is appropriate to continue to apply a 
budget neutrality adjustment to the national standardized amount for 
all hospitals so that the low wage index hospital policy is implemented 
in a budget neutral manner for FY 2022.
    After consideration of the public comments we received, for the 
reasons discussed in this final rule and in the FY 2022 IPPS/LTCH PPS 
proposed rule, we are finalizing our proposal, without modification, to 
apply a budget neutrality adjustment for our low wage index hospital 
policy in the same manner as we applied it in FY 2020 and FY 2021, as a 
uniform budget neutrality factor applied to the standardized amount.
    As we stated in the FY 2022 IPPS/LTCH PPS proposed rule (86 FR 
25407 through 25409), we will continue to apply the policies we 
finalized in the FY 2020 IPPS/LTCH PPS final rule (84 FR 32715) to 
address wage index disparities--that is, the low wage index hospital 
policy, and the exclusion of the wage data of hospitals reclassified 
under section 1886(d)(8)(E) of the Act (as implemented in Sec.  
412.103) from the rural floor and from the calculation of ``the wage 
index for rural areas in the State in which the county is located'' as 
referred to in section 1886(d)(8)(C)(iii) of the Act. For purposes of 
the low wage index hospital policy, based on the data for this final 
rule, for FY 2022, the 25th percentile wage index value across all 
hospitals is 0.8437.

H. FY 2022 Wage Index Tables

    In the FY 2016 IPPS/LTCH PPS final rule (80 FR 49498 and 49807 
through 49808), we finalized a proposal to streamline and consolidate 
the wage index tables associated with the IPPS proposed and final rules 
for FY 2016 and subsequent fiscal years. Effective beginning FY 2016, 
with the exception of Table 4E, we streamlined and consolidated 11 
tables (Tables 2, 3A, 3B, 4A, 4B, 4C, 4D, 4F, 4J, 9A, and 9C) into 2 
tables (Tables 2 and 3). In this FY 2022 IPPS/LTCH PPS final rule, as 
provided beginning with the FY 2021 IPPS/LTCH PPS final rule, we have 
included Table 4A which is titled ``List of Counties Eligible for the 
Out-Migration Adjustment under Section 1886(d)(13) of the Act'' and 
Table 4B titled ``Counties redesignated under section 1886(d)(8)(B) of 
the Act (Lugar Counties).'' We refer readers to section VI. of the 
Addendum to this final rule for a discussion of the wage index tables 
for FY 2022.

I. Revisions to the Wage Index Based on Hospital Redesignations and 
Reclassifications

1. General Policies and Effects of Reclassification and Redesignation
    Under section 1886(d)(10) of the Act, the Medicare Geographic 
Classification Review Board (MGCRB) considers applications by hospitals 
for geographic reclassification for purposes of payment under the IPPS. 
Hospitals must apply to the MGCRB to reclassify not later than 13 
months prior to the start of the fiscal year for which reclassification 
is sought (usually by September 1). We note that this deadline was 
extended for applications for FY 2022 reclassifications to 15 days 
after the public display date of the FY 2021 IPPS/LTCH final rule at 
the Office of the Federal Register, using our authority under section 
1135(b)(5) the Act due to the COVID-19 Public Health Emergency. 
Generally, hospitals must be proximate to the labor market area to 
which they are seeking reclassification and must demonstrate 
characteristics

[[Page 45181]]

similar to hospitals located in that area. The MGCRB issues its 
decisions by the end of February for reclassifications that become 
effective for the following fiscal year (beginning October 1). The 
regulations applicable to reclassifications by the MGCRB are located in 
42 CFR 412.230 through 412.280. (We refer readers to a discussion in 
the FY 2002 IPPS final rule (66 FR 39874 and 39875) regarding how the 
MGCRB defines mileage for purposes of the proximity requirements.) The 
general policies for reclassifications and redesignations and the 
policies for the effects of hospitals' reclassifications and 
redesignations on the wage index are discussed in the FY 2012 IPPS/LTCH 
PPS final rule for the FY 2012 final wage index (76 FR 51595 and 
51596). We note that rural hospitals reclassifying under the MGCRB to 
another State's rural area are not eligible for the rural floor, 
because the rural floor may apply only to urban, not rural, hospitals.
    In addition, in the FY 2012 IPPS/LTCH PPS final rule, we discussed 
the effects on the wage index of urban hospitals reclassifying to rural 
areas under 42 CFR 412.103. In the FY 2020 IPPS/LTCH PPS final rule (84 
FR 42332 through 42336), we finalized a policy to exclude the wage data 
of urban hospitals reclassifying to rural areas under 42 CFR 412.103 
from the calculation of the rural floor. Hospitals that are 
geographically located in States without any rural areas are ineligible 
to apply for rural reclassification in accordance with the provisions 
of 42 CFR 412.103.
    On April 21, 2016, we published an interim final rule with comment 
period (IFC) in the Federal Register (81 FR 23428 through 23438) that 
included provisions amending our regulations to allow hospitals 
nationwide to have simultaneous Sec.  412.103 and MGCRB 
reclassifications. For reclassifications effective beginning FY 2018, a 
hospital may acquire rural status under Sec.  412.103 and subsequently 
apply for a reclassification under the MGCRB using distance and average 
hourly wage criteria designated for rural hospitals. In addition, we 
provided that a hospital that has an active MGCRB reclassification and 
is then approved for redesignation under Sec.  412.103 will not lose 
its MGCRB reclassification; such a hospital receives a reclassified 
urban wage index during the years of its active MGCRB reclassification 
and is still considered rural under section 1886(d) of the Act and for 
other purposes.
    We discussed that when there is both a Sec.  412.103 redesignation 
and an MGCRB reclassification, the MGCRB reclassification controls for 
wage index calculation and payment purposes. We exclude hospitals with 
Sec.  412.103 redesignations from the calculation of the reclassified 
rural wage index if they also have an active MGCRB reclassification to 
another area. That is, if an application for urban reclassification 
through the MGCRB is approved, and is not withdrawn or terminated by 
the hospital within the established timelines, we consider the 
hospital's geographic CBSA and the urban CBSA to which the hospital is 
reclassified under the MGCRB for the wage index calculation. We refer 
readers to the April 21, 2016 IFC (81 FR 23428 through 23438) and the 
FY 2017 IPPS/LTCH PPS final rule (81 FR 56922 through 56930) for a full 
discussion of the effect of simultaneous reclassifications under both 
the Sec.  412.103 and the MGCRB processes on wage index calculations. 
For a discussion on the effects of reclassifications under Sec.  
412.103 on the rural area wage index and the calculation of the rural 
floor, we refer readers to the FY 2020 IPPS/LTCH PPS final rule (84 FR 
42332 through 42336).
    We refer readers to the interim final rule with comment period 
(IFC) (CMS-1762-IFC) simultaneously submitted for public inspection 
with the proposed rule implementing the court's decision in Bates 
County Memorial Hospital v. Azar, 464 F. Supp. 3d 43 (D.D.C. 2020) 
(``Bates'') for further changes to the treatment of Sec.  412.103 
hospitals reclassifying under the MGCRB.
    Comment: A commenter disagreed with CMS' treatment of hospitals 
with dual Sec.  412.103 and MGCRB reclassifications. The commenter 
stated that CMS' policy of considering the hospital's geographic CBSA 
and the urban CBSA to which the hospital is reclassified under the 
MGCRB for the wage index calculation violates the statutory requirement 
to treat Sec.  412.103 hospitals as located in the rural area of the 
state. The commenter specifically requested that CMS include the wages 
of Sec.  412.103 hospitals that also have an active MGCRB 
reclassification in calculating the rural wage of the state if not 
doing so would reduce the wage index for that area, in the same manner 
that geographically rural hospitals with a MGCRB reclassification are 
treated according to Sec.  1886(d)(8)(C)(ii).
    Response: We appreciate the commenter's input. We note that CMS 
includes the wage data of Sec.  412.103 hospitals that do not have an 
MGCRB reclassification in the rural area wage index, consistent with 
the statutory requirement to treat Sec.  412.103 hospitals as rural. 
CMS continues to treats Sec.  412.103 hospitals as rural even if such 
hospitals have an additional MGCRB reclassification by according the 
hospital the benefits of rural status, such as 340B program and RRC 
eligibility. However, in developing our policies for how hospitals with 
dual reclassifications would be treated in wage index calculations 
following our April 21, 2016 IFC (81 FR 23428 through 23438), CMS 
discussed the effect of simultaneous Sec.  412.103 and MGCRB 
reclassifications. We stated that when there is both a Sec.  412.103 
reclassification and an MGCRB reclassification, the MGCRB 
reclassification would control for wage index calculation and payment 
purposes. We explained that ``In these circumstances, we believe it is 
appropriate to rely on the urban MGCRB reclassification to include the 
hospital's wage data in the calculation of the urban CBSA wage index. 
Further, we believe it is appropriate to rely on the urban MGCRB 
reclassification to ensure that the hospital be paid based on its urban 
MGCRB wage index. While rural reclassification confers other rural 
benefits besides the wage index under section 1886(d) of the Act, a 
hospital that chooses to pursue reclassification under the MGCRB (while 
also maintaining a rural reclassification under Sec.  412.103) would do 
so solely for wage index payment purposes.'' (81 FR 23434). We continue 
to believe that that policy, developed through rulemaking, is 
appropriate. Since we did not propose to change our current policy in 
the FY 2022 IPPS/LTCH PPS proposed rule, we are not making any changes 
to this policy in this final rule.
    With regard to the application of the hold harmless policy that the 
commenter referenced at Sec.  1886(d)(8)(C)(ii), the statute requires 
that a rural area be held harmless from the effects of hospitals 
reclassifying under Lugar or the MGCRB. Specifically, Sec.  
1886(d)(8)(C)(ii) states: ``If the application of subparagraph (B) or a 
decision of the Medicare Geographic Classification Review Board or the 
Secretary under paragraph (10), by treating hospitals located in a 
rural county or counties as not being located in the rural area in a 
State, reduces the wage index for that rural area (as applied under 
this subsection), the Secretary shall calculate and apply such wage 
index under this subsection as if the hospitals so treated had not been 
excluded from calculation of the wage index for that rural area.''
    The commenter suggests CMS include the wage data of hospitals with 
Sec.  412.103 reclassifications in the rural area of the State 
referenced in

[[Page 45182]]

Sec.  1886(d)(8)(C)(ii). The rural area wage index, which according to 
the commenter should include Sec.  412.103 hospitals, would be compared 
to a wage index with the effect of MGCRB reclassifications and Lugar 
hospital statuses applied, in order to possibly hold the rural area 
harmless from the effect of MGCRB reclassifications and Lugar hospital 
statuses. There would be numerous downstream effects of such a policy 
across IPPS ratesetting that might harm hospitals, contrary to the 
commenter's intent. For example, using the data associated with this 
final rule, some states would experience a decline of up to 4.8 percent 
in their rural wage index if we were to treat hospitals with dual Sec.  
412.103 and MGCRB reclassifications no differently than geographically 
rural hospitals with MGCRB reclassifications, as the commenter 
suggests. In another example, such a policy would potentially create 
barriers to MGCRB reclassification for rural and Sec.  412.103 
hospitals. If CMS were to treat Sec.  412.103 hospitals in the manner 
the commenter requests by considering such hospitals' data in the rural 
area prior to reclassification, then Sec.  412.103 hospitals would have 
the state's rural area listed as their geographic CBSA in the Three 
Year Average Hourly Wage (AHW) File used for MGCRB reclassification. As 
commenters expressed in comments responding to our May 10, 2021 interim 
final rule with comment period (CMS-1762-IFC) and summarized in section 
III.K.3. of the preamble of this final rule, assigning the rural CBSA 
as the geographic CBSA for Sec.  412.103 hospitals in the Three Year 
AHW File would potentially hamper geographically rural and Sec.  
412.103 hospitals' ability to reclassify. Many geographically rural and 
Sec.  412.103 hospitals would no longer be able to satisfy the wage 
comparison criteria at Sec.  412.230(d)(1)(iii)(C) (requiring a 
hospital's average hourly wage to be at least 106 percent of the 
average hourly wage of all other hospitals in the area in which the 
hospital is located) if the wages of high-wage Sec.  412.103 hospitals 
are included in the area in which the hospital is located prior to 
reclassification. Notably, commenters unanimously requested CMS require 
Sec.  412.103 hospitals to compare their AHW to the AHW of only 
hospitals actually located in the rural area, exclusive of hospitals 
with Sec.  412.103 rural redesignations, for simplicity because 
hospitals may obtain a Sec.  412.103 reclassification at any time and 
would change the rural area's AHW and because including Sec.  412.103 
reclassifications will change the rural areas AHW.
    We did not propose the policy the commenter suggests, and it would 
constitute a significant change with numerous effects on the IPPS wage 
index, as enumerated above. We do not think it would be appropriate to 
adopt such a policy without describing it in a proposed rule and 
obtaining public comments from all relevant stakeholders. Therefore, in 
this final rule we are not adopting the policy the commenter suggested, 
but will consider further addressing the issue in future rulemaking.
2. MGCRB Reclassification and Redesignation Issues for FY 2022
a. FY 2022 Reclassification Application Requirements and Approvals
    As previously stated, under section 1886(d)(10) of the Act, the 
MGCRB considers applications by hospitals for geographic 
reclassification for purposes of payment under the IPPS. The specific 
procedures and rules that apply to the geographic reclassification 
process are outlined in regulations under 42 CFR 412.230 through 
412.280. At the time this final rule was constructed, the MGCRB had 
completed its review of FY 2022 reclassification requests. Based on 
such reviews, there are 406 hospitals approved for wage index 
reclassifications by the MGCRB starting in FY 2022. Because MGCRB wage 
index reclassifications are effective for 3 years, for FY 2022, 
hospitals reclassified beginning in FY 2020 or FY 2021 are eligible to 
continue to be reclassified to a particular labor market area based on 
such prior reclassifications for the remainder of their 3-year period. 
There were 243 hospitals approved for wage index reclassifications in 
FY 2020 that will continue for FY 2022, and 291 hospitals approved for 
wage index reclassifications in FY 2021 that will continue for FY 2022. 
Of all the hospitals approved for reclassification for FY 2020, FY 
2021, and FY 2022, based upon the review at the time of the proposed 
rule, 940 hospitals are in a MGCRB reclassification status for FY 2022 
(with 140 of these hospitals reclassified back to their geographic 
location).
    Under the regulations at 42 CFR 412.273, hospitals that have been 
reclassified by the MGCRB are permitted to withdraw their applications 
if the request for withdrawal is received by the MGCRB any time before 
the MGCRB issues a decision on the application, or after the MGCRB 
issues a decision, provided the request for withdrawal is received by 
the MGCRB within 45 days of the date that CMS' annual notice of 
proposed rulemaking is issued in the Federal Register concerning 
changes to the inpatient hospital prospective payment system and 
proposed payment rates for the fiscal year for which the application 
has been filed. For information about withdrawing, terminating, or 
canceling a previous withdrawal or termination of a 3-year 
reclassification for wage index purposes, we refer readers to Sec.  
412.273, as well as the FY 2002 IPPS final rule (66 FR 39887 through 
39888) and the FY 2003 IPPS final rule (67 FR 50065 through 50066). 
Additional discussion on withdrawals and terminations, and 
clarifications regarding reinstating reclassifications and ``fallback'' 
reclassifications were included in the FY 2008 IPPS final rule (72 FR 
47333) and the FY 2018 IPPS/LTCH PPS final rule (82 FR 38148 through 
38150).
    Finally, we note that in the FY 2021 IPPS/LTCH final rule (85 FR 
58771--58778), CMS finalized an assignment policy for hospitals 
reclassified to CBSAs from which one or more counties moved to a new or 
different urban CBSA under the revised OMB delineations based on OMB 
Bulletin 18-04. We provided a table in that rule (85 FR 58777 and 
58778) which described the assigned CBSA for all the MGCRB cases 
subject to this policy. For such reclassifications that continue to be 
active or are reinstated for FY 2022 (and FY 2023, if applicable), the 
CBSAs assigned in the FY 2021 IPPS/LTCH final rule continue to be in 
effect.
b. Revisions to the Regulations at Sec.  412.278 for Administrator's 
Review
    The regulation at Sec.  412.278(b) addresses the procedure for a 
hospital's request for the Administrator's review of an MGCRB decision. 
In the FY 2021 IPPS/LTCH PPS final rule (85 FR 58788), we eliminated 
the prohibition on submitting a request by facsimile or other 
electronic means so that hospitals may also submit requests for 
Administrator review of MGCRB decisions electronically. In addition, we 
updated the regulation at Sec.  412.278(b)(1) to require the hospital 
to submit an electronic copy of its request for review to CMS' Hospital 
and Ambulatory Policy Group. We specified that copies to CMS' Hospital 
and Ambulatory Policy Group should be submitted via email to wage 
[email protected]. In the proposed rule, we proposed to further revise 
the regulation at Sec.  412.278(b)(1) to specify that the hospital's 
request for review must be in writing and sent to the Administrator, in 
care of the Office of the Attorney Advisor, in the manner directed by 
the

[[Page 45183]]

Office of the Attorney Advisor. We believe that this additional 
language would provide clarity and specificity by addressing any 
changes to the future technology platform for submission of the 
hospital's request for Administrator review. Hospitals will continue to 
be notified of the procedure for requesting Administrator review in the 
decision letters issued by the MGCRB.
    The regulation at Sec.  412.278(f)(2) addresses the timing for the 
Administrator's decision. Specifically, the Administrator issues a 
decision in writing to the party with a copy to CMS not later than 90 
calendar days following the receipt of the party's request for review 
(Sec.  412.278(f)(2)(i)), or not later than 105 calendar days following 
issuance of the MGCRB decision in the case of review at the discretion 
of the Administrator (Sec.  412.278(f)(2)(ii)). While the regulation at 
Sec.  412.278(f)(2)(i) allows the Administrator to toll the 90-day 
timeframe for good cause, the regulation at Sec.  412.278(f)(2)(ii) 
does not expressly provide for tolling the 105 day timeframe in the 
case of review at the discretion of the Administrator. We believe the 
policy regarding tolling should be the same regardless of whether the 
Administrator exercises review at the request of the hospital or at her 
discretion. Therefore, we proposed to also provide for tolling of the 
105-day timeframe at Sec.  412.278(f)(2)(ii). Specifically, we proposed 
to revise Sec.  412.278(f)(2)(ii) to state that the Administrator 
issues a decision in writing to the party with a copy to CMS not later 
than 105 days following issuance of the MGCRB decision in the case of 
review at the discretion of the Administrator, except the Administrator 
may, at his or her discretion, for good cause shown, toll such 105 
days. We received no comments on this proposal and therefore are 
finalizing the proposed revisions to Sec. Sec.  412.278(b)(1) and 
412.278(f)(2)(ii) without modification.
3. Redesignations Under Section 1886(d)(8)(B) of the Act (Lugar Status 
Determinations)
    In the FY 2012 IPPS/LTCH PPS final rule (76 FR 51599 through 
51600), we adopted the policy that, beginning with FY 2012, an eligible 
hospital that waives its Lugar status in order to receive the out-
migration adjustment has effectively waived its deemed urban status 
and, thus, is rural for all purposes under the IPPS effective for the 
fiscal year in which the hospital receives the outmigration adjustment. 
In addition, in that rule, we adopted a minor procedural change that 
would allow a Lugar hospital that qualifies for and accepts the out-
migration adjustment (through written notification to CMS within 45 
days from the publication of the proposed rule) to waive its urban 
status for the full 3-year period for which its out-migration 
adjustment is effective. By doing so, such a Lugar hospital would no 
longer be required during the second and third years of eligibility for 
the out-migration adjustment to advise us annually that it prefers to 
continue being treated as rural and receive the out-migration 
adjustment. In the FY 2017 IPPS/LTCH PPS final rule (81 FR 56930), we 
further clarified that if a hospital wishes to reinstate its urban 
status for any fiscal year within this 3-year period, it must send a 
request to CMS within 45 days of publication of the proposed rule for 
that particular fiscal year. We indicated that such reinstatement 
requests may be sent electronically to wage[email protected]. In the FY 
2018 IPPS/LTCH PPS final rule (82 FR 38147 through 38148), we finalized 
a policy revision to require a Lugar hospital that qualifies for and 
accepts the out-migration adjustment, or that no longer wishes to 
accept the out-migration adjustment and instead elects to return to its 
deemed urban status, to notify CMS within 45 days from the date of 
public display of the proposed rule at the Office of the Federal 
Register. These revised notification timeframes were effective 
beginning October 1, 2017. In addition, in the FY 2018 IPPS/LTCH PPS 
final rule (82 FR 38148), we clarified that both requests to waive and 
to reinstate ``Lugar'' status may be sent to wage[email protected]. To 
ensure proper accounting, we request hospitals to include their CCN, 
and either ``waive Lugar'' or ``reinstate Lugar'', in the subject line 
of these requests.
    In the FY 2020 IPPS/LTCH PPS final rule (84 FR 42314 and 42315), we 
clarified that in circumstances where an eligible hospital elects to 
receive the outmigration adjustment within 45 days of the public 
display date of the proposed rule at the Office of the Federal Register 
in lieu of its Lugar wage index reclassification, and the county in 
which the hospital is located would no longer qualify for an out-
migration adjustment when the final rule (or a subsequent correction 
notice) wage index calculations are completed, the hospital's request 
to accept the outmigration adjustment would be denied, and the hospital 
would be automatically assigned to its deemed urban status under 
section 1886(d)(8)(B) of the Act. We stated that final rule wage index 
values would be recalculated to reflect this reclassification, and in 
some instances, after taking into account this reclassification, the 
out-migration adjustment for the county in question could be restored 
in the final rule. However, as the hospital is assigned a Lugar 
reclassification under section 1886(d)(8)(B) of the Act, it would be 
ineligible to receive the county outmigration adjustment under section 
1886(d)(13)(G) of the Act.

J. Out-Migration Adjustment Based on Commuting Patterns of Hospital 
Employees

    In accordance with section 1886(d)(13) of the Act, as added by 
section 505 of Public Law 108-173, beginning with FY 2005, we 
established a process to make adjustments to the hospital wage index 
based on commuting patterns of hospital employees (the ``out-
migration'' adjustment). The process, outlined in the FY 2005 IPPS 
final rule (69 FR 49061), provides for an increase in the wage index 
for hospitals located in certain counties that have a relatively high 
percentage of hospital employees who reside in the county but work in a 
different county (or counties) with a higher wage index.
    Section 1886(d)(13)(B) of the Act requires the Secretary to use 
data the Secretary determines to be appropriate to establish the 
qualifying counties. When the provision of section 1886(d)(13) of the 
Act was implemented for the FY 2005 wage index, we analyzed commuting 
data compiled by the U.S. Census Bureau that were derived from a 
special tabulation of the 2000 Census journey-to-work data for all 
industries (CMS extracted data applicable to hospitals). These data 
were compiled from responses to the ``long-form'' survey, which the 
Census Bureau used at that time and which contained questions on where 
residents in each county worked (69 FR 49062). However, the 2010 Census 
was ``short form'' only; information on where residents in each county 
worked was not collected as part of the 2010 Census. The Census Bureau 
worked with CMS to provide an alternative dataset based on the latest 
available data on where residents in each county worked in 2010, for 
use in developing a new outmigration adjustment based on new commuting 
patterns developed from the 2010 Census data beginning with FY 2016.
    To determine the out-migration adjustments and applicable counties 
for FY 2016, we analyzed commuting data compiled by the Census Bureau 
that were derived from a custom tabulation

[[Page 45184]]

of the American Community Survey (ACS), an official Census Bureau 
survey, utilizing 2008 through 2012 (5-year) Microdata. The data were 
compiled from responses to the ACS questions regarding the county where 
workers reside and the county to which workers commute. As we discussed 
in prior IPPS/LTCH PPS final rules, most recently in the FY 2021 IPPS/
LTCH PPS final rule (85 FR 58787), we have applied the same policies, 
procedures, and computations since FY 2012. We proposed to use them 
again for FY 2022, as we believe they continue to be appropriate for FY 
2022. We refer readers to the FY 2016 IPPS/LTCH PPS final rule (80 FR 
49500 through 49502) for a full explanation of the revised data source.
    For FY 2022, the out-migration adjustment will continue to be based 
on the data derived from the custom tabulation of the ACS utilizing 
2008 through 2012 (5-year) Microdata. For future fiscal years, we may 
consider determining out-migration adjustments based on data from the 
next Census or other available data, as appropriate. For FY 2022, we 
did not propose any changes to the methodology or data source that we 
used for FY 2016 (81 FR 25071). (We refer readers to a full discussion 
of the out-migration adjustment, including rules on deeming hospitals 
reclassified under section 1886(d)(8) or section 1886(d)(10) of the Act 
to have waived the out-migration adjustment, in the FY 2012 IPPS/LTCH 
PPS final rule (76 FR 51601 through 51602).)
    Comment: A teaching hospital located in a rural area explained that 
itis disadvantaged by the current wage index policy because other 
hospitals in its state are able to benefit from higher wage areas due 
to the out-migration adjustment, which the commenter stated is 
currently unavailable to it. According to the commenter, despite being 
ineligible for an out-migration adjustment, it continues to complete 
for labor with hospitals located in urban areas. As such, the commenter 
would like CMS to consider the impact that the current wage index 
policies has on it and other teaching hospitals like it that are 
located in rural areas, are ineligible for the out-migration adjustment 
and serve a sparsely populated patient service area but compete for 
labor with an urban area with a high concentration of similar 
institutions.
    Response: We appreciate the commenter's concerns. Wage index 
policy, specifically the out-migration adjustment based on commuting 
patterns of hospital employees, is applied according to the statute 
described at section 1886(d)(13) of the Act. As described earlier in 
this section, the out-migration adjustment is based on the data derived 
from the custom tabulation of the ACS utilizing 2008 through 2012 (5-
year) Microdata. For future fiscal years, we may consider determining 
out-migration adjustments based on data from the next Census or other 
available data, as appropriate.
    For the reasons set forth in this final rule and in the FY 2022 
IPPS/LTCH PPS proposed rule, for FY 2022, we are finalizing our 
proposal, without modification, to continue using the same policies, 
procedures, and computations that were used for the FY 2012 out-
migration adjustment and that were applicable for FYs 2016 through 
2021.
    Table 2 associated with this final rule (which is available via the 
internet on the CMS website) includes the proposed out-migration 
adjustments for the FY 2022 wage index. In addition, Table 4A 
associated with this final rule, ``List of Counties Eligible for the 
Out-Migration Adjustment under Section 1886(d)(13) of the Act'' (also 
available via the internet on the CMS website) consists of the 
following: A list of counties that are eligible for the out-migration 
adjustment for FY 2022 identified by FIPS county code, the final FY 
2022 out-migration adjustment, and the number of years the adjustment 
will be in effect.

K. Reclassification From Urban to Rural Under Section 1886(d)(8)(E) of 
the Act Implemented at 42 CFR 412.103

1. Application for Rural Status and Lock-in Date
    Under section 1886(d)(8)(E) of the Act, a qualifying prospective 
payment hospital located in an urban area may apply for rural status 
for payment purposes separate from reclassification through the MGCRB. 
Specifically, section 1886(d)(8)(E) of the Act provides that, not later 
than 60 days after the receipt of an application (in a form and manner 
determined by the Secretary) from a subsection (d) hospital that 
satisfies certain criteria, the Secretary shall treat the hospital as 
being located in the rural area (as defined in paragraph (2)(D)) of the 
State in which the hospital is located. We refer readers to the 
regulations at 42 CFR 412.103 for the general criteria and application 
requirements for a subsection (d) hospital to reclassify from urban to 
rural status in accordance with section 1886(d)(8)(E) of the Act. The 
FY 2012 IPPS/LTCH PPS final rule (76 FR 51595 through 51596) includes 
our policies regarding the effect of wage data from reclassified or 
redesignated hospitals. We refer readers to the FY 2020 IPPS/LTCH PPS 
final rule (84 FR 42332 through 42336) for a discussion on our current 
policy to calculate the rural floor without the wage data of urban 
hospitals reclassifying to rural areas under 42 CFR 412.103.
    Because the wage index is part of the methodology for determining 
the prospective payments to hospitals for each fiscal year, we stated 
in the FY 2017 IPPS/LTCH PPS final rule (81 FR 56931) that we believed 
there should be a definitive timeframe within which a hospital must 
apply for rural status in order for the reclassification to be 
reflected in the next Federal fiscal year's wage data used for setting 
payment rates. Therefore, in the FY 2017 IPPS/LTCH PPS final rule (81 
FR 56931 through 56932), we revised Sec.  412.103(b) by adding 
paragraph (6) to add a lock-in date by which a hospital's application 
for rural status must be filed in order to be treated as rural in the 
wage index and budget neutrality calculations for payment rates for the 
next Federal fiscal year. In the FY 2019 IPPS/LTCH PPS final rule (83 
FR 41384 through 41386), we changed the lock-in date to provide for 
additional time in the ratesetting process and to match the lock-in 
date with another existing deadline, the usual public comment deadline 
for the IPPS proposed rule. We revised Sec.  412.103(b)(6) to specify 
that, in order for a hospital to be treated as rural in the wage index 
and budget neutrality calculations under Sec.  412.64(e)(1)(ii), (e)(2) 
and (4), and (h) for payment rates for the next Federal fiscal year, 
the hospital's application must be approved by the CMS Regional Office 
in accordance with the requirements of Sec.  412.103 no later than 60 
days after the public display date at the Office of the Federal 
Register of the IPPS proposed rule for the next Federal fiscal year.
    The lock-in date does not affect the timing of payment changes 
occurring at the hospital-specific level as a result of 
reclassification from urban to rural under Sec.  412.103. As we 
discussed in the FY 2017 IPPS/LTCH PPS final rule (81 FR 56931) and the 
FY 2019 IPPS/LTCH PPS final rule (83 FR 41385 through 41386), this 
lock-in date also does not change the current regulation that allows 
hospitals that qualify under Sec.  412.103(a) to request, at any time 
during a cost reporting period, to reclassify from urban to rural. A 
hospital's rural status and claims payment reflecting its rural status 
continue to be effective on the filing date of its reclassification 
application, which is the date the CMS Regional Office receives the 
application, in accordance with Sec.  412.103(d). The

[[Page 45185]]

hospital's IPPS claims will be paid reflecting its rural status 
beginning on the filing date (the effective date) of the 
reclassification, regardless of when the hospital applies.
2. Changes to Cancellation Requirements at Sec.  412.103(g)
    In the FY 2020 IPPS/LTCH PPS final rule (84 FR 42322), we noted 
that if an application is approved by the CMS Regional Office after our 
ratesetting lock-in date, the final rule rural wage index value would 
most likely not include the data for this hospital in the ratesetting 
calculation. Therefore, we noted that this may incentivize relatively 
low wage index hospitals to time their applications to avoid reducing 
the State's rural wage index. These hospitals could then conceivably 
cancel their rural reclassifications (effective for next FY), and then 
reapply again after the `lock-in date.' We stated in the FY 2020 IPPS/
LTCH PPS final rule that we planned to monitor this situation over the 
course of FY 2020, and determine if it is necessary to take action to 
prevent this type of gaming in future rulemaking.
    We stated in the FY 2021 IPPS/LTCH PPS final rule (85 FR 58788) 
that hospitals in certain states were indeed timing their rural 
reclassifications and applications to exploit the rural 
reclassification process in order to obtain higher wage index values. 
For example, for FY 2020, at least twenty-one hospitals in one State 
obtained Sec.  412.103 rural reclassifications after the FY 2020 lock-
in date, effectively receiving their State's rural wage index without 
having their wage data included, which would have lowered their State's 
rural wage index. These hospitals then requested to cancel their Sec.  
412.103 rural reclassifications effective for FY 2021, in accordance 
with Sec.  412.103(g)(3). Similarly, five hospitals in another State, 
hospitals with wage data that would have lowered their State's FY 2021 
rural wage index, requested to cancel their Sec.  412.103 rural 
reclassifications for FY 2021, so that the rural wage index would be 
set using the data of one geographically rural hospital and two 
hospitals reclassified under Sec.  412.103 that withdrew their MGCRB 
reclassifications for FY 2021. All five of these hospitals that 
withdrew their rural reclassification effective October 1, 2021 have 
since reapplied and been approved for rural reclassification. At least 
a dozen additional hospitals in this State were also approved for rural 
reclassification during FY 2021. By timing their applications to be 
approved after the lock-in date, these hospitals are receiving a higher 
rural wage index without having their own data included in the rural 
wage index calculation. We believe this practice of applying for and 
canceling rural reclassification to manipulate a State's rural wage 
index is detrimental to the stability and the accuracy of the Medicare 
wage index system.
    In the FY 2008 IPPS/LTCH final rule (72 FR 47371 through 47373), 
CMS addressed an issue of hospitals applying for rural reclassification 
and then requesting cancelation soon after approval. Certain hospitals 
were using rural reclassifications to obtain RRC status, then canceling 
their rural reclassification so they could obtain an MGCRB 
reclassification, and using their prior RRC status in order to benefit 
from favorable MGCRB reclassification rules. To address this, CMS 
finalized a policy that required such hospitals to maintain rural 
status for one full cost reporting year before their rural 
reclassification could be canceled (cancellation was not effective 
until the hospital had been paid as rural for at least one 12-month 
cost-reporting period, and not until the beginning of the FY following 
the request for cancellation and the 12-month cost reporting period 
(Sec.  412.103(g)(2)(ii)). As discussed in the FY 2008 IPPS/LTCH 
proposed rule (72 FR 24812), we stated that we believed this policy was 
reasonable, given that acquired rural status for IPPS hospitals should 
be a considered decision for hospitals that truly wish to be considered 
as rural, and not purely as a mechanism for reclassifying. In the April 
21, 2016 interim final rule with comment period (81 FR 23428 through 
23438)), CMS implemented provisions amending our regulations to allow 
hospitals nationwide to have simultaneous Sec.  412.103 and MGCRB 
reclassifications. In the FY 2020 IPPS/LTCH final rule (42320 through 
42321), CMS removed the requirement that RRCs must be paid as rural for 
one cost reporting year before canceling rural reclassification, as 
there no longer was an incentive to obtain and then cancel rural 
reclassification status to obtain an MGCRB reclassification. However, 
given our observations over the past two fiscal years of a new form of 
wage index gaming, as described in the previous paragraph, we believe 
it is necessary and appropriate to adopt a similar measure to prevent 
rural reclassifications from being used purely as a mechanism for 
statewide wage index manipulation.
    Specifically, we proposed that requests to cancel rural 
reclassifications must be submitted to the CMS Regional Office not 
earlier than one calendar year after the reclassification effective 
date. For example, a hospital that was approved to receive a rural 
reclassification effective October 1, 2021 would not be eligible to 
request cancellation until October 1, 2022. We also proposed an 
additional modification to the effective date of these cancellation 
requests. Currently, all rural reclassification cancellation requests 
must be submitted not less than 120 days before the end of a fiscal 
year (that is, assuming the fiscal year ends on September 30th, no 
cancellation requests may be submitted after June 2nd and before 
October 1st). This timeframe typically aligns closely with the rural 
reclassification lock-in date under Sec.  412.103(b)(6) (the hospital's 
rural reclassification application must be approved by the CMS Regional 
Office no later than 60 days after the public display date of the IPPS/
LTCH PPS proposed rule at the Office of the Federal Register in order 
for a hospital to be treated as rural in the wage index and budget 
neutrality calculations for the next Federal fiscal year). The lock-in 
date and the 120 day cancellation deadline provide timeframes within 
which a hospital must be approved for rural reclassification (to have 
its rural status included in the wage index and budget neutrality 
calculations for the next fiscal year) or request cancellation of rural 
status, respectively, and also give CMS adequate time to incorporate 
these changes in the wage index and budget neutrality calculations 
under Sec.  412.64(e)(1)(ii), (e)(2) and (4), and (h) for payment rates 
for the next Federal fiscal year. Rural reclassifications are effective 
as of the date the application is received (Sec.  412.103(b)(5), (d)), 
and CMS Regional Offices are required to render a determination within 
60 days of receipt of the application (Sec.  412.103(c)). We believe 
that even with the proposed one-year minimum reclassification period 
before cancellation can be requested, there still would be a 
possibility that hospitals could time their applications around the 
lock-in date and 120 day deadline to continue to manipulate the State's 
rural wage index calculation. For example, assuming the lock-in date 
for a given year was May 30th (that is, the date by which the Regional 
Office must approve the application in order for the rural 
reclassification to be included in the wage index and budget neutrality 
calculations for the upcoming fiscal year), a hospital may choose to 
apply for rural reclassification on May 25th, virtually assuring that 
it could not be approved in time to be considered for wage index 
development purposes for the upcoming fiscal year. Assuming our

[[Page 45186]]

one-year minimum reclassification period proposal is finalized, the 
hospital could request cancellation on May 25th the following year. 
Since that date would be prior to 120 day cancellation deadline, a 
hospital could once again cancel its rural reclassification, then 
reapply for rural reclassification status, and once again receive the 
rural wage index for the upcoming fiscal year while excluding its own 
wage data from the calculation. To address this rural wage index 
manipulation, we proposed to eliminate the current rule at Sec.  
412.103(g)(3) (that cancellation must be requested 120 days prior to 
the end of the fiscal year and is effective beginning with the next 
fiscal year) and replace it with a policy that ensures that a hospital 
approved for rural reclassification (and that does not receive an 
additional reclassification) would have its data included in the 
calculation of the rural wage index for at least one Federal fiscal 
year before the rural reclassification status could be canceled. 
Specifically, we proposed to make cancellation requests effective for 
the Federal fiscal year that begins in the calendar year after the 
calendar year in which the cancellation request is submitted. For 
example, we proposed that a cancellation request submitted on December 
31, 2021 would be effective October 1, 2022. But a cancellation request 
submitted one day later on January 1, 2022 would not become effective 
until October 1, 2023.
    Specifically, we proposed to add 412.103(g)(4) to state that for 
all written requests submitted by hospitals on or after October, 1, 
2021 to cancel rural reclassifications, a hospital may cancel its rural 
reclassification by submitting a written request to the CMS Regional 
Office not less than 1 calendar year after the effective date of the 
rural reclassification. The hospital's cancellation of its rural 
reclassification would be effective beginning the Federal fiscal year 
that begins in the calendar year following the calendar year in which 
the cancellation request is submitted. We proposed to make conforming 
revisions to Sec.  412.103(g)(3) to reflect that the rule in Sec.  
412.103(g)(3) applies to requests for cancellation of rural 
reclassification submitted on or after October 1, 2019 and before 
October 1, 2021.
    We considered an alternative policy to increase the current 120 day 
cancellation deadline to a sufficient number of days to ensure that 
hospitals could not time applications and cancellations to straddle the 
lock-in date. Given the floating nature of the lock-in date due to the 
publication of the proposed rule varying year to year, it is difficult 
to determine how long that period would need to be in order to ensure 
our policy goals of preventing rural wage index manipulation are met. 
We acknowledge that our proposals would increase the amount of time a 
hospital must retain rural reclassification before it could cancel that 
status. However, we do not believe these proposed changes would have an 
undue impact on hospitals. In the FY 2021 final rule, 81 percent of 
hospitals with rural reclassifications were assigned a wage index based 
on an MGCRB or ``Lugar'' reclassification, and would not receive a wage 
index based on their rural reclassification.\758\ Another 11 percent 
received a rural wage index value that was greater than or equal to 
their geographically urban area. Since these hospitals are typically 
benefiting by maintaining rural reclassification status, we do not 
believe they would be negatively affected by our proposals. More than 
half of the remaining 9 percent of hospitals with rural 
reclassifications do so to maintain MDH or SCH status. These special 
statuses convey additional financial benefits to hospitals and are not 
typically or routinely canceled by hospitals. We note that in the FY 
2008 IPPS/LTCH final rule (72 FR 47372), we addressed a comment that 
expressed concern that the proposed requirement that a hospital must 
maintain rural status for at least a full 12 months could adversely 
affect hospitals with SCH status since the payment rate as a rural SCH 
may be only slightly higher than the urban Federal rate. Since the form 
of wage index manipulation addressed by the proposed policy in FY 2008 
specifically involved hospitals acquiring rural status to become RRCs, 
CMS opted to limit the policy finalized in FY 2008 to RRCs only. By 
contrast, the form of wage index manipulation we addressed in the 
proposed rule was not limited to any specific hospital type. Therefore, 
we believe it is appropriate to apply it to all hospitals with rural 
reclassification status. We believe the proposed policy of requiring 
that rural reclassification be in effect for at least 1 year before 
cancellation can be requested, and the proposed policy to make rural 
reclassification cancellations effective beginning the Federal fiscal 
year that begins in the calendar year after the calendar year in which 
the cancellation request is submitted will reduce the instances of wage 
index manipulation described previously, as well as reduce volatility 
and promote accuracy in overall wage index values by ensuring that 
hospitals that are being paid a State's rural wage index are eventually 
included, when applicable, in that rural wage index calculation. We 
note that this form of manipulation (hospitals canceling rural status 
to remove their wage data from the rural wage index calculation) 
resulted in the rural wage index for one state increasing by over 4 
percent between the FY 2020 proposed rule and the FY 2020 final rule. 
Based on our analysis, that figure could have been significantly 
greater (as high as 10 percent) in certain States. We further believe 
these proposed policies provide adequate time for hospitals to review 
their reclassification status and make appropriate decisions for future 
fiscal years. Hospitals that meet the proposed 1-year minimum 
requirement in proposed Sec.  412.103(g)(4) would have opportunity 
between the publication date of the final rule (and potential 
correction notices) and the end of the calendar year to evaluate 
whether to cancel or maintain their rural status for the next fiscal 
year.
---------------------------------------------------------------------------

    \758\ ``Lugar'' hospitals may reclassify as rural and retain the 
urban wage index deemed under section 1886(d)(8)(B) of the Act, as 
discussed in the FY 2017 IPPS/LTCH final rule (81 FR 56929).
---------------------------------------------------------------------------

    Comment: We received a comment stating strong support for CMS' 
actions to prevent hospitals from using 412.103 as a mechanism for 
statewide wage index manipulation. However, the commenter requested 
that this policy be limited only to hospitals that obtained rural 
reclassification after October 1, 2020. The commenter stated that CMS 
should allow hospitals with longstanding rural reclassification status 
to maintain an appropriate level of flexibility while appropriately 
restricting cancellations for hospitals that may engage in the form of 
wage index manipulation discussed in the proposed rule. Other 
commenters, while acknowledging CMS' policy motivations, suggested 
alternative revisions to the rural reclassification cancellation policy 
to avoid unfairly penalizing hospitals that are not motivated by the 
form of wage index manipulation discussed in the proposed rule. 
Specifically, a commenter requested CMS, rather than further limit a 
hospital's ability to cancel rural reclassification status, instead 
limit a hospital's ability to reapply for rural reclassification for a 
period of time following an approved for cancellation.
    Another commenter requested CMS exclude hospitals from the proposed 
cancellation policies if they meet a variety of conditions that would 
indicate they are not attempting to obtain their State's rural wage 
index while avoiding the inclusion of their hospital's data in the wage 
index calculations. This commenter stated the

[[Page 45187]]

proposed policies were too onerous, and should be modified to 
specifically target the behavior that CMS is addressing. The commenter 
also recommended excluding hospitals that maintained rural 
reclassification status for at least 2 consecutive years from the newly 
imposed restrictions of the proposed cancellation policy, and also 
suggested CMS explore a policy of making mid-year corrections to wage 
index values to ensure that hospitals that obtain rural 
reclassifications have their data included in its State's rural wage 
index calculations.
    Response: We appreciate the input from commenters. We believe that 
the comments received were generally supportive of CMS' action to limit 
the ability for hospitals to time rural reclassification and 
cancellations in order to receive a higher rural wage index without 
having their own data included in the rural wage index calculation. We 
have reviewed and taken into consideration the suggested modifications 
to our proposed policies. Certain suggestions, such as limiting a 
hospital's ability to reapply for rural reclassification status after 
recently cancelling a prior rural reclassification, may not be 
consistent with the statutory requirements regarding the effective date 
and approval criteria for rural reclassification applications. In our 
proposal to require a cancellation be submitted in the calendar year 
prior to the fiscal year it would become effective, we acknowledged 
this would add a significant amount of time to the current requirement 
at Sec.  412.103(g)(3). Currently, a cancellation request must be 
submitted at least 120 days prior to the end of a fiscal year to be 
effective for the upcoming fiscal year. Under our proposal, requests 
must be submitted approximately 152 days earlier (by December 31st). We 
understand that hospitals wish to have an opportunity to review data in 
the proposed rule to determine whether to maintain or cancel any 
particular reclassification status, including rural reclassifications 
under section Sec.  412.103. However, as discussed in the proposed rule 
(86 FR 25412) there may exist the potential for wage index manipulation 
by timing cancellation requests and new applications around the ``lock-
in'' date and the current 120 day deadline to submit rural 
reclassification cancellation requests. We proposed the policy of 
requiring rural reclassification cancellation requests to be submitted 
in the calendar year prior to the fiscal year it would become 
effective. However, if finalized, our proposal to require rural 
reclassification be held for one full year would mean that any hospital 
that requested cancellation effective for FY 2022 (that is, submitted a 
cancellation request on or before the June 2, 2021 deadline), and 
reapplied for rural reclassification after October 1, 2021, would not 
be eligible to cancel that new reclassification status until FY 2024 at 
the earliest, reducing the urgency to implement the additional 
revisions to the cancellation policy in FY 2022.
    In response to comments received, we believe it would be 
appropriate to delay and potentially revise our proposal to require 
cancellation requests be effective for the Federal fiscal year that 
begins in the calendar year after the calendar year in which the 
cancelation request is submitted in order to assure the policy 
effectively targets the form of wage index manipulation discussed 
previously.
    The current policy of requiring cancellation requests be submitted 
not less than 120 day prior to the end of the Federal fiscal year will 
remain in place while we evaluate alternative methods to obtain our 
policy goals. However, to address the potential for rural wage index 
manipulation in FY 2022 and future years, we are finalizing the 
proposed policy that rural reclassification be in effect for at least 1 
year before cancellation can be requested. Specifically, we are adding 
Sec.  412.103(g)(4) to state that for all written requests submitted by 
hospitals on or after October, 1, 2021 to cancel rural 
reclassifications, a hospital may cancel its rural reclassification by 
submitting a written request to the CMS Regional Office not less than 1 
calendar year after the effective date of the rural reclassification 
and not less than 120 days prior to the end of a Federal fiscal year. 
The hospital's cancellation of the classification is effective 
beginning with the next Federal fiscal year. We believe this policy 
will not affect hospitals with longstanding rural reclassification 
status, would not unduly burden hospitals that obtained rural 
reclassification status for reasons not involving the rural wage index 
calculations, and will effectively address the wage index manipulation 
issue in the upcoming fiscal years.
    We will continue to monitor rural reclassification applications and 
cancellation requests. We will take into consideration the comments we 
have so far received and, if necessary, make additional proposals to 
address this issue further in future fiscal years.
3. Finalization of Interim Final Rule With Comment Period on Provisions 
Related To Modification of Limitations on Redesignation by the Medicare 
Geographic Classification Review Board Interim Final Rule (CMS-1762-
IFC)
    In the interim final rule with comment period (IFC) (CMS-1762-IFC) 
simultaneously submitted for public inspection with the proposed rule, 
CMS made regulatory changes in order to align our policy with the 
decision in Bates. Specifically, the IFC revised the regulations at 
Sec.  412.230 to allow hospitals with a rural redesignation under 
section 1886(d)(8)(E) of the Act to reclassify under the MGCRB using 
the rural reclassified area as the geographic area in which the 
hospital is located effective with reclassifications beginning with FY 
2023. We stated we would also apply the policy in the IFC when deciding 
timely appeals before the Administrator of applications for 
reclassifications beginning with FY 2022 that were denied by the MGCRB 
due to the policy in effect prior to the IFC, which did not permit 
hospitals with rural redesignations to use the rural area's wage data 
for purposes of reclassifying under the MGCRB. In this section of this 
final rule, we are responding to the public comments that we received 
on these provisions in the May 10, 2021 IFC and finalizing the interim 
policies.
a. Background
i. Wage Index for Acute Care Hospitals Paid Under the Hospital 
Inpatient Prospective Payment System (IPPS)
    Under section 1886(d) of the Social Security Act (the Act), 
hospitals are paid based on prospectively set rates. To account for 
geographic area wage level differences, section 1886(d)(3)(E) of the 
Act requires that the Secretary of the Department of Health and Human 
Services (the Secretary) adjust the standardized amounts by a factor 
(established by the Secretary) reflecting the relative hospital wage 
level in the geographic area of the hospital, as compared to the 
national average hospital wage level. We currently define hospital 
labor market areas based on the delineations of statistical areas 
established by the Office of Management and Budget (OMB). The current 
statistical areas (which were implemented beginning with FY 2015) are 
based on revised OMB delineations issued on February 28, 2013, in OMB 
Bulletin No. 13-01, with updates as reflected in OMB Bulletins Nos. 15-
01, 17-01, and 18-04. We refer readers to the FY 2015 IPPS/LTCH PPS 
final rule (79 FR 49951 through 49963) for a full

[[Page 45188]]

discussion of our implementation of the new OMB labor market area 
delineations beginning with the FY 2015 wage index, and to the FY 2021 
IPPS/LTCH PPS final rule (85 FR 58743 through 58755) for a discussion 
of the latest updates to these delineations.
    Section 1886(d)(3)(E) of the Act requires the Secretary to update 
the wage index of hospitals annually, and to base the update on a 
survey of wages and wage-related costs of short-term, acute care 
hospitals. Under section 1886(d)(8)(D) of the Act, the Secretary is 
required to adjust the standardized amounts so as to ensure that 
aggregate payments under the IPPS, after implementation of the 
provisions of sections 1886(d)(8)(B), 1886(d)(8)(C), and 1886(d)(10) of 
the Act, regarding geographic reclassification of hospitals, are equal 
to the aggregate prospective payments that would have been made absent 
these provisions.
ii. Hospital Reclassifications Under Sections 1886(d)(8)(E) and 
1886(d)(10) of the Act
    Hospitals may seek to have their geographic designation 
reclassified. Under section 1886(d)(8)(E) of the Act, a qualifying 
prospective payment hospital located in an urban area may apply for 
rural status. Specifically, section 1886(d)(8)(E) of the Act states 
that ``[f]or purposes of this subsection, not later than 60 days after 
the receipt of an application (in a form and manner determined by the 
Secretary) from a subsection (d) hospital described in clause (ii), the 
Secretary shall treat the hospital as being located in the rural area 
(as defined in paragraph (2)(D)) of the state in which the hospital is 
located.'' The regulations governing these geographic redesignations 
are codified in Sec.  412.103, and such hospitals are therefore 
commonly referred to as ``Sec.  412.103 hospitals.''
    In a separate process, hospitals may also reclassify for purposes 
of the wage index under the IPPS under section 1886(d)(10) of the Act 
by applying to the Medicare Geographic Classification Review Board 
(MGCRB). Hospitals must apply to the MGCRB to reclassify not later than 
13 months prior to the start of the fiscal year for which 
reclassification is sought, generally by September 1. (However, we note 
that this deadline has been extended for applications for FY 2022 
reclassifications to 15 days after the public display date of the FY 
2021 IPPS/LTCH final rule at the Office of the Federal Register, using 
our authority under section 1135(b)(5) the Act due to the COVID-19 
Public Health Emergency.) Generally, hospitals must be proximate to the 
labor market area to which they are seeking reclassification and must 
demonstrate characteristics similar to hospitals located in that area. 
The MGCRB issues its decisions by the end of February for 
reclassifications that become effective for the following fiscal year 
(beginning October 1). The regulations applicable to reclassifications 
by the MGCRB are located in Sec. Sec.  412.230 through 412.280.
    Prior to a court decision in Geisinger Community Medical v. 
Secretary, United States Department of Health and Human Services, 794 
F.3d 383 (3d Cir. 2015) (``Geisinger''), hospitals were only able to 
hold one reclassification at a time: Either under Sec.  412.103 or 
through the MGCRB under section 1886(d)(10) of the Act. The Court of 
Appeals in Geisinger ruled that CMS' prohibition of dual Sec.  412.103 
and MGCRB reclassifications was unlawful, since section 
1886(d)(8)(E)(i) of the Act requires that ``the Secretary shall treat 
the hospital as being located in the rural area,'' inclusive of MGCRB 
reclassification purposes. Therefore, on April 21, 2016, we published 
an interim final rule with comment period (the April 21, 2016 IFC) in 
the Federal Register (81 FR 23428 through 23438) that included 
provisions amending our regulations to allow hospitals nationwide to 
have simultaneous Sec.  412.103 and MGCRB reclassifications.
b. Provisions of the Interim Final Rule With Comment Period
    Pursuant to our April 21, 2016 IFC, for reclassifications effective 
beginning FY 2018, a hospital may acquire rural status under Sec.  
412.103 and subsequently apply for a reclassification under the MGCRB 
using the distance and average hourly wage criteria designated for 
rural hospitals. Hospitals with a Sec.  412.103 redesignation seeking 
additional reclassification under the MGCRB use the rural distance and 
average hourly wage criteria under Sec.  412.230(b)(1), (d)(1)(iii)(C), 
and (d)(1)(iv)(E). For example, under our policy prior to the issuance 
of the May 10, 2021 IFC, a Sec.  412.103 hospital geographically 
located in the urban CBSA of Buffalo-Cheektowaga, NY seeking to 
reclassify under the MGCRB would demonstrate that their wages are at 
least 106 percent (and not 108 percent, as urban hospitals must 
demonstrate) of the average hourly wage of Buffalo-Cheektowaga, NY, to 
meet the criteria at Sec.  412.230(d)(1)(iii)(C).
    However, our policy prior to the issuance of the May 10, 2021 IFC 
compared the average hourly wage of a Sec.  412.103 hospital to its 
geographic urban location, rather than the rural reclassified area, for 
purposes of satisfying certain wage comparison criteria. In response to 
a comment on our April 21, 2016 IFC (81 FR 56925), we stated: ``The 
commenter is correct that the rural distance and average hourly wage 
criteria will be used for hospitals with a Sec.  412.103 redesignation. 
However, the commenter's statement that the average hourly wage of a 
hospital with a Sec.  412.103 redesignation is compared to the average 
hourly wage of hospitals in the State's rural area under Sec.  
412.230(d)(1)(iii)(C) is incorrect. Instead, the hospital's average 
hourly wage would be compared to the average hourly wage of all other 
hospitals in its urban geographic location using the rural distance and 
average hourly wage criteria.''
    On May 14, 2020, the United States District Court for the District 
of Columbia issued a decision in Bates. Bates County Memorial Hospital 
and five other geographically urban hospitals were reclassified to 
rural under Sec.  412.103. They also applied for reclassification under 
the MGCRB, but were denied because their wages were not at least 106 
percent of the geographic urban area in which the hospitals were 
located. Each of the hospitals' average hourly wages were at least 106 
percent of the 3-year average hourly wage of all other hospitals in the 
rural area of the state in which the hospitals are located.
    The court agreed with the Plaintiffs that the statute at section 
1886(d)(8)(E)(i) of Act requires that CMS treat qualifying hospitals as 
being located in the rural area for purposes of section 1886(d) of the 
Act, including MGCRB reclassification. The Bates decision requires that 
CMS consider the rural area to be the area in which the hospital is 
located for the wage comparisons required for MGCRB reclassifications. 
For example, pursuant to Bates, a Sec.  412.103 hospital geographically 
located in the urban CBSA of Buffalo-Cheektowaga, NY seeking to 
reclassify under the MGCRB would demonstrate that their wages are at 
least 106 percent of the average hourly wage of rural NY, rather than 
that of Buffalo-Cheektowaga.
    As a result of the Bates court's decision, we revised our policy in 
the May 10, 2021 IFC so that the redesignated rural area, and not the 
hospital's geographic urban area, are considered the area a Sec.  
412.103 hospital is located in for purposes of meeting MGCRB 
reclassification criteria. Similarly, we revised the regulations to 
consider the redesignated rural area, and not the geographic urban 
area, as

[[Page 45189]]

the area a Sec.  412.103 hospital is located in for the prohibition at 
Sec.  412.230(a)(5)(i) on reclassifying to an area with a pre-
reclassified average hourly wage lower than the pre-reclassified 
average hourly wage for the area in which the hospital is located.
    Specifically, to align our policy with the court's decision in 
Bates, we amended the regulations at Sec.  412.230(a)(1) by adding 
(a)(1)(iii) to state that an urban hospital that has been granted 
redesignation as rural under Sec.  412.103 is considered to be located 
in the rural area of the state for the purposes of this section. We 
also made conforming changes to the regulation at Sec.  
412.230(a)(5)(i) because Sec.  412.230(a)(1) excepts paragraph (a)(5). 
Because Sec.  412.230(a)(1) excepts paragraph (a)(5), we believed it 
was necessary to make a specific conforming revision to Sec.  
412.230(a)(5)(i), in addition to the general rule at Sec.  
412.230(a)(1)(iii), to clarify that the general rule at Sec.  
412.230(a)(1)(iii) applies to Sec.  412.230(a)(5)(i) as well. That is, 
we amended the regulation at Sec.  412.230(a)(5)(i) to add language 
stating that an urban hospital that has been granted redesignation as 
rural under Sec.  412.103 is considered to be located in the rural area 
of the state for the purposes of paragraph (a)(5)(i).
    These changes implemented the Bates court's interpretation of the 
requirement at section 1886(d)(8)(E)(i) of the Act that ``the Secretary 
shall treat the hospital as being located in the rural area.'' That is, 
effective with our in the May 10, 2021 IFC, a Sec.  412.103 hospital 
would be considered to be located in the rural area of the state for 
all purposes of MGCRB reclassification, including the average hourly 
wage comparisons required by Sec.  412.230(a)(5)(i) and (d)(1)(iii)(C). 
For example, for purposes of Sec.  412.230(d)(1)(iii)(C), the Sec.  
412.103 hospital compares its average hourly wage to the average hourly 
wage of all other hospitals in the state's rural area. In addition, for 
purposes of Sec.  412.230(a)(5)(i), a Sec.  412.103 hospital may not be 
redesignated to another area if the pre-classified average hourly wage 
for that area is lower than the pre-reclassified average hourly wage of 
the rural area of the state in which the hospital is located (thus, a 
Sec.  412.103 hospital could potentially reclassify to any area with a 
pre-reclassified average hourly wage that is higher than the pre-
reclassified average hourly wage for the rural area of the state, if it 
meets all other applicable reclassification criteria).
    Therefore, effective for reclassification applications due to the 
MGCRB on September 1, 2021, for reclassification first effective for FY 
2023, a Sec.  412.103 hospital could apply for a reclassification under 
the MGCRB using the state's rural area as the area in which the 
hospital is located. We stated in the May 10, 2021 IFC that we would 
also apply the policy when deciding timely appeals before the 
Administrator under Sec.  412.278 for reclassifications beginning in FY 
2022 that were denied by the MGCRB due to existing policy, which did 
not permit Sec.  412.103 hospitals to be considered located in the 
state's rural area.
    Comment: We received comments in support of our IFC modifying 
limitations on redesignation by the MGCRB. A commenter requested 
clarification regarding the CBSA column typically included in the Three 
Year MGCRB Reclassification Data File that is released in August each 
year. The commenter questioned if the CBSA column for hospitals with a 
Sec.  412.103 reclassification will reflect the redesignated rural CBSA 
that would now be used when determining if a hospital meets the MGCRB 
reclassification criteria, or the hospital's geographic urban CBSA. 
Similarly, another commenter questioned if the Sec.  412.103 hospital 
applying for MGCRB reclassification should include other Sec.  412.103 
hospitals in the rural average hourly wage for this regulation for 
purposes of the home area wage test at Sec.  412.230(d)(1)(iii)(C). 
This commenter suggested that CMS should require hospitals to compare 
their average hourly wage against the average hourly wage calculated 
only for those hospitals actually located in the rural area, exclusive 
of hospitals with 412.103 rural redesignations, for simplicity of 
applying this policy. The commenter explained that because hospitals 
can obtain Sec.  412.103 rural redesignation at any time, it may not be 
clear at the time the MGCRB is reviewing reclassification applications 
which hospitals have obtained Sec.  412.103 rural reclassifications 
since the publication of the most recent IPPS tables.
    Response: We thank the commenters for their support. In response to 
the commenter's question regarding which CBSA will be published in the 
Three Year MGCRB Reclassification Data File used for MGCRB 
reclassification, we are clarifying that the hospital's geographic 
urban CBSA will continue to be listed. Therefore, a Sec.  412.103 
hospital applying for MGCRB reclassification would not include other 
Sec.  412.103 hospitals in the rural average hourly wage for this 
regulation for purposes of the home area wage test at Sec.  
412.230(d)(1)(iii)(C). For the reasons the second commenter suggested, 
we believe this is the most clear and straightforward application of 
this policy to implement the court's decision in Bates. If we were to 
require that the wages and hours of all hospitals with Sec.  412.103 
reclassifications be included in the rural area for purposes of the 
home area wage test, we would need to list the rural CBSA as the 
geographic CBSA for hospitals with Sec.  412.103 reclassifications in 
the Three Year MGCRB Reclassification Data File. However, as the second 
commenter noted, since Sec.  412.103 reclassifications may be obtained 
at any time, it would not be clear if the Three Year MGCRB 
Reclassification Data File accurately captures all hospitals with Sec.  
412.103 reclassifications.
    Comment: A commenter noted that the IFC states that a hospital 
reclassified under Sec.  412.103 could potentially reclassify to any 
area with a prereclassified average hourly wage that is higher than the 
pre-reclassified average hourly wage for the rural area of the state 
for purposes of the regulation at Sec.  412.230(a)(5)(i). The commenter 
asserted that CMS' use of the word ``could'' in this context seems to 
suggest that CMS would allow the hospital to use either its home 
average hourly wage or the rural average hourly wage for purposes of 
the regulation at Sec.  412.230(a)(5)(i). The commenter suggested that 
CMS allow both comparison options, because the rural average hourly 
wage may occasionally be higher than the hospital's home urban area's 
average hourly wage, such as in the state of Massachusetts.
    Response: The commenter's interpretation of our policy is correct. 
While the court's decision in Bates requires CMS to permit hospitals to 
reclassify to any area with a prereclassified average hourly wage that 
is higher than the pre-reclassified average hourly wage for the rural 
area of the state, we do not believe that we are required to limit 
hospitals from using their geographic home area for purposes of the 
regulation at Sec.  412.230(a)(5)(i). Therefore, we are clarifying that 
we would allow hospitals to reclassify to an area with an average 
hourly wage that is higher than the average hourly wage of either the 
hospital's geographic home area or the rural area.
    Comment: A commenter questioned whether a hospital reclassified 
under Sec.  412.103 should include its own wage data and the wage data 
of other hospitals reclassified under Sec.  412.103 in determining the 
rural average hourly wage for purposes of the regulation at Sec.  
412.230(a)(5)(i). The commenter suggested that CMS not require this, 
since including hospitals reclassified under Sec.  412.103 in the rural 
average

[[Page 45190]]

hourly wage would change the average hourly wage from the published 
value in the final rule tables. Accordingly, the commenter requested 
that CMS not include hospitals reclassified under Sec.  412.103 in the 
rural average hourly wage for Sec.  412.230(a)(5)(i) for simplicity in 
applying this policy.
    Response: We agree with the commenter. In calculating the rural 
area's average hourly wage for purposes of applying Sec.  
412.230(a)(5)(i), we are clarifying that we are not requiring hospitals 
to include the wage data of hospitals with Sec.  412.103 rural 
reclassifications. For the reasons the commenter stated, we believe 
this is the simplest and most clear application of the policy the court 
required in Bates.
    In this final rule, we are finalizing the provisions of the May 10, 
2021 IFC without modification, including our revisions to the 
regulations at Sec.  412.230 to allow hospitals with a rural 
redesignation under section 1886(d)(8)(E) of the Act to reclassify 
under the MGCRB using the rural reclassified area as the geographic 
area in which the hospital is located effective with reclassifications 
beginning with FY 2023.

L. Process for Requests for Wage Index Data Corrections

1. Process for Hospitals To Request Wage Index Data Corrections
    The preliminary, unaudited Worksheet S-3 wage data files for the 
proposed FY 2022 wage index were made available on May 18, 2020 and the 
preliminary CY 2019 occupational mix data files for the proposed FY 
2022 wage index were made available on September 8, 2020 through the 
internet on the CMS website at: https://www.cms.gov/medicaremedicare-fee-service-paymentacuteinpatientppswage-index-files/fy-2022-wage-index-home-page.
    On January 29, 2021, we posted a public use file (PUF) at: https://www.cms.gov/medicaremedicare-fee-service-paymentacuteinpatientppswage-index-files/fy-2022-wage-index-home-page containing FY 2022 wage index 
data available as of January 28, 2021. This PUF contains a tab with the 
Worksheet S-3 wage data (which includes Worksheet S-3, Parts II and III 
wage data from cost reporting periods beginning on or after October 1, 
2017 through September 30, 2018; that is, FY 2018 wage data), a tab 
with the occupational mix data (which includes data from the CY 2019 
occupational mix survey, Form CMS-10079), a tab containing the 
Worksheet S-3 wage data of hospitals deleted from the January 29, 2021 
wage data PUF, and a tab containing the CY 2019 occupational mix data 
of the hospitals deleted from the January 29, 2021 occupational mix 
PUF. In a memorandum dated January 22, 2021, we instructed all MACs to 
inform the IPPS hospitals that they service of the availability of the 
January 29, 2021 wage index data PUFs, and the process and timeframe 
for requesting revisions in accordance with the FY 2022 Wage Index 
Timetable.
    In the interest of meeting the data needs of the public, beginning 
with the proposed FY 2009 wage index, we post an additional PUF on the 
CMS website that reflects the actual data that are used in computing 
the proposed wage index. The release of this file does not alter the 
current wage index process or schedule. We notify the hospital 
community of the availability of these data as we do with the current 
public use wage data files through our Hospital Open Door Forum. We 
encourage hospitals to sign up for automatic notifications of 
information about hospital issues and about the dates of the Hospital 
Open Door Forums at the CMS website at: https://www.cms.gov/Outreach-and-Education/Outreach/OpenDoorForums.
    In a memorandum dated April 14, 2020, we instructed all MACs to 
inform the IPPS hospitals that they service of the availability of the 
preliminary wage index data files posted on May 18, 2020, the 
requirement to submit the new CY 2019 occupational mix surveys by 
August 3, 2020 and the process and timeframe for requesting revisions. 
Subsequently, in a memorandum dated July 31, 2020, we revised the date 
hospitals were required to submit the new CY 2019 occupational mix 
surveys from August 3, 2020 to September 3, 2020, the date the 
preliminary CY 2019 occupational mix survey data files were scheduled 
to be posted from August 6, 2020 to September 8, 2020 and the timeframe 
for requesting revisions to the new CY 2019 occupational mix survey 
data.
    If a hospital wished to request a change to its data as shown in 
the May 18, 2020 preliminary wage data files (or September 8 2020 
preliminary CY 2019 occupational mix survey data files), the hospital 
had to submit corrections along with complete, detailed supporting 
documentation to its MAC so that the MAC received them by September 3, 
2020 (or by September 10, 2020 for preliminary CY 2019 occupational mix 
survey data files). Hospitals were notified of these deadlines and of 
all other deadlines and requirements, including the requirement to 
review and verify their data as posted in the preliminary wage index 
data files on the internet, through the letters sent to them by their 
MACs. November 16, 2020 was the deadline for MACs to complete all desk 
reviews for hospital wage and occupational mix data and transmit 
revised Worksheet S-3 wage data and occupational mix data to CMS.
    November 5, 2020 was the date by when MACs notified State hospital 
associations regarding hospitals that failed to respond to issues 
raised during the desk reviews. Additional revisions made by the MACs 
were transmitted to CMS throughout January 2021. CMS published the wage 
index PUFs that included hospitals' revised wage index data on January 
29, 2021. Hospitals had until February 16, 2021, to submit requests to 
the MACs to correct errors in the January 29, 2021 PUF due to CMS or 
MAC mishandling of the wage index data, or to revise desk review 
adjustments to their wage index data as included in the January 29, 
2021 PUF. Hospitals also were required to submit sufficient 
documentation to support their requests. Hospitals' requests and 
supporting documentation must be received by the MAC by the February 
deadline (that is, by February 16, 2021 for the FY 2021 wage index).
    After reviewing requested changes submitted by hospitals, MACs were 
required to transmit to CMS any additional revisions resulting from the 
hospitals' reconsideration requests by March 19, 2021. Under our 
current policy as adopted in the FY 2018 IPPS/LTCH PPS final rule (82 
FR 38153), the deadline for a hospital to request CMS intervention in 
cases where a hospital disagreed with a MAC's handling of wage data on 
any basis (including a policy, factual, or other dispute) was April 2, 
2021. Data that were incorrect in the preliminary or January 29, 2021 
wage index data PUFs, but for which no correction request was received 
by the February 16, 2021 deadline, are not considered for correction at 
this stage. In addition, April 2, 2021 was the deadline for hospitals 
to dispute data corrections de by CMS of which the hospital was 
notified after the January 29, 2021 PUF and at least 14 calendar days 
prior to April 2, 2021 (that is, March 19, 2021), that do not arise 
from a hospital's request for revisions. The hospital's request and 
supporting documentation must be received by CMS (and a copy received 
by the MAC) by the April deadline (that is, by April 2, 2021 for the FY 
2022 wage index). We refer readers to the wage index timeline for 
complete details.
    Hospitals were given the opportunity to examine Table 2 associated 
with the proposed rule, which is listed in section VI. of the Addendum 
to the proposed

[[Page 45191]]

rule and available via the internet on the CMS website at: https://www.cms.gov/medicare/acute-inpatient-pps/fy-2022-ipps-proposed-rule-home-page. Table 2 associated with the proposed rule contained each 
hospital's proposed adjusted average hourly wage used to construct the 
wage index values for the past 3 years, including the proposed FY 2022 
wage index which was constructed from FY 2018 data. We noted in the 
proposed rule that the proposed hospital average hourly wages shown in 
Table 2 only reflected changes made to a hospital's data that were 
transmitted to CMS by early February 2021.
    We posted the final wage index data PUFs on April 30, 2021 on the 
CMS website at: https://www.cms.gov/medicaremedicare-fee-service-paymentacuteinpatientppswage-index-files/fy-2022-wage-index-home-page. 
The April 2021 PUFs are made available solely for the limited purpose 
of identifying any potential errors made by CMS or the MAC in the entry 
of the final wage index data that resulted from the correction process 
previously described (the process for disputing revisions submitted to 
CMS by the MACs by March 19, 2021, and the process for disputing data 
corrections made by CMS that did not arise from a hospital's request 
for wage data revisions as discussed earlier).
    After the release of the April 2021 wage index data PUFs, changes 
to the wage and occupational mix data could only be made in those very 
limited situations involving an error by the MAC or CMS that the 
hospital could not have known about before its review of the final wage 
index data files. Specifically, neither the MAC nor CMS will approve 
the following types of requests:
     Requests for wage index data corrections that were 
submitted too late to be included in the data transmitted to CMS by the 
MACs on or before March 19, 2021.
     Requests for correction of errors that were not, but could 
have been, identified during the hospital's review of the January 29, 
2021 wage index PUFs.
     Requests to revisit factual determinations or policy 
interpretations made by the MAC or CMS during the wage index data 
correction process.
    If, after reviewing the April 2021 final wage index data PUFs, a 
hospital believed that its wage or occupational mix data were incorrect 
due to a MAC or CMS error in the entry or tabulation of the final data, 
the hospital was given the opportunity to notify both its MAC and CMS 
regarding why the hospital believed an error exists and provide all 
supporting information, including relevant dates (for example, when it 
first became aware of the error). The hospital was required to send its 
request to CMS and to the MAC so that it was received no later than May 
28, 2021. May 28, 2021 was also the deadline for hospitals to dispute 
data corrections made by CMS of which the hospital is notified on or 
after 13 calendar days prior to April 2, 2021 (that is, March 20, 
2021), and at least 14 calendar days prior to May 28, 2021 (that is, 
May 14, 2021), that did not arise from a hospital's request for 
revisions. (Data corrections made by CMS of which a hospital was 
notified on or after 13 calendar days prior to May 28, 2021 (that is, 
May 15, 2021) may be appealed to the Provider Reimbursement Review 
Board (PRRB)). In accordance with the FY 2022 wage index timeline 
posted on the CMS website at: https://www.cms.gov/files/document/fy-2022-hospital-wage-index-development-time-table.pdf, the May appeals 
were required to be sent via mail and email to CMS and the MACs. We 
refer readers to the wage index timeline for complete details.
    Verified corrections to the wage index data received timely (that 
is, by May 28, 2021) by CMS and the MACs were incorporated into the 
final FY 2022 wage index, which will be effective October 1, 2021.
    We created the processes previously described to resolve all 
substantive wage index data correction disputes before we finalize the 
wage and occupational mix data for the FY 2022 payment rates. 
Accordingly, hospitals that did not meet the procedural deadlines set 
forth earlier will not be afforded a later opportunity to submit wage 
index data corrections or to dispute the MAC's decision with respect to 
requested changes. Specifically, our policy is that hospitals that do 
not meet the procedural deadlines as previously set forth (requiring 
requests to MACs by the specified date in February and, where such 
requests are unsuccessful, requests for intervention by CMS by the 
specified date in April) will not be permitted to challenge later, 
before the PRRB, the failure of CMS to make a requested data revision. 
We refer readers also to the FY 2000 IPPS final rule (64 FR 41513) for 
a discussion of the parameters for appeals to the PRRB for wage index 
data corrections. As finalized in the FY 2018 IPPS/LTCH PPS final rule 
(82 FR 38154 through 38156), this policy also applies to a hospital 
disputing corrections made by CMS that do not arise from a hospital's 
request for a wage index data revision. That is, a hospital disputing 
an adjustment made by CMS that did not arise from a hospital's request 
for a wage index data revision is required to request a correction by 
the first applicable deadline. Hospitals that do not meet the 
procedural deadlines set forth earlier will not be afforded a later 
opportunity to submit wage index data corrections or to dispute CMS' 
decision with respect to changes.
    Again, we believe the wage index data correction process described 
earlier provides hospitals with sufficient opportunity to bring errors 
in their wage and occupational mix data to the MAC's attention. 
Moreover, because hospitals had access to the final wage index data 
PUFs by late April 2021, they have an opportunity to detect any data 
entry or tabulation errors made by the MAC or CMS before the 
development and publication of the final FY 2022 wage index by August 
2021, and the implementation of the FY 2022 wage index on October 1, 
2021. Given these processes, the wage index implemented on October 1 
should be accurate. Nevertheless, in the event that errors are 
identified by hospitals and brought to our attention after May 28, 
2021, we retain the right to make midyear changes to the wage index 
under very limited circumstances.
    Specifically, in accordance with 42 CFR 412.64(k)(1) of our 
regulations, we make midyear corrections to the wage index for an area 
only if a hospital can show that: (1) The MAC or CMS made an error in 
tabulating its data; and (2) the requesting hospital could not have 
known about the error or did not have an opportunity to correct the 
error, before the beginning of the fiscal year. For purposes of this 
provision, ``before the beginning of the fiscal year'' means by the May 
deadline for making corrections to the wage data for the following 
fiscal year's wage index (for example, May 28, 2021 for the FY 2022 
wage index). This provision is not available to a hospital seeking to 
revise another hospital's data that may be affecting the requesting 
hospital's wage index for the labor market area. As indicated earlier, 
because CMS makes the wage index data available to hospitals on the CMS 
website prior to publishing both the proposed and final IPPS rules, and 
the MACs notify hospitals directly of any wage index data changes after 
completing their desk reviews, we do not expect that midyear 
corrections will be necessary. However, under our current policy, if 
the correction of a data error changes the wage index value for an 
area, the revised wage index value will be effective prospectively from 
the date the correction is made.

[[Page 45192]]

    In the FY 2006 IPPS final rule (70 FR 47385 through 47387 and 
47485), we revised 42 CFR 412.64(k)(2) to specify that, effective on 
October 1, 2005, that is, beginning with the FY 2006 wage index, a 
change to the wage index can be made retroactive to the beginning of 
the Federal fiscal year only when CMS determines all of the following: 
(1) The MAC or CMS made an error in tabulating data used for the wage 
index calculation; (2) the hospital knew about the error and requested 
that the MAC and CMS correct the error using the established process 
and within the established schedule for requesting corrections to the 
wage index data, before the beginning of the fiscal year for the 
applicable IPPS update (that is, by the May 28, 2021 deadline for the 
FY 2022 wage index); and (3) CMS agreed before October 1 that the MAC 
or CMS made an error in tabulating the hospital's wage index data and 
the wage index should be corrected.
    In those circumstances where a hospital requested a correction to 
its wage index data before CMS calculated the final wage index (that 
is, by the May 28, 2021 deadline for the FY 2022 wage index), and CMS 
acknowledges that the error in the hospital's wage index data was 
caused by CMS' or the MAC's mishandling of the data, we believe that 
the hospital should not be penalized by our delay in publishing or 
implementing the correction. As with our current policy, we indicated 
that the provision is not available to a hospital seeking to revise 
another hospital's data. In addition, the provision cannot be used to 
correct prior years' wage index data; it can only be used for the 
current Federal fiscal year. In situations where our policies would 
allow midyear corrections other than those specified in 42 CFR 
412.64(k)(2)(ii), we continue to believe that it is appropriate to make 
prospective-only corrections to the wage index.
    We note that, as with prospective changes to the wage index, the 
final retroactive correction will be made irrespective of whether the 
change increases or decreases a hospital's payment rate. In addition, 
we note that the policy of retroactive adjustment will still apply in 
those instances where a final judicial decision reverses a CMS denial 
of a hospital's wage index data revision request.
2. Process for Data Corrections by CMS After the January 29 Public Use 
File (PUF)
    The process set forth with the wage index timeline discussed in 
section III.L.1. of the preamble of this final rule allows hospitals to 
request corrections to their wage index data within prescribed 
timeframes. In addition to hospitals' opportunity to request 
corrections of wage index data errors or MACs' mishandling of data, CMS 
has the authority under section 1886(d)(3)(E) of the Act to make 
corrections to hospital wage index and occupational mix data in order 
to ensure the accuracy of the wage index. As we explained in the FY 
2016 IPPS/LTCH PPS final rule (80 FR 49490 through 49491) and the FY 
2017 IPPS/LTCH PPS final rule (81 FR 56914), section 1886(d)(3)(E) of 
the Act requires the Secretary to adjust the proportion of hospitals' 
costs attributable to wages and wage-related costs for area differences 
reflecting the relative hospital wage level in the geographic areas of 
the hospital compared to the national average hospital wage level. We 
believe that, under section 1886(d)(3)(E) of the Act, we have 
discretion to make corrections to hospitals' data to help ensure that 
the costs attributable to wages and wage-related costs in fact 
accurately reflect the relative hospital wage level in the hospitals' 
geographic areas.
    We have an established multistep, 15-month process for the review 
and correction of the hospital wage data that is used to create the 
IPPS wage index for the upcoming fiscal year. Since the origin of the 
IPPS, the wage index has been subject to its own annual review process, 
first by the MACs, and then by CMS. As a standard practice, after each 
annual desk review, CMS reviews the results of the MACs' desk reviews 
and focuses on items flagged during the desk review, requiring that, if 
necessary, hospitals provide additional documentation, adjustments, or 
corrections to the data. This ongoing communication with hospitals 
about their wage data may result in the discovery by CMS of additional 
items that were reported incorrectly or other data errors, even after 
the posting of the January 29 PUF, and throughout the remainder of the 
wage index development process. In addition, the fact that CMS analyzes 
the data from a regional and even national level, unlike the review 
performed by the MACs that review a limited subset of hospitals, can 
facilitate additional editing of the data that may not be readily 
apparent to the MACs. In these occasional instances, an error may be of 
sufficient magnitude that the wage index of an entire CBSA is affected. 
Accordingly, CMS uses its authority to ensure that the wage index 
accurately reflects the relative hospital wage level in the geographic 
area of the hospital compared to the national average hospital wage 
level, by continuing to make corrections to hospital wage data upon 
discovering incorrect wage data, distinct from instances in which 
hospitals request data revisions.
    We note that CMS corrects errors to hospital wage data as 
appropriate, regardless of whether that correction will raise or lower 
a hospital's average hourly wage. For example, as discussed in section 
III.C. of the preamble of the FY 2019 IPPS/LTCH PPS final rule (83 FR 
41364), in situations where a hospital did not have documentable 
salaries, wages, and hours for housekeeping and dietary services, we 
imputed estimates, in accordance with policies established in the FY 
2015 IPPS/LTCH PPS final rule (79 FR 49965 through 49967). Furthermore, 
if CMS discovers after conclusion of the desk review, for example, that 
a MAC inadvertently failed to incorporate positive adjustments 
resulting from a prior year's wage index appeal of a hospital's wage-
related costs such as pension, CMS would correct that data error and 
the hospital's average hourly wage would likely increase as a result.
    While we maintain CMS' authority to conduct additional review and 
make resulting corrections at any time during the wage index 
development process, in accordance with the policy finalized in the FY 
2018 IPPS/LTCH PPS final rule (82 FR 38154 through 38156) and as first 
implemented with the FY 2019 wage index (83 FR 41389), hospitals are 
able to request further review of a correction made by CMS that did not 
arise from a hospital's request for a wage index data correction. 
Instances where CMS makes a correction to a hospital's data after the 
January 29 PUF based on a different understanding than the hospital 
about certain reported costs, for example, could potentially be 
resolved using this process before the final wage index is calculated. 
We believe this process and the timeline for requesting review of such 
corrections (as described earlier and in the FY 2018 IPPS/LTCH PPS 
final rule) promote additional transparency to instances where CMS 
makes data corrections after the January 29 PUF, and provide 
opportunities for hospitals to request further review of CMS changes in 
time for the most accurate data to be reflected in the final wage index 
calculations. These additional appeals opportunities are described 
earlier and in the FY 2022 Wage Index Development Time Table, as well 
as in the FY 2018 IPPS/LTCH PPS final rule (82 FR 38154 through 38156).

[[Page 45193]]

M. Labor-Related Share for the FY 2022 Wage Index

    Section 1886(d)(3)(E) of the Act directs the Secretary to adjust 
the proportion of the national prospective payment system base payment 
rates that are attributable to wages and wage-related costs by a factor 
that reflects the relative differences in labor costs among geographic 
areas. It also directs the Secretary to estimate from time to time the 
proportion of hospital costs that are labor-related and to adjust the 
proportion (as estimated by the Secretary from time to time) of 
hospitals' costs that are attributable to wages and wage-related costs 
of the DRG prospective payment rates. We refer to the portion of 
hospital costs attributable to wages and wage-related costs as the 
labor-related share. The labor-related share of the prospective payment 
rate is adjusted by an index of relative labor costs, which is referred 
to as the wage index.
    Section 403 of Public Law 108-173 amended section 1886(d)(3)(E) of 
the Act to provide that the Secretary must employ 62 percent as the 
labor-related share unless this would result in lower payments to a 
hospital than would otherwise be made. However, this provision of 
Public Law 108-173 did not change the legal requirement that the 
Secretary estimate from time to time the proportion of hospitals' costs 
that are attributable to wages and wage-related costs. Thus, hospitals 
receive payment based on either a 62-percent labor-related share, or 
the labor-related share estimated from time to time by the Secretary, 
depending on which labor-related share resulted in a higher payment.
    In the FY 2018 IPPS/LTCH PPS final rule (82 FR 38158 through 
38175), we rebased and revised the hospital market basket. We 
established a 2014-based IPPS hospital market basket to replace the FY 
2010-based IPPS hospital market basket, effective October 1, 2017. 
Using the 2014-based IPPS market basket, we finalized a labor-related 
share of 68.3 percent for discharges occurring on or after October 1, 
2017. In addition, in FY 2018, we implemented this revised and rebased 
labor-related share in a budget neutral manner (82 FR 38522). However, 
consistent with section 1886(d)(3)(E) of the Act, we did not take into 
account the additional payments that would be made as a result of 
hospitals with a wage index less than or equal to 1.0000 being paid 
using a labor-related share lower than the labor-related share of 
hospitals with a wage index greater than 1.0000. In the FY 2021 IPPS/
LTCH PPS final rule (85 FR 58793), for FY 2021, we continued to use a 
labor-related share of 68.3 percent for discharges occurring on or 
after October 1, 2020.
    For FY 2022, as described in section IV. of the preamble of the FY 
2022 IPPS/LTCH PPS proposed rule (86 FR 25416 through 25417), we 
proposed to rebase and revise the IPPS market basket reflecting 2018 
data. We also proposed to recalculate the labor-related share for 
discharges occurring on or after October 1, 2021 using the proposed 
2018-based IPPS market basket. As discussed in Appendix A of the 
proposed rule, we proposed this rebased and revised labor related share 
in a budget neutral manner. However, consistent with section 
1886(d)(3)(E) of the Act, we did not take into account the additional 
payments that would be made as a result of hospitals with a wage index 
less than or equal to 1.0000 being paid using a labor-related share 
lower than the labor-related share of hospitals with a wage index 
greater than 1.0000. We refer readers to section IV. of the preamble of 
this final rule and Appendix A for our finalized policies for the 2018-
based IPPS market basket.
    The labor-related share is used to determine the proportion of the 
national IPPS base payment rate to which the area wage index is 
applied. We include a cost category in the labor-related share if the 
costs are labor intensive and vary with the local labor market. As 
described in section IV. of the preamble of the proposed rule, 
beginning with FY 2022, we proposed to include in the labor-related 
share the national average proportion of operating costs that are 
attributable to the following cost categories in the proposed 2018-
based IPPS market basket: Wages and Salaries; Employee Benefits; 
Professional Fees: Labor-Related; Administrative and Facilities Support 
Services; Installation, Maintenance, and Repair Services; and All Other 
Labor-Related Services, as measured in the proposed 2018-based IPPS 
market basket. Therefore, for FY 2022, we proposed to use a labor-
related share of 67.6 percent for discharges occurring on or after 
October 1, 2021.
    We refer readers to section IV.B.3. of the preamble of this final 
rule for a discussion of our recalculation of the labor-related share 
for discharges occurring on or after October 1, 2021 using the 2018-
based IPPS market basket.
    As discussed in section V.B. of the preamble of this final rule, 
prior to January 1, 2016, Puerto Rico hospitals were paid based on 75 
percent of the national standardized amount and 25 percent of the 
Puerto Rico-specific standardized amount. As a result, we applied the 
Puerto Rico-specific labor-related share percentage and nonlabor-
related share percentage to the Puerto Rico-specific standardized 
amount. Section 601 of the Consolidated Appropriations Act, 2016 (Pub. 
L. 114-113) amended section 1886(d)(9)(E) of the Act to specify that 
the payment calculation with respect to operating costs of inpatient 
hospital services of a subsection (d) Puerto Rico hospital for 
inpatient hospital discharges on or after January 1, 2016, shall use 
100 percent of the national standardized amount. Because Puerto Rico 
hospitals are no longer paid with a Puerto Rico-specific standardized 
amount as of January 1, 2016, under section 1886(d)(9)(E) of the Act as 
amended by section 601 of the Consolidated Appropriations Act, 2016, 
there is no longer a need for us to calculate a Puerto Rico-specific 
labor-related share percentage and nonlabor-related share percentage 
for application to the Puerto Rico-specific standardized amount. 
Hospitals in Puerto Rico are now paid 100 percent of the national 
standardized amount and, therefore, are subject to the national labor-
related share and nonlabor-related share percentages that are applied 
to the national standardized amount. Accordingly, for FY 2022, we did 
not propose a Puerto Rico-specific labor-related share percentage or a 
nonlabor-related share percentage.
    Comment: A commenter stated that if CMS determines that a reduction 
in the labor-related share is supported by data and appropriate for 
either Professional Services Fees or Home Office/Related Organization 
cost weight categories, they requested that--similar to other wage 
index related changes--CMS phase in a reduction of the labor-related 
share. The commenter requested that any phase-in be over a period of 
three years and implemented in a non-budget-neutral manner in 
recognition of hospital finances in the wake of the COVID-19 PHE.
    Response: As noted earlier, section 1886(d)(3)(E) of the Act 
directs the Secretary to adjust the proportion of the national 
prospective payment system base payment rates that are attributable to 
wages and wage-related costs by a factor that reflects the relative 
differences in labor costs among geographic areas. It also directs the 
Secretary to estimate from time to time the proportion of hospital 
costs that are labor-related and to adjust the proportion (as estimated 
by the Secretary from time to time) of hospitals' costs which are 
attributable to wages and wage-related costs of the DRG prospective 
payment rates. In section IV.B.3. of the preamble of this final rule, 
we discuss our recalculation

[[Page 45194]]

of the labor-related share for discharges occurring on or after October 
1, 2021, using the 2018-based IPPS market basket. We believe that the 
labor-related share calculated for FY 2022 accurately and appropriately 
reflects the proportion of hospitals' costs that are attributable to 
wages and wage-related costs. Therefore, we do not believe it is 
necessary or appropriate to phase in the effects of the labor-related 
share percentage finalized in this rule. After consideration of the 
public comments we received, for the reasons discussed in section 
IV.B.3. of the preamble of this final rule and in the FY 2022 IPPS/LTCH 
PPS proposed rule, we are finalizing our proposal to use a labor-
related share of 67.6 percent for discharges occurring on or after 
October 1, 2021, for all hospitals (including Puerto Rico hospitals) 
whose wage indexes are greater than 1.0000.
    Tables 1A and 1B, which are published in section VI. of the 
Addendum to this FY 2022 IPPS/LTCH PPS final rule and available via the 
internet on the CMS website, reflect the national labor-related share, 
which is also applicable to Puerto Rico hospitals. For FY 2022, for all 
IPPS hospitals (including Puerto Rico hospitals) whose wage indexes are 
less than or equal to 1.0000, we are applying the wage index to a 
labor-related share of 62 percent of the national standardized amount. 
For all IPPS hospitals (including Puerto Rico hospitals) whose wage 
indexes are greater than 1.000, for FY 2022, we are applying the wage 
index to the labor-related share of 67.6 percent of the national 
standardized amount.

IV. Rebasing and Revising of the Hospital Market Baskets for Acute Care 
Hospitals

A. Background

    Effective for cost reporting periods beginning on or after July 1, 
1979, we developed and adopted a hospital input price index (that is, 
the hospital market basket for operating costs). Although ``market 
basket'' technically describes the mix of goods and services used in 
providing hospital care, this term is also commonly used to denote the 
input price index (that is, cost category weights and price proxies 
combined) derived from that market basket. Accordingly, the term 
``market basket'' as used in this document refers to the hospital input 
price index.
    The percentage change in the market basket reflects the average 
change in the price of goods and services hospitals purchase in order 
to provide inpatient care. We first used the market basket to adjust 
hospital cost limits by an amount that reflected the average increase 
in the prices of the goods and services used to provide hospital 
inpatient care. This approach linked the increase in the cost limits to 
the efficient utilization of resources.
    Since the inception of the IPPS, the projected change in the 
hospital market basket has been the integral component of the update 
factor by which the prospective payment rates are updated every year. 
An explanation of the hospital market basket used to develop the 
prospective payment rates was published in the Federal Register on 
September 1, 1983 (48 FR 39764). We also refer readers to the FY 2018 
IPPS/LTCH PPS final rule (82 FR 38158 through 38175) in which we 
discussed the most recent previous rebasing of the hospital input price 
index.
    The hospital market basket is a fixed-weight, Laspeyres-type price 
index. A Laspeyres-type price index measures the change in price, over 
time, of the same mix of goods and services purchased in the base 
period. Any changes in the quantity or mix of goods and services (that 
is, intensity) purchased over time are not measured.
    The index itself is constructed in three steps. First, a base 
period is selected (in the proposed rule, we proposed to use 2018 as 
the base period) and total base period expenditures are estimated for a 
set of mutually exclusive and exhaustive spending categories, and the 
proportion of total costs that each category represents are calculated. 
These proportions are called ``cost weights'' or ``expenditure 
weights.'' Second, each expenditure category is matched to an 
appropriate price or wage variable, referred to as a ``price proxy.'' 
In almost every instance, these price proxies are derived from publicly 
available statistical series that are published on a consistent 
schedule (preferably at least on a quarterly basis). Finally, the 
expenditure weight for each cost category is multiplied by the level of 
its respective price proxy. The sum of these products (that is, the 
expenditure weights multiplied by their price index levels) for all 
cost categories yields the composite index level of the market basket 
in a given period. Repeating this step for other periods produces a 
series of market basket levels over time. Dividing an index level for a 
given period by an index level for an earlier period produces a rate of 
growth in the input price index over that timeframe.
    As previously noted, the market basket is described as a fixed-
weight index because it represents the change in price over time of a 
constant mix (quantity and intensity) of goods and services needed to 
provide hospital services. The effects on total expenditures resulting 
from changes in the mix of goods and services purchased subsequent to 
the base period are not measured. For example, a hospital hiring more 
nurses to accommodate the needs of patients would increase the volume 
of goods and services purchased by the hospital, but would not be 
factored into the price change measured by a fixed-weight hospital 
market basket. Only when the index is rebased would changes in the 
quantity and intensity be captured, with those changes being reflected 
in the cost weights. Therefore, we rebase the market basket 
periodically so that the cost weights reflect recent changes in the mix 
of goods and services that hospitals purchase (hospital inputs) to 
furnish inpatient care between base periods.
    We last rebased the hospital market basket cost weights effective 
for FY 2018 (82 FR 38158 through 38175), with 2014 data used as the 
base period for the construction of the market basket cost weights. For 
the FY 2022 IPPS/LTCH PPS proposed rule, we proposed to rebase the IPPS 
operating market basket to reflect the 2018 cost structure for IPPS 
hospitals and to revise applicable cost categories and price proxies 
used to determine the IPPS market basket, as discussed in this final 
rule. We also proposed to rebase and revise the Capital Input Price 
Index (CIPI) as described in section IV.D. of the preamble of this 
final rule.

B. Rebasing and Revising the IPPS Market Basket

    The terms ``rebasing'' and ``revising,'' while often used 
interchangeably, actually denote different activities. ``Rebasing'' 
means moving the base year for the structure of costs of an input price 
index (for example, in the proposed rule, we proposed to shift the base 
year cost structure for the IPPS hospital index from 2014 to 2018). 
``Revising'' means changing data sources or price proxies used in the 
input price index. As published in the FY 2006 IPPS final rule (70 FR 
47403), in accordance with section 404 of Public Law 108-173, CMS 
determined a new frequency for rebasing the hospital market basket. We 
established a rebasing frequency of every 4 years and, therefore, for 
the FY 2022 IPPS update, we proposed to rebase and revise the IPPS 
market basket from 2014 to 2018. We invited public comments on our 
proposed methodology.
    Comment: A few commenters supported the rebasing of the market 
basket. A commenter stated they were in agreement to utilize 2018 data 
for the

[[Page 45195]]

rebased market basket. A commenter stated that they appreciated the 
update of the market basket from 2014 to 2018 as well as the update of 
the labor-related share.
    Response: We appreciate the commenters' support to rebase and 
revise the IPPS market basket from a 2014 base year to a 2018 base 
year. We note that we proposed to use the rebased and revised market 
baskets for FY 2022 in compliance with section 404 of the MMA, which 
required us to established a frequency for updating the IPPS market 
basket cost weights and labor-related share. In compliance with that 
statute, we established a frequency of every 4 years (70 FR 47403). We 
last rebased the hospital market basket cost weights effective for FY 
2018 (82 FR 38158 through 38175), with 2014 data used as the base 
period for the construction of the market basket cost weights.
1. Development of Cost Categories and Weights
a. Use of Medicare Cost Report Data
    The major source of expenditure data for developing the proposed 
rebased and revised hospital market basket cost weights is the 2018 
Medicare cost reports. These 2018 Medicare cost reports are for cost 
reporting periods beginning on and after October 1, 2017 and before 
October 1, 2018. We proposed to use 2018 as the base year because we 
believe that the 2018 Medicare cost reports represent the most recent, 
complete set of Medicare cost report data available to develop cost 
weights for IPPS hospitals at the time of rulemaking. We believe it is 
important to regularly rebase and revise the IPPS market basket to 
reflect more recent data. Historically, the cost weights change 
minimally from year to year as they represent percent of total 
operating costs rather than cost levels; however, given the COVID-19 
public health emergency we will continue to monitor the upcoming 
Medicare cost report data to see if a more frequent rebasing schedule 
is necessary than our current schedule of every 4 years. As was done in 
previous rebasings, these cost reports are from IPPS hospitals only 
(hospitals excluded from the IPPS and CAHs are not included) and are 
based on IPPS Medicare-allowable operating costs. IPPS Medicare-
allowable operating costs are costs that are eligible to be paid under 
the IPPS. For example, the IPPS market basket excludes home health 
agency (HHA) costs as these costs would be paid under the HHA PPS and, 
therefore, these costs are not IPPS Medicare-allowable costs.
    The current set of instructions for the Medicare cost reports for 
hospitals (Form 2552-10, OMB Control Number 0938-0050) can be found in 
Chapter 40 at the following website (https://www.cms.gov/Regulations-and-Guidance/Guidance/Manuals/Paper-Based-Manuals-Items/CMS021935, 
accessed February 17, 2021). As described in these instructions, 
effective for cost reporting periods beginning on or after October 1, 
2015, Worksheet S-3, Part II was revised to add lines 14.01, 14.02, 
25.50, 25.51, 25.52, and 25.53, to enhance the wage index data 
collection. This modification was made for Transmittal 10 and is 
specifically highlighted in the instructions, which can be found at the 
following website: (https://www.cms.gov/Regulations-and-Guidance/Guidance/Transmittals/Downloads/R10P240.pdf, accessed February 17, 
2021). Therefore, as noted later in this section, for the 2018-based 
IPPS market basket, we proposed to use these more detailed lines for 
the development of the market basket cost categories. These detailed 
lines were not available at the time we finalized the 2014-based IPPS 
market basket.
    We proposed to derive costs for eight major expenditures or cost 
categories for the 2018-based IPPS market basket from the CMS Medicare 
cost reports (Form 2552-10, OMB Control Number 0938-0050): Wages and 
Salaries, Employee Benefits, Contract Labor, Pharmaceuticals, 
Professional Liability Insurance (Malpractice), Blood and Blood 
Products, Home Office/Related Organization Contract Labor, and a 
residual ``All Other'' category. The residual ``All Other'' category 
reflects all remaining costs that are not captured in the other seven 
cost categories. These are the same major cost categories from the 
Medicare cost reports that were derived for the 2014-based IPPS market 
basket. In this rule, we describe the detailed methodology for 
obtaining costs for each of the seven cost categories directly 
determined from the Medicare cost reports.
    In order to create a market basket that is representative of IPPS 
hospitals serving Medicare patients and to help ensure accurate major 
cost weights (which is the percent of total Medicare-allowable 
operating costs, as defined in this final rule), we proposed to apply 
edits to remove reporting errors and outliers. Specifically, the IPPS 
Medicare cost reports used to calculate the market basket cost weights 
exclude any providers that reported costs less than or equal to zero 
for the following categories: Total Medicare inpatient costs (Worksheet 
D, Part I, column 1, line 49); Medicare PPS payments (Worksheet E, Part 
A, column 1, line 59); Total salary costs (Worksheet S-3, Part II, 
column 2, line 1). We also limited our sample to providers that had a 
Medicare cost reporting period that was between 10 and 14 months. The 
final sample used included roughly 3,200 Medicare cost reports (about 
94 percent of the universe of IPPS Medicare cost reports for 2018). The 
sample of providers is representative of the national universe of 
providers by ownership-type (proprietary, nonprofit, and government) 
and by urban/rural status.
    First, we proposed to calculate total Medicare-allowable operating 
costs for each hospital. We proposed that total Medicare-allowable 
operating costs are equal to noncapital costs (Worksheet B, Part I, 
column 26 less Worksheet B, Part II, column 26) that are attributable 
to the Medicare-allowable cost centers of the hospital. We proposed 
that Medicare-allowable cost centers are lines 30 through 35, 50 
through 60, 62 through 76, 90, 91, 92.01, 93, 96 and 97. This is the 
same general methodology that was used for the 2014-based IPPS market 
basket. However, we note that for the development of the 2018-based 
IPPS market basket, we conducted a detailed review of the cost centers 
and now proposed to include lines 52, 96, and 97 when deriving total 
Medicare-allowable operating costs as these reflect Medicare-allowable 
services that are reimbursed under the IPPS.
(1) Wages and Salaries Costs
    To derive wages and salaries costs for the Medicare-allowable cost 
centers, we proposed to first calculate total unadjusted wages and 
salaries costs as reported on Worksheet S-3, Part II, column 4, line 1. 
We then proposed to remove the wages and salaries attributable to non-
Medicare-allowable cost centers (that is, excluded areas) as well as a 
portion of overhead wages and salaries attributable to these excluded 
areas. This is the same general methodology that was used to derive 
wages and salaries costs for the 2014-based IPPS market basket. 
However, we note that we proposed minor changes to the Medicare cost 
report lines that are used to derive excluded area wages and salaries 
as well as overhead wages and salaries attributable to these areas as 
described in this rule as we believe these represent a technical 
improvement to the Medicare cost report lines used for the 2014-based 
IPPS market basket. The description of the detailed methodology used 
for the 2014-based IPPS market basket was provided in the FY 2018 IPPS/
LTCH final rule (82 FR 38159).

[[Page 45196]]

    Specifically, we proposed to calculate excluded area wages and 
salaries as equal to the sum of Worksheet S-3, Part II, column 4, lines 
3, 4.01, 5, 6, 7, 7.01, 8, 9, and 10 less Worksheet A, column 1, lines 
20 and 23. Overhead wages and salaries are attributable to the entire 
IPPS facility. Therefore, we proposed to only include the proportion 
attributable to the Medicare-allowable cost centers. Specifically, we 
proposed to estimate the proportion of overhead wages and salaries that 
are not attributable to Medicare-allowable costs centers (that is, 
excluded areas) by first calculating the ratio of total Medicare-
allowable operating costs as previously defined to total facility 
operating costs (Worksheet B, Part I, column 26, line 202 less 
Worksheet B, Part I, column 0, lines 1 and 2). We then proposed to 
multiply this ratio by total overhead wages and salaries (Worksheet S-
3, Part II, column 4, lines 26, 27, 29 through 32, 34, and 36 through 
43).
    Therefore, the proposed wages and salaries costs are equal to total 
wages and salaries costs less: (a) Excluded area wages and salaries 
costs; and (b) overhead wages and salaries costs attributable to the 
excluded areas.
(2) Employee Benefits Costs
    We proposed to derive employee benefits costs using a similar 
methodology as the wages and salaries costs; that is, reflecting 
employee benefits costs attributable to the Medicare-allowable cost 
centers. First, we calculate total unadjusted employee benefits costs 
as the sum of Worksheet S-3, Part II, column 4, lines 17, 18, 20, 22, 
and 25.52. The 2014-based IPPS market basket used Worksheet S-3, Part 
II, column 4, lines 17, 18, 20 and 22 to derive the costs for this 
category. As described previously, line 25.52 reflects a newly added 
line to Worksheet S-3, Part II since the development of the 2014-based 
IPPS market basket.
    We then exclude those employee benefits attributable to the 
overhead wages and salaries for the non-Medicare-allowable cost centers 
(that is, the excluded areas). Employee benefits attributable to the 
non-Medicare-allowable cost centers are derived by multiplying the 
ratio of total employee benefits (equal to the sum of Worksheet S-3, 
Part II, column 4, lines 17, 18, 19, 20, 21, 22, 22.01, 23, 24, 25, 
25.50, 25.51, 25.52, and 25.53) to total wages and salaries (Worksheet 
S-3, Part II, column 4, line 1) by excluded overhead wages and salaries 
(as previously described in section IV.B.1.a.(1). of the preamble of 
this final rule for wages and salaries costs). A similar methodology 
was used in the 2014-based IPPS market basket.
(3) Contract Labor Costs
    Contract labor costs are primarily associated with direct patient 
care services. Contract labor costs for services such as accounting, 
billing, and legal are estimated using other government data sources as 
described in this final rule. We proposed to derive contract labor 
costs for the 2018-based IPPS market basket as the sum of Worksheet S-
3, Part II, column 4, lines 11, 13, and 15. A similar methodology was 
used in the 2014-based IPPS market basket.
(4) Professional Liability Insurance Costs
    We proposed that professional liability insurance (PLI) costs 
(often referred to as malpractice costs) be equal to premiums, paid 
losses, and self-insurance costs reported on Worksheet S-2, Part I, 
columns 1 through 3, line 118.01. A similar methodology was used for 
the 2014-based IPPS market basket.
(5) Pharmaceuticals Costs
    We proposed to calculate pharmaceuticals costs as total costs 
reported for the Pharmacy cost center (Worksheet B, Part I, column 0, 
line 15) and Drugs Charged to Patients cost center (Worksheet B, Part 
I, column 0, line 73) less wages and salaries attributable to these two 
cost centers (Worksheet S-3, Part II, column 4, line 40 and Worksheet 
A, column 1, line 73) less estimated employee benefits attributable to 
these two cost centers. We proposed to estimate the employee benefits 
costs by multiplying the ratio of total employee benefits (equal to the 
sum of Worksheet S-3, Part II, column 4, lines 17, 18, 19, 20, 21, 22, 
22.01, 23, 24, 25, 25.50, 25.51, 25.52, and 25.53) to total wages and 
salaries (Worksheet S-3, Part II, column 4, line 1) by total wages and 
salaries costs for the Pharmacy and Drugs Charged to Patients cost 
centers (equal to the sum of Worksheet S-3, Part II, column 4, line 40 
and Worksheet A, column 1, line 73). The same general methodology was 
used for the 2014-based IPPS market basket. However, we note that for 
the 2014-based IPPS market basket, for calculating the total nonsalary 
costs we used Worksheet A, column 2 for each cost center instead of our 
proposed method of using Worksheet B, Part I, column 0, less salary 
costs. We proposed to use Worksheet B, Part I, column 0 as this would 
reflect reclassifications and adjustments (which are made on columns 
subsequent to Worksheet A columns 1 and 2).
(6) Blood and Blood Products Costs
    We proposed to calculate blood and blood products costs as total 
costs reported for the Whole Blood & Packed Red Blood Cells cost center 
(Worksheet B, Part I, column 0, line 62) and the Blood Storing, 
Processing, & Transfusing cost center (Worksheet B, Part I, column 0, 
Line 63) less wages and salaries attributable to these two cost centers 
(Worksheet A, column 1, lines 62 and 63) less estimated employee 
benefits attributable to these two cost centers. We estimate these 
employee benefits costs by multiplying the ratio of total employee 
benefits (equal to the sum of Worksheet S-3, Part II, column 4, lines 
17, 18, 19, 20, 21, 22, 22.01, 23, 24, 25, 25.50, 25.51, 25.52, and 
25.53) to total wages and salaries (Worksheet S-3, Part II, column 4, 
line 1) by total wages and salaries for the Whole Blood & Packed Red 
Blood Cells and Blood Storing, Processing, & Transfusing cost centers 
(equal to the sum of Worksheet A, Column 1, lines 62 and 63). The same 
general methodology was used for the 2014-based IPPS market basket. 
However, we note that for the 2014-based IPPS market basket, for 
calculating the total nonsalary costs we used Worksheet A, column 2 for 
lines 62 and 63 instead of our proposed method of using Worksheet B, 
Part I, column 0, lines 62 and 63, less salary costs. Similar to our 
proposed method for Pharmaceuticals costs, we proposed to use Worksheet 
B, Part I, column 0 as this would reflect reclassifications and 
adjustments (which are made on columns subsequent to Worksheet A 
columns 1 and 2).
(7) Home Office Contract Labor/Related Organization Costs
    We proposed to determine home office/related organization contract 
labor costs using data reported on Worksheet S-3, Part II, column 4, 
lines 14.01, 14.02, 25.50, and 25.51. Home office/related organization 
contract labor costs in the 2014-based IPPS market basket were 
calculated using a similar method except we used data reported on 
Worksheet S-3, Part II, column 4, line 14. As described previously, 
effective for cost reporting periods beginning on or after October 1, 
2015 (Transmittal 10), Worksheet S-3, Part II was revised to add lines 
14.01, 14.02, 25.50, 25.51, 25.52, and 25.53, to enhance the wage index 
data collection. Therefore, for the 2018-based IPPS market basket, we 
proposed to use these more detailed lines; however, the expenses 
captured on these lines would

[[Page 45197]]

be similar to the expenses originally reported on line 14, prior to the 
break out of the expenses on these new more detailed lines.
    In addition, for the 2014-based IPPS market basket, we then 
multiplied the home office/related organization contract labor costs by 
the ratio of total Medicare-allowable operating costs to total 
operating costs. However, for the 2018-based IPPS market basket, we 
proposed to no longer apply this adjustment since the Medicare cost 
report instructions effective for Transmittal 10 now state that the 
costs reported on these lines should reflect costs associated with 
Medicare-allowable cost centers. Therefore, we no longer believe this 
adjustment is necessary.
b. Final Major Cost Category Computation
    After we derived costs for the seven major cost categories for each 
provider using the Medicare cost report data as previously described, 
we proposed to address data outliers using the following steps. First, 
we divide the costs for each of the seven categories (calculated as 
previously described in this section) by total Medicare-allowable 
operating costs for the provider (calculated as previously described in 
this section) to obtain cost weights for each PPS hospital.
    For each of the major cost weights except the Home Office/Related 
Organization Contract Labor cost weight, we proposed to trim the data 
to remove outliers (a standard statistical process) by: (1) Requiring 
that major expenses (such as Wages and Salaries costs) and total 
Medicare-allowable operating costs be greater than zero; and (2) 
excluding the top and bottom five percent of the major cost weight (for 
example, Wages and Salaries costs as a percent of total Medicare-
allowable operating costs). We note that missing values are assumed to 
be zero consistent with the methodology for how missing values were 
treated in the 2014-based IPPS market basket. After the outliers have 
been removed, we sum the costs for each category across all remaining 
providers. We then divide this by the sum of total Medicare-allowable 
operating costs across all remaining providers to obtain a cost weight 
for the 2018-based IPPS market basket for the given category.
    For the Home Office/Related Organization Contract Labor cost 
weight, we proposed to apply a trim that excludes those reporters above 
the 99th percentile. This allows all providers' Medicare-allowable 
costs to be included, even if their home office/related organization 
contract labor costs were reported to be zero. The Medicare cost report 
data (Worksheet S-2, Part I, line 140) indicate that not all hospitals 
have a home office. IPPS hospitals without a home office would report 
administrative costs that might typically be associated with a home 
office in the Wages and Salaries and Employee Benefits cost weights, or 
in the residual ``All Other'' cost weight if they purchased these types 
of services from external contractors. We believe the trimming 
methodology that excludes those who report a Home Office/Related 
Organization Contract Labor cost weight above the 99th percentile is 
appropriate as it removes extreme outliers while also allowing 
providers with zero home office/related organization contract labor 
costs to be included in the Home Office/Related Organization Contract 
Labor cost weight calculation. Next, similar to the other cost weights, 
after the outliers have been removed, we sum the costs across all 
remaining providers. We then divide this by the sum of total Medicare-
allowable operating costs across all remaining providers to obtain a 
cost weight for the 2018-based IPPS market basket.
    The trimming process is done individually for each cost category so 
that providers excluded from one cost weight calculation are not 
automatically excluded from another cost weight calculation. We note 
that these proposed trimming methods are the same types of edits 
performed for the 2014-based IPPS market basket, as well as other PPS 
market baskets (including but not limited to SNF market basket and HHA 
market basket). We believe this trimming process improves the accuracy 
of the data used to compute the major cost weights by removing possible 
misreported data. We note that for each of the cost weights we 
evaluated the distribution of providers and costs by ownership-type, 
and by urban/rural status. For all of the cost weights, the trimmed 
sample was nationally representative.
    Finally, we calculate the residual ``All Other'' cost weight that 
reflects all remaining costs that are not captured in the seven cost 
categories listed. Table IV-01 shows the major cost categories and 
their respective cost weights as derived from the Medicare cost 
reports.
[GRAPHIC] [TIFF OMITTED] TR13AU21.237

    From 2014 to 2018, the Wages and Salaries and Employee Benefits 
cost weights as calculated directly from the Medicare cost reports 
decreased by approximately 2.4 percentage points and 0.7 percentage 
point, respectively, while the Contract Labor cost weight increased 
slightly by 0.2 percentage point.

[[Page 45198]]

    As we did for the 2014-based IPPS market basket (82 FR 38162), we 
proposed to allocate contract labor costs to the Wages and Salaries and 
Employee Benefits cost weights based on their relative proportions for 
employed labor under the assumption that contract labor costs are 
comprised of both wages and salaries and employee benefits. The 
contract labor allocation proportion for wages and salaries is equal to 
the Wages and Salaries cost weight as a percent of the sum of the Wages 
and Salaries cost weight and the Employee Benefits cost weight. Using 
the 2018 Medicare cost report data, this percentage is 78 percent. 
Therefore, we proposed to allocate approximately 78 percent of the 
Contract Labor cost weight to the Wages and Salaries cost weight and 22 
percent to the Employee Benefits cost weight. The 2014-based IPPS 
market basket also allocated 78 percent of the Contract Labor cost 
weight to the Wages and Salaries cost weight.
    Table IV-02 shows the Wages and Salaries and Employee Benefits cost 
weights after contract labor allocation for the 2014-based IPPS market 
basket and the proposed 2018-based IPPS market basket. In aggregate, 
the Compensation cost weight (calculated using more detailed decimal 
places) decreased from 55.8 percent to 53.0 percent, or 2.8 percentage 
points.
[GRAPHIC] [TIFF OMITTED] TR13AU21.238

    We received one comment on our proposed methodology for developing 
the major cost weights in the 2018-based IPPS market basket.
    Comment: A commenter supported CMS' proposal to derive costs for 
blood and blood products for the 2018-based IPPS market basket from the 
CMS Medicare cost reports. However, they also encouraged CMS to develop 
and release additional educational materials that instruct hospitals on 
how to appropriately report blood products and services on the CMS 
Medicare cost reports. They further stated that blood products and 
services are captured in a wide variety of MS-DRGs, and providers may 
inadvertently exclude them from their cost reports. They stated they 
were committed to working with CMS to educate hospitals on appropriate 
billing for blood products.
    Response: We appreciate the commenter's support of deriving blood 
and blood product costs using the Medicare cost report data. As 
previously stated, the blood and blood products cost weight is based on 
data reported in the Whole Blood & Packed Red Blood Cells cost center 
(line 62) and Blood Storing, Processing & Transfusion cost center (line 
63) of the hospital Medicare cost reports. The instructions state these 
costs should include the direct expenses incurred: In obtaining blood 
directly from donors, in obtaining whole blood and packed red blood 
cells from suppliers and for processing, storing, and transfusing whole 
blood, packed red blood cells, and blood derivatives. We encourage 
hospitals to report these expenses consistent with the Medicare cost 
report instructions. We also welcome any specific suggestions that 
stakeholders may have on these instructions.
    After consideration of the public comments we received, we are 
finalizing the methodology for deriving the major cost weights of the 
2018-based IPPS market basket as proposed.
c. Derivation of the Detailed Cost Weights
    To further divide the ``All Other'' residual cost weight estimated 
from the 2018 Medicare cost report data into more detailed cost 
categories, we proposed to use the 2012 Benchmark I-O ``Use Tables/
Before Redefinitions/Purchaser Value'' for NAICS 622000, Hospitals, 
published by the BEA. These data are publicly available at the 
following website: http://www.bea.gov/industry/io_annual.htm. The BEA 
Benchmark I-O data are generally scheduled for publication every 5 
years on a lagged basis, with the most recent data available for 2012. 
The 2012 Benchmark I-O data are derived from the 2012 Economic Census 
and are the building blocks for BEA's economic accounts. Therefore, 
they represent the most comprehensive and complete set of data on the 
economic processes or mechanisms by which output is produced and 
distributed.\759\ BEA also produces Annual I-O estimates. However, 
while based on a similar methodology, these estimates reflect less 
comprehensive and less detailed data sources and are subject to 
revision when benchmark data become available. Instead of using the 
less detailed Annual I-O data, we proposed to inflate the detailed 2012 
Benchmark I-O data forward to 2018 by applying the annual price changes 
from the respective price proxies to the appropriate market basket cost 
categories that are obtained from the 2012 Benchmark I-O data. In our 
calculations for the proposed rule, we repeated this practice for each 
year. We then calculated the cost shares that each cost category 
represents of the 2012 data inflated to 2018. These resulting 2018 cost 
shares were applied to the ``All Other'' residual cost weight to obtain 
the detailed cost weights for the proposed 2018-based IPPS market 
basket. For example, the cost for Food: Direct Purchases represents 4.8 
percent of the sum of the ``All Other'' 2012 Benchmark I-O Hospital 
Expenditures inflated to 2018. Therefore, the Food: Direct Purchases 
cost weight represents 4.8 percent of the proposed 2018-based IPPS 
market basket's ``All Other'' cost category (32.4 percent), yielding a 
Food: Direct Purchases proposed cost weight of 1.6 percent in the 
proposed 2018-based IPPS market basket (0.048 x 32.4 percent = 1.6 
percent). For the 2014-based IPPS market basket (82 FR 38162), we used 
the same methodology utilizing the 2007 Benchmark I-O data (aged to 
2014).
---------------------------------------------------------------------------

    \759\ http://www.bea.gov/papers/pdf/IOmanual_092906.pdf.
---------------------------------------------------------------------------

    Using this methodology, we proposed to derive 17 detailed cost 
categories

[[Page 45199]]

from the proposed 2018-based IPPS market basket residual cost weight 
(32.4 percent). These categories are: (1) Fuel: Oil and Gas; (2) 
Electricity and Other Non-Fuel Utilities; (3) Food: Direct Purchases; 
(4) Food: Contract Services; (5) Chemicals; (6) Medical Instruments; 
(7) Rubber and Plastics; (8) Paper and Printing Products; (9) 
Miscellaneous Products; (10) Professional Fees: Labor-Related; (11) 
Administrative and Facilities Support Services; (12) Installation, 
Maintenance, and Repair Services; (13) All Other: Labor-Related 
Services; (14) Professional Fees: Nonlabor-Related; (15) Financial 
Services; (16) Telephone Services; and (17) All Other: Nonlabor-Related 
Services.
    The 2014-based IPPS market basket had a separate cost category for 
Water and Sewerage. Due to the size of the estimated cost weight 
(approximately 0.1 percent), we proposed that these costs be included 
in the Electricity and Other Non-Fuel Utilities cost category.
    We received no comments on our proposed methodology for deriving 
the detailed cost weights of the 2018-based IPPS market basket and 
therefore are finalizing this methodology as proposed without 
modification.
2. Selection of Proposed Price Proxies
    After computing the proposed 2018 cost weights for the IPPS market 
basket, it was necessary to select appropriate wage and price proxies 
to reflect the rate of price change for each expenditure category. With 
the exception of the proxy for professional liability insurance (PLI), 
all the proxies we proposed are based on Bureau of Labor Statistics 
(BLS) data and are grouped into one of the following BLS categories:
     Producer Price Indexes--Producer Price Indexes (PPIs) 
measure the average change over time in the selling prices received by 
domestic producers for their output. The prices included in the PPI are 
from the first commercial transaction for many products and some 
services (https://www.bls.gov/ppi/).
     Consumer Price Indexes--Consumer Price Indexes (CPIs) 
measure the average change over time in the prices paid by urban 
consumers for a market basket of consumer goods and services (https://www.bls.gov/cpi/). CPIs are only used when the purchases are similar to 
those of retail consumers rather than purchases at the producer level, 
or if no appropriate PPIs are available.
     Employment Cost Indexes--Employment Cost Indexes (ECIs) 
measure the rate of change in employee wage rates and employer costs 
for employee benefits per hour worked. These indexes are fixed-weight 
indexes and strictly measure the change in wage rates and employee 
benefits per hour. ECIs are superior to Average Hourly Earnings (AHE) 
as price proxies for input price indexes because they are not affected 
by shifts in occupation or industry mix, and because they measure pure 
price change and are available by both occupational group and by 
industry. The industry ECIs are based on the NAICS and the occupational 
ECIs are based on the Standard Occupational Classification System 
(SOC).
    We evaluated the price proxies using the criteria of reliability, 
timeliness, availability, and relevance:
     Reliability. Reliability indicates that the index is based 
on valid statistical methods and has low sampling variability. Widely 
accepted statistical methods ensure that the data were collected and 
aggregated in a way that can be replicated. Low sampling variability is 
desirable because it indicates that the sample reflects the typical 
members of the population. (Sampling variability is variation that 
occurs by chance because only a sample was surveyed rather than the 
entire population.)
     Timeliness. Timeliness implies that the proxy is published 
regularly, preferably at least once a quarter. The market basket levels 
are updated quarterly, and therefore, it is important for the 
underlying price proxies to be up-to-date, reflecting the most recent 
data available. We believe that using proxies that are published 
regularly (at least quarterly, whenever possible) helps to ensure that 
we are using the most recent data available to update the market 
basket. We strive to use publications that are disseminated frequently, 
because we believe that this is an optimal way to stay abreast of the 
most current data available.
     Availability. Availability means that the proxy is 
publicly available. We prefer that our proxies are publicly available 
because this will help ensure that our market basket updates are as 
transparent to the public as possible. In addition, this enables the 
public to be able to obtain the price proxy data on a regular basis.
     Relevance. Relevance means that the proxy is applicable 
and representative of the cost category weight to which it is applied.
    We believe the proposed PPIs, CPIs, and ECIs selected meet these 
criteria. Therefore, we believe that they continue to be the best 
measure of price changes for the cost categories to which they would be 
applied.
    In this final rule, we present a detailed explanation of the price 
proxies that we proposed for each cost category weight. We note that 
many of the proxies that we proposed to use for the proposed 2018-based 
IPPS market basket are the same as those used for the 2014-based IPPS 
market basket.
(1) Wages and Salaries
    We proposed to use the ECI for Wages and Salaries for All Civilian 
Workers in Hospitals (BLS series code CIU1026220000000I) to measure the 
price growth of this cost category. This is the same price proxy used 
in the 2014-based IPPS market basket.
(2) Employee Benefits
    We proposed to use the ECI for Total Benefits for All Civilian 
Workers in Hospitals to measure the price growth of this cost category. 
This ECI is calculated using the ECI for Total Compensation for All 
Civilian Workers in Hospitals (BLS series code CIU1016220000000I) and 
the relative importance of wages and salaries within total 
compensation. This is the same price proxy used in the 2014-based IPPS 
market basket.
(3) Fuel: Oil and Gas
    Similar to the 2014-based IPPS market basket, we proposed to use a 
blend of the PPI Industry for Petroleum Refineries and the PPI 
Commodity for Natural Gas. Our analysis of the Bureau of Economic 
Analysis' 2012 Benchmark I-O data (use table before redefinitions, 
purchaser's value for NAICS 622000 [Hospitals]), shows that 
approximately 96 percent of hospital Fuel: Oil, and Gas expenses are 
for Petroleum Refineries (NAICS 324110) and Natural Gas (NAICS 221200) 
expenses, with Petroleum Refineries expenses accounting for 
approximately 90 percent and Natural Gas expenses accounting for 
approximately 10 percent of this sum. We proposed to create blended 
index of these expenses based on each NAICS' expenses as share of their 
sum. Therefore, we proposed to use a blend of 90 percent of the PPI 
Industry for Petroleum Refineries (BLS series code PCU324110324110) and 
10 percent of the PPI Commodity Index for Natural Gas (BLS series code 
WPU0531) as the price proxy for this cost category. The 2014-based IPPS 
market basket used a 70/30 blend of these price proxies, reflecting the 
2007 I-O data (82 FR 38163). We believe that these two price proxies 
continue to be the most technically appropriate indices available to 
measure the price growth of the Fuel: Oil, and Gas cost category in the 
proposed 2018-based IPPS market basket.

[[Page 45200]]

(4) Electricity and Other Non-Fuel Utilities
    We proposed to use the PPI Commodity for Commercial Electric Power 
(BLS series code WPU0542) to measure the price growth of this cost 
category, as Electricity costs account for 93 percent of these 
expenses. This is the same price proxy used for the Electricity cost 
category in the 2014-based IPPS market basket. As previously noted, we 
proposed to include Water and Sewerage costs within the Electricity and 
Other Non-Fuel Utilities cost category, and to no longer use the CPI 
for Water and Sewerage Maintenance as we did for the 2014-based IPPS 
market basket, due to the small size of this estimated cost weight 
(approximately 0.1 percent).
(5) Professional Liability Insurance
    We proposed to proxy price changes in hospital professional 
liability insurance premiums (PLI) using percentage changes as 
estimated by the CMS Hospital Professional Liability Index. To generate 
these estimates, we collect commercial insurance medical liability 
premiums for a fixed level of coverage while holding nonprice factors 
constant (such as a change in the level of coverage). This is the same 
price proxy used in the 2014-based IPPS market basket.
(6) Pharmaceuticals
    We proposed to use the PPI Commodity for Pharmaceuticals for Human 
Use, Prescription (BLS series code WPUSI07003) to measure the price 
growth of this cost category. This is the same price proxy used in the 
2014-based IPPS market basket.
(7) Food: Direct Purchases
    We proposed to use the PPI Commodity for Processed Foods and Feeds 
(BLS series code WPU02) to measure the price growth of this cost 
category. This is the same price proxy used in the 2014-based IPPS 
market basket.
(8) Food: Contract Services
    We proposed to use the CPI for Food Away From Home (All Urban 
Consumers) (BLS series code CUUR0000SEFV) to measure the price growth 
of this cost category. This is the same price proxy used in the 2014-
based IPPS market basket.
(9) Chemicals
    Similar to the 2014-based IPPS market basket, we proposed to use a 
four-part blended PPI as the proxy for the chemicals cost category in 
the proposed 2018-based IPPS market basket. The proposed blend is 
composed of the PPI Industry for Industrial Gas Manufacturing, Primary 
Products (BLS series code PCU325120325120P), the PPI Industry for Other 
Basic Inorganic Chemical Manufacturing (BLS series code PCU32518-32518-
), the PPI Industry for Other Basic Organic Chemical Manufacturing (BLS 
series code PCU32519-32519-), and the PPI Industry for Other 
Miscellaneous Chemical Product Manufacturing (BLS series code 
PCU325998325998). We note that the four part blended PPI used in the 
2014-based IPPS market basket is composed of the PPI Industry for 
Industrial Gas Manufacturing (BLS series code PCU325120325120P), the 
PPI Industry for Other Basic Inorganic Chemical Manufacturing (BLS 
series code PCU32518-32518-), the PPI Industry for Other Basic Organic 
Chemical Manufacturing (BLS series code PCU32519-32519-), and the PPI 
Industry for Soap and Cleaning Compound Manufacturing (BLS series code 
PCU32561-32561-). For the 2018-based IPPS market basket, we proposed to 
derive the weights for the PPIs using the 2012 Benchmark I-O data. The 
2014-based IPPS market basket used the 2007 Benchmark I-O data to 
derive the weights for the four PPIs (82 FR 38164). We note that in the 
2012 I-O data, the share of total chemicals expenses that the Soap and 
Cleaning Compound Manufacturing (NAICS 325610) represents decreased 
relative to the 2007 I-O data (from 5 percent to 2 percent), while the 
share of the total chemicals expenses that the All Other Chemical 
Product and Preparation manufacturing (NAICS 3259A0) categories 
represents increased (from 5 percent to 7 percent). As a result, we 
proposed to remove the PPI Industry for Soap and Cleaning Compound 
Manufacturing from the proposed blend for the proposed 2018-based IPPS 
market basket and replace it with the PPI Industry for Other 
Miscellaneous Chemical Product Manufacturing (BLS series code 
PCU325998325998).
    Table IV-03 shows the proposed weights for each of the four PPIs 
used to create the blended index compared to those used for the 2014-
based IPPS market basket.
BILLING CODE 4120-01-P
[GRAPHIC] [TIFF OMITTED] TR13AU21.239

(10) Blood and Blood Products
    We proposed to use the PPI Industry for Blood and Organ Banks (BLS 
series code PCU621991621991) to measure the price growth of this cost 
category. This is the same price proxy used in the 2014-based IPPS 
market basket.
(11) Medical Instruments
    We proposed to use a blended price proxy for the Medical 
Instruments category, as shown in Table IV-04. The 2012 Benchmark I-O 
data shows the majority of medical instruments and supply costs are for 
NAICS 339112--Surgical and medical instrument manufacturing costs 
(approximately 56 percent) and NAICS 339113--Surgical appliance and 
supplies manufacturing costs (approximately 43 percent). Therefore, we 
proposed to use a blend of these two price proxies. To proxy the price 
changes associated with NAICS 339112, we proposed using the PPI--
Commodity--Surgical and medical instruments (BLS series code

[[Page 45201]]

WPU1562). This is the same price proxy we used in the 2014-based IPPS 
market basket. To proxy the price changes associated with NAICS 339113, 
we proposed to use a 50/50 blend of the PPI--Commodity--Medical and 
surgical appliances and supplies (BLS series code WPU1563) and the 
PPI--Commodity--Miscellaneous products--Personal safety equipment and 
clothing (BLS series code WPU1571). We proposed to include the latter 
price proxy as it would reflect personal protective equipment including 
but not limited to face shields and protective clothing. The 2012 
Benchmark I-O data does not provide specific expenses for these 
products; however, we recognize that this category reflects costs faced 
by IPPS hospitals.
[GRAPHIC] [TIFF OMITTED] TR13AU21.240

(12) Rubber and Plastics
    We proposed to use the PPI Commodity for Rubber and Plastic 
Products (BLS series code WPU07) to measure the price growth of this 
cost category. This is the same price proxy used in the 2014-based IPPS 
market basket.
(13) Paper and Printing Products
    We proposed to use the PPI Commodity for Converted Paper and 
Paperboard Products (BLS series code WPU0915) to measure the price 
growth of this cost category. This is the same price proxy used in the 
2014-based IPPS market basket.
(14) Miscellaneous Products
    We proposed to use the PPI Commodity for Finished Goods Less Food 
and Energy (BLS series code WPUFD4131) to measure the price growth of 
this cost category. This is the same price proxy used in the 2014-based 
IPPS market basket.
(15) Professional Fees: Labor-Related
    We proposed to use the ECI for Total Compensation for Private 
Industry Workers in Professional and Related (BLS series code 
CIU2010000120000I) to measure the price growth of this category. It 
includes occupations such as legal, accounting, and engineering 
services. This is the same price proxy used in the 2014-based IPPS 
market basket.
(16) Administrative and Facilities Support Services
    We proposed to use the ECI for Total Compensation for Private 
Industry Workers in Office and Administrative Support (BLS series code 
CIU2010000220000I) to measure the price growth of this category. This 
is the same price proxy used in the 2014-based IPPS market basket.
(17) Installation, Maintenance, and Repair Services
    We proposed to use the ECI for Total Compensation for All Civilian 
Workers in Installation, Maintenance, and Repair (BLS series code 
CIU1010000430000I) to measure the price growth of this cost category. 
This is the same proxy used in the 2014-based IPPS market basket.
(18) All Other: Labor-Related Services
    We proposed to use the ECI for Total Compensation for Private 
Industry Workers in Service Occupations (BLS series code 
CIU2010000300000I) to measure the price growth of this cost category. 
This is the same price proxy used in the 2014-based IPPS market basket.
(19) Professional Fees: Nonlabor-Related
    We proposed to use the ECI for Total Compensation for Private 
Industry Workers in Professional and Related (BLS series code 
CIU2010000120000I) to measure the price growth of this category. This 
is the same price proxy that we proposed to use for the Professional 
Fees: Labor-Related cost category and the same price proxy used in the 
2014-based IPPS market basket.
(20) Financial Services
    We proposed to use the ECI for Total Compensation for Private 
Industry Workers in Financial Activities (BLS series code 
CIU201520A000000I) to measure the price growth of this cost category. 
This is the same price proxy used in the 2014-based IPPS market basket.
(21) Telephone Services
    We proposed to use the CPI for Telephone Services (BLS series code 
CUUR0000SEED) to measure the price growth of this cost category. This 
is the same price proxy used in the 2014-based IPPS market basket.
(22) All Other: Nonlabor-Related Services
    We proposed to use the CPI for All Items Less Food and Energy (BLS 
series code CUUR0000SA0L1E) to measure the price growth of this cost 
category. We believe that using the CPI for All Items Less Food and 
Energy avoids double counting of changes in food and energy prices as 
they are already captured elsewhere in the market basket. This is the 
same price proxy used in the 2014-based IPPS market basket.
    We received no comments on the proposed price proxies in the 2018-
based IPPS market basket and therefore are finalizing this proposal 
without modification.
    Table IV-05 sets forth the 2018-based IPPS market basket, including 
the cost categories and their respective weights and price proxies. For 
comparison purposes, the corresponding 2014-based IPPS market basket 
cost weights also are listed.

[[Page 45202]]

[GRAPHIC] [TIFF OMITTED] TR13AU21.241


[[Page 45203]]


[GRAPHIC] [TIFF OMITTED] TR13AU21.242

    Table IV-06 compares both the historical and forecasted percent 
changes in the 2014-based IPPS market basket and the 2018-based IPPS 
market basket. The forecasted growth rates in Table IV-06 are based on 
IHS Global

[[Page 45204]]

Inc.'s (IGI's) second quarter 2021 forecast with historical data 
through first quarter 2021.
[GRAPHIC] [TIFF OMITTED] TR13AU21.243

    There is no difference between the average percent change in the 
2014-based and the 2018-based IPPS market basket over the FY 2017 
through FY 2020 time period. For FY 2022, the increase is projected to 
be 2.7 percent for both the 2014-based and 2018-based IPPS market 
baskets.
3. Labor-Related Share
    Under section 1886(d)(3)(E) of the Act, the Secretary estimates 
from time to time the proportion of payments that are labor-related. 
Section 1886(d)(3)(E) of the Act states that the Secretary shall adjust 
the proportion, (as estimated by the Secretary from time to time) of 
hospitals' costs which are attributable to wages and wage-related 
costs, of the DRG prospective payment rates. We refer to the proportion 
of hospitals' costs that are attributable to wages and wage-related 
costs as the ``labor-related share.''
    The labor-related share is used to determine the proportion of the 
national PPS base payment rate to which the area wage index is applied. 
We include a cost category in the labor-related share if the costs are 
labor intensive and vary with the local labor market. For the FY 2022 
IPPS/LTCH PPS proposed rule, we proposed to include in the labor-
related share the national average proportion of operating costs that 
are attributable to the following cost categories in the proposed 2018-
based IPPS market basket: Wages and Salaries, Employee Benefits, 
Professional Fees: Labor-Related, Administrative and Facilities Support 
Services, Installation, Maintenance, and Repair Services, and All 
Other: Labor-Related Services, as we did in the FY 2018 IPPS/LTCH PPS 
final rule (82 FR 38167).
    Similar to the 2014-based IPPS market basket, we proposed that the 
Professional Fees: Labor-Related cost category includes expenses 
associated with advertising and a proportion of legal services, 
accounting and auditing, engineering, and management consulting. As was 
done in the 2014-based IPPS market basket rebasing, we proposed to 
determine the proportion of legal, accounting and auditing, 
engineering, and management consulting services that meet our 
definition of labor-related services based on a survey of hospitals 
conducted by CMS in 2008 (OMB Control Number 0938-1036). We notified 
the public of our intent to conduct this survey on December 9, 2005 (70 
FR 73250) and received no comments (71 FR 8588).
    A discussion of the composition of the survey and 
poststratification can be found in the FY 2010 IPPS/LTCH PPS final rule 
(74 FR 43850 through 43856). Based on the weighted results of the 
survey, we determined that hospitals purchase, on average, the 
following portions of contracted professional services outside of their 
local labor market:
     34 percent of accounting and auditing services.
     30 percent of engineering services.
     33 percent of legal services.
     42 percent of management consulting services.
    We proposed to apply each of these percentages to its respective 
Benchmark I-O cost category underlying the professional fees cost 
category. This is the methodology that we used to separate the 2014-
based IPPS market basket professional fees cost category into 
Professional Fees: Labor-Related and Professional Fees: Nonlabor-
Related cost categories. We proposed to use the same methodology and 
survey results to separate the professional fees costs for the proposed 
2018-based IPPS market basket into Professional Fees: Labor-Related and 
Professional Fees: Nonlabor-Related cost categories. We stated that we 
believe these survey results are appropriate to use for the proposed 
2018-based IPPS market basket as they empirically determine the 
proportion of contracted professional services purchased by the 
industry that is attributable to local firms and the proportion that is 
purchased from national firms.
    In the proposed 2018-based IPPS market basket, nonmedical 
professional

[[Page 45205]]

fees that were subject to allocation based on these survey results 
represent approximately 6.4 percent of total operating costs (and are 
limited to those fees related to Accounting & Auditing, Legal, 
Engineering, and Management Consulting services). Based on our survey 
results, we proposed to apportion 4.1 percentage points of the 6.4 
percentage point figure into the Professional Fees: Labor-Related share 
cost category and designate the remaining approximately 2.3 percentage 
points into the Professional Fees: Nonlabor-Related cost category.
    In addition to the professional services listed earlier, we also 
classify a proportion of the Home Office/Related Organization cost 
weight into the Professional Fees: Labor-Related cost category as was 
done in the previous rebasing. We believe that many of these costs are 
labor-intensive and vary with the local labor market. However, data 
indicate that not all IPPS hospitals with home offices have home 
offices located in their local labor market. Therefore, we proposed to 
include in the labor-related share only a proportion of the Home 
Office/Related Organization cost weight based on the methodology 
described in this final rule.
    For the proposed 2018-based IPPS market basket, based on Medicare 
cost report data, we found that approximately 65 percent of IPPS 
hospitals reported some type of home office information on their 
Medicare cost report for 2018 (for example, city, State, and zip code). 
Using the data reported on the Medicare cost report, we compared the 
location of the hospital with the location of the hospital's home 
office. We then determined the proportion of costs that should be 
allocated to the labor-related share based on the percent of total 
hospital home office/related organization contract labor costs for 
those hospitals that had home offices located in their respective local 
labor markets--defined as being in the same MSA. We determined a 
hospital's and home office's MSAs using their zip code information from 
the Medicare cost report.
    Based on these data, we determined the proportion of costs that 
should be allocated to the labor-related share based on the percent of 
hospital home office/related organization contract labor costs (equal 
to the sum of Worksheet S-3, Part II, column 4, lines 14.01, 14.02, 
25.50, and 25.51). Using this methodology, we determined that 60 
percent of hospitals' home office compensation costs were for home 
offices located in their respective local labor markets. Therefore, we 
proposed to allocate 60 percent of Home Office/Related Organization 
cost weight to the labor-related share. This is the same proportion we 
used for the 2014-based IPPS market basket, which was based on 2014 
Medicare cost report data.
    In the proposed 2018-based IPPS market basket, the Home Office/
Related Organization cost weight that is subject to allocation based on 
the home office allocation methodology represent 5.9 percent of total 
operating costs. Based on the results of the home office analysis, as 
previously discussed, we apportioned approximately 3.5 percentage 
points of the 5.9 percentage points figure into the Professional Fees: 
Labor-Related cost category and designated the remaining approximately 
2.4 percentage points into the Professional Fees: Nonlabor-Related cost 
category. In summary, based on the two previously mentioned 
allocations, we apportioned 7.6 percentage points of the professional 
fees and home office cost weights into the Professional Fees: Labor-
Related cost category. This amount is added to the portion of 
professional fees that we already identified as labor-related using the 
I-O data such as contracted advertising and marketing costs 
(approximately 1.0 percentage point of total operating costs) resulting 
in a Professional Fees: Labor-Related cost weight of 8.6 percent.
    Table IV-07 presents a comparison of the proposed 2018-based labor-
related share and the 2014-based labor-related share. As discussed in 
section IV.B.1.b. of the preamble of this final rule, the Wages and 
Salaries and Employee Benefits cost weights reflect contract labor 
costs.
[GRAPHIC] [TIFF OMITTED] TR13AU21.244

BILLING CODE 4120-01-C
    Using the cost category weights from the 2018-based IPPS market 
basket, we calculated a labor-related share of 67.6 percent, 
approximately 0.7 percentage point lower than the current labor-related 
share of 68.3 percent. This downward revision to the labor-related 
share is the net effect of two impacts. First, we updated the base year 
cost weights from 2014 to 2018 (-1.8 percentage points), which reflects 
a -2.8 percentage point revision from the compensation cost weight and 
a +1.0 percentage point revision from the labor-related portion of Home 
Office/Related Organization Contract Labor cost weight (60 percent of 
total cost weight). Second, there is an upward revision of 1.1 
percentage points from the impact of updating the detailed cost

[[Page 45206]]

weights to reflect 2012 Input-Output data.
    Therefore, we proposed to use a labor-related share of 67.6 percent 
for discharges occurring on or after October 1, 2021. We continue to 
believe, as we have stated in the past, that these operating cost 
categories are related to, influenced by, or vary with the local 
markets. Therefore, our definition of the labor-related share continues 
to be consistent with section 1886(d)(3) of the Act. We note that 
section 403 of Public Law 108-173 amended sections 1886(d)(3)(E) and 
1886(d)(9)(C)(iv) of the Act to provide that the Secretary must employ 
62 percent as the labor-related share unless 62 percent would result in 
lower payments to a hospital than would otherwise be made.
    We received several comments regarding our calculation of the 
proposed labor-related share based on the 2018-based IPPS market 
basket.
    Comment: Many commenters opposed the proposed change to the labor-
related share from 68.3 percent to 67.6 percent. Several commenters 
stated that this is in large part because they disagree with some of 
the assumptions underlying this proposal. They stated that they are 
concerned that the methodology CMS uses to rebase and revise the labor-
related share is premised on the flawed assumption that some categories 
of labor costs are not subject to geographic variation.
    Several commenters disagreed with CMS' proposal to exclude from the 
labor-related share the proportion of non-medical professional services 
fees presumed to have been purchased outside of the hospital's labor 
market. The commenters disagreed with CMS' assertion/assumption that 
services purchased from national firms are not affected by the local 
labor market. In the commenters' experience, national firms adjust 
their rates for different reasons, including reasons that are largely 
dictated by local labor costs. The commenters stated that when 
hospitals seek professional services, the services they are seeking 
(for example accounting, engineering, management consulting) typically 
are not so unique that they could only be provided by regional or 
national firms. The commenters stated that CMS' own survey data support 
this conclusion, as approximately 60 percent of these services are 
sourced from firms in the local market. The commenters stated that 
costs of services purchased from firms outside the hospital's labor 
market should be included with the labor-related share of costs.
    Response: We disagree with the commenters and believe it is 
appropriate that a proportion of Accounting & Auditing, Legal, 
Engineering, and Management Consulting services costs purchased by 
hospitals should be excluded from the labor-related share. Section 
1886(d)(3)(E)(i) of the Act directs the Secretary to adjust the 
proportion of hospitals' costs which are attributable to wages and 
wage-related costs, of the DRG prospective payment rates computed under 
subparagraph (D) for area differences in hospital wage levels by a 
factor (established by the Secretary) reflecting the relative hospital 
wage level in the geographic area of the hospital compared to the 
national average hospital wage level. It also directs the Secretary to 
estimate from time to time this proportion of hospital costs that are 
labor-related.
    The purpose of the labor-related share is to reflect the proportion 
of the national PPS base payment rate that is adjusted by the 
hospital's wage index (representing the relative costs of their local 
labor market to the national average). Therefore, we include a cost 
category in the labor-related share if the costs are labor intensive 
and vary with the local labor market.
    As acknowledged by the commenter and confirmed by the survey of 
hospitals conducted by CMS in 2008 (as stated above), professional 
services can be purchased from local firms as well as national and 
regional professional services firms. It is not necessarily the case, 
as asserted by the commenter, that these national and regional firms 
have fees that match those in the local labor market even though 
providers have the option to utilize those firms. That is, fees for 
services purchased from firms outside the local labor market may differ 
from those that would be purchased in the local labor market for any 
number of reasons (including but not limited to, the skill level of the 
contracted personnel, higher capital costs, etc.). The approximately 64 
percent of the Professional Fees cost weight allocated to the 
Professional Fees: Labor-related cost weight based on the survey 
results reflect the commenter's assertion that not all Professional 
Fees services are purchased in the local labor market. We believe it is 
reasonable to conclude that those services purchased directly within 
the local labor market are directly related to local labor market 
conditions and, thus, should be included in the labor-related share. 
The remaining 36 percent would reflect different and additional factors 
outside the local labor market and, thus, should be excluded from the 
labor related share.
    The 64 percent is based on a survey conducted by CMS in 2008 as 
detailed in the FY 2010 IPPS/LTCH PPS final rule (74 FR 43850 through 
43856). This was also used to determine the Professional Fees: Labor-
related cost weight in the 2014-based IPPS market basket. We would note 
that CMS is in the process of proposing an additional question to the 
hospital Medicare cost reports (CMS Form 2552-2010; OMB Number 0938-
0050) to help better determine which proportion of Accounting & 
Auditing, Legal, Engineering, and Management Consulting services costs 
are purchased from the local labor market (85 FR 71654). We encourage 
hospitals to fill out this question (if finalized) in future Medicare 
cost report submissions.
    Therefore, for the reasons discussed, we believe our proposed 
methodology of allocating only a portion of Professional Fees to the 
Professional Fees: Labor-Related cost category is appropriate.
    Comment: Several commenters disagreed with the assumption that home 
office compensation costs that occur outside of a hospital's labor 
market are not subject to geographic wage variation, and stated that 
they do not believe that the proposed reclassification to the 
Professional Fees: Non-Labor-Related cost category is justified. The 
commenters stated that the proposed methodology fails to consider that 
the home office is essentially a part of the hospital, and thus the 
hospital, along with its home office, is operating in multiple labor 
markets. The commenters stated that the home office's portion of the 
hospital's labor costs should not be excluded from the labor-related 
share simply because they are not in the same labor market as the 
hospital.
    The commenters stated that even if the wage-index adjustment 
applied to hospital payments is not sufficiently refined to recognize 
this multi-labor-market circumstance, that is no reason to completely 
eliminate the recognition of these costs under the IPPS as being 
affected by local labor market forces. The commenters stated that the 
proposed methodology seems particularly unfair to independent hospitals 
in high-wage areas with no home office costs that will see their 
reimbursement lowered through a reduction in the labor-related share 
because a portion of other hospitals' administrative costs have been 
removed. Therefore, the commenters requested that CMS treat 100 percent 
of home office labor costs as being ``labor related.''
    A commenter conducted their own analysis of the FY 2018 Medicare 
cost report data showing that providers with

[[Page 45207]]

a home office outside of their local labor market were located in areas 
with a wage index below 1 as well as greater than 1. The commenter 
stated that those hospitals in a labor market with a wage index greater 
than 1 had a mean home office average hourly wage costs that were 
greater than the mean home office average hourly wage costs of those 
hospitals in a labor market with a wage index less than 1. The 
commenter claimed that these data indicate that, contrary to CMS' 
assertion, home office salary, wage, and benefit costs for hospitals 
with home offices outside of their labor market are subject to 
geographic wage variation.
    The commenter stated that the agency is not adjusting the full 
proportion of hospitals' wages and wage-related costs subject to 
geographic variation by excluding a cumulative 4.7 percentage points of 
the Non-Medical Professional Fees (2.3 percentage points) and Home 
Office/Related Organization (2.4 percentage points) cost weights from 
the labor-related share.
    Response: As previously stated, the purpose of the labor-related 
share is to determine the proportion of the national PPS base payment 
rate that is adjusted by the hospital's wage index (representing the 
relative costs of their local labor market to the national average). 
Therefore, we include a cost category in the labor-related share if the 
costs are labor intensive and vary with the local labor market.
    As the commenter stated and as validated with the Medicare cost 
report, a hospital's home office can be located outside the hospital's 
local labor market. The proposed methodology for allocating 60 percent 
of the Home Office/Related Organization cost weight (reflecting 
compensation costs) is consistent with the intent of the statute to 
identify the proportion of costs likely to directly vary with the 
hospital's local labor market. Our methodology relies on the Medicare 
cost report data for hospitals reporting home office information to 
determine whether their home office is located in the same local labor 
market (which we define as the hospital's Metropolitan Statistical 
Area). Similar to our rationale as previously discussed, for 
professional fees, we believe it is reasonable to conclude that those 
home office services purchased directly within the local labor market 
are directly related to local labor market conditions while the 
remaining 40 percent would reflect different and additional factors 
and, thus, should be excluded from the labor related share.
    Therefore, we believe our proposed methodology of only allocating a 
portion of the Home Office/Related Organization cost weight into the 
Professional Fees: Labor-related cost weight is appropriate.
    Comment: A commenter stated that as with the adoption of OMB 
Bulletin 18-04, which revises the core-based statistical areas (CBSAs) 
that drive the Medicare wage index, CMS is relying upon 2018 data for 
its proposal to reduce the labor-related component. The commenter 
stated that they believe this 2018 data has been made stale by the 
onset of the current COVID-19 pandemic, which caused significant shifts 
in the labor markets, particularly with regard to wages and fringe 
benefits.
    The commenter stated that the reduction in the labor-related share 
has a disproportionate and significant impact on hospitals in the 
greater New York metropolitan area. The commenter estimated that the 
impact of this proposal for Suburban Hospital Alliance members is 
another $9.6 million in reduced reimbursements. The commenter stated 
that for these reasons, they urge CMS to postpone adjustments to the 
labor component until 2020 Census data can be fully analyzed and 
incorporated into the rates.
    A commenter noted that CMS last rebased the hospital market basket 
cost weights effective for FY 2018, with 2014 data for the base period. 
For FY 2022, CMS proposes to rebase the IPPS operating market basket to 
reflect the 2018 cost structure for IPPS hospitals. The commenter is 
concerned that the data may not be as generalizable to FY 2022 like 
previous years given the effects of COVID-19 on both hospitals and 
other providers directly and to the economy more broadly. They agree 
with CMS that it should continue to monitor the upcoming Medicare cost 
report data to see if a more frequent rebasing schedule is necessary. 
To the extent CMS is already aware of, or is made aware of, cost 
increases due to COVID-19 (for example, staffing, creating new/
alternative care sites), they recommend the agency consider temporary 
modifications to better account for such changes in determining the 
market basket.
    A few commenters stated that although Federal law requires the 
Secretary to update market basket weights, including the labor share, 
more frequently than every five years, it does not dictate the 
methodology for doing so. The commenters stated that the COVID-19 
emergency has had an unusual and unexpected impact on hospital wages in 
many places, and especially in urban areas with already higher-than-
average wages (that is, wage indexes greater than 1.0). The commenters 
stated that the proposed reduction of the labor-related share would 
apply only to geographic areas with a wage index greater than 1.0 and 
would therefore reduce reimbursement to those very hospitals that 
already faced the highest labor costs just as those costs are further 
increasing in response to the public health emergency. The commenters 
stated that it is too soon to measure that impact and impose this type 
of cut on so many hospitals.
    Response: We appreciate the commenters' concerns regarding how 
operating expenses for hospitals may have been impacted by the PHE. 
However, we disagree with the commenters that the update of the labor-
related share should be postponed. As published in the FY 2006 IPPS 
final rule (70 FR 47403), in accordance with section 404 of Public Law 
108-173, CMS determined a new frequency for rebasing the hospital 
market basket, including the labor-related share, of every four years. 
Therefore, our proposal is consistent with this finalized policy to 
update the labor-related share to reflect the rebased and revised IPPS 
market basket, which is now based on 2018 data. Additionally, it is a 
technical improvement for the labor related share to reflect more 
current data (2018) than maintain a share based on older (2014) data.
    The market basket cost share weights are based on the relative 
shares of expenses by category. In order to evaluate the impact of the 
PHE on the market basket cost weights, CMS would need to have a 
complete dataset that would provide expenditure levels for all 
categories of expenses to determine the relative shares of each cost 
category. However, there is not a comprehensive set of 2020 cost data 
for hospitals available at this time. As stated previously, we plan to 
review the Medicare cost report data as soon as complete information is 
available and evaluate these data for future rulemaking.
    After consideration of the public comments we received, we are 
finalizing the 2018-based IPPS market basket and labor-related share as 
proposed.

C. Market Basket for Certain Hospitals Presently Excluded From the IPPS

    In the FY 2010 IPPS/RY 2010 LTCH PPS final rule (74 FR 43857), we 
adopted the use of the FY 2006-based IPPS operating market basket 
percentage increase to update the target amounts for children's 
hospitals, PPS-excluded cancer hospitals and religious nonmedical 
health care institutions (RNHCIs). Children's hospitals and PPS-

[[Page 45208]]

excluded cancer hospitals and RNHCIs are still reimbursed solely under 
the reasonable cost-based system, subject to the rate-of-increase 
limits. Under these limits, an annual target amount (expressed in terms 
of the inpatient operating cost per discharge) is set for each hospital 
based on the hospital's own historical cost experience trended forward 
by the applicable rate-of-increase percentages.
    In the FY 2014 IPPS/LTCH PPS final rule (78 FR 50603), under the 
broad authority in sections 1886(b)(3)(A) and (B), 1886(b)(3)(E), and 
1871 of the Act and section 4454 of the BBA, consistent with our use of 
the IPPS operating market basket percentage increase to update target 
amounts, we adopted the use of the FY 2010-based IPPS operating market 
basket percentage increase to update the target amounts for children's 
hospitals, PPS-excluded cancer hospitals, and RNHCIs that are paid on 
the basis of reasonable cost subject to the rate-of-increase limits 
under Sec.  413.40. In addition, as discussed in the FY 2015 IPPS/LTCH 
PPS final rule (79 FR 50156 through 50157), consistent with Sec. Sec.  
412.23(g), 413.40(a)(2)(ii)(A), and 413.40(c)(3)(viii), we also used 
the percentage increase in the FY 2010-based IPPS operating market 
basket to update the target amounts for short-term acute care hospitals 
located outside the 50 States, the District of Columbia, and Puerto 
Rico (that is, hospitals located in the U.S. Virgin Islands, Guam, the 
Northern Mariana Islands, and American Samoa). These hospitals also are 
paid on the basis of reasonable cost, subject to the rate-of-increase 
limits under Sec.  413.40. In the FY 2018 IPPS/LTCH PPS final rule, we 
finalized the use of the 2014-based IPPS operating market basket for FY 
2018 and subsequent fiscal years to update the target amounts for 
children's hospitals, PPS-excluded cancer hospitals, RNHCIs, and short-
term acute care hospitals located outside the 50 states, the District 
of Columbia, and Puerto Rico (that is, hospitals located in the U.S. 
Virgin Islands, Guam, the Northern Mariana Islands, and American Samoa) 
that are paid on the basis of reasonable cost subject to the rate-of-
increase limits under Sec.  413.40. We refer the reader to the FY 2018 
IPPS/LTCH PPS final rule (82 FR 38170) for discussion of why we believe 
it is appropriate to use the percentage increase in the IPPS operating 
market basket to update the target amounts for these excluded 
facilities.
    As discussed in this section IV. of the preamble of the FY 2022 
IPPS/LTCH PPS proposed rule, we proposed to rebase and revise the IPPS 
operating market basket to a 2018 base year. We continue to believe 
that it is appropriate to use the increase in the IPPS operating market 
basket to update the target amounts for these excluded facilities, as 
discussed in prior rulemaking. Therefore, we proposed to use the 
percentage increase in the proposed 2018-based IPPS operating market 
basket to update the target amounts for children's hospitals, the PPS-
excluded cancer hospitals, RNHCIs, and short-term acute care hospitals 
located outside the 50 states, the District of Columbia, and Puerto 
Rico (that is, hospitals located in the U.S. Virgin Islands, Guam, the 
Northern Mariana Islands, and American Samoa) for FY 2022 and 
subsequent fiscal years. Accordingly, for FY 2022, the rate-of increase 
percentage to be applied to the target amount for these hospitals would 
be the FY 2022 percentage increase in the 2018-based IPPS operating 
market basket.
    We received no comments on this proposal and therefore are 
finalizing this proposal without modification.

D. Rebasing and Revising the Capital Input Price Index (CIPI)

    The CIPI was originally described in the FY 1993 IPPS final rule 
(57 FR 40016). There have been subsequent discussions of the CIPI 
presented in the IPPS proposed and final rules. The FY 2018 IPPS/LTCH 
PPS final rule (82 FR 38170 through 38175) described the most recent 
rebasing and revising of the CIPI to a 2014 base year, which reflected 
the capital cost structure of IPPS hospitals available at that time.
    For the FY 2022 IPPS update, we proposed to rebase and revise the 
CIPI to a 2018 base year to reflect a more current structure of capital 
costs for IPPS hospitals. This proposed 2018-based CIPI was derived 
using 2018 cost reports for IPPS hospitals, which includes providers 
whose cost reporting period began on or after October 1, 2017, and 
prior to September 30, 2018. We also proposed to start with the same 
subset of Medicare cost reports from IPPS hospitals as previously 
described in section IV.B.1.a. of the preamble of this rule. As with 
the 2014-based index, we proposed to develop two sets of weights to 
derive the proposed 2018-based CIPI. The first set of weights 
identifies the proportion of hospital capital expenditures attributable 
to each expenditure category, while the second set of weights is a set 
of relative vintage weights for depreciation and interest. The set of 
vintage weights is used to identify the proportion of capital 
expenditures within a cost category that is attributable to each year 
over the useful life of the capital assets in that category. A more 
thorough discussion of vintage weights is provided later in this 
section.
    Using 2018 Medicare cost reports, we are able to obtain capital 
costs for the following categories: Depreciation, Interest, Lease, and 
Other. Specifically, we proposed to determine what proportion of total 
capital costs that each category represents using the data reported by 
IPPS hospitals on Worksheet A-7, Part III. As shown in the left column 
of Table IV-08, in 2018 depreciation expenses accounted for 67.5 
percent of total capital costs, interest expenses accounted for 14.6 
percent, leasing expenses accounted for 13.3 percent, and other capital 
expenses accounted for 4.7 percent.
    We also proposed to allocate lease costs across each of the 
remaining capital cost categories as was done in the 2014-based CIPI. 
We proposed to proportionally distribute leasing costs among the cost 
categories of Depreciation, Interest, and Other, reflecting the 
assumption that the underlying cost structure of leases is similar to 
that of capital costs in general. As was done for the 2014-based CIPI, 
we proposed to assume that 10 percent of the lease costs as a 
proportion of total capital costs represents overhead and to assign 
those costs to the Other capital cost category accordingly. Therefore, 
we assumed that approximately 1.3 percent (13.3 percent x 0.1) of total 
capital costs represent lease costs attributable to overhead, and we 
proposed to add this 1.3 percent to the 4.7 percent Other cost category 
weight. We then proposed to distribute the remaining lease costs (12.0 
percent, or 13.3 percent-1.3 percent) proportionally across the three 
cost categories (Depreciation, Interest, and Other) based on the 
proportion that these categories comprise of the sum of the 
Depreciation, Interest, and Other cost categories (excluding lease 
expenses). For example, the Other cost category represented 5.4 percent 
of all three cost categories (Depreciation, Interest, and Other) prior 
to any lease expenses being allocated. This 5.4 percent is applied to 
the 12.0 percent of remaining lease expenses so that another 0.6 
percent of lease expenses as a percent of total capital costs is 
allocated to the Other cost category. Therefore, the resulting proposed 
Other cost weight is 6.6 percent (4.7 percent + 1.3 percent + 0.6 
percent). This is the same methodology used for the 2014-based CIPI. 
The resulting cost weights of the proposed allocation of lease expenses 
are shown in the right column of Table IV-08.
BILLING CODE 4120-01-P

[[Page 45209]]

[GRAPHIC] [TIFF OMITTED] TR13AU21.245

    Finally, we proposed to further divide the Depreciation and 
Interest cost categories. We proposed to separate the Depreciation cost 
category into the following two categories: (1) Building and Fixed 
Equipment and (2) Movable Equipment. We also proposed to separate the 
Interest cost category into the following two categories: (1) 
Government/Nonprofit; and (2) For-profit.
    To disaggregate the depreciation cost weight, we needed to 
determine the percent of total depreciation costs for IPPS hospitals 
(after the allocation of lease costs) that are attributable to building 
and fixed equipment, which we hereafter refer to as the ``fixed 
percentage.'' Based on Worksheet A-7, Part III data from the 2018 IPPS 
Medicare cost reports, we have determined that depreciation costs for 
building and fixed equipment account for approximately 51 percent of 
total depreciation costs, while depreciation costs for movable 
equipment account for approximately 49 percent of total depreciation 
costs. As was done for the 2014-based CIPI, we proposed to apply this 
fixed percentage to the depreciation cost weight (after leasing costs 
are included) to derive a Depreciation cost weight attributable to 
Building and Fixed Equipment and a Depreciation cost weight 
attributable to Movable Equipment.
    To disaggregate the interest cost weight, we needed to determine 
the percent of total interest costs for IPPS hospitals that are 
attributable to government and nonprofit facilities, which we hereafter 
refer to as the ``nonprofit percentage,'' because interest price 
pressures tend to differ between nonprofit and for-profit facilities. 
We proposed to use interest costs data from Worksheet A-7, Part III of 
the 2018 Medicare cost reports for IPPS hospitals, which is the same 
methodology used for the 2014-based CIPI. The nonprofit percentage 
determined using this method is 90 percent. Table IV-09 in the proposed 
rule provided a comparison of the 2014-based CIPI cost weights and the 
proposed 2018-based CIPI cost weights. This table is also included 
below and reflects the final 2018-based CIPI cost weights.
    We received no comments on the methodology to derive the cost 
weights of the proposed 2018-based CIPI and therefore are finalizing 
this methodology without modification.
    After the capital cost category weights were computed, it was 
necessary to select appropriate price proxies to reflect the rate-of-
increase for each expenditure category. With the exception of the For-
profit interest cost category, we proposed to apply the same price 
proxies as were used in the 2014-based CIPI, which are listed in Table 
IV-09. We also proposed to continue to vintage weight the capital price 
proxies for Depreciation and Interest to capture the long-term 
consumption of capital. This vintage weighting method is the same 
method that was used for the 2014-based CIPI and is described later in 
this section of this rule.
    We proposed to continue to proxy the Depreciation--Building and 
Fixed Equipment cost category by the BEA Chained Price Index for 
Private Fixed Investment in Structures, Nonresidential, Hospitals and 
Special Care (BEA Table 5.4.4. Price Indexes for Private Fixed 
Investment in Structures by Type). As stated in the FY 2010 IPPS/LTCH 
final rule (74 FR 43860), for the FY 2006-based CIPI we finalized the 
use of this index to measure the price growth of this cost category. 
This BEA index is intended to capture prices for construction of 
facilities such as hospitals, nursing homes, hospices, and 
rehabilitation centers. For the Depreciation--Movable Equipment cost 
category, we proposed to continue to measure the price growth using the 
PPI Commodity for Machinery and Equipment (BLS series code WPU11). This 
price index reflects price inflation associated with a variety of 
machinery and equipment that would be utilized by hospitals including 
but not limited to communication equipment, computers, and medical 
equipment. For the Nonprofit Interest cost category, we proposed to 
continue to measure the price growth using the average yield on 
domestic municipal bonds (Bond Buyer 20-bond index).
    For the For-profit Interest cost category, we proposed to use the 
iBoxx AAA Corporate Bond Yield index instead of the Moody's AAA 
Corporate Bond Yield index that was used for the 2014-based IPPS market 
basket. Effective for December 2020, the Moody's AAA Corporate Bond 
series is no longer available for use under license to IGI, the 
nationally-recognized economic and financial forecasting firm with 
which we contract to forecast the components of the market baskets and 
MFP. Therefore, we proposed to replace the price proxy for the For-
profit Interest cost category. We compared the iBoxx AAA Corporate Bond 
Yield index with the Moody's AAA Corporate Bond Yield index and found 
that the average growth rates in the two series were similar. Over the 
historical time period of FY 2000 to FY 2020, the 4-quarter percent 
change moving average growth in the iBoxx series was approximately 0.1 
percentage point higher, on average, than the Moody's AAA corporate 
Bond Yield index.
    For the Other capital cost category (including insurances, taxes, 
and other capital-related costs), we proposed to continue to measure 
the price growth using the CPI for Rent of Primary Residence (All Urban 
Consumers) (BLS series code CUUS0000SEHA), which would reflect the 
price growth of these costs. We believe that these price proxies 
continue to be the most appropriate proxies for IPPS capital costs that 
meet our selection criteria of relevance, timeliness, availability, and 
reliability.
    We received no comments on our proposed price proxies for the 2018-

[[Page 45210]]

based CIPI and therefore are finalizing without modification.
[GRAPHIC] [TIFF OMITTED] TR13AU21.246

    Because capital is acquired and paid for over time, capital 
expenses in any given year are determined by both past and present 
purchases of physical and financial capital. The vintage-weighted 2018-
based CIPI is intended to capture the long-term consumption of capital, 
using vintage weights for depreciation (physical capital) and interest 
(financial capital). These vintage weights reflect the proportion of 
capital purchases attributable to each year of the expected life of 
building and fixed equipment, movable equipment, and interest.
    Vintage weights are an integral part of the CIPI. Capital costs are 
inherently complicated and are determined by complex capital purchasing 
decisions, over time, based on such factors as interest rates and debt 
financing. In addition, capital is depreciated over time instead of 
being consumed in the same period it is purchased. By accounting for 
the vintage nature of capital, we are able to provide an accurate and 
stable annual measure of price changes. Annual nonvintage price changes 
for capital are unstable due to the volatility of interest rate changes 
and, therefore, do not reflect the actual annual price changes for IPPS 
capital costs. The CIPI reflects the underlying stability of the 
capital acquisition process.
    To calculate the vintage weights for depreciation and interest 
expenses, we first needed a time series of capital purchases for 
building and fixed equipment and movable equipment. We found no single 
source that provides an appropriate time series of capital purchases by 
hospitals for all of the previously noted components of capital 
purchases. The early Medicare cost reports did not have sufficient 
capital data to meet this need. Data we obtained from the American 
Hospital Association (AHA) did not include annual capital purchases. 
However, we were able to obtain data on total expenses back to 1963 
from the AHA. Consequently, we proposed to use data from the AHA Panel 
Survey and the AHA Annual Survey to obtain a time series of total 
expenses for hospitals. We then proposed to use data from the AHA Panel 
Survey supplemented with the ratio of depreciation to total hospital 
expenses obtained from the Medicare cost reports to derive a trend of 
annual depreciation expenses for 1963 through 2018. We proposed to 
separate these depreciation expenses into annual amounts of building 
and fixed equipment depreciation and movable equipment depreciation as 
determined earlier. From these annual depreciation amounts, we derived 
annual end-of-year book values for building and fixed equipment and 
movable equipment using the expected life for each type of asset 
category. We used the AHA data and similar methodology to derive the 
2014-based IPPS capital market basket.
    To continue to calculate the vintage weights for depreciation and 
interest expenses, we also needed to account for the expected lives for 
building and fixed equipment, movable equipment, and interest for the 
proposed 2018-based CIPI. We proposed to calculate the expected lives 
using Medicare cost report data. The expected life of any asset can be 
determined by dividing the value of the asset (excluding fully 
depreciated assets) by its current year depreciation amount. This 
calculation yields the estimated expected life of an asset if the rates 
of depreciation were to continue at current year levels, assuming 
straight-line depreciation. Using this proposed method, we determined 
the average expected life of building and fixed equipment to be equal 
to 27 years, and the average expected life of movable equipment to be 
equal to 12 years. For the expected life of interest, we believe that 
vintage weights for interest should represent the average expected life 
of building and fixed equipment because, based on previous research 
described in the FY 1997 IPPS final rule (61 FR 46198), the expected 
life of hospital debt instruments and the expected life of buildings 
and fixed equipment are similar. We note that the 2014-based CIPI was 
also based on an expected average life of building and fixed equipment 
of 27 years and an expected average life of movable equipment of 12 
years.
    Multiplying these expected lives by the annual depreciation amounts 
results in annual year-end asset costs for building and fixed equipment 
and movable equipment. We then calculated a time series, beginning in 
1964, of annual capital purchases by subtracting the previous year's 
asset costs from the current year's asset costs.
    For the building and fixed equipment and movable equipment vintage

[[Page 45211]]

weights, we proposed to use the real annual capital-related purchase 
amounts for each asset type to capture the actual amount of the 
physical acquisition, net of the effect of price inflation. These real 
annual capital-related purchase amounts are produced by deflating the 
nominal annual purchase amount by the associated price proxy as 
provided earlier in this final rule. For the interest vintage weights, 
we proposed to use the total nominal annual capital-related purchase 
amounts to capture the value of the debt instrument (including, but not 
limited to, mortgages and bonds). Using these capital purchases time 
series specific to each asset type, we proposed to calculate the 
vintage weights for building and fixed equipment, for movable 
equipment, and for interest.
    The vintage weights for each asset type are deemed to represent the 
average purchase pattern of the asset over its expected life (in the 
case of building and fixed equipment and interest, 27 years, and in the 
case of movable equipment, 12 years). For each asset type, we proposed 
to use the time series of annual capital purchases amounts available 
from 2018 back to 1964. These data allow us to derive twenty-nine 27-
year periods of capital purchases for building and fixed equipment and 
interest, and forty-four 12-year periods of capital purchases for 
movable equipment. For each 27-year period for building and fixed 
equipment and interest, or 12-year period for movable equipment, we 
proposed to calculate annual vintage weights by dividing the capital-
related purchase amount in any given year by the total amount of 
purchases over the entire 27-year or 12-year period. This calculation 
was done for each year in the 27-year or 12-year period and for each of 
the periods for which we have data. We then calculated the average 
vintage weight for a given year of the expected life by taking the 
average of these vintage weights across the multiple periods of data.
    We received no comments on our proposed vintage weights and 
therefore are finalizing without modification.
    The vintage weights for the 2018-based CIPI and the 2014-based CIPI 
are presented in Table IV-10.

[[Page 45212]]

[GRAPHIC] [TIFF OMITTED] TR13AU21.247

    The process of creating vintage-weighted price proxies requires 
applying the vintage weights to the price proxy index where the last 
applied vintage weight in Table IV-10 is applied to the most recent 
data point. We have provided on the CMS website an example of how the 
vintage weighting price proxies are calculated, using example vintage 
weights and example price indices. The example can be found under the 
following CMS website link: http://www.cms.gov/Research-Statistics-Data-and-Systems/Statistics-Trends-and-Reports/MedicareProgramRatesStats/MarketBasketResearch.html in the zip file 
titled ``Weight Calculations as described in the IPPS FY 2010 Proposed 
Rule.''
    As noted, we did not receive any public comments on our methodology 
for deriving the proposed 2018-based CIPI. Accordingly, in this final 
rule and for the reasons discussed, we are finalizing the 2018-based 
CIPI as proposed. Table IV-11 in this section of this final rule 
compares both the historical and forecasted percent changes in the 
2014-based CIPI and the 2018-based CIPI based on IGI's second quarter 
2021 forecast with historical data through first quarter 2021.

[[Page 45213]]

[GRAPHIC] [TIFF OMITTED] TR13AU21.248

    IHS Global, Inc. forecasts a 1.1 percent increase in the 2018-based 
CIPI for FY 2022, as shown in Table IV-11. The underlying vintage-
weighted price increases for depreciation (including building and fixed 
equipment and movable equipment) and interest (including government/
nonprofit and for-profit) based on the 2018-based CIPI are included in 
Table IV-12.
[GRAPHIC] [TIFF OMITTED] TR13AU21.249

    Rebasing the CIPI from 2014 to 2018 did not have an impact on the 
percent change in the forecasted update for FY 2022 when rounded, as 
shown in Table IV-11.

V. Other Decisions and Changes to the IPPS for Operating Costs

A. Changes in the Inpatient Hospital Update for FY 2022 (Sec.  
412.64(d))

1. FY 2022 Inpatient Hospital Update
    In accordance with section 1886(b)(3)(B)(i) of the Act, each year 
we update the national standardized amount for inpatient hospital 
operating costs by a factor called the ``applicable percentage 
increase.'' For FY 2022, we are setting the applicable percentage 
increase by applying the adjustments listed in this section in the same 
sequence as we did for FY 2021. (We note that section 
1886(b)(3)(B)(xii) of the Act required an additional reduction each 
year only for FYs 2010 through 2019.) Specifically, consistent with 
section 1886(b)(3)(B) of the Act, as amended by sections 3401(a) and

[[Page 45214]]

10319(a) of the Affordable Care Act, we are setting the applicable 
percentage increase by applying the following adjustments in the 
following sequence. The applicable percentage increase under the IPPS 
for FY 2022 is equal to the rate-of-increase in the hospital market 
basket for IPPS hospitals in all areas, subject to all of the 
following:
     A reduction of one-quarter of the applicable percentage 
increase (prior to the application of other statutory adjustments; also 
referred to as the market basket update or rate-of-increase (with no 
adjustments)) for hospitals that fail to submit quality information 
under rules established by the Secretary in accordance with section 
1886(b)(3)(B)(viii) of the Act.
     A reduction of three-quarters of the applicable percentage 
increase (prior to the application of other statutory adjustments; also 
referred to as the market basket update or rate-of-increase (with no 
adjustments)) for hospitals not considered to be meaningful EHR users 
in accordance with section 1886(b)(3)(B)(ix) of the Act.
     An adjustment based on changes in economy-wide multifactor 
productivity (MFP) (the productivity adjustment).
    Section 1886(b)(3)(B)(xi) of the Act, as added by section 3401(a) 
of the Affordable Care Act, states that application of the productivity 
adjustment may result in the applicable percentage increase being less 
than zero.
    We note, in compliance with section 404 of the MMA, in the proposed 
rule, we proposed to replace the 2014-based IPPS operating and capital 
market baskets with the rebased and revised 2018-based IPPS operating 
and capital market baskets for FY 2022.
    We proposed to base the proposed FY 2022 market basket update used 
to determine the applicable percentage increase for the IPPS on IHS 
Global Inc.'s (IGI's) fourth quarter 2020 forecast of the proposed 
2018-based IPPS market basket rate-of-increase with historical data 
through third quarter 2020, which was estimated to be 2.5 percent. We 
also proposed that if more recent data subsequently became available 
(for example, a more recent estimate of the market basket update and 
the productivity adjustment), we would use such data, if appropriate, 
to determine the FY 2022 market basket update and the productivity 
adjustment in this final rule. We received public comments regarding 
the rebasing and revising of the IPPS operating market basket and refer 
readers to section IV.B. of this final rule for a complete discussion 
on the rebasing and revising of the market basket. In section IV.B., we 
are finalizing our proposals without modification and, therefore, are 
using the finalized rebased and revised 2018- based IPPS market basket 
rate-of increase for FY 2022.
    Based on more recent data available for this FY 2022 IPPS/LTCH PPS 
final rule (that is, IGI's second quarter 2021 forecast of the 2018-
based IPPS market basket rate-of-increase with historical data through 
the first quarter of 2021), we estimate that the FY 2022 market basket 
update used to determine the applicable percentage increase for the 
IPPS is 2.7 percent.
    For FY 2022, depending on whether a hospital submits quality data 
under the rules established in accordance with section 
1886(b)(3)(B)(viii) of the Act (hereafter referred to as a hospital 
that submits quality data) and is a meaningful EHR user under section 
1886(b)(3)(B)(ix) of the Act (hereafter referred to as a hospital that 
is a meaningful EHR user), there are four possible applicable 
percentage increases that can be applied to the standardized amount, as 
specified in the table that appears later in this section.
    In the FY 2012 IPPS/LTCH PPS final rule (76 FR 51689 through 
51692), we finalized our methodology for calculating and applying the 
productivity adjustment. As we explained in that rule, section 
1886(b)(3)(B)(xi)(II) of the Act, as added by section 3401(a) of the 
Affordable Care Act, defines this productivity adjustment as equal to 
the 10-year moving average of changes in annual economy-wide, private 
nonfarm business MFP (as projected by the Secretary for the 10-year 
period ending with the applicable fiscal year, calendar year, cost 
reporting period, or other annual period). The Bureau of Labor 
Statistics (BLS) publishes the official measure of private nonfarm 
business MFP. We refer readers to the BLS website at http://www.bls.gov/mfp for the BLS historical published MFP data.
    MFP is derived by subtracting the contribution of labor and capital 
input growth from output growth. The projections of the components of 
MFP are currently produced by IGI, a nationally recognized economic 
forecasting firm with which CMS contracts to forecast the components of 
the market baskets and MFP. A complete description of the MFP 
projection methodology is available on the CMS website at: http://www.cms.gov/Research-Statistics-Data-and-Systems/Statistics-Trends-and-Reports/MedicareProgramRatesStats/MarketBasketResearch.html. We note 
that beginning with this FY 2022 final rule, we refer to this 
adjustment as the productivity adjustment rather than the MFP 
adjustment to more closely track the statutory language in section 
1886(b)(3)(B)(xi)(II) of the Act. We note that the adjustment continues 
to rely on the same underlying data and methodology.
    For FY 2022, we proposed a productivity adjustment of 0.2 
percentage point. Similar to the market basket update, for the proposed 
rule, we used IGI's fourth quarter 2020 forecast of MFP to compute the 
proposed FY 2022 productivity adjustment. As noted previously, we 
proposed that if more recent data subsequently became available, we 
would use such data, if appropriate, to determine the FY 2022 market 
basket update and the productivity adjustment for this final rule. 
Based on more recent data available for this FY 2022 IPPS/LTCH PPS 
final rule (that is, IGI's second quarter 2021 forecast), the current 
estimate of the productivity adjustment for FY 2022 is 0.7 percentage 
point.
    We did not receive any public comments on our proposal to use more 
recent available data to determine the final market basket update and 
the productivity adjustment. Therefore, for this final rule, we are 
finalizing a market basket update of 2.7 percent and a productivity 
adjustment of 0.7 percentage point based on the more recent available 
data.
    Based on these more recent data available, for this final rule, we 
have determined four applicable percentage increases to the 
standardized amount for FY 2022, as specified in the following table:

[[Page 45215]]

[GRAPHIC] [TIFF OMITTED] TR13AU21.250

BILLING CODE 4120-01-C
    In the FY 2020 IPPS/LTCH PPS final rule (84 FR 42344), we revised 
our regulations at 42 CFR 412.64(d) to reflect the current law for the 
update for FY 2020 and subsequent fiscal years. Specifically, in 
accordance with section 1886(b)(3)(B) of the Act, we added paragraph 
(d)(1)(viii) to Sec.  412.64 to set forth the applicable percentage 
increase to the operating standardized amount for FY 2020 and 
subsequent fiscal years as the percentage increase in the market basket 
index, subject to the reductions specified under Sec.  412.64(d)(2) for 
a hospital that does not submit quality data and Sec.  412.64(d)(3) for 
a hospital that is not a meaningful EHR user, less a productivity 
adjustment. (As previously noted, section 1886(b)(3)(B)(xii) of the Act 
required an additional reduction each year only for FYs 2010 through 
2019.)
    Section 1886(b)(3)(B)(iv) of the Act provides that the applicable 
percentage increase to the hospital-specific rates for SCHs and MDHs 
equals the applicable percentage increase set forth in section 
1886(b)(3)(B)(i) of the Act (that is, the same update factor as for all 
other hospitals subject to the IPPS). Therefore, the update to the 
hospital-specific rates for SCHs and MDHs also is subject to section 
1886(b)(3)(B)(i) of the Act, as amended by sections 3401(a) and 
10319(a) of the Affordable Care Act. (Under current law, the MDH 
program is effective for discharges on or before September 30, 2022, as 
discussed in the FY 2019 IPPS/LTCH PPS final rule (83 FR 41429 through 
41430).)
    For FY 2022, we proposed the following updates to the hospital-
specific rates applicable to SCHs and MDHs: a proposed update of 2.3 
percent for a hospital that submits quality data and is a meaningful 
EHR user; a proposed update of 0.425 percent for a hospital that 
submits quality data and is not a meaningful EHR user; a proposed 
update of 1.675 percent for a hospital that fails to submit quality 
data and is a meaningful EHR user; and a proposed update of -0.2 
percent for a hospital that fails to submit quality data and is not an 
meaningful EHR user. As noted previously, for the FY 2022 IPPS/LTCH PPS 
proposed rule, we used IGI's fourth quarter 2020 forecast of the 
proposed 2018-based IPPS market basket update with historical data 
through third quarter 2020. Similarly, we used IGI's fourth quarter 
2020 forecast of the productivity adjustment. We proposed that if more 
recent data subsequently became available (for example, a more recent 
estimate of the market basket update and the productivity adjustment), 
we would use such data, if appropriate, to determine the update in the 
final rule.
    We did not receive any public comments on our proposal. Therefore, 
we are finalizing the proposal to determine the update to the hospital 
specific rates for SCHs and MDHs in this final rule using the more 
recent available data, as previously discussed.
    For this final rule, based on more recent available data, we are 
finalizing the following updates to the hospital specific rates 
applicable to SCHs and MDHs: An update of 2.0 percent for a hospital 
that submits quality data and is a meaningful EHR user; an update of 
1.325 percent for a hospital that fails to submit quality data and is a 
meaningful EHR user; an update of -0.025 percent for a hospital that 
submits quality data and is not a meaningful EHR user; and an update of 
-0.7 percent for a hospital that fails to submit quality data and is 
not a meaningful EHR user.
2. FY 2022 Puerto Rico Hospital Update
    Section 602 of Public Law 114-113 amended section 1886(n)(6)(B) of 
the Act to specify that subsection (d) Puerto Rico hospitals are 
eligible for incentive payments for the meaningful use of certified EHR 
technology, effective beginning FY 2016. In addition, section 
1886(n)(6)(B) of the Act was amended to specify that the adjustments to 
the applicable percentage increase under section 1886(b)(3)(B)(ix) of 
the Act apply to subsection (d) Puerto Rico hospitals that are not 
meaningful EHR users, effective beginning FY 2022. Accordingly, for FY 
2022, section 1886(b)(3)(B)(ix) of the Act in conjunction with section 
602(d) of Public Law 114-113 requires that any subsection (d) Puerto 
Rico hospital that

[[Page 45216]]

is not a meaningful EHR user as defined in section 1886(n)(3) of the 
Act and not subject to an exception under section 1886(b)(3)(B)(ix) of 
the Act will have ``three-quarters'' of the applicable percentage 
increase (prior to the application of other statutory adjustments), or 
three-quarters of the applicable market basket rate-of-increase, 
reduced by 33\1/3\ percent. The reduction to three-quarters of the 
applicable percentage increase for subsection (d) Puerto Rico hospitals 
that are not meaningful EHR users increases to 66\2/3\ percent for FY 
2023, and, for FY 2024 and subsequent fiscal years, to 100 percent. (We 
note that section 1886(b)(3)(B)(viii) of the Act, which specifies the 
adjustment to the applicable percentage increase for ``subsection (d)'' 
hospitals that do not submit quality data under the rules established 
by the Secretary, is not applicable to hospitals located in Puerto 
Rico.) The regulations at 42 CFR 412.64(d)(3)(ii) reflect the current 
law for the update for subsection (d) Puerto Rico hospitals for FY 2022 
and subsequent fiscal years. In the FY 2019 IPPS/LTCH PPS final rule, 
we finalized the payment reductions (83 FR 41674).
    For FY 2022, consistent with section 1886(b)(3)(B) of the Act, as 
amended by section 602 of Public Law 114-113, we are setting the 
applicable percentage increase for Puerto Rico hospitals by applying 
the following adjustments in the following sequence. Specifically, the 
applicable percentage increase under the IPPS for Puerto Rico hospitals 
will be equal to the rate of-increase in the hospital market basket for 
IPPS hospitals in all areas, subject to a 33\1/3\ percent reduction to 
three-fourths of the applicable percentage increase (prior to the 
application of other statutory adjustments; also referred to as the 
market basket update or rate-of-increase (with no adjustments)) for 
Puerto Rico hospitals not considered to be meaningful EHR users in 
accordance with section 1886(b)(3)(B)(ix) of the Act, and then subject 
to the productivity adjustment at section 1886(b)(3)(B)(xi) of the Act. 
As noted previously, section 1886(b)(3)(B)(xi) of the Act states that 
application of the productivity adjustment may result in the applicable 
percentage increase being less than zero.
    Based on IGI's fourth quarter 2020 forecast of the proposed 2018-
based IPPS market basket update with historical data through third 
quarter 2020, in the FY 2022 IPPS/LTCH PPS proposed rule, in accordance 
with section 1886(b)(3)(B) of the Act, as discussed previously, for 
Puerto Rico hospitals we proposed a market basket update of 2.5 percent 
and a productivity adjustment of 0.2 percent. Therefore, for FY 2022, 
depending on whether a Puerto Rico hospital is a meaningful EHR user, 
we stated that there are two possible applicable percentage increases 
that can be applied to the standardized amount. Based on these data, we 
determined the following proposed applicable percentage increases to 
the standardized amount for FY 2022 for Puerto Rico hospitals:
     For a Puerto Rico hospital that is a meaningful EHR user, 
we proposed an applicable percentage increase to the FY 2022 operating 
standardized amount of 2.3 percent (that is, the FY 2022 estimate of 
the proposed market basket rate-of-increase of 2.5 percent less an 
adjustment of 0.2 percentage point for the proposed productivity 
adjustment).
     For a Puerto Rico hospital that is not a meaningful EHR 
user, we proposed an applicable percentage increase to the operating 
standardized amount of 1.675 percent (that is, the FY 2022 estimate of 
the proposed market basket rate-of-increase of 2.5 percent, less an 
adjustment of 0.625 percentage point (the proposed market basket rate 
of-increase of 2.5 percent x 0.75)/3) for failure to be a meaningful 
EHR user, less an adjustment of 0.2 percentage point for the proposed 
productivity adjustment.
    As noted previously, we proposed that if more recent data 
subsequently become available, we would use such data, if appropriate, 
to determine the FY 2022 market basket update and the productivity 
adjustment for the FY 2022 IPPS/LTCH PPS final rule.
    We did not receive any public comment on our proposal with respect 
to the Puerto Rico hospital update.
    As previously discussed in section V.A.1, based on more recent data 
available for this FY 2022 IPPS/LTCH PPS final rule (that is, IGI's 
second quarter 2021 forecast of the 2018-based IPPS market basket rate-
of-increase with historical data through the first quarter of 2021), we 
estimate that the FY 2022 market basket update used to determine the 
applicable percentage increase for the IPPS is 2.7 percent and a 
productivity adjustment of 0.7 percent. Therefore, in accordance with 
section 1886(b)(3)(B) of the Act, for this final rule, for Puerto Rico 
hospitals the more recent update of the market basket update is 2.7 
percent and a productivity adjustment of 0.7 percent. For FY 2022, 
depending on whether a Puerto Rico hospital is a meaningful EHR user, 
there are two possible applicable percentage increases that can be 
applied to the standardized amount. Based on these data, we determined 
the following applicable percentage increases to the standardized 
amount for FY 2022 for Puerto Rico hospitals:
     For a Puerto Rico hospital that is a meaningful EHR user, 
an applicable percentage increase to the FY 2022 operating standardized 
amount of 2.0 percent (that is, the FY 2022 estimate of the market 
basket rate-of-increase of 2.7 percent less an adjustment of 0.7 
percentage point for the productivity adjustment).
     For a Puerto Rico hospital that is not a meaningful EHR 
user, an applicable percentage increase to the operating standardized 
amount of 1.325 percent (that is, the FY 2022 estimate of the market 
basket rate-of-increase of 2.7 percent, less an adjustment of 0.675 
percentage point (the market basket rate of-increase of 2.7 percent x 
0.75)/3) for failure to be a meaningful EHR user, less an adjustment of 
0.7 percentage point for the productivity adjustment.

B. Rural Referral Centers (RRCs) Annual Updates to Case-Mix Index (CMI) 
and Discharge Criteria (Sec.  412.96)

    Under the authority of section 1886(d)(5)(C)(i) of the Act, the 
regulations at Sec.  412.96 set forth the criteria that a hospital must 
meet in order to qualify under the IPPS as a rural referral center 
(RRC). RRCs receive special treatment under both the DSH payment 
adjustment and the criteria for geographic reclassification.
    Section 402 of Public Law 108-173 raised the DSH payment adjustment 
for RRCs such that they are not subject to the 12-percent cap on DSH 
payments that is applicable to other rural hospitals. RRCs also are not 
subject to the proximity criteria when applying for geographic 
reclassification. In addition, they do not have to meet the requirement 
that a hospital's average hourly wage must exceed, by a certain 
percentage, the average hourly wage of the labor market area in which 
the hospital is located.
    Section 4202(b) of Public Law 105-33 states, in part, that any 
hospital classified as an RRC by the Secretary for FY 1991 shall be 
classified as such an RRC for FY 1998 and each subsequent fiscal year. 
In the August 29, 1997 IPPS final rule with comment period (62 FR 
45999), we reinstated RRC status for all hospitals that lost that 
status due to triennial review or MGCRB reclassification. However, we 
did not reinstate the status of hospitals that lost RRC status because 
they were now urban for all purposes because of the OMB designation of 
their geographic area as urban. Subsequently, in the August 1, 2000 
IPPS final rule (65 FR 47089), we indicated that we were revisiting 
that decision. Specifically, we

[[Page 45217]]

stated that we would permit hospitals that previously qualified as an 
RRC and lost their status due to OMB redesignation of the county in 
which they are located from rural to urban, to be reinstated as an RRC. 
Otherwise, a hospital seeking RRC status must satisfy all of the other 
applicable criteria. We use the definitions of ``urban'' and ``rural'' 
specified in subpart D of 42 CFR part 412. One of the criteria under 
which a hospital may qualify as an RRC is to have 275 or more beds 
available for use (Sec.  412.96(b)(1)(ii)). A rural hospital that does 
not meet the bed size requirement can qualify as an RRC if the hospital 
meets two mandatory prerequisites (a minimum case-mix index (CMI) and a 
minimum number of discharges), and at least one of three optional 
criteria (relating to specialty composition of medical staff, source of 
inpatients, or referral volume). (We refer readers to Sec.  
412.96(c)(1) through (5) and the September 30, 1988 Federal Register 
(53 FR 38513) for additional discussion.) With respect to the two 
mandatory prerequisites, a hospital may be classified as an RRC if--
     The hospital's CMI is at least equal to the lower of the 
median CMI for urban hospitals in its census region, excluding 
hospitals with approved teaching programs, or the median CMI for all 
urban hospitals nationally; and
     The hospital's number of discharges is at least 5,000 per 
year, or, if fewer, the median number of discharges for urban hospitals 
in the census region in which the hospital is located. The number of 
discharges criterion for an osteopathic hospital is at least 3,000 
discharges per year, as specified in section 1886(d)(5)(C)(i) of the 
Act.
1. Amendment to Timeframe used for Case-Mix Index (CMI) Under Sec.  
412.96(c)(1) and Sec.  412.96(h) and Discharges Under Sec.  412.96(i) 
for RRC Classification
a. Case-Mix Index (CMI)
    As previously noted, in addition to meeting other criteria, to 
qualify for initial RRC status for cost reporting periods beginning on 
or after October 1 of a given fiscal year, under Sec.  412.96(c)(1), a 
hospital must meet the minimum case-mix index (CMI) value during the 
most recent Federal fiscal year that ended at least one year prior to 
the beginning of the cost reporting period for which the hospital is 
seeking RRC status. We typically use the data from the Federal fiscal 
year that is two years prior to the Federal fiscal year for which a 
hospital is seeking RRC status to compute the national and regional 
median CMI values, as these are generally the best available data at 
the time of the development of the proposed and final rules. For 
example, in the FY 2021 IPPS/LTCH PPS final rule, we calculated the 
national and regional median CMIs using discharges occurring during FY 
2019 (October 1, 2018 through September 30, 2019).
    However, as discussed in the FY 2022 IPPS/LTCH PPS proposed rule 
(86 FR 25437), the best available data to use for certain purposes of 
this FY 2022 rulemaking may not be the FY 2020 data that we would 
ordinarily use, due to the impact of the COVID-19 PHE. We stated in the 
proposed rule that we believe that the differences in utilization for 
certain types of services in FY 2020 as compared to what would have 
been expected in the absence of the PHE also affects the calculation of 
the CMI values used for purposes of determining RRC status. We noted 
that the CMI values calculated using the FY 2020 data are significantly 
different from the CMI values calculated using the FY 2019 data. As 
such, while we would normally have proposed to use data from FY 2020 to 
calculate CMI values, we instead proposed to use values that are based 
on discharges occurring during FY 2019 (October 1, 2018 through 
September 30, 2019), and include claims posted to CMS' records through 
March 2020. We made available for public comment the CMI values 
calculated using the FY 2020 data that we would ordinarily propose to 
use (86 FR 25784).
    Accordingly, we proposed to amend Sec.  412.96(c)(1) with regard to 
the data to be used in identifying the CMI value for an individual 
hospital that is used to determine whether the hospital meets the CMI 
criteria for purposes for RRC classification. Specifically, we proposed 
to amend Sec.  412.96(c)(1) to indicate that the individual hospital's 
CMI value for discharges during the same Federal fiscal year used to 
compute the national and regional CMI values is used for purposes of 
determining whether a hospital qualifies for RRC classification. We 
also proposed to amend Sec.  412.96(h)(1) to provide for the use of the 
best available data rather than the latest available data in 
calculating the national and regional CMI criteria.
    Commenters supported these proposals. We are therefore finalizing 
these proposals, including the proposed amendments, without 
modification.
b. Discharges
    As previously noted, in addition to meeting other criteria, to 
qualify for initial RRC status for cost reporting periods beginning on 
or after October 1 of a given fiscal year, under Sec.  412.96(c)(2), a 
hospital must meet the minimum number of discharges during its cost 
reporting period that began during the same fiscal year as the cost 
reporting periods used to compute the regional median discharges. We 
typically use the cost reporting periods that are 3 years prior to the 
fiscal year for which a hospital is seeking RRC status to compute the 
regional median discharges, as these are generally the latest cost 
report data available at the time of the development of the proposed 
and final rules. For example, in the FY 2021 IPPS/LTCH PPS final rule, 
we calculated the regional standards based on discharges for urban 
hospitals' cost reporting periods that began during FY 2018.
    However, as discussed in section I.F. of the FY 2022 IPPS/LTCH PPS 
proposed rule (86 FR 25437), the best available data to use for certain 
purposes of this FY 2022 rulemaking may not be the FY 2019 cost report 
data that we would ordinarily use, due to the impact of the COVID-19 
PHE. We stated that we believe that the differences in utilization for 
certain types of services in FY 2019 cost reporting periods that 
spanned the PHE as compared to what would have been expected in the 
absence of the PHE also affects the calculation of the regional median 
discharges used for purposes of determining RRC status. We noted that 
the regional median discharges calculated using the FY 2019 cost report 
data are different from the regional median discharges values 
calculated using the FY 2018 data. As such, while we ordinarily would 
have proposed to calculate the regional median discharges based on cost 
reports with cost reporting periods beginning in FY 2019 (October 1, 
2018 through September 30, 2019), we instead proposed to calculate the 
regional median discharges based on cost reports with cost reporting 
periods beginning in FY 2018 (October 1, 2017 through September 30, 
2018). We made available for public comment the regional median 
discharges calculated using FY 2019 cost report data that we would 
ordinarily propose to use (86 FR 25784).
    Accordingly, we proposed to amend the regulations at Sec.  
412.96(i)(1) and (2), which describe the methodology for calculating 
the number of discharges criteria, to provide for the use of the best 
available data rather than the latest available or most recent data 
when calculating the regional discharges for RRC classification.
    Commenters supported these proposals. We are therefore finalizing 
these proposals, including the proposed amendments, without 
modification.

[[Page 45218]]

2. Case-Mix Index (CMI)
    Section 412.96(c)(1) provides that CMS establish updated national 
and regional CMI values in each year's annual notice of prospective 
payment rates for purposes of determining RRC status. The methodology 
we used to determine the national and regional CMI values is set forth 
in the regulations at Sec.  412.96(c)(1)(ii), in conjunction with the 
amendment to provide for the use of the best available data rather than 
the use of the latest available data. The national median CMI value for 
FY 2022 is based on the CMI values of all urban hospitals nationwide, 
and the regional median CMI values for FY 2022 are based on the CMI 
values of all urban hospitals within each census region, excluding 
those hospitals with approved teaching programs (that is, those 
hospitals that train residents in an approved GME program as provided 
in Sec.  413.75). For the reasons discussed previously, the values are 
based on discharges occurring during FY 2019 (October 1, 2018 through 
September 30, 2019), and include claims posted to CMS' records through 
March 2020.
    In the FY 2022 IPPS/LTCH PPS proposed rule (86 FR 25438), we 
proposed that, in addition to meeting other criteria, if rural 
hospitals with fewer than 275 beds are to qualify for initial RRC 
status for cost reporting periods beginning on or after October 1, 
2021, they must have a CMI value for FY 2019 that is at least--
     1.7049 (national--all urban); or
     The median CMI value (not transfer-adjusted) for urban 
hospitals (excluding hospitals with approved teaching programs as 
identified in Sec.  413.75) calculated by CMS for the census region in 
which the hospital is located.
    The proposed median CMI values by region were set forth in a table 
in the proposed rule (86 FR 25439). We stated in the proposed rule that 
we may update the proposed CMI values in the FY 2022 final rule to 
reflect finalized policies for FY 2022, including the best available 
data.
    Commenters supported these proposals. Therefore, based on the best 
available data (FY 2019 claims received through March 2020), in 
addition to meeting other criteria, if rural hospitals with fewer than 
275 beds are to qualify for initial RRC status for cost reporting 
periods beginning on or after October 1, 2021, they must have a CMI 
value for FY 2019 that is at least:
     1.7049 (national--all urban); or
     The median CMI value (not transfer-adjusted) for urban 
hospitals (excluding hospitals with approved teaching programs as 
identified in Sec.  413.75) calculated by CMS for the census region in 
which the hospital is located.
    The final CMI values by region are set forth in the following 
table.
[GRAPHIC] [TIFF OMITTED] TR13AU21.251

    A hospital seeking to qualify as an RRC should obtain its hospital-
specific CMI value (not transfer-adjusted) from its MAC. Data are 
available on the Provider Statistical and Reimbursement (PS&R) System. 
In keeping with our policy on discharges, the CMI values are computed 
based on all Medicare patient discharges subject to the IPPS MS-DRG-
based payment.
3. Discharges
    Section 412.96(c)(2)(i) provides that CMS set forth the national 
and regional numbers of discharges criteria in each year's annual 
notice of prospective payment rates for purposes of determining RRC 
status. As specified in section 1886(d)(5)(C)(ii) of the Act, the 
national standard is set at 5,000 discharges. In the FY 2022 IPPS/LTCH 
PPS proposed rule (86 FR 25438), for FY 2022, consistent with our 
proposed amendments to Sec.  412.96(i)(1) and (2) to provide for the 
use of the best available data rather than the latest available or most 
recent data, we proposed to update the regional standards based on 
discharges for urban hospitals' cost reporting periods that began 
during FY 2018 (that is, October 1, 2017 through September 30, 2018). 
Therefore, we proposed that, in addition to meeting other criteria, a 
hospital, if it is to qualify for initial RRC status for cost reporting 
periods beginning on or after October 1, 2021, must have, as the number 
of discharges for its cost reporting period that began during FY 2018, 
at least--
     5,000 (3,000 for an osteopathic hospital); or
     If less, the median number of discharges for urban 
hospitals in the census region in which the hospital is located. (We 
refer readers to the table set forth in the FY 2022 IPPS/LTCH PPS 
proposed rule at 86 FR 25439). We note, that for this final rule, we 
calculated the median number of discharges for urban hospitals using 
the latest update of FY 2018 HCRIS data. There was no change in the 
median number of discharges from the proposed rule. Commenters 
supported these proposals.
    Therefore, based on the best available discharge data at this time, 
that is, for cost reporting periods that began during FY 2018, the 
final median number of discharges for urban hospitals by census region 
are set forth in the following table.

[[Page 45219]]

[GRAPHIC] [TIFF OMITTED] TR13AU21.252

    We note that because the median number of discharges for hospitals 
in each census region is greater than the national standard of 5,000 
discharges, under this final rule, 5,000 discharges is the minimum 
criterion for all hospitals, except for osteopathic hospitals for which 
the minimum criterion is 3,000 discharges.

C. Payment Adjustment for Low-Volume Hospitals (Sec.  412.101)

1. Background
    Section 1886(d)(12) of the Act provides for an additional payment 
to each qualifying low-volume hospital under the IPPS beginning in FY 
2005. The additional payment adjustment to a low-volume hospital 
provided for under section 1886(d)(12) of the Act is in addition to any 
payment calculated under section 1886 of the Act. Therefore, the 
additional payment adjustment is based on the per discharge amount paid 
to the qualifying hospital under section 1886 of the Act. In other 
words, the low-volume hospital payment adjustment is based on total per 
discharge payments made under section 1886 of the Act, including 
capital, DSH, IME, and outlier payments. For SCHs and MDHs, the low-
volume hospital payment adjustment is based in part on either the 
Federal rate or the hospital-specific rate, whichever results in a 
greater operating IPPS payment.
    As discussed in the FY 2019 IPPS/LTCH PPS final rule (83 FR 41398 
through 41399), section 50204 of the Bipartisan Budget Act of 2018 
(Pub. L. 115-123) modified the definition of a low-volume hospital and 
the methodology for calculating the payment adjustment for low-volume 
hospitals for FYs 2019 Through 2022. (Section 50204 of Pub. L. 115-123 
also extended prior changes to the definition of a low-volume hospital 
and the methodology for calculating the payment adjustment for low-
volume hospitals through FY 2018.) Currently, the low-volume hospital 
qualifying criteria provide that a hospital must have fewer 3,800 total 
discharges during the fiscal year, and the hospital must be located 
more than 15 road miles from the nearest ``subsection (d)'' hospital. 
These criteria will remain in effect through FY 2022. Beginning with FY 
2023, the low-volume hospital qualifying criteria and payment 
adjustment will revert to the statutory requirements that were in 
effect prior to FY 2011. Therefore, in order for a hospital to continue 
to qualify as a low-volume hospital on or after October 1, 2022, it 
must have fewer than 200 total discharges during the fiscal year and be 
located more than 25 road miles from the nearest ``subsection (d)'' 
hospital (see Sec.  412.101(b)(2)(i)). (For additional information on 
the low-volume hospital payment adjustment prior to FY 2018, we refer 
readers to the FY 2017 IPPS/LTCH PPS final rule (81 FR 56941 through 
56943). For additional information on the low-volume hospital payment 
adjustment for FY 2018, we refer readers to the FY 2018 IPPS notice 
(CMS-1677-N) that appeared in the April 26, 2018 Federal Register (83 
FR 18301 through 18308).)
2. Temporary Changes to the Low-Volume Hospital Definition and Payment 
Adjustment Methodology for FYs 2019 Through 2022
    As discussed earlier, section 50204 of the Bipartisan Budget Act of 
2018 further modified the definition of a low-volume hospital and the 
methodology for calculating the payment adjustment for low-volume 
hospitals for FYs 2019 through 2022. Specifically, the qualifying 
criteria for low-volume hospitals under section 1886(d)(12)(C)(i) of 
the Act were amended to specify that, for FYs 2019 through 2022, a 
subsection (d) hospital qualifies as a low-volume hospital if it is 
more than 15 road miles from another subsection (d) hospital and has 
less than 3,800 total discharges during the fiscal year. Section 
1886(d)(12)(D) of the Act was also amended to provide that, for 
discharges occurring in FYs 2019 through 2022, the Secretary shall 
determine the applicable percentage increase using a continuous, linear 
sliding scale ranging from an additional 25 percent payment adjustment 
for low-volume hospitals with 500 or fewer discharges to a zero percent 
additional payment for low-volume hospitals with more than 3,800 
discharges in the fiscal year. Consistent with the requirements of 
section 1886(d)(12)(C)(ii) of the Act, the term ``discharge'' for 
purposes of these provisions refers to total discharges, regardless of 
payer (that is, Medicare and non-Medicare discharges).
    In the FY 2019 IPPS/LTCH PPS final rule (83 FR 41399), to implement 
this requirement, we specified a continuous, linear sliding scale 
formula to determine the low-volume hospital payment adjustment for FYs 
2019 through 2022 that is similar to the continuous, linear sliding 
scale formula used to determine the low-volume hospital payment 
adjustment originally established by the Affordable Care Act and 
implemented in the regulations at Sec.  412.101(c)(2)(ii) in the FY 
2011 IPPS/LTCH PPS final rule (75 FR 50240 through 50241). Consistent 
with the statute, we provided that qualifying hospitals with 500 or 
fewer total discharges will receive a low-volume hospital payment 
adjustment of 25 percent. For qualifying hospitals with fewer than 
3,800 discharges but more than 500 discharges, the low-volume payment 
adjustment is calculated by subtracting from 25 percent the proportion 
of payments associated with the discharges in excess of 500. As such, 
for qualifying hospitals with fewer than 3,800 total discharges but 
more than 500 total discharges, the low-volume hospital payment 
adjustment for FYs 2019

[[Page 45220]]

through 2022 is calculated using the following formula:
    Low-Volume Hospital Payment Adjustment = 0.25-[0.25/3300] x (number 
of total discharges-500) = (95/330)-(number of total discharges/
13,200).
    For this purpose, we specified that the ``number of total 
discharges'' is determined as total discharges, which includes Medicare 
and non-Medicare discharges during the fiscal year, based on the 
hospital's most recently submitted cost report. The low-volume hospital 
payment adjustment for FYs 2019 through 2022 is set forth in the 
regulations at 42 CFR 412.101(c)(3).
3. Process for Requesting and Obtaining the Low-Volume Hospital Payment 
Adjustment
    In the FY 2011 IPPS/LTCH PPS final rule (75 FR 50238 through 50275 
and 50414) and subsequent rulemaking (for example, the FY 2019 IPPS/
LTCH PPS final rule (83 FR 41399 through 41401)), we discussed the 
process for requesting and obtaining the low-volume hospital payment 
adjustment. Under this previously established process, a hospital makes 
a written request for the low-volume payment adjustment under Sec.  
412.101 to its MAC. This request must contain sufficient documentation 
to establish that the hospital meets the applicable mileage and 
discharge criteria. The MAC will determine if the hospital qualifies as 
a low-volume hospital by reviewing the data the hospital submits with 
its request for low-volume hospital status in addition to other 
available data. Under this approach, a hospital will know in advance 
whether or not it will receive a payment adjustment under the low-
volume hospital policy. The MAC and CMS may review available data such 
as the number of discharges, in addition to the data the hospital 
submits with its request for low-volume hospital status, in order to 
determine whether or not the hospital meets the qualifying criteria. 
(For additional information on our existing process for requesting the 
low-volume hospital payment adjustment, we refer readers to the FY 2019 
IPPS/LTCH PPS final rule (83 FR 41399 through 41401).)
    As explained earlier, for FY 2019 and subsequent fiscal years, the 
discharge determination is made based on the hospital's number of total 
discharges, that is, Medicare and non-Medicare discharges, as was the 
case for FYs 2005 through 2010. Under Sec.  412.101(b)(2)(i) and (iii), 
a hospital's most recently submitted cost report is used to determine 
if the hospital meets the discharge criterion to receive the low-volume 
payment adjustment in the current year. As discussed in the FY 2019 
IPPS/LTCH PPS final rule (83 FR 41399 and 41400), we use cost report 
data to determine if a hospital meets the discharge criterion because 
this is the best available data source that includes information on 
both Medicare and non-Medicare discharges. (For FYs 2011 through 2018, 
the most recently available MedPAR data were used to determine the 
hospital's Medicare discharges because non-Medicare discharges were not 
used to determine if a hospital met the discharge criterion for those 
years.) Therefore, a hospital should refer to its most recently 
submitted cost report for total discharges (Medicare and non-Medicare) 
in order to decide whether or not to apply for low-volume hospital 
status for a particular fiscal year.
    As also discussed in the FY 2019 IPPS/LTCH PPS final rule, in 
addition to the discharge criterion, for FY 2019 and for subsequent 
fiscal years, eligibility for the low-volume hospital payment 
adjustment is also dependent upon the hospital meeting the applicable 
mileage criterion specified in Sec.  412.101(b) (2)(i) or (iii) for the 
fiscal year. Specifically, to meet the mileage criterion to qualify for 
the low-volume hospital payment adjustment for FY 2022, as was the case 
for FYs 2019, 2020 and 2021, a hospital must be located more than 15 
road miles from the nearest subsection (d) hospital. (We define in 
Sec.  412.101(a) the term ``road miles'' to mean ``miles'' as defined 
in Sec.  412.92(c)(1) (75 FR 50238 through 50275 and 50414).) For 
establishing that the hospital meets the mileage criterion, the use of 
a web-based mapping tool as part of the documentation is acceptable. 
The MAC will determine if the information submitted by the hospital, 
such as the name and street address of the nearest hospitals, location 
on a map, and distance from the hospital requesting low-volume hospital 
status, is sufficient to document that it meets the mileage criterion. 
If not, the MAC will follow up with the hospital to obtain additional 
necessary information to determine whether or not the hospital meets 
the applicable mileage criterion.
    In accordance with our previously established process, a hospital 
must make a written request for low-volume hospital status that is 
received by its MAC by September 1 immediately preceding the start of 
the Federal fiscal year for which the hospital is applying for low-
volume hospital status in order for the applicable low-volume hospital 
payment adjustment to be applied to payments for its discharges for the 
fiscal year beginning on or after October 1 immediately following the 
request (that is, the start of the Federal fiscal year).\760\ For a 
hospital whose request for low-volume hospital status is received after 
September 1, if the MAC determines the hospital meets the criteria to 
qualify as a low-volume hospital, the MAC will apply the applicable 
low-volume hospital payment adjustment to determine payment for the 
hospital's discharges for the fiscal year, effective prospectively 
within 30 days of the date of the MAC's low-volume status 
determination.
---------------------------------------------------------------------------

    \760\ We note that for FY 2021, we established a deadline of 
September 15, 2020 for receipt of a hospital's written request its 
MAC in order for the low-volume hospital payment adjustment to be 
applied to payments for a hospital's discharges beginning on or 
after October 1, 2020, as discussed in the FY 2021 IPPS/LTCH PPS 
final rule (85 FR 58803).
---------------------------------------------------------------------------

    Consistent with this previously established process, for FY 2022, 
we proposed that a hospital must submit a written request for low-
volume hospital status to its MAC that includes sufficient 
documentation to establish that the hospital meets the applicable 
mileage and discharge criteria (as described earlier). Consistent with 
historical practice, for FY 2022, we proposed that a hospital's written 
request must be received by its MAC no later than September 1, 2021 in 
order for the low-volume hospital payment adjustment to be applied to 
payments for its discharges beginning on or after October 1, 2021. If a 
hospital's written request for low-volume hospital status for FY 2022 
is received after September 1, 2021, and if the MAC determines the 
hospital meets the criteria to qualify as a low-volume hospital, the 
MAC would apply the low-volume hospital payment adjustment to determine 
the payment for the hospital's FY 2022 discharges, effective 
prospectively within 30 days of the date of the MAC's low-volume 
hospital status determination. We noted that this proposal is generally 
consistent with the process for requesting and obtaining the low-volume 
hospital payment adjustment for FY 2021 (85 FR 58802 through 
58803).\761\
---------------------------------------------------------------------------

    \761\ As noted, CMS established a deadline of September 15, 2020 
for receipt of the hospital's written request for FY 2021, as 
discussed in the FY 2021 IPPS/LTCH PPS final rule.
---------------------------------------------------------------------------

    Under this process, a hospital receiving the low-volume hospital 
payment adjustment for FY 2021 may continue to receive a low-volume 
hospital payment adjustment for FY 2022 without reapplying if it 
continues to meet the applicable mileage and discharge criteria (which, 
as discussed previously, are the same qualifying criteria that apply 
for FY 2021). In this case, a hospital's request can include a

[[Page 45221]]

verification statement that it continues to meet the mileage criterion 
applicable for FY 2022. (Determination of meeting the discharge 
criterion is discussed earlier in this section.) We note that a 
hospital must continue to meet the applicable qualifying criteria as a 
low-volume hospital (that is, the hospital must meet the applicable 
discharge criterion and mileage criterion for the fiscal year) in order 
to receive the payment adjustment in that fiscal year; that is, low-
volume hospital status is not based on a ``one-time'' qualification (75 
FR 50238 through 50275). Consistent with historical policy, a hospital 
must submit its request, including this written verification, for each 
fiscal year for which it seeks to receive the low-volume hospital 
payment adjustment, and in accordance with the timeline described 
earlier.
    Comment: We received comments expressing continued support of the 
low-volume hospital payment adjustment changes included in the 
Bipartisan Budget Act of 2018.
    Response: We appreciate commenters' support.
    We received no public comments on our proposals related to the 
process for requesting and obtaining the low-volume hospital payment 
adjustment, therefore, we are finalizing our proposals as previously 
described, without modification.

D. Indirect Medical Education (IME) Payment Adjustment Factor (Sec.  
412.105)

    Under the IPPS, an additional payment amount is made to hospitals 
with residents in an approved graduate medical education (GME) program 
in order to reflect the higher indirect patient care costs of teaching 
hospitals relative to nonteaching hospitals. The payment amount is 
determined by use of a statutorily specified adjustment factor. The 
regulations regarding the calculation of this additional payment, known 
as the IME adjustment, are located at Sec.  412.105. We refer readers 
to the FY 2012 IPPS/LTCH PPS final rule (76 FR 51680) for a full 
discussion of the IME adjustment and IME adjustment factor. Section 
1886(d)(5)(B)(ii)(XII) of the Act provides that, for discharges 
occurring during FY 2008 and fiscal years thereafter, the IME formula 
multiplier is 1.35. Accordingly, for discharges occurring during FY 
2022, the formula multiplier is 1.35. We estimate that application of 
this formula multiplier for the FY 2022 IME adjustment will result in 
an increase in IPPS payment of 5.5 percent for every approximately 10 
percent increase in the hospital's resident-to-bed ratio.
    We did not receive any comments regarding the IME adjustment 
factor, which, as noted earlier, is statutorily required. Accordingly, 
for discharges occurring during FY 2022, the IME formula multiplier is 
1.35.

E. Payment Adjustment for Medicare Disproportionate Share Hospitals 
(DSHs) for FY 2022 (Sec.  412.106)

1. General Discussion
    Section 1886(d)(5)(F) of the Act provides for additional Medicare 
payments to subsection (d) hospitals that serve a significantly 
disproportionate number of low-income patients. The Act specifies two 
methods by which a hospital may qualify for the Medicare 
disproportionate share hospital (DSH) adjustment. Under the first 
method, hospitals that are located in an urban area and have 100 or 
more beds may receive a Medicare DSH payment adjustment if the hospital 
can demonstrate that, during its cost reporting period, more than 30 
percent of its net inpatient care revenues are derived from State and 
local government payments for care furnished to patients with low 
incomes. This method is commonly referred to as the ``Pickle method.'' 
The second method for qualifying for the DSH payment adjustment, which 
is the most common, is based on a complex statutory formula under which 
the DSH payment adjustment is based on the hospital's geographic 
designation, the number of beds in the hospital, and the level of the 
hospital's disproportionate patient percentage (DPP). A hospital's DPP 
is the sum of two fractions: The ``Medicare fraction'' and the 
``Medicaid fraction.'' The Medicare fraction (also known as the ``SSI 
fraction'' or ``SSI ratio'') is computed by dividing the number of the 
hospital's inpatient days that are furnished to patients who were 
entitled to both Medicare Part A and Supplemental Security Income (SSI) 
benefits by the hospital's total number of patient days furnished to 
patients entitled to benefits under Medicare Part A. The Medicaid 
fraction is computed by dividing the hospital's number of inpatient 
days furnished to patients who, for such days, were eligible for 
Medicaid, but were not entitled to benefits under Medicare Part A, by 
the hospital's total number of inpatient days in the same period.
    Because the DSH payment adjustment is part of the IPPS, the 
statutory references to ``days'' in section 1886(d)(5)(F) of the Act 
have been interpreted to apply only to hospital acute care inpatient 
days. Regulations located at 42 CFR 412.106 govern the Medicare DSH 
payment adjustment and specify how the DPP is calculated as well as how 
beds and patient days are counted in determining the Medicare DSH 
payment adjustment. Under Sec.  412.106(a)(1)(i), the number of beds 
for the Medicare DSH payment adjustment is determined in accordance 
with bed counting rules for the IME adjustment under Sec.  412.105(b).
    Section 3133 of the Patient Protection and Affordable Care Act, as 
amended by section 10316 of the same Act and section 1104 of the Health 
Care and Education Reconciliation Act (Pub. L. 111-152), added a 
section 1886(r) to the Act that modifies the methodology for computing 
the Medicare DSH payment adjustment. (For purposes of this final rule, 
we refer to these provisions collectively as section 3133 of the 
Affordable Care Act.) Beginning with discharges in FY 2014, hospitals 
that qualify for Medicare DSH payments under section 1886(d)(5)(F) of 
the Act receive 25 percent of the amount they previously would have 
received under the statutory formula for Medicare DSH payments. This 
provision applies equally to hospitals that qualify for DSH payments 
under section 1886(d)(5)(F)(i)(I) of the Act and those hospitals that 
qualify under the Pickle method under section 1886(d)(5)(F)(i)(II) of 
the Act.
    The remaining amount, equal to an estimate of 75 percent of what 
otherwise would have been paid as Medicare DSH payments, reduced to 
reflect changes in the percentage of individuals who are uninsured, is 
available to make additional payments to each hospital that qualifies 
for Medicare DSH payments and that has uncompensated care. The payments 
to each hospital for a fiscal year are based on the hospital's amount 
of uncompensated care for a given time period relative to the total 
amount of uncompensated care for that same time period reported by all 
hospitals that receive Medicare DSH payments for that fiscal year.
    Section 1886(r) of the Act requires that, for FY 2014 and each 
subsequent fiscal year, a subsection (d) hospital that would otherwise 
receive DSH payments made under section 1886(d)(5)(F) of the Act 
receives two separately calculated payments. Specifically, section 
1886(r)(1) of the Act provides that the Secretary shall pay to such 
subsection (d) hospital (including a Pickle hospital) 25 percent of the 
amount the hospital would have received under section 1886(d)(5)(F) of 
the Act for DSH payments, which represents the empirically justified 
amount for such payment, as determined by the MedPAC in its March 2007 
Report to Congress.

[[Page 45222]]

We refer to this payment as the ``empirically justified Medicare DSH 
payment.''
    In addition to this empirically justified Medicare DSH payment, 
section 1886(r)(2) of the Act provides that, for FY 2014 and each 
subsequent fiscal year, the Secretary shall pay to such subsection (d) 
hospital an additional amount equal to the product of three factors. 
The first factor is the difference between the aggregate amount of 
payments that would be made to subsection (d) hospitals under section 
1886(d)(5)(F) of the Act if subsection (r) did not apply and the 
aggregate amount of payments that are made to subsection (d) hospitals 
under section 1886(r)(1) of the Act for such fiscal year. Therefore, 
this factor amounts to 75 percent of the payments that would otherwise 
be made under section 1886(d)(5)(F) of the Act.
    The second factor is, for FY 2018 and subsequent fiscal years, 1 
minus the percent change in the percent of individuals who are 
uninsured, as determined by comparing the percent of individuals who 
were uninsured in 2013 (as estimated by the Secretary, based on data 
from the Census Bureau or other sources the Secretary determines 
appropriate, and certified by the Chief Actuary of CMS), and the 
percent of individuals who were uninsured in the most recent period for 
which data are available (as so estimated and certified), minus a 
statutory adjustment of 0.2 percentage point for FYs 2018 and 2019.
    The third factor is a percent that, for each subsection (d) 
hospital, represents the quotient of the amount of uncompensated care 
for such hospital for a period selected by the Secretary (as estimated 
by the Secretary, based on appropriate data), including the use of 
alternative data where the Secretary determines that alternative data 
are available which are a better proxy for the costs of subsection (d) 
hospitals for treating the uninsured, and the aggregate amount of 
uncompensated care for all subsection (d) hospitals that receive a 
payment under section 1886(r) of the Act. Therefore, this third factor 
represents a hospital's uncompensated care amount for a given time 
period relative to the uncompensated care amount for that same time 
period for all hospitals that receive Medicare DSH payments in the 
applicable fiscal year, expressed as a percent.
    For each hospital, the product of these three factors represents 
its additional payment for uncompensated care for the applicable fiscal 
year. We refer to the additional payment determined by these factors as 
the ``uncompensated care payment.''
    Section 1886(r) of the Act applies to FY 2014 and each subsequent 
fiscal year. In the FY 2014 IPPS/LTCH PPS final rule (78 FR 50620 
through 50647) and the FY 2014 IPPS interim final rule with comment 
period (78 FR 61191 through 61197), we set forth our policies for 
implementing the required changes to the Medicare DSH payment 
methodology made by section 3133 of the Affordable Care Act for FY 
2014. In those rules, we noted that, because section 1886(r) of the Act 
modifies the payment required under section 1886(d)(5)(F) of the Act, 
it affects only the DSH payment under the operating IPPS. It does not 
revise or replace the capital IPPS DSH payment provided under the 
regulations at 42 CFR part 412, subpart M, which were established 
through the exercise of the Secretary's discretion in implementing the 
capital IPPS under section 1886(g)(1)(A) of the Act.
    Finally, section 1886(r)(3) of the Act provides that there shall be 
no administrative or judicial review under section 1869, section 1878, 
or otherwise of any estimate of the Secretary for purposes of 
determining the factors described in section 1886(r)(2) of the Act or 
of any period selected by the Secretary for the purpose of determining 
those factors. Therefore, there is no administrative or judicial review 
of the estimates developed for purposes of applying the three factors 
used to determine uncompensated care payments, or the periods selected 
in order to develop such estimates.
2. Eligibility for Empirically Justified Medicare DSH Payments and 
Uncompensated Care Payments
    As explained earlier, the payment methodology under section 3133 of 
the Affordable Care Act applies to ``subsection (d) hospitals'' that 
would otherwise receive a DSH payment made under section 1886(d)(5)(F) 
of the Act. Therefore, hospitals must receive empirically justified 
Medicare DSH payments in a fiscal year in order to receive an 
additional Medicare uncompensated care payment for that year. 
Specifically, section 1886(r)(2) of the Act states that, in addition to 
the payment made to a subsection (d) hospital under section 1886(r)(1) 
of the Act, the Secretary shall pay to such subsection (d) hospitals an 
additional amount. Because section 1886(r)(1) of the Act refers to 
empirically justified Medicare DSH payments, the additional payment 
under section 1886(r)(2) of the Act is limited to hospitals that 
receive empirically justified Medicare DSH payments in accordance with 
section 1886(r)(1) of the Act for the applicable fiscal year.
    In the FY 2014 IPPS/LTCH PPS final rule (78 FR 50622) and the FY 
2014 IPPS interim final rule with comment period (78 FR 61193), we 
provided that hospitals that are not eligible to receive empirically 
justified Medicare DSH payments in a fiscal year will not receive 
uncompensated care payments for that year. We also specified that we 
would make a determination concerning eligibility for interim 
uncompensated care payments based on each hospital's estimated DSH 
status for the applicable fiscal year (using the most recent data that 
are available). We indicated that our final determination on a 
hospital's eligibility for uncompensated care payments will be based on 
the hospital's actual DSH status at cost report settlement for that 
payment year.
    In the FY 2014 IPPS/LTCH PPS final rule (78 FR 50622) and in the 
rulemaking for subsequent fiscal years, we have specified our policies 
for several specific classes of hospitals within the scope of section 
1886(r) of the Act. For the FY 2022 IPPS/LTCH PPS proposed rule, we 
proposed to determine eligibility for interim uncompensated care 
payments based on each hospital's estimated DSH status for the 
applicable fiscal year using the best available data, as discussed in 
section V.E. of the preamble of the proposed rule. In the proposed 
rule, we also referred readers to a discussion of the inpatient 
Provider Specific File in section II.A.4 of the Addendum of the 
proposed rule (86 FR 25725). In the FY 2022 IPPS/LTCH PPS proposed rule 
(86 FR 25443 and 25444), we discussed our specific policies regarding 
eligibility to receive empirically justified Medicare DSH payments and 
uncompensated care payments for FY 2022 with respect to the following 
hospitals:
     Subsection (d) Puerto Rico hospitals that are eligible for 
DSH payments also are eligible to receive empirically justified 
Medicare DSH payments and uncompensated care payments under the new 
payment methodology (78 FR 50623 and 79 FR 50006).
     Maryland hospitals are not eligible to receive empirically 
justified Medicare DSH payments and uncompensated care payments under 
the payment methodology of section 1886(r) of the Act because they are 
not paid under the IPPS. As discussed in the FY 2019 IPPS/LTCH PPS 
final rule (83 FR 41402 through 41403), CMS and the State have entered 
into an agreement to govern payments to Maryland hospitals under a new 
payment model, the Maryland Total Cost of Care (TCOC) Model, which

[[Page 45223]]

began on January 1, 2019. Under the Maryland TCOC Model, Maryland 
hospitals will not be paid under the IPPS in FY 2022, and will be 
ineligible to receive empirically justified Medicare DSH payments and 
uncompensated care payments under section 1886(r) of the Act.
     Sole community hospitals (SCHs) that are paid under their 
hospital-specific rate are not eligible for Medicare DSH payments. SCHs 
that are paid under the IPPS Federal rate receive interim payments 
based on what we estimate and project their DSH status to be prior to 
the beginning of the Federal fiscal year (based on the best available 
data at that time) subject to settlement through the cost report, and 
if they receive interim empirically justified Medicare DSH payments in 
a fiscal year, they also will receive interim uncompensated care 
payments for that fiscal year on a per discharge basis, subject as well 
to settlement through the cost report. Final eligibility determinations 
will be made at the end of the cost reporting period at settlement, and 
both interim empirically justified Medicare DSH payments and 
uncompensated care payments will be adjusted accordingly (78 FR 50624 
and 79 FR 50007).
     Medicare-dependent, small rural hospitals (MDHs) are paid 
based on the IPPS Federal rate or, if higher, the IPPS Federal rate 
plus 75 percent of the amount by which the Federal rate is exceeded by 
the updated hospital-specific rate from certain specified base years 
(76 FR 51684). The IPPS Federal rate that is used in the MDH payment 
methodology is the same IPPS Federal rate that is used in the SCH 
payment methodology. Section 50205 of the Bipartisan Budget Act of 2018 
(Pub. L. 115-123), enacted on February 9, 2018, extended the MDH 
program for discharges on or after October 1, 2017, through September 
30, 2022. Because MDHs are paid based on the IPPS Federal rate, they 
continue to be eligible to receive empirically justified Medicare DSH 
payments and uncompensated care payments if their DPP is at least 15 
percent, and we apply the same process to determine MDHs' eligibility 
for empirically justified Medicare DSH and uncompensated care payments 
as we do for all other IPPS hospitals. Due to the extension of the MDH 
program, MDHs will continue to be paid based on the IPPS Federal rate 
or, if higher, the IPPS Federal rate plus 75 percent of the amount by 
which the Federal rate is exceeded by the updated hospital-specific 
rate from certain specified base years. Accordingly, we proposed to 
continue to make a determination concerning eligibility for interim 
uncompensated care payments based on each hospital's estimated DSH 
status for the applicable fiscal year (using the best available data). 
Our final determination on the hospital's eligibility for uncompensated 
care payments will be based on the hospital's actual DSH status at cost 
report settlement for that payment year. In addition, as we do for all 
IPPS hospitals, we will calculate a Factor 3 and an uncompensated care 
payment amount for all MDHs, regardless of whether they are projected 
to be eligible for Medicare DSH payments during the fiscal year, but 
the denominator of Factor 3 of the uncompensated care payment 
methodology will be based only on the uncompensated care data from the 
hospitals that we have projected to be eligible for Medicare DSH 
payments during the fiscal year.
     IPPS hospitals that elect to participate in the Bundled 
Payments for Care Improvement Advanced (BPCI Advanced) model starting 
October 1, 2018, will continue to be paid under the IPPS and, 
therefore, are eligible to receive empirically justified Medicare DSH 
payments and uncompensated care payments. For further information 
regarding the BPCI Advanced model, we refer readers to the CMS website 
at: https://innovation.cms.gov/initiatives/bpci-advanced/.
     IPPS hospitals that participate in the Comprehensive Care 
for Joint Replacement Model (80 FR 73300) continue to be paid under the 
IPPS and, therefore, are eligible to receive empirically justified 
Medicare DSH payments and uncompensated care payments. In the FY 2022 
IPPS/LTCH PPS proposed rule, we referred readers to the interim final 
rule with request for comments that appeared in the November 6, 2020 
Federal Register for a discussion of the Model (85 FR 71167 through 
71173). In that interim final rule, we extended the Model's Performance 
Year 5 to September 30, 2021. In a subsequent final rule that appeared 
in the May 3, 2021 Federal Register (86 FR 23496), we further extended 
the Model for an additional three performance years. The Model's 
Performance Year 8 will end on December 31, 2024.
     Hospitals participating in the Rural Community Hospital 
Demonstration Program are not eligible to receive empirically justified 
Medicare DSH payments and uncompensated care payments under section 
1886(r) of the Act because they are not paid under the IPPS (78 FR 
50625 and 79 FR 50008). The Rural Community Hospital Demonstration 
Program was originally authorized for a 5-year period by section 410A 
of the Medicare Prescription Drug, Improvement, and Modernization Act 
of 2003 (MMA) (Pub. L. 108-173), and extended for another 5-year period 
by sections 3123 and 10313 of the Affordable Care Act (Pub. L. 114-
255). The period of performance for this 5-year extension period ended 
December 31, 2016. Section 15003 of the 21st Century Cures Act (Public 
Law 114-255), enacted December 13, 2016, again amended section 410A of 
Public Law 108-173 to require a 10-year extension period (in place of 
the 5-year extension required by the Affordable Care Act), therefore 
requiring an additional 5-year participation period for the 
demonstration program. Section 15003 of Pub. L. 114-255 also required a 
solicitation for applications for additional hospitals to participate 
in the demonstration program. The Consolidated Appropriations Act of 
2020 (Pub. L. 116-260) amended section 410A of Pub. L. 108-173 to 
extend the Rural Community Hospital Demonstration Program for an 
additional 5-year period. At the time of issuance of the proposed rule, 
we believed 27 hospitals might participate in the demonstration program 
at the start of FY 2022. At the time of development of this final rule, 
there are 26 hospitals that will be participating in the demonstration 
program in FY 2022. Under the payment methodology that applies during 
the third 5-year extension period for the demonstration program, 
participating hospitals do not receive empirically justified Medicare 
DSH payments, and they are also excluded from receiving interim and 
final uncompensated care payments.
    We received no comments on our proposal to continue the policy of 
using the best available data regarding a hospital's estimated DSH 
status for purposes of determining eligibility for interim 
uncompensated care payments for FY 2022. Therefore, we are finalizing 
as proposed without modifications. Our final determination of a 
hospital's eligibility for uncompensated care payments will continue to 
be based on the hospital's actual DSH status at cost report settlement 
for that payment year.
    We received public comments that were outside the scope of this 
proposed rule. Specifically, commenters expressed concerns related to 
Section 340B eligibility. Because we consider these public comments to 
be outside the scope of the proposed rule, we are not addressing them 
in this final rule.

[[Page 45224]]

3. Empirically Justified Medicare DSH Payments
    As we have discussed earlier, section 1886(r)(1) of the Act 
requires the Secretary to pay 25 percent of the amount of the Medicare 
DSH payment that would otherwise be made under section 1886(d)(5)(F) of 
the Act to a subsection (d) hospital. Because section 1886(r)(1) of the 
Act merely requires the program to pay a designated percentage of these 
payments, without revising the criteria governing eligibility for DSH 
payments or the underlying payment methodology, we stated in the FY 
2014 IPPS/LTCH PPS final rule that we did not believe that it was 
necessary to develop any new operational mechanisms for making such 
payments. Therefore, in the FY 2014 IPPS/LTCH PPS final rule (78 FR 
50626), we implemented this provision by advising the Medicare 
Administrative Contractors (MACs) to simply adjust the interim claim 
payments to the requisite 25 percent of what would have otherwise been 
paid. We also made corresponding changes to the hospital cost report so 
that these empirically justified Medicare DSH payments can be settled 
at the appropriate level at the time of cost report settlement. We 
provided more detailed operational instructions and cost report 
instructions following issuance of the FY 2014 IPPS/LTCH PPS final rule 
that are available on the CMS website at: http://www.cms.gov/Regulations-and-Guidance/Guidance/Transmittals/2014-Transmittals-Items/R5P240.html.
4. Uncompensated Care Payments
    As we discussed earlier, section 1886(r)(2) of the Act provides 
that, for each eligible hospital in FY 2014 and subsequent years, the 
uncompensated care payment is the product of three factors. These three 
factors represent our estimate of 75 percent of the amount of Medicare 
DSH payments that would otherwise have been paid, an adjustment to this 
amount for the percent change in the national rate of uninsurance 
compared to the rate of uninsurance in 2013, and each eligible 
hospital's estimated uncompensated care amount relative to the 
estimated uncompensated care amount for all eligible hospitals. In this 
section of this final rule, we discuss the data sources and 
methodologies for computing each of these factors, our final policies 
for FYs 2014 through 2021, and the policies we are finalizing for FY 
2022.
a. Calculation of Factor 1 for FY 2022
    Section 1886(r)(2)(A) of the Act establishes Factor 1 in the 
calculation of the uncompensated care payment. Section 1886(r)(2)(A) of 
the Act states that this factor is equal to the difference between: (1) 
The aggregate amount of payments that would be made to subsection (d) 
hospitals under section 1886(d)(5)(F) of the Act if section 1886(r) of 
the Act did not apply for such fiscal year (as estimated by the 
Secretary); and (2) the aggregate amount of payments that are made to 
subsection (d) hospitals under section 1886(r)(1) of the Act for such 
fiscal year (as so estimated). Therefore, section 1886(r)(2)(A)(i) of 
the Act represents the estimated Medicare DSH payments that would have 
been made under section 1886(d)(5)(F) of the Act if section 1886(r) of 
the Act did not apply for such fiscal year. Under a prospective payment 
system, we would not know the precise aggregate Medicare DSH payment 
amount that would be paid for a Federal fiscal year until cost report 
settlement for all IPPS hospitals is completed, which occurs several 
years after the end of the Federal fiscal year. Therefore, section 
1886(r)(2)(A)(i) of the Act provides authority to estimate this amount, 
by specifying that, for each fiscal year to which the provision 
applies, such amount is to be estimated by the Secretary. Similarly, 
section 1886(r)(2)(A)(ii) of the Act represents the estimated 
empirically justified Medicare DSH payments to be made in a fiscal 
year, as prescribed under section 1886(r)(1) of the Act. Again, section 
1886(r)(2)(A)(ii) of the Act provides authority to estimate this 
amount.
    Therefore, Factor 1 is the difference between our estimates of: (1) 
The amount that would have been paid in Medicare DSH payments for the 
fiscal year, in the absence of the new payment provision; and (2) the 
amount of empirically justified Medicare DSH payments that are made for 
the fiscal year, which takes into account the requirement to pay 25 
percent of what would have otherwise been paid under section 
1886(d)(5)(F) of the Act. In other words, this factor represents our 
estimate of 75 percent (100 percent minus 25 percent) of our estimate 
of Medicare DSH payments that would otherwise be made, in the absence 
of section 1886(r) of the Act, for the fiscal year.
    In the FY 2022 IPPS/LTCH PPS proposed rule (86 FR 25444 through 
25447), in order to determine Factor 1 in the uncompensated care 
payment formula for FY 2022, we proposed to continue the policy 
established in the FY 2014 IPPS/LTCH PPS final rule (78 FR 50628 
through 50630) and in the FY 2014 IPPS interim final rule with comment 
period (78 FR 61194) of determining Factor 1 by developing estimates of 
both the aggregate amount of Medicare DSH payments that would be made 
in the absence of section 1886(r)(1) of the Act and the aggregate 
amount of empirically justified Medicare DSH payments to hospitals 
under 1886(r)(1) of the Act. Consistent with the policy that has 
applied in previous years, we proposed that these estimates will not be 
revised or updated subsequent to the publication of our final 
projections in this FY 2022 IPPS/LTCH PPS final rule.
    Therefore, in order to determine the two elements of proposed 
Factor 1 for FY 2022 (Medicare DSH payments prior to the application of 
section 1886(r)(1) of the Act, and empirically justified Medicare DSH 
payments after application of section 1886(r)(1) of the Act), for this 
final rule, we used the most recently available projections of Medicare 
DSH payments for the fiscal year, as calculated by CMS' Office of the 
Actuary (OACT) using the most recently filed Medicare hospital cost 
reports with Medicare DSH payment information and the most recent 
Medicare DSH patient percentages and Medicare DSH payment adjustments 
provided in the IPPS Impact File. The determination of the amount of 
DSH payments is partially based on OACT's Part A benefits projection 
model. One of the results of this model is inpatient hospital spending. 
Projections of DSH payments require projections for expected increases 
in utilization and case-mix. The assumptions that were used in making 
these projections and the resulting estimates of DSH payments for FY 
2019 through FY 2022 are discussed in the table titled ``Factors 
Applied for FY 2019 through FY 2022 to Estimate Medicare DSH 
Expenditures Using FY 2018 Baseline.''
    For purposes of calculating Factor 1 and modeling the impact of the 
FY 2022 IPPS/LTCH PPS proposed rule, we used the Office of the 
Actuary's January 2021 Medicare DSH estimates, which were based on data 
from the September 2020 update of the Medicare Hospital Cost Report 
Information System (HCRIS) and the FY 2021 IPPS/LTCH PPS final rule 
IPPS Impact File, published in conjunction with the publication of the 
FY 2021 IPPS/LTCH PPS final rule. Because SCHs that are projected to be 
paid under their hospital-specific rate are excluded from the 
application of section 1886(r) of the Act, these hospitals also were 
excluded from the January 2021 Medicare DSH estimates. Furthermore, 
because section 1886(r) of the Act specifies that the uncompensated 
care payment is in addition to the empirically justified

[[Page 45225]]

Medicare DSH payment (25 percent of DSH payments that would be made 
without regard to section 1886(r) of the Act), Maryland hospitals, 
which are not eligible to receive DSH payments, were also excluded from 
the Office of the Actuary's January 2021 Medicare DSH estimates. The 27 
hospitals that were anticipated to participate in the Rural Community 
Hospital Demonstration Program in FY 2022 were also excluded from these 
estimates, because under the payment methodology that applies during 
the third 5-year extension period, these hospitals are not eligible to 
receive empirically justified Medicare DSH payments or interim and 
final uncompensated care payments.
    For the proposed rule, using the data sources as previously 
discussed, the Office of the Actuary's January 2021 estimate of 
Medicare DSH payments for FY 2022 without regard to the application of 
section 1886(r)(1) of the Act, was approximately $14.098 billion. 
Therefore, also based on the January 2021 estimate, the estimate of 
empirically justified Medicare DSH payments for FY 2022, with the 
application of section 1886(r)(1) of the Act, was approximately $3.524 
billion (or 25 percent of the total amount of estimated Medicare DSH 
payments for FY 2022). Under Sec.  412.106(g)(1)(i) of the regulations, 
Factor 1 is the difference between these two OACT estimates. Therefore, 
in the proposed rule, we proposed that Factor 1 for FY 2022 would be $ 
10,573,368,841.28, which is equal to 75 percent of the total amount of 
estimated Medicare DSH payments for FY 2021 ($14,097,825,121.71 minus 
$3,524,456,280.43). In the FY 2022 IPPS/LTCH PPS proposed rule, we 
noted that consistent with our approach in previous rulemakings, OACT 
intended to use more recent data that may become available for purposes 
of projecting the final Factor 1 estimates for this FY 2022 IPPS/LTCH 
PPS final rule.
    As we noted in the FY 2022 IPPS/LTCH PPS proposed rule, the Factor 
1 estimates for proposed rules are generally consistent with the 
economic assumptions and actuarial analysis used to develop the 
President's Budget estimates under current law, and the Factor 1 
estimates for final rules are generally consistent with those used for 
the Midsession Review of the President's Budget. As we have in the 
past, for additional information on the development of the President's 
Budget, we refer readers to the Office of Management and Budget website 
at: https://www.whitehouse.gov/omb/budget. Consistent with historical 
practice, we indicated that we expected the Midsession Review would 
have updated economic assumptions and actuarial analysis, which would 
be used for the development of Factor 1 estimates in the final rule. At 
the time of developing this final rule, the Midsession Review was not 
yet available, therefore the estimates in this final rule are generally 
consistent with the economic assumptions and actuarial analysis used to 
develop the forthcoming Medicare Trustees Report.
    For a general overview of the principal steps involved in 
projecting future inpatient costs and utilization, we refer readers to 
the ``2020 Annual Report of the Boards of Trustees of the Federal 
Hospital Insurance and Federal Supplementary Medical Insurance Trust 
Funds'' available on the CMS website at: https://www.cms.gov/Research-Statistics-Data-and-Systems/Statistics-Trends-and-Reports/ReportsTrustFunds/index.html?redirect=/reportstrustfunds/ under 
``Downloads.'' We note that the annual reports of the Medicare Boards 
of Trustees to Congress represent the Federal Government's official 
evaluation of the financial status of the Medicare Program. The 
actuarial projections contained in these reports are based on numerous 
assumptions regarding future trends in program enrollment, utilization 
and costs of health care services covered by Medicare, as well as other 
factors affecting program expenditures. In addition, although the 
methods used to estimate future costs based on these assumptions are 
complex, they are subject to periodic review by independent experts to 
ensure their validity and reasonableness.
    We also refer readers to the 2018 Actuarial Report on the Financial 
Outlook for Medicaid for a discussion of general issues regarding 
Medicaid projections. (available at: https://www.cms.gov/Research-Statistics-Data-and-Systems/Research/ActuarialStudies/MedicaidReport).
    Comment: As in previous years, a common concern and/or request 
expressed by some commenters was the need for greater transparency in 
the methodology used by CMS and OACT to calculate Factor 1; several 
commenters specifically requested that a detailed description of the 
methodology and the data behind the assumptions be made public. 
Commenters requested that this information be provided in advance of 
the publication of the final rule and in the IPPS proposed rule each 
year going forward, in order that the data be available to replicate 
CMS' DSH calculation and comment sufficiently in future years. 
Similarly, another commenter requested that CMS provide hospitals and 
other stakeholders with a supplementary table and additional commentary 
on the year-to-year changes from the FY 2021 final rule to the FY 2022 
proposed rule for the variables that comprise the ``Other'' factor. The 
commenter requested that CMS provide this information and allow for a 
brief supplemental comment period prior to finalizing the FY 2022 rule. 
The commenter stated that if CMS is unable to provide additional 
information in such a manner, then it should use the ``Other'' factor 
from the FY 2021 final rule for the FY 2022 final rule. Another 
commenter suggested that the methodology and assumptions in projecting 
DSH costs be reviewed by independent experts.
    Additionally, a commenter asserted that the lack of opportunity 
afforded to hospitals to review the data used in rulemaking is in 
violation of the Administrative Procedure Act and expressed concerns 
about the lack of transparency in how Factor 1 is calculated, arguing 
that hospitals cannot meaningfully comment on the methodology given the 
lack of details. In particular, this commenter asserted that the 
proposed rule neither explained the assumption that Medicaid expansion 
would draw enrollees who are healthier than the average Medicaid 
beneficiary and, by extension, would have fewer hospital visits, nor 
described the data CMS used in making this assumption.
    Response: We thank the commenters for their input. We disagree with 
commenters' assertion regarding the lack of transparency with respect 
to the methodology and assumptions used in the calculation of Factor 1. 
As explained in the FY 2022 IPPS/LTCH PPS proposed rule, and in this 
section of this final rule, we have been and continue to be transparent 
about the methodology and data used to estimate Factor 1. Regarding the 
comments referencing the Administrative Procedure Act, we note that 
under the Administrative Procedure Act, a proposed rule is required to 
include either the terms or substance of the proposed rule or a 
description of the subjects and issues involved. In this case, the FY 
2022 IPPS/LTCH PPS proposed rule did include a detailed discussion of 
our proposed Factor 1 methodology and the data sources that would be 
used in making our final estimate. Accordingly, we believe commenters 
were able to meaningfully comment on our proposed estimate of Factor 1.
    To provide context, we note that Factor 1 is not estimated in 
isolation from other projections made by OACT. The Factor 1 estimates 
for proposed

[[Page 45226]]

rules are generally consistent with the economic assumptions and 
actuarial analysis used to develop the President's Budget estimates 
under current law, and the Factor 1 estimates in this final rule are 
generally consistent with those used for the forthcoming ``2021 Annual 
Report of the Boards of Trustees of the Federal Hospital Insurance and 
Federal Supplementary Medical Insurance Trust Funds'' which will be 
made available on the CMS website at: https://www.cms.gov/Research-Statistics-Data-and-Systems/Statistics-Trends-and-Reports/ReportsTrustFunds/index.html under ``Downloads.'' For additional 
information on the development of the President's Budget, we refer 
readers to the OMB website at: https://www.whitehouse.gov/omb/budget.
    For a general overview of the principal steps involved in 
projecting future inpatient costs and utilization, we refer readers to 
the forthcoming 2021 Medicare Trustees Report. We note that the annual 
reports of the Medicare Boards of Trustees to Congress represent the 
Federal Government's official evaluation of the financial status of the 
Medicare Program. The actuarial projections contained in these reports 
are based on numerous assumptions regarding future trends in program 
enrollment, utilization and costs of health care services covered by 
Medicare, as well as other factors affecting program expenditures. In 
addition, although the methods used to estimate future costs based on 
these assumptions are complex, they are subject to periodic review by 
independent experts to ensure their validity and reasonableness.
    We also refer readers to the 2018 Actuarial Report on the Financial 
Outlook for Medicaid which is available on the CMS website at: https://www.cms.gov/Research-Statistics-Data-and-Systems/Research/ActuarialStudies/Downloads/MedicaidReport2018.pdf for a discussion of 
general issues regarding Medicaid projections. Additionally, as 
described in more detail later in this section, in the FY 2022 IPPS/
LTCH PPS proposed rule, we included information regarding the data 
sources, methods, and assumptions employed by the actuaries in 
determining the OACT's estimate of Factor 1. In summary, we indicated 
the historical HCRIS data update OACT used to identify Medicare DSH 
payments, we explained that the most recent Medicare DSH payment 
adjustments provided in the IPPS Impact File were used, and we provided 
the components of all update factors that were applied to the 
historical data to estimate the Medicare DSH payments for the upcoming 
fiscal year, along with the associated rationale and assumptions. This 
discussion also included a description of the ``Other'' and 
``Discharges'' assumptions, as well as additional information regarding 
how we address the Medicaid and CHIP expansion.
    Regarding the commenters' requests for further information on our 
assumptions regarding the effect of Medicaid expansion on the Medicaid 
population, we provide a discussion of more recent estimates and 
assumptions regarding Medicaid expansion as part of the discussion of 
the final Factor 1 for FY 2022, which also incorporates the estimated 
impact of the COVID-19 pandemic.
    Comment: Many commenters requested that CMS calculate estimated DSH 
payments for purposes of Factor 1 without adjusting for the impact of 
the COVID-19 PHE, which the commenters believed would align with other 
CMS proposals regarding COVID-19 PHE data (for example, IPPS and LTCH 
ratesetting proposal to use FY 2019 claims data). Many other commenters 
urged CMS to consider freezing data prior to the PHE for purposes of 
the Factor 1 methodology. Commenters stated that excluding PHE impacts 
from Factor 1 methodology would allow more time to evaluate national 
Medicare uncompensated care funding and the ongoing impacts of the 
COVID-19 pandemic on beneficiaries and hospitals providing care.
    Some commenters requested that CMS revisit the estimate for Factor 
1 and provide greater transparency regarding its calculations, as they 
disagree with CMS' proposed 7.1% decrease from FY 2021. For example, 
according to a commenter, the September 2020 extract of HCRIS cost 
report files used in OACT's Factor 1 methodology for purposes of the 
proposed rule reflected providers that had minimal COVID-19 data (that 
is, March 2020 and earlier data), and this commenter requested that CMS 
revisit the estimates and provide greater transparency. Some commenters 
believed that CMS should work to mitigate the effect of the pandemic 
and associated anomalies in FY 2020 and 2021 cost report data that will 
have an adverse on uncompensated care payments in future years.
    Many commenters asserted that there was a much higher Medicaid 
enrollment in 2020-2021 during the pandemic than CMS estimated for 
purposes of Factor 1. A commenter referred to a New York Times article 
from June 21, 2021, which indicated that nearly 10 million Americans 
enrolled in Medicaid and CHIP during the pandemic. This same commenter 
also disagreed with OACT's assumption of lower utilization by newly 
eligible Medicaid enrollees, and the commenter believed that lower 
utilization was caused by patients' reluctance to seek care and instead 
opting to delay care and elective procedures during the PHE. The 
commenter urged CMS to be transparent in how the ``Other'' factor was 
determined and share the data behind its assumptions.
    Another commenter cited survey data from the Kaiser Family 
Foundation that show a 7.7 million (or 10.8%) increase in Medicaid/CHIP 
enrollment from February 2020 to November 2020. Further, they noted 
that the 0.9 percentage point increase in the estimated increase in 
Medicaid enrollment for FY 2021 (FY 2021 Final Rule, 0.3%, FY 2022 
Proposed Rule, 1.2%) does not explain the reduction in the estimate of 
the ``other'' factor for FY 2021--as such they can only infer there was 
a significant decrease in one or more of the ``other'' variables that 
negated the increased estimate of Medicaid eligibility. To this end, 
commenters requested additional explanation for the proposed decrease 
to the ``other'' factor for FY 2021. Some commenters believed the 20% 
add-on to payments for COVID-10 discharges would have contributed to an 
increase in the ``other'' factor, rather than a decrease.
    Many commenters questioned the proposed rule's estimate of the 
``Discharges'' factor, in particular. Some commenters referenced a 
Kaufman Hall study, which showed that the year-to-date adjusted 
discharges were up 5.9% and the year-over-year and adjusted discharges 
were up 66.4% as of April 2021. A commenter also referred to national 
utilization data from Strata Decision Technology and stated that total 
inpatient admissions began to increase starting in February 2021, 
consistent with declines in COVID-19 inpatient volumes. The commenter 
stated that, although, FY 2021 volumes will remain lower than historic, 
pre-pandemic levels, the trends indicate that FY 2021 volumes will 
continue to increase. These comments urged CMS to carefully monitor 
changes in discharge volume when estimating Factor 1 for FY 2022. A 
commenter urged CMS to use a later update to the claims data consistent 
with the data that CMS otherwise uses to model IPPS impacts and set 
relative weights in a typical year. While some commenters believed that 
using the latest available data when finalizing Factor 1 might capture 
more of the increases in utilization that are

[[Page 45227]]

anticipated for FY 2022, a commenter noted that the use of more recent 
data alone may not fully account for the increase in discharges during 
the second half of FY 2021. Another commenter noted that OACT's 
estimate of the ``Discharges'' factor was based on preliminary FY 2021 
claims data, given the lack of time for ``claims run out.''
    Additionally, commenters requested further explanation regarding 
the estimate of the ``Other'' factor used to estimate Medicare DSH 
payments, and in particular an analysis of the difference between total 
inpatient hospital discharges and IPPS discharges, along with the 
agency's quantitative analysis of the interplay between the various 
factors grouped together as ``Other'' factors impacting estimated DSH 
payments. Specifically, commenters requested that OACT address the 
expected increase in IPPS discharges as a percentage of total inpatient 
hospital discharges in the latter half of FY 2021 and the impact of 
these FY 2021 data trends on the ``Other'' factors impacting estimated 
DSH Medicare payments for FY 2021. A commenter mentioned that, 
according to their own analysis, total inpatient discharges and IPPS 
discharges have changed in a similar manner. Another commenter stated 
that CMS has not adequately measured the impact of the shift away from 
direct patient care to telehealth care, in terms of hospital volumes 
and payments. A commenter also suggested that CMS use OACT's estimate 
of FY 2021 Medicare discharges from the FY 2021 Final Rule to estimate 
discharges for FY 2022 ``Discharge'' factor. Similarly, another 
commenter suggested that CMS use estimates of the ``Other'' factor 
variables from the FY 2021 Final Rule for FY 2022, because of the 
commenter's concerns with the transparency of the Factor 1 estimates in 
the FY 2022 proposed rule.
    Other commenters believed that as vaccination rates increase and 
infection rates decline, people can be expected to begin addressing 
their deferred medical needs in the year ahead. As a result, these 
commenters indicated that the historical data used to estimate 
inpatient hospital utilization among Medicare and Medicaid-covered 
individuals understates the actual amount of inpatient care hospitals 
are likely to provide in the coming year.
    Response: We thank the commenters for their input on impact 
projections, such as the impact on Medicaid enrollment from the COVID-
19 PHE, and have taken into consideration the concerns commenters have 
raised in making our projection of Factor 1 for this FY 2022 IPPS/LTCH 
PPS final rule. In updating our estimate of Factor 1, we considered, as 
appropriate, the same set of factors that we used in the proposed rule, 
as updated to account for the unique economic situation presented by 
the COVID-19 PHE. We note that the estimated increases in new Medicaid 
enrollees used for the ``Other'' factor are generally consistent with 
the updated Factor 2 calculation described in the next section. The 
updated estimates for the ``Discharges'' and ''Case Mix'' factors 
incorporate the latest estimates from OACT of the impact of COVID-19 on 
the Medicare program. We provide further details on the updated Factor 
1 estimate and data sources as part of the discussion of the final 
Factor 1 estimate for FY 2022 in this section of the rule.
    Regarding the comments requesting further explanation of the 
difference between total inpatient hospital discharges and IPPS 
discharges, we note that the ``Discharges'' factor used to estimate 
Medicare DSH expenditures relates to IPPS discharges for DSH eligible 
hospitals. As discussed further in this section, the ``Other'' factor 
includes an estimate of the effect of the difference between total 
inpatient hospital discharges compared to discharges at IPPS hospitals 
(particularly those in DSH hospitals). Based on the data sources and 
modeling that are used for Factor 1, we do not break down this effect 
to the level that commenters are requesting additional information. In 
other words, we do not project each individual effect that is part of 
``Other'' factor. We note that the OACT's FY 2022 estimate of 1.0038 
for the ``Other'' factor is an increase relative to the FY 2021 
estimate of 0.9662 for the ``Other'' factor.
    Regarding the comments requesting that we exclude and/or mitigate 
the impacts of the pandemic when estimating Factor 1 for FY 2022, we 
note that the statute specifies that Factor 1 is based on the amount of 
disproportionate share payments that would otherwise be made to a 
subsection (d) hospital for the fiscal year. As discussed further in 
this section, OACT's estimates of Medicare DSH payments used in the 
development of Factor 1, reflect the estimated impact of the COVID-19 
pandemic on DSH payments. We do not believe that excluding and/or 
mitigating the impact of the pandemic through adjustments to Factor 1 
calculation would be consistent with the statute.
    After consideration of the public comments we received, we are 
finalizing, as proposed, the methodology for calculating Factor 1 for 
FY 2022. We discuss the resulting Factor 1 amount for FY 2022 in this 
section. For this final rule, OACT used the most recently submitted 
Medicare cost report data from the March 31, 2021 update of HCRIS to 
identify Medicare DSH payments and the most recent Medicare DSH payment 
adjustments provided in the Impact File published in conjunction with 
the publication of the FY 2021 IPPS/LTCH PPS final rule and applied 
update factors and assumptions for future changes in utilization and 
case-mix to estimate Medicare DSH payments for the upcoming fiscal 
year. The July 2021 OACT estimate for Medicare DSH payments for FY 
2022, without regard to the application of section 1886(r)(1) of the 
Act, was approximately $13.985 billion. This estimate excluded Maryland 
hospitals participating in the Maryland All-Payer Model, hospitals 
participating in the Rural Community Hospital Demonstration, and SCHs 
paid under their hospital-specific payment rate. Therefore, based on 
the July 2021 estimate, the estimate of empirically justified Medicare 
DSH payments for FY 2022, with the application of section 1886(r)(1) of 
the Act, was approximately $3.496 billion (or 25 percent of the total 
amount of estimated Medicare DSH payments for FY 2022). Under Sec.  
412.106(g)(1)(i) of the regulations, Factor 1 is the difference between 
these two OACT estimates. Therefore, the final Factor 1 for FY 2022 is 
$10,488,564,546.74, which is equal to 75 percent of the total amount of 
estimated Medicare DSH payments for FY 2022 ($13,984,752,728.99 minus 
$3,496,188,182.25). OACT's final estimates for FY 2022 began with a 
baseline of $13.882 billion in Medicare DSH expenditures for FY 2018. 
The following table shows the factors applied to update this baseline 
through the current estimate for FY 2022:

[[Page 45228]]

[GRAPHIC] [TIFF OMITTED] TR13AU21.253

    In this table, the discharges column shows the changes in the 
number of Medicare fee-for-service (FFS) inpatient hospital discharges. 
The figures for FY 2019 and FY 2020 are based on Medicare claims data 
that have been adjusted by a completion factor to account for 
incomplete claims data. The discharge figure for FY 2021 is based on 
preliminary data. The discharge figure for FY 2022 is an assumption 
based on recent trends recovering back to the long-term trend and 
assumptions related to how many beneficiaries will be enrolled in 
Medicare Advantage (MA) plans. The discharge figures for FY 2020 to FY 
2022 reflect the estimated impact of the COVID-19 pandemic. The case-
mix column shows the estimated change in case-mix for IPPS hospitals. 
The case-mix figures for FY 2019 and FY 2020 are based on actual data 
adjusted by a completion factor. The case-mix figure for FY 2021 is 
based on preliminary data. The case-mix factor figures for FY 2020 and 
FY 2021 have been adjusted for the estimated impact of the COVID-19 
pandemic. The FY 2022 increase is an estimate based on the 
recommendation of the 2010-2011 Medicare Technical Review Panel. The 
``Other'' column shows the increase in other factors that contribute to 
the Medicare DSH estimates. These factors include the difference 
between the total inpatient hospital discharges and the IPPS 
discharges, and various adjustments to the payment rates that have been 
included over the years but are not reflected in the other columns 
(such as the change in rates for the 2-midnight stay policy and the 20 
percent add-on for COVID-19 discharges). In addition, the ``Other'' 
column includes a factor for the Medicaid expansion due to the 
Affordable Care Act. The factor for Medicaid expansion was developed 
using public information and statements for each State regarding its 
intent to implement the expansion. Based on the information available 
at the time of development of this final rule, it is assumed that 
approximately 55 percent of all individuals who were potentially newly 
eligible Medicaid enrollees in 2018, 2019, and 2020 resided in States 
that had elected to expand Medicaid eligibility, and approximately 60 
percent of all individuals who were potentially newly eligible Medicaid 
enrollees in 2021 and thereafter, resided in States that had elected to 
expand Medicaid eligibility. In the future, these assumptions may 
change based on actual participation by States. The ''Other'' column 
also includes the estimated impacts on Medicaid enrollment due to the 
COVID-19 pandemic. In the proposed rule, we noted that, based on the 
most recent available data at that time, it was estimated that Medicaid 
enrollment increased by 2.9 percent in FY 2020 and would increase by an 
additional 1.2 percent in FY 2021. For this final rule, we have used 
updated assumptions of Medicaid enrollment. For a further discussion, 
we refer readers to the OACT's Memorandum on Factor 1, available at 
https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/AcuteInpatientPPS/dsh.
    For a discussion of general issues regarding Medicaid projections, 
we refer readers to the 2018 Actuarial Report on the Financial Outlook 
for Medicaid, which is available on the CMS website at: https://www.cms.gov/Research-Statistics-Data-and-Systems/Research/ActuarialStudies/Downloads/MedicaidReport2017.pdf. We note that, in 
developing their estimates of the effect of Medicaid expansion on 
Medicare DSH expenditures, our actuaries have assumed that the new 
Medicaid enrollees are healthier than the average Medicaid recipient 
and, therefore, use fewer hospital services. Specifically, based on the 
most recent available data, OACT assumed per capita spending for 
Medicaid beneficiaries who enrolled due to the expansion to be 78 
percent of the average per capita expenditures for a pre-expansion 
Medicaid beneficiary due to the better health of these beneficiaries. 
In the FY 2022 IPPS/LTCH PPS proposed rule (86 FR 25446), we noted that 
this is an updated assumption based on more recent data compared to the 
data available at the time of the FY 2021 IPPS/LTCH PPS final rule. 
This same assumption was used for the new Medicaid beneficiaries who 
enrolled in 2020 and thereafter due to the COVID-19 pandemic. This 
assumption is consistent with recent internal estimates of Medicaid per 
capita spending pre-expansion and post-expansion.
    The following table shows the factors that are included in the 
``Update'' column of the previous table:

[[Page 45229]]

[GRAPHIC] [TIFF OMITTED] TR13AU21.254

b. Calculation of Factor 2 for FY 2022
(1) Background
    Section 1886(r)(2)(B) of the Act establishes Factor 2 in the 
calculation of the uncompensated care payment. Section 
1886(r)(2)(B)(ii) of the Act provides that, for FY 2018 and subsequent 
fiscal years, the second factor is 1 minus the percent change in the 
percent of individuals who are uninsured, as determined by comparing 
the percent of individuals who were uninsured in 2013 (as estimated by 
the Secretary, based on data from the Census Bureau or other sources 
the Secretary determines appropriate, and certified by the Chief 
Actuary of CMS) and the percent of individuals who were uninsured in 
the most recent period for which data are available (as so estimated 
and certified), minus 0.2 percentage point for FYs 2018 and 2019. In FY 
2020 and subsequent fiscal years, there is no longer a reduction. We 
note that, unlike section 1886(r)(2)(B)(i) of the Act, which governed 
the calculation of Factor 2 for FYs 2014, 2015, 2016, and 2017, section 
1886(r)(2)(B)(ii) of the Act permits the use of a data source other 
than the CBO estimates to determine the percent change in the rate of 
uninsurance beginning in FY 2018. In addition, for FY 2018 and 
subsequent years, the statute does not require that the estimate of the 
percent of individuals who are uninsured be limited to individuals who 
are under 65 years of age.
    As we discussed in the FY 2018 IPPS/LTCH PPS final rule (82 FR 
38197), in our analysis of a potential data source for the rate of 
uninsurance for purposes of computing Factor 2 in FY 2018, we 
considered the following: (1) The extent to which the source accounted 
for the full U.S. population; (2) the extent to which the source 
comprehensively accounted for both public and private health insurance 
coverage in deriving its estimates of the number of uninsured; (3) the 
extent to which the source utilized data from the Census Bureau; (4) 
the timeliness of the estimates; (5) the continuity of the estimates 
over time; (6) the accuracy of the estimates; and (7) the availability 
of projections (including the availability of projections using an 
established estimation methodology that would allow for calculation of 
the rate of uninsurance for the applicable Federal fiscal year). As we 
explained in the FY 2018 IPPS/LTCH PPS final rule, these considerations 
are consistent with the statutory requirement that this estimate be 
based on data from the Census Bureau or other sources the Secretary 
determines appropriate and help to ensure the data source will provide 
reasonable estimates for the rate of uninsurance that are available in 
conjunction with the IPPS rulemaking cycle. We proposed to use a 
methodology similar to the one that was used in FY 2018 through FY 2021 
to determine Factor 2 for FY 2022.
    In the FY 2018 IPPS/LTCH PPS final rule (82 FR 38197 and 38198), we 
explained that we determined the source that, on balance, best meets 
all of these considerations is the uninsured estimates produced by OACT 
as part of the development of the National Health Expenditure Accounts 
(NHEA). The NHEA represents the government's official estimates of 
economic activity (spending) within the health sector. The information 
contained in the NHEA has been used to study numerous topics related to 
the health care sector, including, but not limited to, changes in the 
amount and cost of health services purchased and the payers or programs 
that provide or purchase these services; the economic causal factors at 
work in the health sector; the impact of policy changes, including 
major health reform; and comparisons to other countries' health 
spending. Of relevance to the determination of Factor 2 is that the 
comprehensive and integrated structure of the NHEA creates an ideal 
tool for evaluating changes to the health care system, such as the mix 
of the insured and uninsured, because this information is integral to 
the well-established NHEA methodology. A full description of the 
methodology used to develop the NHEA is available on the CMS website 
at: https://www.cms.gov/files/document/definitions-sources-and-methods.pdf.
    The NHEA estimates of U.S. population reflect the Census Bureau's 
definition of the resident-based population, which includes all people 
who usually reside in the 50 States or the District of Columbia, but 
excludes residents living in Puerto Rico and areas under U.S. 
sovereignty, members of the U.S. Armed Forces overseas, and U.S. 
citizens whose usual place of residence is outside of the U.S., plus a 
small (typically less than 0.2 percent of population) adjustment to 
reflect Census undercounts. For fiscal years 2014 through 2017, the 
estimates for Factor 2 were made using the CBO's uninsured population 
estimates for the under 65 population. For FY 2018 and subsequent 
years, the statute does not restrict the estimate to the measurement of 
the percent of individuals under the age of 65 who are uninsured. 
Accordingly, as we explained in the FY 2018 IPPS/LTCH PPS proposed and 
final rules, we believe it is appropriate to use an estimate that 
reflects the rate

[[Page 45230]]

of uninsurance in the U.S. across all age groups. In addition, we 
continue to believe that a resident-based population estimate more 
fully reflects the levels of uninsurance in the United States that 
influence uncompensated care for hospitals than an estimate that 
reflects only legal residents. The NHEA estimates of uninsurance are 
for the total U.S. population (all ages) and not by specific age 
cohort, such as the population under the age of 65.
    The NHEA includes comprehensive enrollment estimates for total 
private health insurance (PHI) (including direct and employer-sponsored 
plans), Medicare, Medicaid, the Children's Health Insurance Program 
(CHIP), and other public programs, and estimates of the number of 
individuals who are uninsured. Estimates of total PHI enrollment are 
available for 1960 through 2019, estimates of Medicaid, Medicare, and 
CHIP enrollment are available for the length of the respective 
programs, and all other estimates (including the more detailed 
estimates of direct-purchased and employer-sponsored insurance) are 
available for 1987 through 2019. The NHEA data are publicly available 
on the CMS website at: https://www.cms.gov/Research-Statistics-Data-and-Systems/Statistics-Trends-and-Reports/NationalHealthExpendData/index.html.
    In order to compute Factor 2, the first metric that is needed is 
the proportion of the total U.S. population that was uninsured in 2013. 
In developing the estimates for the NHEA, OACT's methodology included 
using the number of uninsured individuals for 1987 through 2009 based 
on the enhanced Current Population Survey (CPS) from the State Health 
Access Data Assistance Center (SHADAC). The CPS, sponsored jointly by 
the U.S. Census Bureau and the U.S. Bureau of Labor Statistics (BLS), 
is the primary source of labor force statistics for the population of 
the United States. (We refer readers to the website at: http://www.census.gov/programs-surveys/cps.html.) The enhanced CPS, available 
from SHADAC (available at: http://datacenter.shadac.org) accounts for 
changes in the CPS methodology over time. OACT further adjusts the 
enhanced CPS for an estimated undercount of Medicaid enrollees (a 
population that is often not fully captured in surveys that include 
Medicaid enrollees due to a perceived stigma associated with being 
enrolled in the Medicaid program or confusion about the source of their 
health insurance).
    To estimate the number of uninsured individuals for 2010 through 
2019, OACT extrapolates from the 2009 CPS data through 2018 using data 
from the National Health Interview Survey (NHIS) and then, for 2019, 
OACT extrapolates using the American Community Survey (ACS). The NHIS 
is one of the major data collection programs of the National Center for 
Health Statistics (NCHS), which is part of the Centers for Disease 
Control and Prevention (CDC). For both the NHIS and ACS, the U.S. 
Census Bureau is the data collection agent. The results from these data 
sources have been instrumental over the years in providing data to 
track health status, health care access, and progress toward achieving 
national health objectives. For further information regarding the NHIS, 
we refer readers to the CDC website at: https://www.cdc.gov/nchs/nhis/index.htm. For further information regarding the ACS, we refer readers 
to the Census Bureau's website at: https://www.census.gov/programs-surveys/acs/. In deriving the number of uninsured for the most recent 
release of the national health expenditure accounts, there were two 
concerns related to the data sources typically used. The NHIS underwent 
a redesign in 2019 and cautioned its users against comparing the year-
over-year trend from 2018-2019 as a result. Also, the Census Bureau 
indicated that it experienced data collection issues for the 2019 CPS, 
which may have been affected by the COVID-19 pandemic, and similarly 
cautioned its users to be aware of the potential impact on trend 
analysis between 2018 and 2019. Consequently, the ACS data were used 
for estimating 2019.
    The next metrics needed to compute Factor 2 are projections of the 
rate of uninsurance in both CY 2021 and CY 2022. On an annual basis, 
OACT projects enrollment and spending trends for the coming 10-year 
period. Those projections use the latest NHEA historical data, 
available at the time of their construction. The NHEA projection 
methodology accounts for expected changes in enrollment across all of 
the categories of insurance coverage previously listed. The sources for 
projected growth rates in enrollment for Medicare, Medicaid, and CHIP 
include the latest Medicare Trustees Report, the Medicaid Actuarial 
Report, or other updated estimates as produced by OACT. Projected rates 
of growth in enrollment for private health insurance and the uninsured 
are based largely on OACT's econometric models, which rely on the set 
of macroeconomic assumptions underlying the latest Medicare Trustees 
Report. Greater detail can be found in OACT's report titled 
``Projections of National Health Expenditure: Methodology and Model 
Specification,'' which is available on the CMS website at: https://www.cms.gov/Research-Statistics-Data-and-Systems/Statistics-Trends-and-Reports/NationalHealthExpendData/Downloads/ProjectionsMethodology.pdf.
    The use of data from the NHEA to estimate the rate of uninsurance 
is consistent with the statute and meets the criteria we have 
identified for determining the appropriate data source. Section 
1886(r)(2)(B)(ii) of the Act instructs the Secretary to estimate the 
rate of uninsurance for purposes of Factor 2 based on data from the 
Census Bureau or other sources the Secretary determines appropriate. 
The NHEA utilizes data from the Census Bureau; the estimates are 
available in time for the IPPS rulemaking cycle; the estimates are 
produced by OACT on an annual basis and are expected to continue to be 
produced for the foreseeable future; and projections are available for 
calendar year time periods that span the upcoming fiscal year. 
Timeliness and continuity are important considerations because of our 
need to be able to update this estimate annually. Accuracy is also a 
very important consideration and, all things being equal, we would 
choose the most accurate data source that sufficiently meets our other 
criteria.
    We refer readers to OACT's Memorandum on Certification of Rates of 
Uninsured prepared for the FY 2022 IPPS/LTCH proposed rule for further 
details on the methodology and assumptions that were used in the 
projection of the uninsurance rate.\762\
---------------------------------------------------------------------------

    \762\ OACT Memorandum on Certification of Rates of Uninsured. 
March 12, 2021. Available at: https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/AcuteInPatientPPS/dsh.html.
---------------------------------------------------------------------------

(2) Factor 2 for FY 2022
    As discussed in the FY 2022 IPPS/LTCH PPS proposed rule (86 FR 
25448 and 25449), using these data sources and the previously described 
methodologies, OACT estimated that the uninsured rate for the 
historical, baseline year of 2013 was 14 percent and for CYs 2021 and 
2022 is 10.2 percent and 10.1 percent, respectively. The projected 
rates of uninsurance for CY 2021 and 2022 reflect the estimated impact 
of the COVID-19 pandemic. As required by section 1886(r)(2)(B)(ii) of 
the Act, the Chief Actuary of CMS has certified these estimates. 
However, for purposes of this final rule, we note that the OACT has 
added an addendum to the memo to reflect an updated estimate of 
projected rates of uninsurance for CY

[[Page 45231]]

2021 and 2022, as discussed in our responses to comments.
    As with the CBO estimates on which we based Factor 2 for fiscal 
years before FY 2018, the NHEA estimates are for a calendar year. Under 
the approach originally adopted in the FY 2014 IPPS/LTCH PPS final 
rule, we have used a weighted average approach to project the rate of 
uninsurance for each fiscal year. We continue to believe that, in order 
to estimate the rate of uninsurance during a fiscal year accurately, 
Factor 2 should reflect the estimated rate of uninsurance that 
hospitals will experience during the fiscal year, rather than the rate 
of uninsurance during only one of the calendar years that the fiscal 
year spans. Accordingly, we proposed to continue to apply the weighted 
average approach used in past fiscal years in order to estimate the 
rate of uninsurance for FY 2022.
    As part of the development of the proposed Factor 2 for FY 2021, 
OACT certified the estimate of the rate of uninsurance for FY 2022 
determined using this weighted average approach to be reasonable and 
appropriate for purposes of section 1886(r)(2)(B)(ii) of the Act. 
However, in the proposed rule, we noted that we might also consider the 
use of more recent data that may become available for purposes of 
estimating the rates of uninsurance used in the calculation of the 
final Factor 2 for FY 2022. In particular, we noted that any potential 
impacts from the American Rescue Plan Act were not reflected in our 
estimates for the proposed rule, due to the timing for the development 
and publication of the FY 2022 IPPS/LTCH proposed rule.
    In the proposed rule, we outlined the calculation of the proposed 
Factor 2 for FY 2022 as follows:
    Percent of individuals without insurance for CY 2013: 14 percent.
    Percent of individuals without insurance for CY 2021: 10.2 percent.
    Percent of individuals without insurance for CY 2022: 10.1 percent.
    Percent of individuals without insurance for FY 2022 (0.25 times 
0.0102) + (0.75 times 0.0101): 10.1 percent.
    1- [verbar]((0.101-0.14)/0.14)[verbar] = 1-0.2786 = 0.7214 (72.14 
percent).
    For FY 2020 and subsequent fiscal years, section 1886(r)(2)(B)(ii) 
of the Act no longer includes any reduction to the previous calculation 
in order to determine Factor 2. Therefore, we proposed that Factor 2 
for FY 2022 would be 72.14 percent.
    The proposed FY 2022 uncompensated care amount was 
$10,573,368,841.28 * 0.7214 = $7,627,628,282.10.
[GRAPHIC] [TIFF OMITTED] TR13AU21.255

    We invited public comments on the proposed Factor 2 for FY 2022.
    Comment: As with the comments received on proposed Factor 1, a 
majority of commenters discussed the proposed Factor 2 in the context 
of the COVID-19 PHE. Many commenters urged CMS to be transparent in the 
calculation of Factor 2 and stated that agency assumptions and data 
sources should be accurate and publicly available. Many commenters 
urged OACT to update its projections of the rates of uninsurance to 
reflect changes in the rate of uninsurance due to the COVID-19 PHE, and 
in particular, current economic conditions. A commenter also 
recommended that the agency account for regulatory or legislative 
changes that could drive up uninsured rates as well as external 
factors, such as shifts in economic conditions.
    Many commenters requested that CMS consider the shifts from 
commercial insurance to Medicaid when calculating Factor 2. A commenter 
stated that the writers of the Affordable Care Act could not have 
foreseen that such a drastic shift in insurance patterns would occur in 
a short amount of time, as a result of a pandemic.
    Many commenters highlighted the proposed decrease of approximately 
$660 million in total uncompensated care payments in the FY 2022 
proposed rule compared to estimated total uncompensated care payments 
for FY 2021, which, according to a commenter, conflicts with CMS' goal 
of advancing health equity and reducing healthcare disparities.
    Commenters referred to the significant increase in unemployment due 
to the pandemic and stated that it seems counterintuitive that the 
percentage of uninsured decreased. Another commenter stated that the 
reduction in uncompensated care payments, in part because of a 
projected reduction in the number of uninsured individuals, is 
inconsistent with the increase in care that hospitals have provided to 
uninsured patients during the past year. Therefore, many commenters 
requested that for FY 2022 CMS maintain total uncompensated care 
payments at the current level for FY 2021, due to the pandemic. Some 
commenters recommended that CMS follow a similar path as in other IPPS 
policies proposed for FY 2022 and use FY 2019 data again in place of FY 
2020 data when calculating the uninsured rates for Factor 2.
    A commenter indicated that other government reports have 
contradicted many of the most important assumptions made concerning 
Factor 2. For example, the CBO issued a report on nationwide health 
insurance levels, which concluded that the Affordable Care Act had 
insured fewer individuals than previously estimated. Additionally, they 
noted that in the President's 2018 Economic Report, the Administration 
noted that not only was the overall coverage expansion less than 
initially expected, but it was also due more to Medicaid expansion than 
was initially projected.
    A commenter also noted that in projecting coverage levels for FY 
2022, the proposed rule assumed an under-reporting of Medicaid coverage 
``due to a perceived stigma associated with being enrolled in the 
Medicaid program or confusion about the source of their health 
insurance,'' yet there is nothing in the proposed rule to indicate that 
the agency has applied this same presumption of under reporting in 
calculating Factor 1, where increased Medicaid coverage would serve to 
increase expected DSH payments. The commenter concluded that it appears 
that the agency has applied internally inconsistent assumptions on 
Medicaid expansion between Factors 1 and 2 with no explanation.
    Many commenters recommended using the latest available data when 
finalizing Factor 2. Commenters believed that using more timely and 
accurate data would reflect an increase in the uninsured population in 
FY 2021 and FY 2022. A commenter requested that CMS revisit its 
approach to calculating uncompensated care funding, as current data 
likely includes too much noise.
    Response: We thank the commenters for their input and their 
recommendations regarding the estimate of Factor 2 included in the 
proposed rule. We refer readers to the Addendum to the OACT memo for 
further details on the methodology and updated assumptions used in the 
calculation of

[[Page 45232]]

the projection of the uninsurance rate for this final rule. In brief, 
using the past estimates from NHEA from earlier this year as a 
baseline, OACT estimated the impacts of employment changes on insurance 
coverage to update the estimate of the rates of uninsurance for CY 2021 
and CY 2022. We note that this approach takes into account relevant 
developments since publication of the proposed rule, including faster-
than-anticipated employment growth, an improving economic outlook based 
on a consensus of the Blue Chip forecasters, and substantial recent and 
anticipated, temporary increases in Medicaid enrollment (associated in 
part with the Maintenance of Effort requirement under the FFCRA for 
states to qualify to receive higher Medicaid payments during the PHE).
    In response to the comments concerning transparency, we reiterate 
that we have been and continue to be transparent with respect to the 
methodology and data used to estimate Factor 2. The FY 2022 IPPS/LTCH 
PPS proposed rule included a detailed discussion of our proposed Factor 
2 methodology as well as the data sources that would be used in making 
our final estimate. For purposes of this final rule, we are using an 
updated projected rate of uninsurance to better reflect the impact of 
the PHE for the COVID-19 pandemic. A detailed description of the 
methodology used to update our estimates can be found in the 
accompanying memo (available at: https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/AcuteInpatientPPS/dsh). Section 
1886(r)(2)(B)(ii) of the Act permits us to use a data source other than 
the CBO estimates to determine the percent change in the rate of 
uninsurance beginning in FY 2018. We continue to believe that the NHEA 
data and methodology that were used to estimate Factor 2 for this final 
rule are transparent and best meet all of our considerations for 
ensuring reasonable estimates for the rate of uninsurance that are 
available in conjunction with the IPPS rulemaking cycle. We also 
believe it is appropriate to update the NHEA-based projection of the FY 
2022 rate of uninsurance that appeared in the proposed rule using 
recent unemployment data from BLS, and associated projections of that 
metric as published in the Blue Chip Economic Indicators report.
    Many commenters requested that CMS consider the shifts from 
commercial insurance to Medicaid when calculating Factor 2. The 
projections utilized here capture shifts between insurance categories 
such as from commercial insurance to Medicaid and any resulting impact 
on the uninsured population. Regarding the comments recommending that 
we maintain total uncompensated care payments at the FY 2021 level, we 
note that section 1886(r)(2)(B)(ii) provides that Factor 2 should be 
determined by comparing the percent of individuals who are uninsured in 
2013 with the number of individuals ``who are uninsured in the most 
recent period for which data is available.'' Because data are available 
to permit OACT to estimate the rate of uninsurance for CY 2021 and CY 
2022, we believe using these data to estimate Factor 2 for FY 2022 is 
appropriate and consistent with the statute. In particular, maintaining 
total uncompensated care payments at the FY 2021 level would fail to 
reflect updated expectations regarding the level of uninsurance during 
FY 2022 associated with changing economic conditions, newly available 
data on Medicaid and Marketplace enrollment, the estimated impacts from 
the Families First Coronavirus Response Act (FFCRA), including the 
provision requiring a Medicaid Maintenance of Effort, the CARES Act, 
and the American Rescue Plan Act.
    After consideration of the public comments we received, we are 
updating the calculation of Factor 2 for FY 2022 to incorporate more 
recent data, as we proposed. The final estimates of the percent of 
uninsured individuals have been certified by the Chief Actuary of CMS. 
The calculation of the final Factor 2 for FY 2022 using a weighted 
average of OACT's updated projections for CY 2021 and CY 2022 is as 
follows:
     Percent of individuals without insurance for CY 2013: 14 
percent.
     Percent of individuals without insurance for CY 2021: 9.8 
percent.
     Percent of individuals without insurance for CY 2022: 9.5 
percent.
     Percent of individuals without insurance for FY 2022 (0.25 
times 0.098) + (0.75 times 0.095): 9.6 percent.
    1- [verbar]((0.096-0.14)/0.14)[verbar] = 1-0.3143 = 0.6857 (68.57 
percent). Therefore, the final Factor 2 for FY 2022 is 68.57 percent. 
The final FY 2022 uncompensated care amount is $10,488,564,546.74 * 
0.6857 = $7,192,008,709.70.
[GRAPHIC] [TIFF OMITTED] TR13AU21.256

c. Calculation of Factor 3 for FY 2022
(1) General Background
    Section 1886(r)(2)(C) of the Act defines Factor 3 in the 
calculation of the uncompensated care payment. As we have discussed 
earlier, section 1886(r)(2)(C) of the Act states that Factor 3 is equal 
to the percent, for each subsection (d) hospital, that represents the 
quotient of: (1) The amount of uncompensated care for such hospital for 
a period selected by the Secretary (as estimated by the Secretary, 
based on appropriate data (including, in the case where the Secretary 
determines alternative data are available that are a better proxy for 
the costs of subsection (d) hospitals for treating the uninsured, the 
use of such alternative data)); and (2) the aggregate amount of 
uncompensated care for all subsection (d) hospitals that receive a 
payment under section 1886(r) of the Act for such period (as so 
estimated, based on such data).
    Therefore, Factor 3 is a hospital-specific value that expresses the 
proportion of the estimated uncompensated care amount for each 
subsection (d) hospital and each subsection (d) Puerto Rico hospital 
with the potential to receive Medicare DSH payments relative to the 
estimated uncompensated care amount for all hospitals estimated to 
receive Medicare DSH payments in the fiscal year for which the 
uncompensated care payment is to be made. Factor 3 is applied to the 
product of Factor 1 and Factor 2 to determine the amount of the 
uncompensated care payment that each eligible hospital will receive for 
FY 2014 and subsequent fiscal years. In order to implement the 
statutory requirements for this factor of the uncompensated care 
payment formula, it was necessary to determine: (1) The definition of 
uncompensated care or, in other words, the specific items that are to 
be included in the numerator (that is, the estimated uncompensated care 
amount for an individual hospital) and the denominator (that is, the 
estimated uncompensated care amount for all hospitals estimated to 
receive Medicare DSH payments in the applicable fiscal year); (2) the 
data source(s) for the estimated uncompensated care amount; and (3) the 
timing and manner of

[[Page 45233]]

computing the quotient for each hospital estimated to receive Medicare 
DSH payments. The statute instructs the Secretary to estimate the 
amounts of uncompensated care for a period based on appropriate data. 
In addition, we note that the statute permits the Secretary to use 
alternative data in the case where the Secretary determines that such 
alternative data are available that are a better proxy for the costs of 
subsection (d) hospitals for treating individuals who are uninsured.
    In the course of considering how to determine Factor 3 during the 
rulemaking process for FY 2014, the first year for which section 
1886(r) of the Act was in effect, we considered defining the amount of 
uncompensated care for a hospital as the uncompensated care costs of 
that hospital and determined that Worksheet S-10 of the Medicare cost 
report would potentially provide the most complete data regarding 
uncompensated care costs for Medicare hospitals. However, because of 
concerns regarding variations in the data reported on Worksheet S-10 
and the completeness of these data, we did not use Worksheet S-10 data 
to determine Factor 3 for FY 2014, or for FYs 2015, 2016, or 2017. 
Instead, we used alternative data on the utilization of insured low-
income patients, as measured by patient days, which we believed would 
be a better proxy for the costs of hospitals in treating the uninsured 
and therefore appropriate to use in calculating Factor 3 for these 
years. Of particular importance in our decision to use proxy data was 
the relative newness of Worksheet S-10, which went into effect on May 
1, 2010. At the time of the rulemaking for FY 2014, the most recent 
available cost reports would have been from FYs 2010 and 2011 and 
submitted on or after May 1, 2010, when the new Worksheet S-10 went 
into effect. However, we indicated our belief that Worksheet S-10 could 
ultimately serve as an appropriate source of more direct data regarding 
uncompensated care costs for purposes of determining Factor 3 once 
hospitals were submitting more accurate and consistent data through 
this reporting mechanism.
    In the FY 2018 IPPS/LTCH PPS final rule (82 FR 38202), we stated 
that we could no longer conclude that alternative data to the Worksheet 
S-10 are available for FY 2014 that are a better proxy for the costs of 
subsection (d) hospitals for treating individuals who are uninsured. 
Hospitals were on notice as of FY 2014 that Worksheet S-10 could 
eventually become the data source for CMS to calculate uncompensated 
care payments. Furthermore, hospitals' cost reports from FY 2014 had 
been publicly available for some time, and CMS had analyses of 
Worksheet S-10, conducted both internally and by stakeholders, 
demonstrating that Worksheet S-10 accuracy had improved over time. 
Analyses performed by MedPAC had already shown that the correlation 
between audited uncompensated care data from 2009 and the data from the 
FY 2011 Worksheet S-10 was over 0.80, as compared to a correlation of 
approximately 0.50 between the audited uncompensated care data and 2011 
Medicare SSI and Medicaid days. Based on this analysis, MedPAC 
concluded that use of Worksheet S-10 data was already better than using 
Medicare SSI and Medicaid days as a proxy for uncompensated care costs, 
and that the data reported on Worksheet S-10 would improve over time as 
the data are actually used to make payments (81 FR 25090). In addition, 
a 2007 MedPAC analysis of data from the Government Accountability 
Office (GAO) and the American Hospital Association (AHA) had suggested 
that Medicaid days and low-income Medicare days are not an accurate 
proxy for uncompensated care costs (80 FR 49525).
    Subsequent analyses from Dobson/DaVanzo, originally commissioned by 
CMS for the FY 2014 rulemaking and updated in later years, compared 
Worksheet S-10 and IRS Form 990 data and assessed the correlation in 
Factor 3s derived from each of the data sources. Our analyses on 
balance led us to believe that we had reached a tipping point in FY 
2018 with respect to the use of the Worksheet S-10 data. We refer 
readers to the FY 2018 IPPS/LTCH PPS final rule (82 FR 38201 through 
38203) for a complete discussion of these analyses. We found further 
evidence for this tipping point when we examined changes to the FY 2014 
Worksheet S-10 data submitted by hospitals following the publication of 
the FY 2017 IPPS/LTCH PPS final rule.
    We also recognized commenters' concerns that, in continuing to use 
Medicaid days as part of the proxy for uncompensated care, it would be 
possible for hospitals in States that choose to expand Medicaid to 
receive higher uncompensated care payments because they may have more 
Medicaid patient days than hospitals in a State that does not choose to 
expand Medicaid. Because the earliest Medicaid expansions under the 
Affordable Care Act began in 2014, the 2011, 2012, and 2013 Medicaid 
days used to calculate uncompensated care payments in FYs 2015, 2016, 
and 2017 are the latest available data on Medicaid utilization that do 
not reflect the effects of these Medicaid expansions. Accordingly, if 
we had used only low-income insured days to estimate uncompensated care 
for FY 2018, we would have needed to hold the time period of these data 
constant and use data on Medicaid days from 2011, 2012, and 2013 in 
order to avoid the risk of any redistributive effects arising from the 
decision to expand Medicaid in certain States. In the FY 2018 IPPS/LTCH 
PPS final rule, we finalized a methodology under which we calculated 
Factor 3 for all eligible hospitals, with the exception of Puerto Rico 
hospitals and Indian Health Service (IHS) and Tribal hospitals, using 
Worksheet S-10 data from FY 2014 cost reports in conjunction with low-
income insured days proxy data based on Medicaid days and SSI days. The 
time period for the Medicaid days data was FY 2012 and FY 2013 cost 
reports (82 FR 38208 through 38213).
    As we stated in the FY 2019 IPPS/LTCH PPS final rule (83 FR 41414), 
with the additional steps we had taken to ensure the accuracy and 
consistency of the data reported on Worksheet S-10 since the 
publication of the FY 2018 IPPS/LTCH PPS final rule, we continued to 
believe that we could no longer conclude that alternative data to the 
Worksheet S-10 are currently available for FY 2014 that are a better 
proxy for the costs of subsection (d) hospitals for treating 
individuals who are uninsured. Similarly, the actions that we have 
taken to improve the accuracy and consistency of the Worksheet S-10 
data, including the opportunity for hospitals to resubmit Worksheet S-
10 data for FY 2015, led us to conclude that there were no alternative 
data to the Worksheet S-10 data currently available for FY 2015 that 
would be a better proxy for the costs of subsection (d) hospitals for 
treating uninsured individuals. Accordingly, in the FY 2019 IPPS/LTCH 
PPS final rule (83 FR 41428), we advanced the time period of the data 
used in the calculation of Factor 3 forward by 1 year and used 
Worksheet S-10 data from FY 2014 and FY 2015 cost reports in 
combination with the low income insured days proxy for FY 2013 to 
determine Factor 3 for FY 2019. We note that, as discussed in the FY 
2020 IPPS/LTCH PPS final rule (84 FR 42366), the use of three years of 
data to determine Factor 3 for FY 2018 and FY 2019 had the effect of 
smoothing the transition from the use of low-income insured days to the 
use of Worksheet S-10 data.
    As discussed in the FY 2019 IPPS/LTCH PPS final rule (83 FR 41424), 
we received overwhelming feedback from commenters emphasizing the

[[Page 45234]]

importance of audits in ensuring the accuracy and consistency of data 
reported on the Worksheet S-10. We began auditing the Worksheet S-10 
data for selected hospitals in the Fall of 2018 so that the audited 
uncompensated care data from these hospitals would be available in time 
for use in the FY 2020 IPPS/LTCH PPS proposed rule. The audits began 
with 1 year of data (that is, FY 2015 cost reports) in order to 
maximize the available audit resources and not spread those audit 
resources over multiple years, potentially diluting their 
effectiveness. We chose to begin the audits with the FY 2015 cost 
reports primarily because this was the most recent year of data that we 
had broadly allowed to be resubmitted by hospitals, and many hospitals 
had already made considerable efforts to amend their FY 2015 reports in 
preparation for the FY 2019 rulemaking. We also considered that we had 
used the FY 2015 data as part of the calculation of the FY 2019 
uncompensated care payments; therefore, the data had been subject to 
public comment and scrutiny.
    In the FY 2020 IPPS/LTCH PPS final rule (84 FR 42368), we finalized 
our proposal to use a single year of Worksheet S-10 cost report data 
from FY 2015 in the methodology for determining Factor 3 for FY 2020. 
Although some commenters expressed support for the alternative policy 
of using the FY 2017 Worksheet S-10 data to determine each hospital's 
share of uncompensated care costs in FY 2020, given the feedback from 
commenters in response to both the FY 2019 and FY 2020 IPPS/LTCH PPS 
proposed rules, emphasizing the importance of audits in ensuring the 
accuracy and consistency of data reported on the Worksheet S-10, we 
concluded that the FY 2015 Worksheet S-10 data were the best available 
audited data to be used in determining Factor 3 for FY 2020. We also 
noted that we had begun auditing the FY 2017 data in July 2019, with 
the goal of having the FY 2017 audited data available for future 
rulemaking.
    In the FY 2021 IPPS/LTCH PPS final rule (85 FR 58823 through 
58825), we finalized our proposal to use the most recent available 
single year of audited Worksheet S-10 data to determine Factor 3 for FY 
2021 and subsequent fiscal years. We explained our belief that using 
the most recent audited data available before the applicable Federal 
fiscal year, will more accurately reflect a hospital's uncompensated 
care costs, as opposed to averaging multiple years of data. We noted 
that if a hospital has relatively different data between cost report 
years, we potentially would be diluting the effect of our considerable 
auditing efforts and introducing unnecessary variability into the 
calculation if we were to use multiple years of data to calculate 
Factor 3. Therefore, we also believed using a single year of audited 
cost report data is an appropriate methodology to determine Factor 3 
for FY 2021 and subsequent years, except for IHS and Tribal hospitals 
and hospitals located in Puerto Rico. For IHS and Tribal hospitals and 
Puerto Rico hospitals, we finalized the use of a low-income insured 
days proxy to determine Factor 3 for FY 2021. We did not finalize a 
methodology to determine Factor 3 for IHS and Tribal hospitals and 
Puerto Rico hospitals for FY 2022 and subsequent years because we 
believed further consideration and review of these hospitals' Worksheet 
S-10 data was necessary (85 FR 58825).
    In the FY 2021 IPPS/LTCH PPS final rule, we finalized the 
definition ``uncompensated care'' for FY 2021 and subsequent fiscal 
years, for purposes of determining uncompensated care costs and 
calculating Factor 3 (85 FR 58825 through 58828). We are continuing to 
use the definition that we had initially adopted in the FY 2018 IPPS/
LTCH PPS final rule. Specifically, ``uncompensated care'' is defined as 
the amount on Line 30 of Worksheet S-10, which is the cost of charity 
care (Line 23) and the cost of non-Medicare bad debt and non-
reimbursable Medicare bad debt (Line 29). We refer readers to the FY 
2021 IPPS/LTCH PPS rule (85 FR 58825 through 58828) for a discussion of 
additional topics related to the definition of uncompensated care. We 
noted in the FY 2021 IPPS/LTCH PPS final rule that the Paper Reduction 
Act (PRA) package for Form CMS-2552-10 (OMB Control Number 0938-0050, 
expiration date March 31, 2022) would offer an additional opportunity 
to comment on the cost reporting instructions. A PRA package with 
comment period appeared in the November 10, 2020 Federal Register (85 
FR 71653). We thank stakeholders for their comments on the PRA package 
and we will respond to those comments in a separate Federal Register 
document.
(2) Background on the Methodology Used To Calculate Factor 3 for FY 
2021 and Subsequent Fiscal Years
    Section 1886(r)(2)(C) of the Act governs both the selection of the 
data to be used in calculating Factor 3, and also allows the Secretary 
the discretion to determine the time periods from which we will derive 
the data to estimate the numerator and the denominator of the Factor 3 
quotient. Specifically, section 1886(r)(2)(C)(i) of the Act defines the 
numerator of the quotient as the amount of uncompensated care for a 
subsection (d) hospital for a period selected by the Secretary. Section 
1886(r)(2)(C)(ii) of the Act defines the denominator as the aggregate 
amount of uncompensated care for all subsection (d) hospitals that 
receive a payment under section 1886(r) of the Act for such period. In 
the FY 2014 IPPS/LTCH PPS final rule (78 FR 50638), we adopted a 
process of making interim payments with final cost report settlement 
for both the empirically justified Medicare DSH payments and the 
uncompensated care payments required by section 3133 of the Affordable 
Care Act. Consistent with that process, we also determined the time 
period from which to calculate the numerator and denominator of the 
Factor 3 quotient in a way that would be consistent with making interim 
and final payments. Specifically, we must have Factor 3 values 
available for hospitals that we estimate will qualify for Medicare DSH 
payments and for those hospitals that we do not estimate will qualify 
for Medicare DSH payments but that may ultimately qualify for Medicare 
DSH payments at the time of cost report settlement.
    In the FY 2021 IPPS/LTCH PPS final rule, we applied the following 
policies as part of the Factor 3 methodology: (1) The policy regarding 
newly merged hospitals that was initially adopted in the FY 2015 IPPS/
LTCH PPS final rule; (2) the policies regarding annualization and long 
cost reports that were adopted in the FY 2018 and FY 2019 IPPS/LTCH PPS 
final rules, including a modified policy for the rare cases where a 
provider has no cost report for the fiscal year that is used in the 
Factor 3 methodology because the cost report for the previous fiscal 
year spans both years; (4) the modified new hospital policy that was 
finalized in the FY 2020 IPPS/LTCH PPS final rule; (5) the new merger 
policy adopted in the FY 2021 IPPS/LTCH PPS final rule that accounts 
for the merger effective date; and (6) the policies regarding the 
application of statistical trim methodologies to potentially aberrant 
CCRs and potentially aberrant uncompensated care costs reported on the 
Worksheet S-10.
    In the FY 2021 IPPS/LTCH PPS final rule (85 FR 58829), we continued 
to treat hospitals that merge after the development of the final rule 
for the applicable fiscal year similar to new hospitals. As explained 
in the FY 2015 IPPS/LTCH PPS final rule, for these newly merged 
hospitals, we do not have data currently available to calculate a 
Factor 3 amount that accounts for the merged hospital's uncompensated 
care

[[Page 45235]]

burden (79 FR 50021). In the FY 2015 IPPS/LTCH PPS final rule, we 
finalized a policy under which Factor 3 for hospitals that we do not 
identify as undergoing a merger until after the public comment period 
and additional review period following the publication of the final 
rule or that undergo a merger during the fiscal year would be 
recalculated similar to new hospitals (79 FR 50021 and 50022). 
Consistent with past policy, interim uncompensated care payments for 
newly merged hospitals are based only on the data for the surviving 
hospital's CCN available the time of the development of the final rule. 
However, at cost report settlement, we will determine the newly merged 
hospital's final uncompensated care payment based on the uncompensated 
care costs reported on its FY 2021 cost report. That is, we will revise 
the numerator of Factor 3 for the newly merged hospital to reflect the 
uncompensated care costs reported on the newly merged hospital's FY 
2021 cost report.
    In FY 2021 IPPS/LTCH PPS final rule (85 FR 58829), we continued the 
policy that was finalized in the FY 2018 IPPS/LTCH PPS final rule of 
annualizing uncompensated care cost data reported on the Worksheet S-10 
if a hospital's cost report does not equal 12 months of data, except in 
the case of mergers, which would be subject to the modified merger 
policy adopted for FY 2021. In addition, we continued the policies that 
were finalized in the FY 2019 IPPS/LTCH PPS final rule (83 FR 41415) 
regarding the use of the longest cost report available within the 
Federal fiscal year. However, we adopted a modified policy for those 
rare situations where a hospital has a cost report that starts in one 
fiscal year but spans the entirety of the following fiscal year such 
that the hospital has no cost report starting in that subsequent fiscal 
year. Under this modified policy, we use the cost report that spans 
both fiscal years for purposes of calculating Factor 3 when data from 
the latter fiscal year are used in the Factor 3 methodology.
    In the FY 2021 IPPS/LTCH PPS final rule (85 FR 58829 and 58830), we 
continued the modified new hospital policy for new hospitals that did 
not have data for the cost reporting period(s) used in the Factor 3 
calculation for FY 2021. Under the modified policy originally adopted 
for FY 2020, new hospitals that have a preliminary projection of being 
eligible for Medicare DSH based on their most recent available 
disproportionate patient percentages may receive interim empirically 
justified DSH payments. However, because these hospitals did not have a 
FY 2017 cost report to use in the Factor 3 calculation and the 
projection of eligibility for DSH payments was still preliminary, the 
MAC will make a final determination concerning whether the hospital is 
eligible to receive Medicare DSH payments at cost report settlement 
based on its FY 2021 cost report. If the hospital is ultimately 
determined to be eligible for Medicare DSH payments for FY 2021, the 
hospital will receive an uncompensated care payment calculated using a 
Factor 3, where the numerator is the uncompensated care costs reported 
on Worksheet S-10 of the hospital's FY 2021 cost report, and the 
denominator is the sum of the uncompensated care costs reported on 
Worksheet S-10 of the FY 2017 cost reports for all DSH-eligible 
hospitals.
    In the FY 2021 IPPS/LTCH PPS final rule, we finalized a new merger 
policy that accounts for the merger effective date (85 FR 58828 through 
58829). To more accurately estimate UCC for the hospitals involved in a 
merger when the merger effective date occurs partway through the 
surviving hospital's cost reporting period, we finalized a policy of 
not annualizing the acquired hospital's data. Under this policy, we use 
only the portion of the acquired hospital's unannualized UCC data that 
reflects the UCC incurred prior to the merger effective date, but after 
the start of the surviving hospital's current cost reporting period. To 
do this, we calculate a multiplier to be applied to the acquired 
hospital's UCC. This multiplier represents the portion of the UCC data 
from the acquired hospital that should be incorporated with the 
surviving hospital's data to determine UCC for purposes of determining 
Factor 3 for the surviving hospital. This multiplier is obtained by 
calculating the number of days between the start of the applicable cost 
reporting period for the surviving hospital and the merger effective 
date, and then dividing this result by the total number of days in the 
reporting period of the acquired hospital. Applying this multiplier to 
the acquired hospital's unannualized UCC data will determine the final 
portion of the acquired hospital's UCC that should be added to that of 
the surviving hospital for purposes of determining Factor 3 for the 
merged hospital.
    In the FY 2021 IPPS/LTCH PPS final rule (85 FR 58831 and 58832), we 
continued to apply a CCR trim methodology similar to the CCR trim 
methodology policy that has been used for purposes of determining 
uncompensated care payments since FY 2018. This CCR trim methodology is 
consistent with the approach used in the outlier payment methodology 
under Sec.  412.84(h)(3)(ii), which states that the Medicare contractor 
may use a statewide average CCR for hospitals whose operating or 
capital CCR is in excess of 3 standard deviations above the 
corresponding national geometric mean. We refer readers to the 
discussion in the FY 2021 IPPS/LTCH PPS final rule (85 FR 58831) for a 
detailed description of the steps used to determine the applicable CCR.
    In addition, we continued the UCC data trim methodology for rare 
situations where a hospital has potentially aberrant data that are 
unrelated to its CCR (85 FR 58832). However, because we had audited the 
FY 2017 Worksheet S-10 data for a number of hospitals, we explained 
that we no longer believe it is necessary to apply the trim methodology 
for hospitals whose cost report has been audited. Accordingly, for FY 
2021 we finalized a policy under which we exclude hospitals that were 
part of the audits from the trim methodology for potentially aberrant 
UCC. In the FY 2021 IPPS/LTCH PPS final rule (85 FR 58831), we also 
modified the potentially aberrant UCC trim methodology when it is 
applied to all-inclusive rate providers (AIRPs). Under this modified 
trim methodology, when an AIRP's total UCC are greater than 50 percent 
of its total operating costs when calculated using the CCR included on 
its FY 2017 cost report, we will recalculate the AIRP's UCC using the 
CCR reported on Worksheet S-10, line 1 of the hospital's most recent 
available prior year cost report that does not result in UCC of over 50 
percent of total operating costs.
    In the FY 2021 IPPS/LTCH PPS final rule (85 FR 58824 and 58825), we 
continued the policy we first adopted for FY 2018 of substituting data 
regarding FY 2013 low-income insured days for the Worksheet S-10 data 
when determining Factor 3 for IHS and Tribal hospitals and subsection 
(d) Puerto Rico hospitals that have a FY 2013 cost report. We stated 
our belief that this approach was appropriate as the FY 2013 data 
reflect the most recent available information regarding these 
hospitals' low-income insured days before any expansion of Medicaid. In 
addition, because we continued to use 1 year of insured low income 
patient days as a proxy for uncompensated care for Puerto Rico 
hospitals and residents of Puerto Rico are not eligible for SSI 
benefits, we continued to use a proxy for SSI days for Puerto Rico 
hospitals consisting of 14 percent of the hospital's Medicaid days, as 
finalized in the FY 2017 IPPS/LTCH PPS final rule (81 FR 56953 through 
56956).

[[Page 45236]]

    We refer readers to the FY 2021 IPPS/LTCH PPS final rule (85 FR 
58817) for a discussion of the approach that we continued in FY 2021 to 
determine Factor 3 for new Puerto Rico hospitals. In brief, Puerto Rico 
hospitals that do not have a FY 2013 cost report are considered new 
hospitals and subject to the new hospital policy, as discussed 
previously. Specifically, the numerator of the Factor 3 calculation 
will be the uncompensated care costs reported on Worksheet S-10 of the 
hospital's cost report for the applicable fiscal year and the 
denominator is the same denominator that is determined prospectively 
for purposes of determining Factor 3 for all DSH-eligible hospitals.
    Therefore, for FY 2021, we finalized the following methodology to 
compute Factor 3 for each hospital:
    Step 1: Selecting the provider's longest cost report from its 
Federal fiscal year (FFY) 2017 cost reports. (Alternatively, in the 
rare case when the provider has no FFY 2017 cost report because the 
cost report for the previous Federal fiscal year spanned the FFY 2017 
time period, the previous Federal fiscal year cost report would be used 
in this step.)
    Step 2: Annualizing the uncompensated care costs (UCC) from 
Worksheet S-10 Line 30, if the cost report is more than or less than 12 
months. (If applicable, use the statewide average CCR (urban or rural) 
to calculate uncompensated care costs.)
    Step 3: Combining adjusted and/or annualized uncompensated care 
costs for hospitals that merged.
    Step 4: Calculating Factor 3 for IHS and Tribal hospitals and 
Puerto Rico hospitals that have a FY 2013 cost report using the low-
income insured days proxy based on FY 2013 cost report data and the 
most recent available SSI ratio (or, for Puerto Rico hospitals, 14 
percent of the hospital's FY 2013 Medicaid days). (Alternatively, in 
the rare case when a provider has no FFY applicable cost report because 
the cost report for the previous Federal fiscal year spanned the time 
period, the previous Federal fiscal year cost report would be used in 
this step.) The denominator is calculated using the low-income insured 
days proxy data from all DSH eligible hospitals. Consistent with the 
policy adopted in the FY 2019 IPPS/LTCH PPS final rule, if a hospital 
did not have both Medicaid days for FY 2013 and SSI days for FY 2018 
available for use in the calculation of Factor 3 in Step 4, we 
considered the hospital not to have data available for Step 4.
    Step 5: Calculating Factor 3 for the remaining DSH eligible 
hospitals using annualized uncompensated care costs (Worksheet S-10 
Line 30) based on FY 2017 cost report data (from Step 1, 2, or 3). The 
hospitals for which Factor 3 was calculated in Step 4 are excluded from 
this calculation.
    We also stated that the methodology adopted in the FY 2021 IPPS/
LTCH PPS final rule for purposes of determining Factor 3 for FY 2021 
would apply for FY 2022 and subsequent years, using Worksheet S-10 data 
from the most recent cost reporting year for which audits have been 
conducted. However, we did not finalize a methodology to determine 
Factor 3 for FY 2022 and subsequent years for IHS and Tribal hospitals 
and Puerto Rico hospitals that have a FY 2013 cost report because we 
believed further consideration and review of these hospitals' Worksheet 
S-10 data is necessary.
    We amended the regulations at Sec.  412.106(g)(1)(iii)(C) by adding 
a new paragraph (7) to reflect the methodology for computing Factor 3 
for FY 2021. We also added a new paragraph (8) to reflect the policy 
adopted for all subsequent fiscal years of using the most recent 
available single year of audited Worksheet S-10 data to calculate 
Factor 3 for all eligible hospitals, except IHS and Tribal hospitals 
and Puerto Rico Hospitals.
(3) Methodology for Calculating Factor 3 for FY 2022
(a) Use of Audited FY 2018 Data To Calculate Factor 3 for FY 2022
    Audits of FY 2018 cost reports began in 2020 and those audited 
reports were available, in time for the development of the proposed 
rule. Feedback from the audits of the FY 2015 and FY 2017 reports and 
lessons learned were incorporated into the audit process for the FY 
2018 reports. We again chose to audit 1 year of data (that is, FY 2018) 
in order to maximize the available audit resources and not spread those 
audit resources over multiple years, potentially diluting their 
effectiveness.
    Given that the FY 2018 Worksheet S-10 data are the most recent 
available audited data, in the FY 2022 IPPS/LTCH PPS proposed rule, we 
stated that we believe, on balance, that the FY 2018 Worksheet S-10 
data are the best available data to use for calculating Factor 3 for FY 
2022. As discussed in the FY 2020 IPPS/LTCH PPS proposed and final 
rules (84 FR 19419 and 84 FR 42364), we continue to believe that mixing 
audited and unaudited data for individual hospitals by averaging 
multiple years of data could potentially lead to a less smooth result. 
To the extent that the audited FY 2018 data for a hospital may be 
relatively different from its FY 2017 data (whether audited or 
unaudited), we potentially would be diluting the effect of the 
revisions to the cost reporting instructions and our considerable 
auditing efforts, while introducing unnecessary variability into the 
calculation if we were to use multiple years of data to calculate 
Factor 3 for FY 2022. In the FY 2022 IPPS/LTCH proposed rule, we 
recognized that the FY 2017 reports also include audited data for some 
hospitals. However, the FY 2018 cost reports are the most recent year 
of audited data and, and reflect the revisions to the Worksheet S-10 
cost report instructions that were effective on October 1, 2017.
    Accordingly, consistent with the policy adopted in the FY 2021 
IPPS/LTCH PPS final rule and codified in the regulations at Sec.  
412.106(g)(8), in the FY 2022 IPPS/LTCH PPS proposed rule we used a 
single year of Worksheet S-10 data from FY 2018 cost reports to 
calculate Factor 3 for FY 2022 for all eligible hospitals with the 
exception of IHS and Tribal hospitals and Puerto Rico hospitals that 
have a cost report for 2013. As discussed in a later section, we 
proposed to continue to use the low-income insured days proxy to 
calculate Factor 3 for these hospitals for one more year. In the 
proposed rule, we noted that the proposed uncompensated care payments 
to hospitals whose FY 2018 Worksheet S-10 data have been audited 
represent approximately 99.6 percent of the proposed total 
uncompensated care payments for FY 2022. For purposes of the FY 2022 
IPPS/LTCH PPS proposed rule, we used a HCRIS extract updated through 
February 19, 2021. We also noted that we intended to use the March 2021 
update of HCRIS for the FY 2022 final rule and the respective March 
updates for all future final rules. However, we also indicated that we 
might consider the use of more recent data that may become available 
after March 2021, but prior to the development of the final rule, if 
appropriate, for purposes of calculating the final Factor 3 for the FY 
2022 IPPS/LTCH PPS final rule. We invited public comments on our 
proposed methodology for calculating Factor 3 for FY 2022, including, 
but not limited to, our proposed use of FY 2018 Worksheet S-10 data (86 
FR 25457).
    Comment: Several commenters expressed general support for the use 
of audited Worksheet S-10 data to estimate each hospital's share of 
uncompensated care costs in FY 2022 and/or in future years. Commenters 
commended CMS for its efforts to

[[Page 45237]]

ensure the accuracy and consistency of the data reported through 
revised instructions and ongoing refinements to the audit process.
    A commenter expressed concerns about the validity and comparability 
of Worksheet S-10 data, especially in the absence of auditing all DSH-
eligible hospitals. Another commenter asserted that using Worksheet S-
10 data to calculate Factor 3 could result in an inequitable 
distribution because Worksheet S-10 does not ``offset hospital UC 
[uncompensated care] losses with non-Medicare sources of subsidies such 
as Medicaid DSH and related Medicaid waiver [uncompensated care] pool 
funds.'' A commenter recommended that CMS eliminate the reliance on 
Worksheet S-10 data as a measure of uncompensated care because 
Worksheet S-10 methodology does not account for hospitals with high 
levels of uncompensated care from patients on public insurance. The 
commenter noted that these hospitals with high uncompensated care are 
unable to offset their charity care and bad debt losses with additional 
sources such as direct taxes or state and local appropriations. They 
recommended that CMS develop a measure that acknowledges those inherent 
problems or make exceptions and provide specific protections for 
hospitals that serve very low-income and medically complex populations. 
Another commenter requested that CMS ensure its methodology for 
determining UC payments accurately captures the full range of UC costs 
that hospitals incur when treating low-income and uninsured individuals 
to ensure safety net hospitals receive adequate support.
    Response: We appreciate the support for our policy of using the 
most recent year of audited Worksheet S-10 data for the computation of 
Factor 3. We also appreciate the input from those commenters who are 
opposed to the use of data from Worksheet S-10 in the calculation of 
Factor 3. Regarding those comments that expressed concerns that 
Worksheet S-10 data lack validity and are not comparable across 
hospitals, we note that consistent with the policy adopted in the FY 
2021 IPPS/LTCH PPS final rule, we are continuing to use audited 
Worksheet S-10 cost report data to determine Factor 3 for FY 2022. Our 
decision to adopt a policy of using audited Worksheet S-10 data to 
determine Factor 3 was based upon the results of analyses of Worksheet 
S-10 data conducted both internally and by stakeholders which 
demonstrate that Worksheet S-10 accuracy has improved over time. As 
part of our ongoing quality control and data improvement measures, we 
have revised the cost report instructions (Transmittal 11). 
Additionally, we have conducted audits of the FY 2018 Worksheet S-10 
data for an expanded number of hospitals, and we have begun auditing 
the FY 2019 Worksheet S-10 data to further improve provider reporting 
and overall accuracy. Moreover, as hospitals gain more experience with 
completing the Worksheet S-10 and build upon lessons learned from the 
audits, we believe the data obtained from these cost reports will 
continue to improve and become more consistent. Therefore, we continue 
to believe that the Worksheet S-10 data is the best available source 
for the uncompensated care costs of subsection (d) hospitals.
    Comment: Many commenters supported the use of a single year of FY 
2018 Worksheet S-10 data for the calculation of Factor 3 for FY 2022. 
Commenters noted that the FY 2018 cost reports are the most recent 
reports which have been subject to audit and that these audits have 
continued to improve the accuracy and reliability of Worksheet S-10 
data over time. Commenters supporting the continued use of Worksheet S-
10 data also indicated that the FY 2018 cost reports are the most 
extensive as significantly more hospitals underwent Worksheet S-10 
audits. In addition, some commenters indicated that the FY 2018 cost 
reports reflect the improvements called for under the most recent 
revised Worksheet S-10 instructions.
    However, many other commenters expressed opposition to using a 
single year of Worksheet S-10 data in the calculation of uncompensated 
care payments for FY 2022 and future years. The primary concern 
expressed by these commenters was the possibility that such an approach 
would lead to significant variation in year-to-year uncompensated care 
payments, especially in light of external factors that may affect a 
hospital's finances on a one-time basis. These commenters pointed to 
CMS' historical practice of using data from multiple years to determine 
uncompensated care payments and argued that such an approach would 
mitigate year-to-year fluctuations and avoid a skewed distribution of 
uncompensated care payments, while also ensuring accuracy, stability, 
and predictability for providers. Some stakeholders indicated that CMS 
will no longer have to be concerned about mixing audited and unaudited 
data from multiple years as the agency continues to audit Worksheet S-
10 data each year.
    The most common alternative recommended by commenters who opposed 
the use of a single year of FY 2018 data for the calculation of Factor 
3 in FY 2022 was the use of two years of historical Worksheet S-10 
data. Several commenters recommended a transitional period where FY 
2017 and FY 2018 Worksheet S-10 data would be used to determine Factor 
3 for FY 2022, because both years have been subject to audits. These 
commenters also suggested the use of FY 2017, FY 2018, and FY 2019 data 
to determine FY 2023 uncompensated care payments, followed by the 
continued use of three years of audited Worksheet S-10 data thereafter. 
As an alternative, a commenter suggested the use of audited FY 2018 and 
FY 2019 data to determine Factor 3 for FY 2023, and a subsequent 
transition to using three years of audited data for the FY 2024 
uncompensated care payments, if using data from more than one year's 
cost report for FY 2022 was not feasible.
    Some commenters acknowledged the efforts CMS has taken to improve 
the accuracy of Worksheet S-10 data through the audit process. Yet, 
several commenters expressed concerns about the accuracy and 
reliability of using a single year of Worksheet S-10 audited data. Some 
commenters requested that CMS further monitor uncompensated care 
payments over time for potential anomalies and fluctuations. Other 
commenters recommended CMS consider omitting or making appropriate 
adjustments to cost report data due to the effects of the COVID-19 
public health emergency (PHE) when calculating Factor 3 and determining 
the distribution of uncompensated care payments in future years. In 
addition, a commenter suggested that CMS regularly assess the cost 
report data for irregular trends and their potential impact on the 
allocation of uncompensated care payments.
    Response: We are grateful to those commenters who expressed their 
support for using the FY 2018 Worksheet S-10 data to determine each 
hospital's share of uncompensated care costs in FY 2022. As noted in 
the FY 2022 IPPS/LTCH PPS proposed rule, we believe, that, on balance, 
the FY 2018 Worksheet S-10 data are the best available data to use for 
calculating Factor 3 for FY 2022.
    Regarding the commenters' suggestion of using multiple years of 
audited Worksheet S-10 data, we will consider using multiple years of 
data when the vast majority of providers have been audited for more 
than one fiscal year under the revised reporting instructions. We 
expect that the number of audits will continue to increase from 
previous years. Further, we continue to believe

[[Page 45238]]

that mixing audited and unaudited data for individual hospitals by 
averaging multiple years of data could potentially lead to a less 
smooth result. To the extent that the audited FY 2018 Worksheet S-10 
data for a hospital are relatively different from its audited or 
unaudited FY 2017 Worksheet S-10 data (for example, as a general 
statement, audits can materially impact a hospital's data), we 
potentially would be diluting the effect of the revisions to the cost 
reporting instructions and our considerable auditing efforts, while 
introducing unnecessary variability into the calculation if we were to 
use multiple years of data to calculate Factor 3 for FY 2022. For 
example, there are some unaudited FY 2017 reports that have a larger 
than $5 million absolute difference in uncompensated care costs between 
a hospital's unaudited FY 2017 report and a hospital's audited FY 2018 
report. We believe using the most recent year of audited data is an 
appropriate methodology for DSH uncompensated care payments.
    As explained in the FY 2021 IPPS/LTCH PPS final rule (85 FR 58820), 
we also note that if a blend of multiple years of cost report data (for 
example, FY 2017, FY 2018, and/or FY 2019) were to be used, some 
hospitals in states that expanded Medicaid eligibility during this time 
period may have experienced significant reductions in uncompensated 
care costs following the expansion due to increased Medicaid coverage 
of many previously uninsured individuals. In this situation, if an 
average that included pre-expansion uncompensated care cost data were 
used, the Factor 3 calculated for the hospital may be a less accurate 
reflection of the relative uncompensated care burden of the hospital. 
Thus, we believe using only the FY 2018 cost report data will result in 
a more accurate and more updated reflection of each hospital's 
proportion of uncompensated care costs. We also agree with those 
commenters that noted FY 2018 cost reports reflect the first year of 
data reported under the revised to Worksheet S-10 instructions that 
were effective on October 1, 2017, and have further improved the data 
quality. Accordingly, consistent with the regulation at Sec.  
412.106(g)(1)(iii)(C)(8), we will calculate Factor 3 for FY 2022 using 
FY 2018 Worksheet S-10 data, which is the most recent cost reporting 
year for which audits have been conducted and which we continue to 
believe is the best available data for purposes of calculating Factor 3 
for FY 2022.
    For the same reasons, we also continue to have confidence that the 
best available data in future years will be the Worksheet S-10 data for 
cost reporting years for which audits have been conducted under the 
revised reporting instructions. Regarding the commenters' suggestions 
for FY 2023 and FY 2024, we are not making any modifications to our 
existing policy on calculating Factor 3 for future fiscal years at this 
time. We will continue to monitor uncompensated care payments for 
fluctuations and evaluate any anomalies as we move forward with using 
only one year of audited Worksheet S-10 data for Factor 3 calculations.
    Regarding commenters' concerns about and suggestions for addressing 
the impact of the COVID-19 PHE in future years, we believe it would be 
premature to attempt in this rulemaking to modify the methodology for 
calculating Factor 3 or determining uncompensated care payments for a 
future fiscal year. We will consider this issue further in future 
rulemaking when the FY 2020 and FY 2021 cost reporting data are more 
fully available to be analyzed.
    The following comments relate to the definition of uncompensated 
care costs:
    Comment: With regard to the definition of uncompensated care, 
several commenters urged CMS to include unreimbursed costs (shortfalls) 
from Medicaid, CHIP, and State and local indigent care programs. 
According to commenters, these shortfalls represent substantial losses 
as those programs often do not fully cover the cost of providing care. 
Several commenters also argued that including Medicaid shortfalls as 
uncompensated care in Worksheet S-10 is especially important for 
hospitals in states that have expanded Medicaid. According to the 
commenters, these hospitals tend to be worse off under the current 
definition of uncompensated care, as compared to hospitals in states 
that did not expand. Some commenters provided CMS with methodologies 
for how to account for Medicaid shortfalls, including a recommendation 
that CMS develop a measure similar in nature to the Medicaid low-income 
utilization rate (LIUR) formula that includes Medicaid shortfalls and 
uninsured care rates to calculate uncompensated care costs for purposes 
of Factor 3. Another commenter suggested specific revisions to 
Worksheet S-10 to better reflect the actual Medicaid shortfalls 
incurred by hospitals. These revisions included allowing hospitals to 
include all GME-related costs and to reduce their Medicaid revenue by 
the amount of any contributions to funding the nonfederal share of the 
Medicaid program, whether through provider taxes, intergovernmental 
transfers (IGTs), or certified public expenditures (CPEs).
    Response: We appreciate commenters' suggestions for revisions and/
or modifications to Worksheet S-10. We will consider the concerns 
raised by commenters as part of future cost report clarifications, and 
will make modifications as necessary to further improve and refine the 
information that is reported on Worksheet S-10 to support collection of 
the information necessary to implement section 1886(r)(2) of the Act. 
With regard to the comments requesting that payment shortfalls from 
Medicaid and state and local indigent care programs be included in 
uncompensated care cost calculations, we continue to believe there are 
compelling arguments for excluding such shortfalls from the definition 
of uncompensated care. First, we note that we did not propose any 
changes to the definition of uncompensated care costs, which was 
finalized in the FY 2021 IPPS/LTCH PPS final rule as the amount on Line 
30 of Worksheet S-10, which is the cost of charity care (Line 23) and 
the cost of non-Medicare bad debt and non-reimbursable Medicare bad 
debt (Line 29). Additionally, and as noted in past rulemaking, several 
key stakeholders, including MedPAC, do not consider Medicaid shortfalls 
in their definition of uncompensated care. Furthermore, we continue to 
believe that it is most consistent with section 1886(r)(2) of the Act 
for Medicare uncompensated care payments to target hospitals that incur 
a disproportionate share of uncompensated care for patients with no 
insurance coverage. We also note that even if we agreed that it would 
be appropriate to adjust the definition of uncompensated care to 
include Medicaid shortfalls, this would not be a feasible option at 
this time due to computational limitations. Specifically, computing 
such shortfalls is operationally problematic because Medicaid pays 
hospitals a single DSH payment that in part covers the hospital's costs 
in providing care to the uninsured and in part covers estimates of the 
Medicaid ``shortfalls.'' Therefore, it is not clear how CMS would 
determine how much of the ``shortfall'' is left after the Medicaid DSH 
payment is made. In addition, in some States, hospitals return a 
portion of their Medicaid revenues to the State via provider taxes and 
receive supplemental payments in return (along with the Federal match), 
making the computation of ``shortfalls'' even more complex.

[[Page 45239]]

    Comment: Commenters also suggested that CMS include all patient 
care costs when calculating the cost to charge ratio (CCR) used in 
Worksheet S-10, including costs associated with training medical 
residents, supporting physician and professional services, and paying 
provider taxes, so as to determine uncompensated care costs more 
accurately for purposes of the Worksheet S-10. A commenter also 
suggested that CMS incorporate the costs of organ transplant programs 
into the CCR calculation as hospitals incur significant costs related 
to uninsured and underinsured populations that are not addressed 
through payments for organ acquisition costs.
    Response: As we have consistently stated in past final rules (84 FR 
42378 and 85 FR 58826) in response to similar comments, we believe that 
the purpose of uncompensated care payments is to provide additional 
payment to hospitals for treating the uninsured, not for other costs 
incurred, including costs associated with supporting and training 
physicians and other professionals or paying provider taxes associated 
with Medicaid, as commenters have suggested.
    Additionally, because the CCR on Line 1 of Worksheet S-10 is 
obtained from Worksheet C, Part I, and is also used in other IPPS rate 
setting contexts (such as high-cost outliers and the calculation of the 
MS-DRG relative weights) from which it is appropriate to exclude the 
costs associated with organ transplant programs, supporting physician 
and professional services and GME, we remain hesitant to adjust CCRs in 
the narrower context of calculating uncompensated care costs. 
Therefore, as stated in past final rules, we continue to believe that 
it is not appropriate, at this time, to modify the calculation of the 
CCR on Line 1 of Worksheet S-10 to include any additional costs in the 
numerator of the CCR calculation.
    For issues related to the cost report instruction, which are beyond 
the scope of this rulemaking, we refer commenters to the forthcoming 
Paper Reduction Act (PRA) package comment period for Form 2552-10 (OMB 
Control Number 0938-0050), which will be the appropriate forum for 
recommending modifications to Worksheet S-10.
    Comment: Some stakeholders offered suggestions regarding the 
uncompensated care payment calculation that appear to be outside the 
scope of the policies discussed in the proposed rule. One such comment 
included a recommendation that CMS change the distribution of 
uncompensated care payments and set a cap on uncompensated care 
payments, for instance, by implementing a statistical trim threshold on 
uncompensated care costs reported on the Worksheet S-10 costs that are 
greater than 40% of Worksheet A expenses. These commenters also 
suggested that uncompensated care payments in excess of the cap could 
be redistributed to all other eligible hospitals. Another commenter 
suggested that hospitals that report aberrant uncompensated care costs 
on their Worksheet S-10 be penalized by receiving a Factor 3 of 0, 
rather than a Factor 3 determined using our trim methodology.
    In addition, some commenters requested that CMS consider policies 
to mitigate the effect of the COVID-19 PHE on FY 2020 and FY 2021 cost 
reports, which will impact future uncompensated care distributions for 
FY 2024 and FY 2025. In relation to this recommendation, several 
commenters suggested that CMS consider and/or finalize a policy that 
would preclude using FY 2020 and FY 2021 Worksheet S-10 data to 
calculate Factor 3, as these data will likely be affected by COVID-19 
PHE and are likely to be unrepresentative of other years, given the 
unique pressures that hospitals faced during that time.
    Response: We thank commenters for their continued concern regarding 
the distribution of uncompensated care payments and the impact of the 
COVID-19 PHE on future uncompensated care payments distributions. 
Regarding commenters' recommendation that we implement a cap on 
uncompensated care payments, we believe that our policy for trimming 
uncompensated care costs that are an extremely high ratio, greater than 
50 percent, of a hospital's total operating costs for the same year as 
described the FY 2021 final rule (85 FR 58832), balances our desire to 
exclude potentially aberrant data with our concern regarding 
inappropriately reducing uncompensated care payments to a hospital that 
may have a legitimately high ratio as determined through an audit of 
their Worksheet S-10 data. Additionally, we note that the statutory 
language governing Factor 3 does not specify any upper limit to a 
hospital's uncompensated care payment.
    Regarding the commenter's suggestion that hospitals with aberrant 
cost report data get penalized with a Factor 3 of 0, we note that 
consistent with the policies adopted in the FY 2021 IPPS/LTCH final 
rule we intend to continue our policy of trimming potentially aberrant 
CCRs by applying the state-wide average CCR for providers with a CCR 
above the proposed ceiling. As discussed previously, we will also 
continue to implement the trim methodology for potentially aberrant UCC 
for purposes of determining Factor 3. In addition, for FY 2022, we 
proposed to trim potentially aberrant charity care cost data for 
hospitals that are currently not projected to be DSH eligible and do 
not have audited FY 2018 Worksheet S-10 data by excluding the hospital 
from the prospective Factor 3 calculation if that hospital's insured 
patient's charity care costs exceed a threshold of 60 percent of total 
uncompensated care costs and a dollar threshold of $7 million. We 
believe these policies appropriately address potentially aberrant data 
in UCC distribution for the purposes of calculating Factor 3.
    The commenters' suggestion that we adjust the methodology for 
determining uncompensated care costs in this rulemaking to reflect the 
impact of the COVID-19 PHE is premature. Moreover, it is not clear at 
this time what methodology would be used to determine any such an 
adjustment and what data source could be used. Because cost reporting 
data for the period covered by the COVID-19 PHE is not yet available to 
be analyzed, we believe it would be premature to attempt in this 
rulemaking to modify the methodology for determining uncompensated care 
payments for a future year specifically to address the impact of the 
COVID-19 PHE. We intend to consider the potential impact of the COVID-
19 PHE on the determination of uncompensated care costs in future 
rulemaking, as appropriate.
    The following comments relate to the Worksheet S-10 audit process:
    Comment: As in previous years, the auditing process for the FY 2018 
Worksheet S-10 was a common topic among many commenters. Several 
commenters agreed that the data from audited FY 2018 Worksheet S-10s 
have improved in accuracy when compared to previous years of data and 
cover a larger share of DSH-eligible hospitals. Other commenters also 
commended CMS' efforts to improve the Worksheet S-10 data through the 
audit process and revised instructions. Some commenters agreed that the 
use of audited Worksheet S-10 data is the most appropriate for 
calculating Factor 3 and determining DSH payments. A commenter 
supported CMS' approach of focusing its limited audit resources on the 
hospitals receiving the highest amounts of uncompensated care payments.
    Still, many commenters expressed concerns with the Worksheet S-10 
audits. Several commenters

[[Page 45240]]

recommended that CMS implement a comprehensive audit process and expand 
the Worksheet S-10 audits to include all DSH-eligible hospitals 
receiving uncompensated care payments. In contrast, a commenter 
recommended that CMS audit a reasonable fraction of providers each 
year, such as one-third of DSH hospitals, and implement a three year 
rotation to audit all DSH hospitals over the course of three rulemaking 
cycles.
    Some commenters requested that CMS decrease the provider burden 
associated with Worksheet S-10 audits, such as by minimizing the 
significant investment of time and resources required to prepare the 
necessary audit documentation for auditors. Stakeholders also urged CMS 
to conduct consistent and equitable audits across providers. Others 
suggested that CMS revisit the scope of the audits to target specific 
data elements, which would decrease provider burden.
    Additionally, a few commenters suggested that CMS ensure 
transparency and consistency in the audit process by making the audit 
materials and protocols publicly available. A commenter also requested 
that CMS promulgate the audit policy and protocols through notice and 
comment rulemaking. Some commenters suggested that the Medicare Wage 
Index audit process could be a model for Worksheet S-10 audits. A 
commenter referred to the IRS Form 990 audits as separate example. This 
commenter asserted that the IRS Form 990 audits have been completely 
different from the Worksheet S-10 audits of uncompensated costs, and 
stated that the hospitals' IRS audits have not resulted in 
disallowance.
    Other commenters urged CMS to develop a transparent timeframe for 
the audit process, with communication to providers about expectations 
and adequate lead time to avoid short response times. A commenter urged 
CMS to complete audits well in advance of future rulemaking to ensure 
that cost report data are accurate and available to be used in 
determining Factor 3. They also requested that CMS establish a 
standardized and streamlined process across auditors, which would 
include clear timelines for information submission and guidance on 
acceptable documentation to meet audit requirements. A commenter also 
requested that CMS select hospitals for audits in an equitable way and 
disclose the criteria used to identify hospitals subject to audits.
    Commenters noted the need for a timely review and appeals process 
for any adverse findings or inconsistent audit disallowances. 
Additionally, commenters urged CMS to consider seeking input from 
hospitals and working with MACs in developing the Worksheet S-10 audit 
process to further promote clarity and consistency. To this end, a 
commenter requested that CMS review audit findings to ensure MACs and 
their subcontractors are applying audit protocols consistently across 
hospitals nationwide. A commenter urged CMS to implement fatal edits to 
ensure that the Worksheet S-10 is submitted completely and is 
internally consistent, and to instruct MACs to audit negative, missing, 
or suspicious information.
    As part of requesting stability in the Worksheet S-10 audit 
process, a commenter expressed their concerns with the inconsistent and 
different sampling and extrapolation techniques employed by MACs during 
Worksheet S-10 audits. They highlighted the different sampling methods 
and error rate thresholds used to justify extrapolation, which the 
commenter believes have produced varied outcomes for hospitals and 
could impact uncompensated care payments. In addition, this commenter 
requested that CMS apply the same audit criteria that are used for 
retrospective audits of empirically justified DSH payments, which are 
determined using SSI/Medicare and Medicaid eligible days. The commenter 
also stated that hospitals should have the same protections afforded by 
the appeal rights available for empirically justified DSH payments.
    Response: We thank commenters for their feedback on the audits of 
the FY 2018 Worksheet S-10 data and their recommendations for future 
audits. As we have stated previously in response to comments regarding 
audit protocols, these are provided to the MACs in advance of the 
audit, in order to assure consistency during the audit process. We 
began auditing the FY 2018 Worksheet S-10 data for selected hospitals 
last year so that the audited uncompensated care data for these 
hospitals would be available in time for use in the FY 2022 IPPS/LTCH 
PPS proposed rule. We chose to focus the audit on the FY 2018 cost 
reports in order to maximize the available audit resources. We also 
note that FY 2018 data are the most recent year of audited data 
reported under the revised cost report instructions that were effective 
on October 1, 2017.
    In response to the consistent feedback from commenters emphasizing 
the importance of audits in ensuring the accuracy and consistency of 
data reported on the Worksheet S-10, we have also started the process 
of auditing FY 2019 Worksheet S-10 data. We recognize that a number of 
commenters have suggested we audit all hospitals. However, as discussed 
in the FY 2022 IPPS/LTCH PPS proposed rule (86 FR 25453), we note that 
the proposed uncompensated care payments to hospitals whose FY 2018 
Worksheet S-10 data have been audited represent approximately 99.6 
percent of the proposed total uncompensated care payments for FY 2022, 
which is an increase from the 65 percent captured in the FY 2017 
audits. While our limited audit resources mean that it is not feasible 
to commit to auditing all hospitals every year, we will continue to 
expand the number of audited providers captured in the FY 2019 audits, 
as was done in the FY 2018 audits. We expect the number of audits will 
continue to increase over time, resulting in improved Worksheet S-10 
data over the years.
    We appreciate all commenters' input and recommendations on how to 
improve our audit process and reiterate our commitment to continue 
working with the MACs and providers on audit improvements, including 
changes to increase the efficiency of the audit process and build on 
the lessons learned in previous audit years. Regarding commenters' 
requests for a standard audit timeline, we do not intend to establish a 
fixed timeline for audits across MACs at this time so that we can 
retain the flexibility to use our limited audit resources to address 
and prioritize audit needs across all CMS programs each year. We note 
that MACs work closely with providers regarding scheduling dates during 
the Worksheet S-10 audit process.
    Regarding commenters' requests that we make public the audit 
instructions and criteria, as we previously stated in the FY 2021 IPPS/
LTCH final rule (85 FR 58822) and prior rules, we do not make review 
protocols public as CMS desk review and audit protocols are 
confidential and are for CMS and MAC use only. Concerning the request 
that we promulgate the Worksheet S-10 audit policy and protocols 
through notice and comment rulemaking, we do not believe it would be 
appropriate to seek comment on audit protocols that are confidential. 
Rather, it is sufficient that we provide stakeholders with notice of 
our proposed methodology for determining uncompensated care payments 
and the data sources that will be used, so that they may have a 
meaningful opportunity to submit their views on the proposed 
methodology and the adequacy of the data for the intended purpose.

[[Page 45241]]

    Regarding commenters' recommendations that we establish a timely 
review and appeals process for the Worksheet S-10 audits, we do not 
intend on introducing such a process at this time in order to maximize 
limited audit resources. However, we will continue to work with 
stakeholders to address their concerns regarding the accuracy and 
consistency of data reported on Worksheet S-10. We will also continue 
to work with the MACs each year to further improve the consistency of 
the audit process across providers and MACs.
    Concerning the suggestion to implement a fatal edit on Worksheet S- 
10, we note that we did not propose any additional edits to Worksheet 
S-10 data in the FY 2022 IPPS/LTCH PPS proposed rule. Furthermore, we 
continue to believe that the ongoing MAC reviews of hospitals' 
Worksheet S-10 data coupled with our efforts to improve reporting 
through revised instructions, as well as providers' growing experience 
with reporting uncompensated care costs outweigh the value of any 
``fatal'' edits to the Worksheet S-10 data.
    Concerning the commenter's request that we apply the same audit 
criteria that are used for empirically justified DSH payments, those 
audit protocols are also confidential and are for CMS and MAC use only. 
As explained previously, we continue to believe that audit protocols 
(for example, criteria) should be confidential, so we disagree with the 
commenter about making public any audit protocols. To the extent that 
the commenter is implying that the confidentiality of the audit 
protocols causes inconsistency in auditing across the MACs, we also 
disagree and will continue to work with the MACs each year to ensure a 
consistent audit process across providers and MACs.
    The following comments relate to the Worksheet S-10 cost report 
instructions:
    Comment: With regard to Worksheet S-10 instructions, a commenter 
appreciated the effort CMS has undertaken to improve the clarity of the 
Worksheet S-10 instructions. Some commenters also offered suggestions 
for CMS' calculation of uncompensated care costs, including possible 
changes to Worksheet S-10. Specifically, a commenter mentioned that 
multiplying the CCR by copayment amounts written off as charity care 
significantly understates the cost of charity care as these amounts 
have already been reduced through rate negotiation with the payor. 
Accordingly, the commenter requested that CMS instruct hospitals to 
report copayments for insured patients that are to be written off as 
charity care in Column 2, line 20, thereby excluding them from costs 
reduced by the CCR. Another commenter requested that CMS clarify the 
instructions for line 29 of the Worksheet S-10 regarding non-Medicare 
bad debt for insured patients and urged the agency not to apply the CCR 
to these amounts, adding that making this change would be consistent 
with the way CMS treats non-reimbursed Medicare bad debt.
    Another commenter observed that Worksheet S-10 fails to account for 
all patient care costs when determining uncompensated care costs by 
ignoring the costs hospitals incur in training residents, supporting 
physicians and professional services, and provider taxes related to 
Medicaid revenue. The commenter requested that the agency refine 
Worksheet S-10 to include these costs. In particular, the commenter 
suggested that in calculating the CCR, the agency ``use total of 
Worksheet A, column 3 lines 1 through 17, reduced by the amount of 
worksheet A-9, line 10, as the cost component; and use worksheet C, 
column 8, line 200, as the charge component.'' According to the 
commenter, implementing this change would incorporate additional 
patient care costs incurred by hospitals, such as Graduate Medical 
Education (GME). Similarly, another commenter requested that CMS 
include teaching costs in determining uncompensated care costs on line 
30 of Worksheet S-10 because excluding these costs disproportionately 
affects teaching hospitals and academic medical centers.
    In addition, a commenter suggested that just as unreimbursed costs 
for charity care patients are recognized as uncompensated care costs, 
so should the shortfall of state or local indigent care programs, 
adding that CMS should also refine Worksheet S-10 data on Medicaid 
shortfalls to better resemble actual shortfalls incurred by hospitals. 
To this end, the commenter recommended that a more accurate measure of 
Medicaid shortfalls could include the incorporation of GME costs in the 
CCR. Another recommendation was that CMS allow hospitals to reduce 
Medicaid revenues by intergovernmental transfers (IGTs), provider 
reimbursement taxes, or certified public expenditures (CPEs). While the 
commenter agreed that Medicaid shortfalls, as currently reported on 
Worksheet S-10, should not be included in the uncompensated care cost 
estimation, they added that these data will be increasingly useful for 
informational purposes as more individuals gain access to Medicaid 
coverage. Similarly, a couple of other commenters requested that CMS 
undertake additional efforts to include a hospital's Medicaid 
shortfalls by incorporating line 31 of Worksheet S-10 into the 
calculation of a hospital's uncompensated care costs in Factor 3.
    A commenter stated that CMS should afford providers with ample 
opportunities to provide feedback and receive education on Worksheet S-
10 instructions and requested that CMS clearly communicate regarding 
revisions to cost report instructions and cost report submission 
deadlines. The commenter further recommended that CMS provide 
additional outreach and educational materials to hospitals about 
Worksheet S-10. Another commenter encouraged CMS to postpone the 
implementation of revisions to form CMS-2552-10, Hospital and Health 
Care Complex Cost Report, to allow providers more time to implement the 
required operational changes that the revisions would entail.
    Response: We appreciate commenters' concerns regarding the need for 
clarification of the Worksheet S-10 instructions, as well as their 
suggestions for form revisions to improve reporting. We reiterate our 
commitment to continuing to work with stakeholders to address their 
concerns regarding Worksheet S-10 instructions and reporting through 
provider education and further refinement of the instructions as 
appropriate. We also encourage providers to discuss with their 
respective MACs any questions regarding clarifications of instructions 
and/or reporting.
    We continue to believe that our efforts to refine the instructions 
have improved provider understanding of the Worksheet S-10 and added 
clarity to the instructions, as noted by a commenter. We also recognize 
that there are continuing opportunities to further improve the accuracy 
and consistency of the information that is reported on the Worksheet S-
10, and to the extent that commenters have raised new questions and 
concerns regarding the reporting requirements, we will attempt to 
address them through future rulemaking and/or provider outreach. 
However, as stated in previous rules, we continue to believe that the 
Worksheet S-10 instructions are sufficiently clear and allow hospitals 
to accurately complete Worksheet S-10.
    Regarding the comments requesting specific structural changes to 
Worksheet S-10 and/or further clarification of the reporting 
instructions, as well as the recommendation that we postpone the 
implementation of revisions to Form CMS-2552-10 (OMB Control Number 
0938-0050, expiration date March 31,

[[Page 45242]]

2022), we note that these comments fall outside the scope of this final 
rule. We therefore refer commenters to the forthcoming Paper Reduction 
Act (PRA) package comment period for the Worksheet S-10, which will be 
the appropriate forum to raise specific questions about or suggestions 
for modifications and clarifications to Worksheet S-10, including the 
reporting instructions.
    For commenters' reference, additional materials regarding 
clarifications to the Worksheet S-10 instructions are contained in the 
MLN article titled ``Updates to Medicare's Cost Report Worksheet S-10 
to Capture Uncompensated Care Data'', available at https://www.cms.gov/Outreach-and-Education/Medicare-Learning-Network-MLN/MLNMattersArticles/Downloads/se17031.pdf, as well as the Worksheet S-10 
Q&As on the CMS DSH website in the download section, available at: 
https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/AcuteInpatientPPS/Downloads/Worksheet-S-10-UCC-QandAs.pdf.
 IHS and Tribal Hospitals
    For the reasons discussed in the FY 2018 IPPS/LTCH PPS final rule 
(82 FR 38209), we continue to recognize that the use of data from 
Worksheet S-10 to calculate the uncompensated care amount for IHS and 
Tribal hospitals may jeopardize these hospitals' payments due to their 
unique funding structure. Prior to the proposed rulemaking for FY 2022, 
CMS consulted with IHS and Tribal hospitals regarding uncompensated 
care reporting. We are considering the input received through this 
consultation with IHS and Tribal hospitals for future rulemaking.
    Therefore, for IHS and Tribal hospitals, we proposed to continue 
the policy first adopted in the FY 2018 rulemaking regarding the low-
income patient proxy. Specifically, for FY 2022 we proposed to 
determine Factor 3 for these hospitals based on Medicaid days for FY 
2013 and the most recent available year of data on SSI days. The 
aggregate amount of uncompensated care that is used in the Factor 3 
denominator for these hospitals would continue to be based on the low-
income patient proxy; that is, the aggregate amount of uncompensated 
care determined for all DSH eligible hospitals using the low-income 
insured days proxy. As we explained in the FY 2022 IPPS/LTCH PPS 
proposed rule (86 FR 24543), we continue to believe this approach is 
appropriate because the FY 2013 data reflect the most recent available 
information regarding these hospitals' Medicaid days before any 
expansion of Medicaid. We also note that all IHS and Tribal hospitals 
have a FY 2013 cost report that can be used for purposes of determining 
Factor 3. At the time of development of the proposed rule, for modeling 
purposes, we computed Factor 3 for these hospitals using FY 2013 
Medicaid days from a HCRIS extract updated through February 19, 2021, 
and the FY 2018 SSI days.
    Comment: Commenters expressed support for CMS' proposal to continue 
using low-income patient days as a proxy to calculate Factor 3 IHS and 
Tribal hospitals for FY 2022, with a commenter suggesting the use of 
the proxy in future years as well. Another commenter recommended that 
in subsequent years CMS allow Indian Health Care Provider (IHCP) 
hospitals the option of continuing to use the low-income days proxy 
measure or data from Worksheet S-10 to calculate uncompensated care 
amounts for the purposes of determining uncompensated care payments. 
Several commenters reiterated their support for a modified policy of 
paying Tribal and IHS hospitals 100% of Medicare DSH and requested that 
CMS explain why they did not propose this policy again.
    A commenter also expressed dismay that CMS has yet to address the 
concerns previously mentioned with regard to the application of the 
uncompensated care cost policy to IHS and Tribal hospitals. The 
commenter requested that at a minimum, CMS give stakeholders one year 
to provide comments on a proposed policy and allow an additional three 
years as an implementation phase for the newly developed methodology.
    The commenter indicated that, in the event uncompensated care 
payments for IHS and Tribal hospitals were to be determined using 
Worksheet S-10 data, 26 facilities with less than 100 beds would stand 
to collectively lose $7.5 million in DSH payments, while the two 
largest facilities would stand to gain $6.9 million. The commenter also 
noted that only two IHS and Tribal hospitals, both of which have more 
than 100 beds, would not be subject to the 12 percent cap on DSH 
payments. They recommended that CMS remove the 12 percent cap as this 
``would advance the intent of the Congress to maximize Federal 
resources for the Indian health system.'' The commenter added that if 
the 12 percent cap cannot be addressed via a statutory fix, CMS should 
work with hospitals to adopt changes to the methodology for calculating 
uncompensated care and charity care that address the unique 
circumstances of the Indian health system so that the disproportionate 
impact of the cap is offset. Further, while the commenter recognized 
that the cap ``is statutorily imposed by the MMA [Medicare 
Modernization Act] and that CMS cannot act unilaterally to change it,'' 
they proposed that the agency work with Congress to remove the cap from 
all IHS and Tribal hospitals.
    The commenter also noted that IHS and Tribal Hospitals also face a 
unique legal standing such that they do not ``fit well into the 
framework that CMS is proposing to adjust for uncompensated care 
payments.'' The commenter added that the inability to charge any Indian 
for services, including copays, and the provisions contained within 
treaties with the Federal Government and judicial rulings, mean that 
these hospitals are subject to a very unique method of calculating 
uncompensated care costs. The commenter maintained that the calculation 
of uncompensated care payments should be done in such a way as to 
maximize these hospitals' access to Federal resources. The commenter 
suggested that CMS work with IHS and Tribal facilities as well as the 
consortium to provide guidance on how these facilities should report 
uncompensated care on Worksheet S-10. In this regard, another commenter 
expressed that a significant challenge for IHS and Tribal hospitals is 
that CMS may be interpreting that ``IHCPs do not have uncompensated 
care costs under Worksheet S-10, because base funding for the costs of 
patient care is provided through Congressional appropriations and might 
construe this as all care being considered compensated.'' However, 
commenters state that IHS appropriations do not fully fund the costs of 
care and that many tribal health programs invest non-Federal resources 
``to furnish care that could easily be classified as uncompensated care 
since IHCPs may not charge beneficiaries to receive care and, thus, may 
not have the accounting methods to track these costs.'' In summary, the 
commenter stated that IHCP hospitals are currently unable to report 
charity care and non-Medicare bad debt in a way that is consistent with 
the definition of uncompensated care in the regulation.
    Additionally, a commenter stated that the information technology 
systems used by IHS and Tribal hospitals are not equipped to collect 
the necessary data for the Worksheet S-10, noting that while IHS 
recently received funding to upgrade its information technology system, 
it will take some time, potentially years, before it is fully 
functional. The commenter urged CMS to work and consult with IHS to 
develop any new proposed methodology for

[[Page 45243]]

calculating uncompensated and charity care for IHS and Tribal hospitals 
that would be used as an alternative to Worksheet S-10 to ensure that 
it accurately captures uncompensated and charity care provided by these 
facilities. Another commenter requested that CMS take additional time 
to work with the Tribal Technical Advisory Group and IHS and Tribal 
hospitals in the event it transitions these facilities to a new payment 
methodology for the calculation of Medicare DSH payments.
    Response: We also appreciate the concerns raised and the input 
offered by commenters regarding the methodology for calculating 
uncompensated care payments for IHS and Tribal hospitals. We continue 
to recognize the unique nature of these hospitals and the special 
circumstances IHS and Tribal hospitals face, and we reiterate our 
commitment to continue working with stakeholders, including through 
tribal consultation, as we revisit the issue of Medicare uncompensated 
care payments to these hospitals for the FY 2023 rulemaking. We are not 
making any changes to the current policy for calculating uncompensated 
care payments for IHS and Tribal hospitals at this time, and we look 
forward to continuing to collaborate on methodological approaches in 
the future.
    After consideration of the comments received, we are finalizing our 
proposal to use the low-income insured days proxy to determine Factor 3 
for IHS and Tribal hospitals for FY 2022.
 Puerto Rico Hospitals
    In the FY 2021 IPPS/LTCH PPS proposed rule, we proposed to 
determine Factor 3 for Puerto Rico hospitals using Worksheet S-10 data 
starting in FY 2022. We did not finalize this proposal in the FY 2021 
IPPS/LTCH PPS final rule (85 FR 58825) because we believed further 
consideration was necessary. However, we noted that we continued to 
believe Worksheet S-10 data is the appropriate long-term source for 
information on uncompensated care for hospitals located in Puerto Rico.
    As explained in the FY 2022 IPPS/LTCH PPS proposed rule (86 FR 
25453), we are continuing to consider the reporting challenges in 
Puerto Rico that may negatively impact the ability of Puerto Rico 
hospitals to report uncompensated care. Accordingly, for FY 2022 we 
proposed to determine Factor 3 for Puerto Rico hospitals that have a FY 
2013 cost report based on the low-income patient proxy. We would 
determine Factor 3 for these hospitals based on Medicaid days for FY 
2013 and the most recent available year of data on SSI days. The 
aggregate amount of uncompensated care that is used in the Factor 3 
denominator for these hospitals would continue to be based on the low-
income patient proxy; that is, the aggregate amount of uncompensated 
care determined for all DSH eligible hospitals using the low-income 
insured days proxy. At the time of development of the proposed rule, 
for modeling purposes, we computed Factor 3 for these hospitals using 
FY 2013 Medicaid days from a recent HCRIS extract and the most recent 
available data on SSI days, which was the FY 2018 SSI days. In 
addition, because we proposed to continue to use 1 year of insured low-
income patient days as a proxy for uncompensated care for Puerto Rico 
hospitals and residents of Puerto Rico are not eligible for SSI 
benefits, we proposed to continue to use a proxy for SSI days for 
Puerto Rico hospitals, consisting of 14 percent of a hospital's 
Medicaid days, as finalized in the FY 2017 IPPS/LTCH PPS final rule (81 
FR 56953 through 56956).
    Comment: Several commenters supported CMS' proposal to continue the 
use of low-income days as a proxy for hospitals located in Puerto Rico 
for FY 2022. Commenters also supported the use of 14 percent of a 
hospital's Medicaid days to determine SSI days for hospitals in Puerto 
Rico, as finalized in the 2017 Inpatient IPPS/LTCH PPS final rule. A 
commenter noted that using the Worksheet S-10 to calculate 
uncompensated care costs for hospitals located in Puerto Rico would 
have a severe, unfavorable economic effect, which would exacerbate the 
already precarious financial conditions these hospitals face. This 
commenter suggested that CMS consider allowing a period of at least 
four to five years under the low-income days proxy to evaluate the 
``advancement done in the accounting methodology and reimbursement 
factor for PR [Puerto Rico].''
    According to the commenter, a transition to the Worksheet S-10 
would risk the financial stability of 40 percent of hospitals in Puerto 
Rico, which have already incurred significant losses as a result of the 
COVID-19 pandemic. The commenter expressed concern that the Worksheet 
S-10 has an ``implied penalty'' for Puerto Rico hospitals due to their 
low-cost structure as compared to higher cost hospitals located in the 
mainland US., adding that using Worksheet S-10 to calculate Factor 3 
would not account for the deficiency in Medicaid reimbursement for 
Puerto Rico Hospitals. The commenter also stated that Puerto Rico's 
government health program, known as VITAL, covers approximately 1.2 
million inhabitants of the total 3 million population of Puerto Rico. 
The commenter stated that ``several services not paid by the insurance 
companies contracted by the Puerto Rico Government to provide services 
to VITAL's beneficiaries are absorbed by the hospital because the 
coverage provided by VITAL does not allow the hospital to collect such 
unpaid services from the patient.'' Additionally, the commenter stated 
that currently some hospitals in Puerto Rico do not have a charity care 
policy, even though they provide charity care services. Instead, these 
services are often inappropriately accounted for as a ``contractual 
adjustment.'' The commenter further explained that those hospitals in 
Puerto Rico with a charity care policy in place do not know how to 
optimize their accounting systems to accommodate such policies, adding 
that hospitals may also be inappropriately accounting for bad debts. 
The commenter concluded that all of these factors understate the 
components of uncompensated care costs, and that technical education is 
needed to address the challenges Puerto Rico hospitals have regarding 
charity care and bad debt reporting, which would take years to address.
    Response: We appreciate the concerns raised by commenters regarding 
the calculation of Factor 3 for hospitals in Puerto Rico. Regarding the 
recommendation that we provide Puerto Rico hospitals a 4- to 5-year 
continuation of the current policy before the transition to the use of 
Worksheet S-10, we continue to invite commenters to provide further 
input as we revisit the use of Worksheet S-10 data from Puerto Rico 
hospitals in the Factor 3 methodology in future rulemaking and assess 
the results of FY 2019 audits for these hospitals. We will consider the 
commenters' concerns regarding the unique financial circumstances and 
challenges faced by Puerto Rico hospitals related to uncompensated care 
cost reporting on Worksheet S-10 in future rulemaking as appropriate.
    After consideration of the comments received, we are finalizing the 
use of low-income insured days proxy to determine Factor 3 for Puerto 
Rico hospitals for FY 2022.
(b) Methodology for Calculating Factor 3 for FY 2022
    As we explained in the FY 2022 IPPS/LTCH PPS proposed rule (86 FR 
25454), for purposes of determining Factor 3 for FY 2022, we are 
applying the methodology adopted in the FY 2021 IPPS/LTCH PPS final 
rule. Specifically, we are applying the following policies: (1) The 
merger policies that were

[[Page 45244]]

initially adopted in the FY 2015 IPPS/LTCH PPS final rule (79 FR 
50021), as modified in the FY 2021 IPPS/LTCH PPS final rule to 
incorporate the use of a multiplier to account for merger effective 
date; (2) the policy for providers with multiple cost reports, 
beginning in the same fiscal year, of using the longest cost report and 
annualizing Medicaid data and uncompensated care data if a hospital's 
cost report does not equal 12 months of data; (3) the policy, as 
modified in the FY 2021 IPPS/LTCH PPS final rule, for the rare case 
where a hospital has a cost report that starts in one fiscal year and 
spans the entirety of the following fiscal year, such that the hospital 
has no cost report for that subsequent fiscal year, of using the cost 
report that spans both fiscal years for the latter fiscal year; (4) the 
new hospital policy, as modified in the FY 2020 IPPS/LTCH PPS final 
rule; (5) the newly merged hospital policy; and (6) the policies 
regarding the application of statistical trim methodologies to 
potentially aberrant CCRs and potentially aberrant uncompensated care 
costs reported on the Worksheet S-10.
    Comment: A commenter noted that CMS' policy of annualizing the data 
for the longest cost report period for a hospital in a fiscal year 
disadvantages providers who have undergone a change in ownership 
(CHOW). According to the commenter, there are cases when the hospital 
undergoes a CHOW in the later part of their 12-month cost reporting 
period, and in such cases the first stub-period's uncompensated care 
costs would be annualized for purposes of calculating Factor 3. The 
commenter notes that this approach poses a problem because the 
annualized stub-period would understate the hospital's uncompensated 
care as compared to the full combination of pre- and post- CHOW reports 
due to ``significant presumptive charity write-offs occurring in the 
last month of the 2nd stub period [not annualized].'' The commenter 
provided an example of such case, where a hospital's Factor 3 was 
understated by 20 percent under the current policy of annualizing the 
longest cost report.
    The commenter also noted that the use of annualization may 
understate or overstate a hospital's uncompensated care due to seasonal 
fluctuations, and that in the event of a CHOW, such annualization would 
not be needed if both cost report stubs, pre- and post- CHOW, would 
equal 12 months. The commenter also provided analysis that demonstrated 
significant uncompensated care payment impacts, both positive and 
negative, due to the current policy (only the longest cost report stub 
would be utilized for hospitals that underwent a CHOW) as compared to 
combining stub-period cost reports that account for all 12 months.
    To address these issues, the commenter requested that CMS utilize a 
combined stub-period cost report that accounts for all 12 months of 
uncompensated care data for hospitals that have undergone CHOWs but 
maintained their fiscal year ends when calculating Factor 3.
    Response: We thank the commenter for expressing their concerns and 
suggestions. We believe that the current policy of using the longest 
cost report available in a fiscal year for a hospital and annualizing 
its data meets, in practice, the policy goals of adjusting 
uncompensated care costs for purposes of the Factor 3 calculation. In 
addition, given that CHOWs are not mergers, we do not, at this time, 
consider it necessary to combine data across cost reports. There are 
also inherent issues in combining cost reports for CHOW hospitals in 
that, as the commenter noted, the true annual volume of uncompensated 
care for some providers could be overestimated or underestimated as a 
result. We believe CHOWs and the timing of charity write-offs are 
hospital business decisions. We also note that we did not propose any 
changes to the policy for providers with multiple cost reports; and, we 
would want to collect additional input and suggestions from 
stakeholders before considering making any potential modifications or 
refinements to the current policy for hospitals with multiple cost 
reports in future rulemaking. Therefore, we are not adopting the 
commenter's recommendation at this time.
 New Hospital for Purposes of Factor 3
    We are continuing to apply the new hospital policy that was 
initially adopted in the FY 2020 IPPS/LTCH PPS final rule to determine 
Factor 3 for new hospitals that do not have an FY 2018 cost report to 
use in the Factor 3 calculation (that is, hospitals with CCNs 
established on or after October 1, 2018). In the FY 2020 IPPS/LTCH PPS 
final rule, we modified the new hospital policy that was initially 
adopted in the FY 2014 IPPS/LTCH PPS final rule (78 FR 50643) and 
continued to apply through FY 2019 (83 FR 41417). Under this modified 
policy, if a new hospital has a preliminary projection of being 
eligible for DSH payments based on its most recent available 
disproportionate patient percentage, it may receive interim empirically 
justified DSH payments. However, new hospitals will not receive interim 
uncompensated care payments during FY 2022 because we will have no FY 
2018 uncompensated care data on which to determine what those interim 
payments should be. The MAC will make a final determination concerning 
whether the hospital is eligible to receive Medicare DSH payments at 
cost report settlement based on its FY 2022 cost report. If the 
hospital is ultimately determined to be eligible for Medicare DSH 
payments for FY 2022, the hospital will receive an uncompensated care 
payment calculated using a Factor 3, where the numerator is the 
uncompensated care costs reported on Worksheet S-10 of the hospital's 
FY 2022 cost report, and the denominator is the sum of the 
uncompensated care costs reported on Worksheet S-10 of the FY 2018 cost 
reports for all DSH-eligible hospitals. This denominator will be the 
same denominator that is determined prospectively for purposes of 
determining Factor 3 for all DSH-eligible hospitals, with the exception 
of Puerto Rico hospitals and IHS and Tribal hospitals.
 Newly Merged Hospitals
    We are continuing to treat hospitals that merge after the 
development of the final rule for the applicable fiscal year similar to 
new hospitals. As explained in the FY 2015 IPPS/LTCH PPS final rule, 
for these newly merged hospitals, we do not have data currently 
available to calculate a Factor 3 amount that accounts for the merged 
hospital's uncompensated care burden (79 FR 50021). In the FY 2015 
IPPS/LTCH PPS final rule, we finalized a policy under which Factor 3 
for hospitals that we do not identify as undergoing a merger until 
after the public comment period and additional review period following 
the publication of the final rule or that undergo a merger during the 
fiscal year will be recalculated similar to new hospitals (79 FR 50021 
and 50022). Consistent with the policy adopted in the FY 2015 IPPS/LTCH 
PPS final rule, we will continue to treat newly merged hospitals in a 
similar manner to new hospitals, such that the newly merged hospital's 
final uncompensated care payment will be determined at cost report 
settlement. The numerator of the newly merged hospital's Factor 3 will 
be based on the cost report of only the surviving hospital (that is, 
the newly merged hospital's cost report) for the current fiscal year. 
However, if the hospital's cost reporting period includes less than 12 
months of data, the data from the newly merged hospital's cost

[[Page 45245]]

report will be annualized for purposes of the Factor 3 calculation.
    Consistent with past policy, interim uncompensated care payments 
for the newly merged hospital will be based only on the data for the 
surviving hospital's CCN available at the time of the development of 
the final rule. In other words, the eligibility of a newly merged 
hospital to receive interim uncompensated care payments for FY 2022 and 
the amount of any interim uncompensated care payments, will be based 
only on the FY 2018 cost report available for the surviving CCN at the 
time the final rule is developed. However, at cost report settlement, 
we will determine the newly merged hospital's final uncompensated care 
payment based on the uncompensated care costs reported on its FY 2022 
cost report. That is, we will revise the numerator of Factor 3 for the 
newly merged hospital to reflect the uncompensated care costs reported 
on the newly merged hospital's FY 2022 cost report.
    Comment: A commenter supported the policy of making interim 
uncompensated care payments to newly merged hospitals based on the 
surviving hospital's cost report for FY 2018 and then determining the 
final uncompensated care payment for these hospitals at cost report 
settlement based on the FY 2022 cost report for the merged hospital. 
The commenter also supported the continuation of our current policy for 
determining uncompensated care payments for new hospitals.
    Response: We appreciate the commenter's support for these policies. 
We are not making modifications to our existing policy regarding newly 
merged hospitals.
 CCR Trim Methodology
    The calculation of a hospital's total uncompensated care costs on 
Worksheet S-10 requires the use of the hospital's cost to charge ratio 
(CCR). Consistent with the process for trimming CCRs used in the FY 
2021 IPPS/LTCH PPS final rule (85 FR 58831 and 58832), we apply the 
following steps to determine the applicable CCR:
    Step 1: Remove Maryland hospitals. In addition, we remove all-
inclusive rate providers because their CCRs are not comparable to the 
CCRs calculated for other IPPS hospitals.
    Step 2: For FY 2018 cost reports, calculate a CCR ``ceiling'' with 
the following data: for each IPPS hospital that was not removed in Step 
1 (including non-DSH eligible hospitals), we use cost report data to 
calculate a CCR by dividing the total costs on Worksheet C, Part I, 
Line 202, Column 3 by the charges reported on Worksheet C, Part I, Line 
202, Column 8. (Combining data from multiple cost reports from the same 
fiscal year is not necessary, as the longer cost report will be 
selected.) The ceiling is calculated as 3 standard deviations above the 
national geometric mean CCR for the applicable fiscal year. This 
approach is consistent with the methodology for calculating the CCR 
ceiling used for high-cost outliers. Remove all hospitals that exceed 
the ceiling so that these aberrant CCRs do not skew the calculation of 
the statewide average CCR.
    Step 3: Using the CCRs for the remaining hospitals in Step 2, 
determine the urban and rural statewide average CCRs for FY 2018 for 
hospitals within each State (including non-DSH eligible hospitals), 
weighted by the sum of total hospital discharges from Worksheet S-3, 
Part I, Line 14, Column 15.
    Step 4: Assign the appropriate statewide average CCR (urban or 
rural) calculated in Step 3 to all hospitals, excluding all-inclusive 
rate providers, with a CCR for FY 2018 greater than 3 standard 
deviations above the national geometric mean for that fiscal year (that 
is, the CCR ``ceiling''). For both the proposed rule and this final 
rule, the statewide average CCR was applied to 10 hospitals, of which 3 
hospitals had FY 2018 Worksheet S-10 data.
    Step 5: For providers that did not report a CCR on Worksheet S-10, 
Line 1, we assign them the statewide average CCR as determined in step 
3.
    After completing the previously described steps, we re-calculate 
the hospital's uncompensated care costs (Line 30) using the trimmed CCR 
(the statewide average CCR (urban or rural, as applicable)).
 Uncompensated Care Data Trim Methodology
    In the FY 2022 IPPS/LTCH PPS proposed rule (86 FR 25455), we noted 
that after applying the CCR trim methodology there are rare situations 
where a hospital has potentially aberrant data that are unrelated to 
its CCR. Therefore, under the trim methodology for potentially aberrant 
UCC that was included as part of the methodology for purposes of 
determining Factor 3 in the FY 2021 final rule (85 FR 58832), if the 
hospital's uncompensated care costs for FY 2018 are an extremely high 
ratio (greater than 50 percent) of its total operating costs, we will 
determine the ratio of uncompensated care costs to the hospital's total 
operating costs from another available cost report, and apply that 
ratio to the total operating expenses for the potentially aberrant 
fiscal year to determine an adjusted amount of uncompensated care 
costs. Specifically, if the hospital's FY 2018 cost report is 
determined to include potentially aberrant data, data from the FY 2019 
cost report will be used for the ratio calculation. Thus, the 
hospital's uncompensated care costs for FY 2018 will be trimmed by 
multiplying its FY 2018 total operating costs by the ratio of 
uncompensated care costs to total operating costs from the hospital's 
FY 2019 cost report to calculate an estimate of the hospital's 
uncompensated care costs for FY 2018 for purposes of determining Factor 
3 for FY 2022.
    As we noted in the proposed rule, we have audited the FY 2018 
Worksheet S-10 data for a number of hospitals. Because the UCC data for 
these hospitals have been subject to audit, we believe there is 
increased confidence that if high uncompensated care costs are reported 
by these audited hospitals, the information is accurate. Therefore, 
consistent with the policy that was adopted in the FY 2021 IPPS/LTCH 
PPS final rule, it is unnecessary to apply the trim methodology for 
these audited hospitals.
    In addition to the existing UCC trim methodology, we proposed to 
apply a new trim specific to certain hospitals that do not have audited 
FY 2018 Worksheet S-10 data. In the FY 2022 IPPS/LTCH PPS proposed rule 
(86 FR 25455), we noted that in rare cases, hospitals that are not 
currently projected to be DSH eligible and that do not have audited 
Worksheet S-10 data may have a potentially aberrant amount of insured 
patients' charity care costs (line 23 column 2). We proposed to use a 
threshold of three standard deviations from the mean ratio of insured 
patients' charity care costs to total uncompensated care costs (line 23 
column 2 divided by line 30) and a dollar threshold of $7 million, 
which is the median total uncompensated care cost reported on FY 2018 
cost reports for hospitals that are projected to be DSH eligible, 
excluding IHS and Tribal hospitals and Puerto Rico hospitals. 
Therefore, for FY 2022, we proposed that in the rare case that a 
hospital's insured patients' charity care costs are greater than $7 
million and the ratio of the hospital's cost of insured patient charity 
care (line 23 column 2) to total uncompensated care costs (line 30) is 
greater than 60 percent (rounded from 58 percent), we would exclude the 
hospital from the prospective Factor 3 calculation. This proposed trim 
would only impact hospitals that are not currently projected to be DSH 
eligible;

[[Page 45246]]

and therefore, are not part of the calculation of the denominator of 
Factor 3, which includes only uncompensated care costs for projected 
DSH eligible hospitals. If a hospital would be trimmed under both the 
existing UCC trim methodology and this proposed new trim, we proposed 
to apply this new trim in place of the existing UCC trim methodology. 
We explained that we believe the proposed new trim more appropriately 
addresses potentially aberrant insured patient charity care costs 
compared to the existing trim, because the existing trim is based 
solely on the ratio of total uncompensated care costs to total 
operating costs and does not consider the level of insured patients' 
charity care costs.
    In addition, we also proposed that, for the hospitals that would be 
subject to the proposed trim, if the hospital is ultimately determined 
to be DSH eligible at cost report settlement, then the MAC would 
calculate a Factor 3 after reviewing the uncompensated care information 
reported on Worksheet S-10 of the hospital's FY 2022 cost report. We 
believe if a hospital subject to this proposed trim is ultimately 
determined to be DSH eligible at cost report settlement, its 
uncompensated care payment should be calculated only after the 
hospital's reporting of insured charity care costs on its FY 2022 
Worksheet S-10 has been reviewed. We note that this approach is 
comparable to the policy for new hospitals for which we cannot 
calculate a prospective Factor 3 because they do not have Worksheet S-
10 data for the relevant fiscal year.
    Comment: A commenter supported the policy not to adjust 
uncompensated care costs from hospitals that have been audited and 
found in compliance by their MAC and encouraged CMS to work with MACs 
to distinguish between inaccurate and legitimate values. Another 
commenter supported the proposed policy of trimming potentially 
aberrant charity care cost data from hospitals that are currently not 
projected to be DSH eligible and do not have audited FY 2018 Worksheet 
S-10 data by excluding the hospital from the prospective Factor 3 
calculation.
    Response: We appreciate the commenters' support. We reiterate our 
continued efforts to work with the MACs to improve the accuracy of the 
uncompensated care costs reported on Worksheet S-10. After 
consideration of the comments received, we are finalizing the proposed 
policy for trimming potentially aberrant charity care costs for 
hospitals that are not projected to be DSH eligible and that do not 
have an audited Worksheet S-10 for FY 2018.
 Summary of Methodology
    In summary, for FY 2022, we will compute Factor 3 for each hospital 
using the following steps:
    Step 1: Select the provider's longest cost report from its Federal 
fiscal year (FFY) 2018 cost reports. (Alternatively, in the rare case 
when the provider has no FFY 2018 cost report because the cost report 
for the previous Federal fiscal year spanned the FFY 2018 time period, 
the previous Federal fiscal year cost report will be used in this 
step.)
    Step 2: Annualize the uncompensated care costs (UCC) from Worksheet 
S-10 Line 30, if the cost report is more than or less than 12 months. 
(If applicable, use the statewide average CCR (urban or rural) to 
calculate uncompensated care costs.)
    Step 3: Combine adjusted and/or annualized uncompensated care costs 
for hospitals that merged using the merger policy.
    Step 4: Calculate Factor 3 for IHS and Tribal hospitals and Puerto 
Rico hospitals that have a cost report for 2013 using the low-income 
insured days proxy based on FY 2013 cost report data and the most 
recent available SSI ratio (or, for Puerto Rico hospitals, 14 percent 
of the hospital's FY 2013 Medicaid days). The denominator is calculated 
using the low-income insured days proxy data from all DSH eligible 
hospitals.
    Step 5: Calculate Factor 3 for the remaining DSH eligible hospitals 
using annualized uncompensated care costs (Worksheet S-10 Line 30) 
based on FY 2018 cost report data (from Step 1, 2 or 3). New hospitals 
and the hospitals for which Factor 3 was calculated in Step 4 are 
excluded from this calculation.
    We proposed to amend the regulation at Sec.  412.106 by adding a 
new paragraph (g)(1)(iii)(C)(9) to reflect the methodology for 
computing Factor 3 for FY 2022 for IHS and Tribal hospitals and for 
Puerto Rico hospitals that have a 2013 cost report. We also proposed to 
make a conforming change to limit the reference to Puerto Rico 
hospitals in paragraph (g)(1)(iii)(C)(8) to those Puerto Rico hospitals 
that have a cost report for 2013.
    Comment: A couple of commenters recommended that CMS use the 
traditional payment reconciliation process to calculate final payments 
for uncompensated care costs pursuant to section 1886(r)(2) of the Act. 
These commenters did not object to CMS using prospective estimates, 
derived from the best data available, to calculate interim payments for 
uncompensated care costs. However, the commenters stated that interim 
payments should be subject to later reconciliation based on estimates 
derived from actual data from the applicable Federal fiscal year. The 
commenters also noted that not all FY 2018 Worksheet S-10 cost reports 
were audited and that the use of a blend of audited and unaudited data 
would be arbitrary and inconsistent with the statutory requirements. 
These same commenters also expressed the need for meaningful engagement 
on concerns raised in the rulemaking process and stated that the 
statutory preclusion of review leaves intact the agency's 
responsibilities, including the rulemaking requirements of the 
Administrative Procedure Act and the Medicare Act.
    Response: Consistent with the position that we have taken in 
rulemaking for previous years, we continue to believe that applying our 
best estimates of the three factors used in the calculation of 
uncompensated care payments to determine payments prospectively is most 
conducive to administrative efficiency, finality, and predictability in 
payments (78 FR 50628; 79 FR 50010; 80 FR 49518; 81 FR 56949; 82 FR 
38195; and 84 FR 42373). We continue to believe that, in affording the 
Secretary the discretion to estimate the three factors used to 
determine uncompensated care payments and by including a prohibition 
against administrative and judicial review of those estimates in 
section 1886(r)(3) of the Act, Congress recognized the importance of 
finality and predictability under a prospective payment system. As a 
result, we do not agree with the commenter's suggestion that we should 
establish a process for reconciling our estimates of uncompensated care 
payments, which would be contrary to the notion of prospectively. 
Furthermore, we note that this rulemaking has been conducted consistent 
with the requirements of the Administrative Procedure Act and Title 
XVIII of the Act. Under the Administrative Procedure Act, a proposed 
rule is required to include either the terms or substance of the 
proposed rule or a description of the subjects and issues involved. In 
this case, the FY 2022 IPPS/LTCH PPS proposed rule included a detailed 
discussion of the methodology for calculating Factor 3 for FY 2022 and 
the data that would be used. All proposed modifications to the 
methodology that was adopted in the FY 2021 IPPS/LTCH PPS final rule 
(85 FR 58833) for FY 2021 and subsequent fiscal years were discussed in 
detail in the proposed rule, and we solicited comments on the proposed 
methodology for FY 2022 (86

[[Page 45247]]

FR 25457). We made public the best data available at the time of the 
proposed rule, in order to allow hospitals to understand the 
anticipated impact of the proposed methodology and to submit comments, 
and we have considered those comments in determining our final policies 
for FY 2022.
    Comment: A commenter urged CMS not to use the HCRIS extract from 
March 2021 to calculate the final Factor 3 for FY 2022, mentioning that 
in the proposed rule, the agency indicated it would consider using a 
later HCRIS extract for the purposes of calculating the final Factor 3 
for the FY 2022 IPPS/LTCH PPS final rule. According to the commenter, 
it would be appropriate to use a later HCRIS extract considering the 
``last minute'' Worksheet S-10 audit adjustments made by the MACs, 
which were made beyond CMS' expected timeframe of using a December 2020 
HCRIS extract for the FY 2022 proposed rule and a March HCRIS extract 
for the FY 2022 final rule. The commenter asserted that due to these 
delayed adjustments, they did not have ample time to scrutinize the 
data. Additionally, the commenter provided their analysis regarding 
reports with changes to Worksheet S-10 data between the December 2020 
and March 2021 HCRIS extracts; specifically, the commenter stated that 
15 percent of hospitals eligible for uncompensated care payments 
received a negative adjustment, which the commenter believed warrants 
using more recent, accurate cost report extract.
    Response: We appreciate the commenter's concerns regarding the 
HCRIS extract proposed for use in the FY 2022 IPPS/LTCH final rule. We 
also agree with the commenter's recommendation on using a later HCRIS 
extract for calculating Factor 3 for FY 2022. We recognize that at the 
time of the March HCRIS extract, MACs were resolving inadvertent report 
upload discrepancies, which delayed the availability of the most up-to-
date reports with audited Worksheet S-10 data for some hospitals. For 
example, there was a delay in uploading some amended reports to 
incorporate Worksheet S-10 audit results. Therefore, we are finalizing 
the use of the June 30 HCRIS extract to calculate Factor 3 for this FY 
2022 IPPS/LTCH PPS final rule. We believe on balance this is the best 
available data for purposes of calculating Factor 3 for FY 2022.
    Additionally, in the rare situations where a MAC mishandled a 
report in the upload process (such as, by accepting an amended report, 
reopening a report, and/or adjusting uncompensated care cost data on a 
report, but the corrected uncompensated care cost data were 
inadvertently omitted from the June 30, 2021 extract of the HCRIS), we 
used the corrected version of the report after confirming the 
appropriate report version with the applicable MAC.
    We note that for purposes of Factor 3 calculations for future 
years, we still intend to use the most recent data available for the 
applicable rulemaking, which generally means the respective December 
HCRIS extract for purposes of future proposed rules. We expect that the 
December HCRIS extract would reflect the completed Worksheet S-10 audit 
results available in time for development of the proposed rule for the 
applicable fiscal year and that the respective HCRIS extract public use 
files, which are posted on the CMS website quarterly, would include the 
most recent audited cost report information for the applicable fiscal 
year, and be available for public scrutiny. Furthermore, as noted in 
the FY 2022 IPPS/LTCH PPS proposed rule, we intend to use the 
respective March HCRIS for future final rules, because we believe 
audited Worksheet S-10 data from FY 2019 reports will be available 
before the development of the FY 2023 proposed rule and final rule.
(c) Per Discharge Amount of Interim Uncompensated Care Payments
    Since FY 2014, we have made interim uncompensated care payments 
during the fiscal year on a per discharge basis. We have used a 3-year 
average of the number of discharges for a hospital to produce an 
estimate of the amount of the hospital's uncompensated care payment per 
discharge. Specifically, the hospital's total uncompensated care 
payment amount for the applicable fiscal year, is divided by the 
hospital's historical 3-year average of discharges computed using the 
most recent available data to determine the uncompensated care payment 
per discharge for that fiscal year.
    We proposed to modify this calculation for FY 2022 to be based on 
the average of FY 2018 and FY 2019 historical discharge data, rather 
than a 3-year average that includes data from FY 2018, FY 2019, and FY 
2020. We explained our belief that computing a 3-year average with the 
FY 2020 discharge data would underestimate discharges, due to the 
decrease in discharges during the pandemic. Under the proposed 
approach, the resulting 2-year average of discharges would be used to 
calculate the per discharge payment amount that will be used to make 
interim uncompensated care payments to each projected DSH eligible 
hospital during FY 2022. The interim uncompensated care payments made 
to a hospital during the fiscal year are reconciled following the end 
of the year to ensure that the final payment amount is consistent with 
the hospital's prospectively determined uncompensated care payment for 
the Federal fiscal year.
    In the FY 2021 IPPS/LTCH PPS final rule (85 FR 58833 and 58834), we 
finalized a voluntary process through which a hospital may submit a 
request to its MAC for a lower per discharge interim uncompensated care 
payment amount, including a reduction to zero, once before the 
beginning of the Federal fiscal year and/or once during the Federal 
fiscal year. In conjunction with this request, the hospital must 
provide supporting documentation demonstrating there would likely be a 
significant recoupment (for example, 10 percent or more of the 
hospital's total uncompensated care payment or at least $100,000) at 
cost report settlement if the per discharge amount is not lowered. For 
example, a hospital might submit documentation showing a large 
projected increase in discharges during the fiscal year to support 
reduction of its per discharge uncompensated care payment amount. As 
another example, a hospital might request that its per discharge 
uncompensated care payment amount be reduced to zero midyear if the 
hospital's interim uncompensated care payments during the year have 
already surpassed the total uncompensated care payment calculated for 
the hospital.
    Under the policy we finalized in the FY 2021 IPPS/LTCH PPS final 
rule, the hospital's MAC would evaluate these requests and the 
supporting documentation before the beginning of the Federal fiscal 
year and/or with midyear requests when the historical average number of 
discharges is lower than hospital's projected FY 2022 discharges. If 
following review of the request and the supporting documentation, the 
MAC agrees that there likely would be significant recoupment of the 
hospital's interim Medicare uncompensated care payments at cost report 
settlement, the only change that will be made is to lower the per 
discharge amount either to the amount requested by the hospital or 
another amount determined by the MAC to be appropriate to reduce the 
likelihood of a substantial recoupment at cost report settlement. If 
the MAC determines it would be appropriate to reduce the interim 
Medicare uncompensated care payment per discharge amount, that updated 
amount

[[Page 45248]]

will be used for purposes of the outlier payment calculation for the 
remainder of the Federal fiscal year. We refer readers to the Addendum 
to the proposed rule for a more detailed discussion of the steps for 
determining the operating and capital Federal payment rate and the 
outlier payment calculation. No change would be made to the total 
uncompensated care payment amount determined for the hospital on the 
basis of its Factor 3. In other words, any change to the per discharge 
uncompensated care payment amount will not change how the total 
uncompensated care payment amount will be reconciled at cost report 
settlement.
    Comment: Several commenters expressed support for the proposed 
policy of using the average of FY 2018 and FY 2019 discharge data, 
rather than a three-year average, which would also include FY 2020 
discharges. The commenters agreed that this change is appropriate in 
light of the COVID-19 PHE.
    Response: We thank commenters for their support. We are finalizing 
our proposal to modify the methodology used to estimate a hospital's 
average number of discharges to be based on FY 2018 and FY 2019 
historical discharge data, rather than a 3-year average that includes 
data from FY 2018, FY 2019, and FY 2020. We agree with commenters that 
including FY 2020 discharge data would underestimate discharges due to 
the effects of the COVID-19 PHE.
    Comment: A commenter recommended that CMS apply a growth factor to 
the claims average in the DSH Public Use File, in order to account for 
the growth in Medicare eligible population due to aging baby boomers. 
According to the commenter, the growth factor could be based on 
``calculating the growth in Part A fee-for-service average monthly 
enrollment'' from Congressional Budget Office (CBO) published 
estimates. Based on the commenter's calculations, the growth factor 
could be 1.08, which is the quotient from dividing 66 million Part A 
beneficiaries in 2022 by 61 million in 2019.
    The commenter also requested that the agency establish a limit on 
the estimated per claim amount due to exorbitant per-claim values of up 
to $117,599. The commenter stated that such amounts could produce 
significantly high coinsurance charges for Medicare Advantage (MA) 
beneficiaries if services are rendered out-of-network, which could 
exceed an MA beneficiary's out-of-pocket maximum. The commenter also 
mentioned that the approach of determining per-discharge uncompensated 
care payments based on Medicare patient volumes rather than 
uncompensated care volumes produces cash flow swings for hospitals with 
significant amounts of uncompensated care but low Medicare patient 
volumes, resulting in interim uncompensated care payments that do not 
reflect the actual costs incurred by the hospital.
    Regarding CMS' current policy under which hospitals may request 
that their MAC adjust per-claim payment amounts, the commenter stated 
that it seemed unlikely that hospitals would want to request a lower or 
zero per-claim uncompensated care payments because of inherent 
incentives to maximize their cash flow. To this end, the commenter 
recommends that CMS place a cap on the amount of the per-discharge 
interim uncompensated care payments ``within the range of $5,233-
$10,466, which represents a range of one to two standard deviations of 
the Estimated Per Claim Amounts for all qualifying hospitals.''
    Response: We thank the commenter for sharing their concerns and 
feedback. We continue to believe that allowing hospitals the 
opportunity of voluntarily requesting a decrease to the per-discharge 
amount of interim uncompensated care payments may facilitate greater 
payment predictability throughout the year and limit recoupment of 
overpayments as part of cost report settlement. Regarding the 
commenter's other suggestions, such as applying a growth factor as part 
of the per discharge calculation, we may consider this input for any 
potential modifications or refinements to our policy for determining 
interim uncompensated care payments in future rulemaking; however, at 
this time, we are not adopting any changes to the current policy.
(d) Process for Notifying CMS of Merger Updates and To Report Upload 
Issues
    As we have done for every proposed and final rule beginning in FY 
2014, in conjunction with this final rule, we will publish on the CMS 
website a table listing Factor 3 for all hospitals that we estimate 
will receive empirically justified Medicare DSH payments in FY 2022 
(that is, those hospitals that will receive interim uncompensated care 
payments during the fiscal year), and for the remaining subsection (d) 
hospitals and subsection (d) Puerto Rico hospitals that have the 
potential of receiving a Medicare DSH payment in the event that they 
receive an empirically justified Medicare DSH payment for the fiscal 
year as determined at cost report settlement. However, we note that a 
Factor 3 will not be published for the hospitals that are subject to 
the new trim we are adopting in this final rule, which is similar to 
the approach for new hospitals, which also do not have a Factor 3 
published. Although we noted in the FY2022 IPPS/LTCH PPS proposed rule, 
that if more recent data become available, then we would use such data 
in the final rule, at the time of development of this final rule, the 
FY 2019 SSI ratios were not available. Accordingly, for purposes of 
this final rule, we computed Factor 3 for IHS and Tribal hospitals and 
Puerto Rico hospitals using the most recent available data regarding 
SSI days from the FY 2018 SSI ratios.
    We also will publish a supplemental data file containing a list of 
the mergers that we are aware of and the computed uncompensated care 
payment for each merged hospital. In the DSH uncompensated care 
supplemental data file, we list new hospitals and the 8 hospitals that 
are subject to the new trim, with a N/A in the Factor 3 column. We note 
that two of the hospitals that were projected to be subject to the trim 
in the proposed rule, are no longer participating in the Medicare 
program.
    Hospitals had 60 days from the date of public display of the FY 
2022 IPPS/LTCH PPS proposed rule in the Federal Register to review the 
table and supplemental data file published on the CMS website in 
conjunction with the proposed rule and to notify CMS in writing of 
issues related to mergers and/or to report potential upload 
discrepancies due to MAC mishandling of the Worksheet S-10 data during 
the report submission process (for example, report not reflecting audit 
results due to MAC mishandling or most recent report differs from 
previously accepted amended report due to MAC mishandling). We stated 
that comments raising issues that are specific to the information 
included in the table and supplemental data file could be submitted to 
the CMS inbox at [email protected]. We indicated that we would 
address comments related to mergers and/or reporting upload 
discrepancies submitted to the CMS DSH inbox as appropriate in the 
table and the supplemental data file that we publish on the CMS website 
in conjunction with the publication of the FY 2022 IPPS/LTCH PPS final 
rule. All other comments submitted in response to our proposed policies 
for determining uncompensated care payments for FY 2022 must have been 
submitted in one of three ways found in the ADDRESSES section of the 
proposed rule before the

[[Page 45249]]

close of the comment period in order to be assured consideration. In 
addition, this CMS DSH inbox is not intended for Worksheet S-10 audit 
process related emails, which should be directed to the MACs.
    For FY 2022, we again proposed that hospitals would have 15 
business days from the date of public display of the FY 2022 IPPS/LTCH 
PPS final rule in the Federal Register to review and submit comments on 
the accuracy of the table and supplemental data file published in 
conjunction with the final rule. We stated that any changes to Factor 3 
arising from this review would be posted on the CMS website and would 
be effective beginning October 1, 2021. We also explained that we 
continue to believe that hospitals have sufficient opportunity during 
the comment period for the proposed rule to provide information about 
recent and/or pending mergers and/or to report upload discrepancies. 
Hospitals do not enter into mergers without advanced planning. A 
hospital can inform CMS during the comment period for the proposed rule 
regarding any merger activity not reflected in supplemental file 
published in conjunction with the proposed rule. As discussed in an 
earlier section of this final rule, we also stated that we expected to 
use data from the March 2021 HCRIS extract for the FY 2022 final rule, 
which contributed to our increased confidence that hospitals would be 
able to comment on mergers and report any upload discrepancies during 
the comment period for the proposed rule. However, we noted that we 
might consider using more recent data that may become available after 
March 2021, but before the final rule for the purpose of calculating 
the final Factor 3s for the FY 2022 IPPS/LTCH PPS final rule. In the 
event that there are any remaining merger updates and/or upload 
discrepancies after the final rule, the 15 business days from the date 
of public display of the FY 2022 IPPS/LTCH PPS final rule deadline 
should allow for the time necessary to prepare and make any corrections 
to Factor 3 calculations before the beginning of the Federal fiscal 
year.
    Comment: A commenter notified CMS that in reviewing the DSH 
Supplemental File for the FY 2022 proposed rule, their merger was not 
listed and only one hospital was included in the file. The commenter 
requested assurance that the merger would appear in the FY 2022 final 
rule. Another commenter reported what it deemed to be an erroneous 
adjustment made by a MAC to copayment amounts that had been written off 
and had been reported on the Worksheet S-10 as charity care. The 
commenter urged CMS to reverse the adjustment made by the MAC to their 
uncompensated care costs for purposes of calculating Factor 3 in FY 
2022.
    Response: We appreciate the commenters' diligence in checking that 
their own reports and data were properly processed in DSH Public Use 
File. We have accounted for the merger and the report discrepancies 
identified by commenters, as appropriate, in the development of the DSH 
supplemental data file published in conjunction with this FY 2022 IPPS/
LTCH PPS final rule, and we will continue to pay diligent attention to 
any data issues and work internally and with our contractors to resolve 
these issues in a timely manner. In regard to the merger notification, 
we thank the commenter for informing CMS of the merger activity not 
reflected in supplemental file published in conjunction with the 
proposed rule. Regarding the commenter reporting a disagreement related 
to Worksheet S-10 audit adjustments, as explained in the proposed rule, 
inquiries related to the audit process should be directed to the 
respective MAC.
    After consideration of the comments received, we are finalizing our 
proposal to afford hospitals 15 business days from the public display 
of this FY 2022 IPPS/LTCH PPS final rule to submit comments on the 
accuracy of the supplemental data file, including with respect to 
mergers and/or report upload discrepancies. We also note that the 
historical FY 2018 cost reports are publicly available on a quarterly 
basis on the CMS website for analysis and additional review of cost 
report data, separate from the supplemental data file published with 
this final rule.

F. Counting Days Associated With Section 1115 Demonstration Projects in 
the Medicaid Fraction

    We continue to review the large number of comments on the proposed 
revision to the regulation relating to the treatment of section 1115 
waiver days for purposes of the DSH adjustment. Due to the number and 
nature of the comments that we received on our proposal, we intend to 
address the public comments in a separate document. We refer 
individuals interested in reviewing the background information and the 
discussion regarding these policies to the FY 2022 IPPS/LTCH PPS 
proposed rule (86 FR 25457 through 25459).

G. Hospital Readmissions Reduction Program: Updates and Changes 
(Sec. Sec.  412.150 Through 412.154)

1. Statutory Basis for the Hospital Readmissions Reduction Program
    Section 1886(q) of the Act, as amended by section 15002 of the 21st 
Century Cures Act, establishes the Hospital Readmissions Reduction 
Program. Under the Hospital Readmissions Reduction Program, Medicare 
payments under the acute inpatient prospective payment system (IPPS) 
for discharges from an applicable hospital, as defined under section 
1886(d) of the Act, may be reduced to account for certain excess 
readmissions. Section 15002 of the 21st Century Cures Act requires the 
Secretary to compare hospitals with respect to the proportion of 
beneficiaries who are dually eligible for Medicare and full-benefit 
Medicaid (``dually eligible beneficiaries'') in determining the extent 
of excess readmissions. We refer readers to the FY 2016 IPPS/LTCH PPS 
final rule (80 FR 49530 through 49531) and the FY 2018 IPPS/LTCH PPS 
final rule (82 FR 38221 through 38240) for a detailed discussion of and 
additional information on the statutory history of the Hospital 
Readmissions Reduction Program.
2. Regulatory Background
    We refer readers to the following final rules for detailed 
discussions of the regulatory background and descriptions of the 
current policies for the Hospital Readmissions Reduction Program:
     FY 2012 IPPS/LTCH PPS final rule (76 FR 51660 through 
51676);
     FY 2013 IPPS/LTCH PPS final rule (77 FR 53374 through 
53401);
     FY 2014 IPPS/LTCH PPS final rule (78 FR 50649 through 
50676);
     FY 2015 IPPS/LTCH PPS final rule (79 FR 50024 through 
50048);
     FY 2016 IPPS/LTCH PPS final rule (80 FR 49530 through 
49543);
     FY 2017 IPPS/LTCH PPS final rule (81 FR 56973 through 
56979);
     FY 2018 IPPS/LTCH PPS final rule (82 FR 38221 through 
38240);
     FY 2019 IPPS/LTCH PPS final rule (83 FR 41431 through 
41439);
     FY 2020 IPPS/LTCH PPS final rule (84 FR 42380 through 
42390); and
     FY 2021 IPPS/LTCH PPS final rule (85 FR 58844 through 
58847).
    We have also codified certain requirements of the Hospital 
Readmissions Reduction Program at 42 CFR 412.152 through 412.154. In 
section V.G.15 of the preamble of this final rule, we are updating the 
regulatory text at 42 CFR 412.154(f)(4) to add the phrase ``or 
successor website'' in order to reflect the change in the CMS website 
name

[[Page 45250]]

from Hospital Compare to Care Compare.
3. Summary of the Policies for the Hospital Readmissions Reduction 
Program
    In the FY 2022 IPPS/LTCH PPS proposed rule (86 FR 25460 through 
25462), we proposed to adopt a cross-program measure suppression policy 
due to the impact of the COVID-19 public health emergency (PHE) on 
quality measurement and pay-for-performance programs including the 
Hospital Readmissions Reduction Program. We also proposed to suppress 
the Hospital 30-Day, All-Cause, Risk-Standardized Readmission Rate 
(RSRR) following Pneumonia Hospitalization measure (NQF #0506) and we 
provided information on technical specification updates for the 
remaining five condition/procedure-specific readmission measures to 
exclude COVID-19 diagnosed patients from the measure denominators 
beginning in fiscal year (FY) 2023 (86 FR 25462 through 25464). 
Additionally, we proposed to use the MedPAR data to determine aggregate 
payments that aligns with the applicable period for FY 2022 (86 FR 
25464 through 25465). We also proposed the automatic adoption of the 
use of MedPAR data corresponding to the applicable period beginning 
with the FY 2023 program year and all subsequent program years, unless 
otherwise specified by the Secretary (86 FR 25465). In addition, we 
clarified our Extraordinary Circumstances (ECE) Policy (86 FR 25466 
through 25468).
    In this final rule, we are finalizing our proposals as proposed. We 
discuss these finalized proposals in greater detail in this final rule.
    Finally, we requested public comment on possible future 
stratification of results by race and ethnicity for our condition/
procedure-specific readmission measures and by expansion of 
standardized data collection to additional social factors, such as 
language preference and disability status (86 FR 25468 through 25469). 
We also sought comment in that section on mechanisms of incorporating 
other demographic characteristics into analysis that address and 
advance health equity, such as the potential to include administrative 
and self-reported data to measure co-occurring disability status.
4. Current Measures
    The Hospital Readmissions Reduction Program currently includes six 
applicable conditions/procedures: Acute myocardial infarction (AMI); 
heart failure (HF); pneumonia; elective primary total hip arthroplasty/
total knee arthroplasty (THA/TKA); chronic obstructive pulmonary 
disease (COPD); and coronary artery bypass graft (CABG) surgery.
    We continue to believe the measures we have adopted adequately meet 
the goals of the Hospital Readmissions Reduction Program. However, due 
to the potentially substantial relationship between pneumonia and 
COVID-19, we proposed to suppress temporarily the inclusion of the 
Hospital 30-Day, All-Cause, Risk-Standardized Readmission Rate (RSRR) 
following Pneumonia Hospitalization measure (NQF #0506) in the Hospital 
Readmissions Reduction Program measure set for the FY 2023 applicable 
period in the FY 2022 IPPS/LTCH PPS proposed rule (86 FR 25462 through 
25464). We also provided information on technical specification updates 
for the remaining five condition/procedure-specific readmission 
measures to exclude COVID-19 diagnosed patients from the measure 
denominators, including the Hospital 30-Day All-Cause Risk-Standardized 
Readmission Rate (RSRR) Following Acute Myocardial Infarction (AMI) 
Hospitalization (NQF #0505), the Hospital 30-Day, All-Cause, Unplanned, 
Risk-Standardized Readmission Rate (RSRR) Following Coronary Artery 
Bypass Graft (CABG) Surgery (NQF #2515), the Hospital 30-Day, All-
Cause, Risk-Standardized Readmission Rate (RSRR) Following Chronic 
Obstructive Pulmonary Disease (COPD) Hospitalization (NQF #1891), the 
Hospital 30-Day, All-Cause, Risk-Standardized Readmission Rate (RSRR) 
Following Heart Failure Hospitalization (NQF #0330), and the Hospital-
Level 30-Day, All-Cause Risk-Standardized Readmission Rate (RSRR) 
Following Elective Primary Total Hip Arthroplasty (THA) and/or Total 
Knee Arthroplasty (TKA) (NQF #1551) beginning in FY 2023 (86 FR 25464).
    We refer readers to the FY 2019 IPPS/LTCH PPS final rule (83 FR 
41431 through 41439) for more information about how the Hospital 
Readmissions Reduction Program supports CMS' goal of bringing quality 
measurement, transparency, and improvement together with value-based 
purchasing to the hospital inpatient care setting through the 
Meaningful Measures Framework. We refer readers to section IX.A of the 
proposed rule (86 FR 25549 through 25554), where we requested 
information on potential actions and priority areas that would enable 
the continued transformation of our quality measurement enterprise 
toward greater digital capture of data and use of the FHIR standard (as 
described in that section). We also refer readers to section IX.B. of 
the proposed rule (86 FR 25554 through 25561), where we requested 
information on potentially expanding the scope of our methodology to 
adjust outcomes measurement to recognize disparities in care, to 
include statistically estimated race and ethnicity information.
5. Flexibility for Changes That Affect Quality Measures During a 
Performance Period in the Hospital Readmissions Reduction Program
    In previous rules, we have identified the need for flexibility in 
our quality programs to account for the impact of changing conditions 
that are beyond participating facilities' or practitioners' control. We 
identified this need because we would like to ensure that participants 
in our programs are not affected negatively when their quality 
performance suffers not due to the care provided, but due to external 
factors.
    A significant example of the type of external factor that may 
affect quality measurement is the COVID-19 public health emergency 
(PHE), which has had and continues to have significant and ongoing 
effects on the provision of medical care in the country and around the 
world. The COVID-19 PHE impedes effective quality measurement in 
several ways. Changes to clinical practices to accommodate safety 
protocols for medical personnel and patients, as well as unpredicted 
changes in the number of stays and facility-level case mixes, have 
affected the data used in quality measurement and the resulting quality 
scores. Measures used in the Hospital Readmissions Reduction Program 
need to be evaluated to determine whether their specifications need to 
be updated to account for new clinical guidelines, diagnoses or 
procedure codes, and medications that we have observed during the PHEs. 
Additionally, COVID-19 prevalence is not identical across the country, 
meaning that the medical provider community has been affected 
differently at different times throughout the calendar year. Under 
those circumstances, we remain significantly concerned that the 
Hospital Readmissions Reduction Program's quality measurement scores 
are distorted, which would result in skewed payment incentives and 
inequitable payments, particularly for hospitals that have treated more 
COVID-19 patients than others.
    It is not our intention to penalize hospitals for performance on 
measures that are affected significantly by global events like the 
COVID-19 PHE. As previously discussed, the COVID-19 PHE has had, and 
continues to have,

[[Page 45251]]

significant and enduring effects on health care systems around the 
world, and affects care decisions, including readmissions to the 
hospital as measured by the Hospital Readmissions Reduction Program. As 
a result of the PHE, hospitals could provide care to their patients 
that meets the underlying clinical standard but results in worse 
measured performance, and by extension, reduced payments in the 
Hospital Readmissions Reduction Program. We are concerned that regional 
and temporal differences in COVID-19 prevalence during the FY 2022 and 
FY 2023 Hospital Readmissions Reduction Program applicable periods, 
which includes data collected during the PHE, have directly affected 
hospitals' readmissions measure performance for the FY 2022 and FY 2023 
program years. Although regional and temporal differences in COVID-19 
prevalence rates would not necessarily represent differences in the 
quality of care furnished by hospitals, they would directly affect the 
payment adjustments that these hospitals would receive and could result 
in an unfair and inequitable distribution in the assessment of 
penalties for excess readmissions. These inequities could be especially 
pronounced for hospitals that have treated a large number of COVID-19 
patients.
    Therefore, we proposed to adopt a policy for the duration of the 
PHE for COVID-19 that would enable us to suppress the use of quality 
measures via adjustment to the Hospital Readmissions Reduction 
Program's scoring methodology if we determined that circumstances 
caused by the COVID-19 PHE affected those measures and the associated 
``excess readmissions'' calculations significantly (86 FR 25460 through 
25462). Under the proposed policy, if we determined that the 
suppression of a Hospital Readmissions Reduction Program measure was 
warranted for a Hospital Readmissions Reduction Program applicable 
period, we would propose to calculate the measure's rates for that 
program year but then suppress the use of those rates to make changes 
to hospitals' Medicare payments. In the Hospital Readmissions Reduction 
Program, this policy would have the effect of temporarily weighting the 
affected measure at zero percent in the program's scoring methodology 
until adjustments were made, the affected portion of the performance 
period for the measure was made no longer applicable to program 
scoring, or the measure was removed entirely through rulemaking. We 
would still provide feedback reports to hospitals as part of program 
activities, including to inform their quality improvement activities, 
and to ensure that they were made aware of the changes in performance 
rates that we observed. We would also publicly report suppressed 
measures' data with appropriate caveats noting the limitations of the 
data due to the PHE for COVID-19.
    In developing the proposed policy, we considered what circumstances 
caused by the PHE for COVID-19 would affect a quality measure 
significantly enough to warrant its suppression in a value-based 
purchasing program. We stated our belief that significant deviation in 
measured performance that can be reasonably attributed to the PHE is a 
significant indicator of changes in clinical conditions that could 
affect quality measurement. Similarly, we stated our belief that a 
measure may be focused on a clinical topic or subject that is proximal 
to the disease, pathogen, or other health impacts of the PHE. As has 
been the case during the COVID-19 PHE, we stated our belief that rapid 
or unprecedented changes in clinical guidelines and care delivery, 
potentially including appropriate treatments, drugs, or other protocols 
could affect quality measurement significantly and should not be 
attributed to the participating facility positively or negatively. We 
also noted that scientific understanding of a particular disease or 
pathogen may evolve quickly during an emergency, especially in cases of 
new diseases or conditions. Finally, we stated our belief that, as 
evidenced during the COVID-19 PHE, national or regional shortages or 
changes in health care personnel, medical supplies, equipment, 
diagnostic tools, and patient case volumes or facility-level case mix 
could result in significant distortions to quality measurement.
    Based on these considerations, we developed a number of Measure 
Suppression Factors that we believed should guide our determination of 
whether to suppress a Hospital Readmissions Reduction Program measure 
for one or more program years that overlap with the PHE for COVID-19. 
We proposed to adopt these Measure Suppression Factors for use in the 
Hospital Readmissions Reduction Program, and for consistency, the 
following value-based purchasing programs: Hospital VBP Program, HAC 
Reduction Program, Skilled Nursing Facility Value-Based Purchasing 
Program, and End-Stage Renal Disease Quality Incentive Program. We 
stated our belief that these Measure Suppression Factors would help us 
evaluate the Hospital Readmissions Reduction Program's measures and 
that their adoption in the other value-based purchasing programs, as 
previously noted, would help ensure consistency in our measure 
evaluations across programs. We proposed Measure Suppression Factors as 
follows:
     Significant deviation in national performance on the 
measure during the PHE for COVID-19, which could be significantly 
better or significantly worse compared to historical performance during 
the immediately preceding program years.
     Clinical proximity of the measure's focus to the relevant 
disease, pathogen, or health impacts of the PHE for COVID-19.
     Rapid or unprecedented changes in--
    ++ Clinical guidelines, care delivery or practice, treatments, 
drugs, or related protocols, or equipment or diagnostic tools or 
materials; or
    ++ The generally accepted scientific understanding of the nature or 
biological pathway of the disease or pathogen, particularly for a novel 
disease or pathogen of unknown origin.
     Significant national shortages or rapid or unprecedented 
changes in--
    ++ Healthcare personnel;
    ++ Medical supplies, equipment, or diagnostic tools or materials; 
or
    ++ Patient case volumes or facility-level case mix.
    We also considered alternatives to the proposed policy that could 
also fulfill our objective to not hold hospitals accountable for 
measure results under the Program that are distorted due to the PHE for 
COVID-19. As previously noted, the country continues to grapple with 
the effects of the COVID-19 PHE, and in March 2020, CMS issued a 
nationwide, blanket ECE for all hospitals and other facilities 
participating in our quality reporting and value-based purchasing 
programs in response to the COVID-19 PHE. This blanket ECE waived all 
data reporting requirements for Q1 and Q2 2020 data, including waiving 
the use of claims data and data collected through the CDC's web-based 
surveillance system for this data period, and quality data collection 
resumed on July 1, 2020. We considered extending this blanket ECE for 
Q3 and Q4 2020. This alternative would protect providers and suppliers 
from having their quality data used for quality scoring purposes in the 
event that such data had been affected significantly by the COVID-19 
PHE. However, this option would make providers' quality data collection 
and reporting to CMS no longer mandatory and would leave no 
comprehensive data available for us to

[[Page 45252]]

provide confidential performance feedback to providers nor for 
monitoring and to inform decision-making for potential future 
programmatic changes, particularly if the PHE were extended.
    As an alternative to the proposed quality measure suppression 
policy, we also considered not making any further changes to the 
program and implementing it as previously specified. However, this 
alternative would have meant assessing hospitals using quality measure 
data that had been significantly affected by the PHE for COVID-19. 
Additionally, given the geographic disparities in the COVID-19 PHE's 
effects, implementation of the program as previously finalized would 
place hospitals in regions that were more heavily affected by the PHE 
in Q3 and Q4 of 2020 at a disadvantage compared to hospitals in regions 
that were more heavily affected during the first two quarters of CY 
2020.
    We viewed this measure suppression proposal as a necessity to 
ensure that the Hospital Readmissions Reduction Program did not reward 
or penalize hospitals based on factors that the program's measures were 
not designed to accommodate. We intended for the proposed policy to 
provide short-term relief to hospitals if we determined that one or 
more of the Measure Suppression Factors warranted the suppression of 
one or more of the program's measures.
    We invited public comments on this proposal for the adoption of a 
measure suppression policy for the Hospital Readmissions Reduction 
Program for the duration of the PHE for COVID-19, and also on the 
proposed Measure Suppression Factors that we developed for purposes of 
the proposed policy.
    We also invited comment on whether we should consider adopting a 
measure suppression policy in the situation of a future national PHE, 
and if so, whether under such a policy, we should have the flexibility 
to suppress certain measures without specifically proposing to do so in 
rulemaking.
    We also requested comment on whether we should in future years 
consider adopting any form of regional adjustment for the proposed 
measure suppression policy that could take into account any disparate 
effects of circumstances affecting hospitals around the country that 
would prompt us to suppress a measure. For example, COVID-19 affected 
different regions of the country at different rates depending on 
factors like time of year, geographic density, State and local 
policies, and health care system capacity. We also requested 
commenters' feedback on whether we should consider a suppression policy 
with more granular effects based on our assessment of the geographic 
effects of the circumstances, rather than suppress a measure completely 
by assigning it a 0 percent weight during any future PHEs. We asked 
commenters to discuss how region-based measure suppression could be 
accounted for within the program's scoring methodology.
    We invited public comment on this proposal. The comments we 
received and our responses are set forth in this section of this rule.
    Comment: Many commenters expressed support for our proposed measure 
suppression policy, agreeing with our stated goal of ensuring that 
hospitals are not rewarded or penalized for their quality performance 
based on non-representative data. Some commenters recommended that we 
ensure that the suppression policy does not unintentionally penalize 
hospitals.
    Response: We thank the commenters for their support. We acknowledge 
commenters' concern that the suppression policy should not 
unintentionally penalize hospitals. As discussed in the proposed rule 
and in section V.G.6 of this final rule, we proposed to suppress the 
CMS 30-Day Pneumonia Readmission Measure (NQF #0506) in the Hospital 
Readmissions Reduction Program due to the impacts of the COVID-19 PHE 
on this measure for purposes of scoring and payment adjustments because 
of our concern in the ability to make fair, national comparisons of 
hospitals across the country.
    Comment: Several commenters expressed support for our proposal to 
provide confidential performance feedback to hospitals on suppressed 
measures.
    Response: We thank the commenters for their support. We will 
provide confidential feedback reports to hospitals for the pneumonia 
readmission measure using the current specifications. In these 
confidential reports, hospitals will be able to see which of their 
patients were readmitted to the hospital, and which of their patients 
were excluded from the measure denominator to inform hospital quality 
improvement initiatives.
    Comment: Some commenters expressed concerns about our proposed 
suppression policy. Some commenters suggested that we should limit this 
policy to the current PHE given the unique circumstances involved in 
the COVID-19 pandemic. A few commenters expressed concerns about CMS 
being empowered to implement scoring adjustments and payment changes 
outside of rulemaking, and worried that comparisons between suppressed 
and unsuppressed scores would be unfair.
    Response: We thank the commenters for their feedback. We do not 
intend for this policy to implement subregulatory scoring adjustments 
or payment changes beyond the COVID-19 PHE. Any scoring adjustments or 
payment changes that might address a different, future fiscal year of 
the program due to the COVID-19 PHE or another type of public health 
emergency would be proposed through rulemaking. We view the COVID-19 
PHE as exceptional and, as with the measure suppression proposal, we 
will continue to maintain our quality programs via rulemaking. We 
acknowledge the commenters' concerns about potentially unfair 
comparisons between suppressed and unsuppressed performance 
information, and will consider for future rulemaking any such issues we 
identify.
    Comment: Several commenters stated that we should not publicly 
report suppressed data, suggesting that data unfit to determine 
payments should not be publicly reported, while others suggested that 
we should note clearly that any publicly-reported data has been 
affected by the COVID-19 PHE.
    Response: We understand the commenters concern about publicly 
reporting measure data from during the PHE due to COVID-19. However, as 
noted previously in section V.G.5. of the preamble of this final rule, 
we will make clear in the public presentation of the data that the 
measure has been suppressed for purposes of scoring and payment 
adjustments because of the effects of the COVID-19 PHE. Displaying this 
information will promote transparency on the impacts of the PHE due to 
COVID-19, and we will appropriately caveat the data in order to 
mitigate public confusion.
    Comment: Several commenters recommended that we carefully study the 
effects of the measure suppression policy and the measure suppression 
factors to inform any suppression policies for future PHEs. Several 
commenters recommended that we work with stakeholders before adopting 
additional measure suppression policies or any subregulatory policy 
changes on this topic in the future, including any potential changes to 
the Measure Suppression Factors, and requested that we explain the 
effects of any changes to the Suppression Factors in detail. A 
commenter suggested that we continue monitoring the effects of COVID-19 
on 2021 quality performance and consider updating measure 
specifications to exclude COVID-19 patients or change our risk 
adjustment models. Other commenters suggested that we closely

[[Page 45253]]

monitor the shorter performance periods, as well as the effects of the 
policy on future benchmarking, and that we assess the indirect effects 
that the COVID-19 PHE has had on all aspects of medical care delivery.
    Response: We share commenters' concerns about the potential long-
term effects of the measure suppression policy, including the measure 
suppression factors. We intend to work carefully with stakeholders 
before adopting any additional policies or policy changes on this topic 
in the future. We agree with commenters that we should monitor the 
COVID-19 PHE's ongoing effects carefully and we will work with measure 
developers to refine measure specifications as circumstances warrant. 
We will also assess performance periods, benchmarks, and other effects 
of the COVID-19 PHE carefully, and we will monitor the policy's effects 
as we implement it. We welcome stakeholders' continuing feedback as we 
continue responding to the PHE.
    Comment: Some commenters expressed support for the proposed Measure 
Suppression Factors, while others suggested that we include more 
flexibility in the Suppression Factors, particularly to account for 
future PHEs, and that we consult with stakeholders when applying these 
factors in the future. A commenter recommended that we include more 
flexible language in our suppression factors to account for our 
evolving understanding of COVID-19.
    Response: We thank the commenters for this feedback. While we 
appreciate the commenter's suggestion that we incorporate more 
flexibility into the current Measure Suppression Factors, we believe 
the specificity with which we proposed them was necessary to provide 
hospitals, patients/consumers, and other stakeholders with insight into 
the decision-making process that we employed in response to the COVID-
19 PHE. However, we will also engage with stakeholders when developing 
and implementing these Suppression Factors for future PHEs.
    Comment: Some commenters recommended that we refine our proposed 
Measure Suppression Factors. Some commenters suggested that we define 
them more precisely to be fully transparent with the factors' terms and 
effects, arguing that we have not defined what we consider to be 
``significant'' deviation in national performance on a measure during a 
PHE. A commenter also argued that the Suppression Factors should be 
focused on effects on Medicare beneficiaries, not on providers or 
circumstances that may be within the control of providers. A commenter 
suggested that we consider suppressing measures for individual 
hospitals where performance may have deviated significantly from past 
performance, while another commenter recommended that we ensure that 
the Suppression Factors do not assess provider organizations' quality 
per se, but rather, the PHE at issue.
    Response: We thank the commenters for this feedback. We believe 
that some level of discretion is necessary in the face of evolving 
circumstances like those that have confronted us in the COVID-19 PHE, 
which is why we have designed our Measure Suppression Factors to have a 
certain degree of flexibility as to the factors' terms and effects. In 
deciding which measures to suppress, and as discussed further in 
section V.G.6. of this final rule, we examined each measure and 
determined that the evidence showed deviation in the individual measure 
performance data associated with the COVID-19 PHE. We believe providing 
the evidence for the measure suppressions included in this final rule 
is transparent and provides sufficient explanation for our rationales. 
We note further that we designed several of the measure suppression 
factors to account for circumstances that could affect the health and 
safety of patients and healthcare personnel, and we believe that 
situations like personal protective equipment (PPE) shortages affect 
the care provided to Medicare beneficiaries. We recommend that any 
individual hospitals that believe that they have faced extraordinary 
circumstances that affect their quality performance that have not been 
addressed by the suppression policy, consider seeking an Extraordinary 
Circumstances Exception.\763\
---------------------------------------------------------------------------

    \763\ For more information regarding Extraordinary Circumstances 
Exceptions requests under the Hospital Readmissions Reduction 
Program, please see: https://qualitynet.cms.gov/impatient/hrrp/participation#tab2.
---------------------------------------------------------------------------

    Comment: Some commenters supported regional adjustments to the 
measure suppression policy, suggesting that we should account for 
disparate effects of circumstances like the COVID-19 pandemic around 
the country. Commenters requested that we seek stakeholders' feedback 
before adopting more granular suppression policies in the future. A 
commenter cautioned against regional adjustments, suggesting that such 
adjustments would not account for differences in PHE prevalence at 
safety-net hospitals that take on leading roles during PHEs.
    Response: We thank the commenters for their feedback and will 
consider it for future rulemaking. We share the commenter's concern 
that adjustments to account for regional differences in a PHE's effects 
may not fully capture those differences.
    After consideration of the public comments we received, we are 
finalizing our proposal to adopt a measure suppression policy and 
proposed Measure Suppression Factors for the duration of the COVID-19 
PHE.
6. Provisions That Address the Impact of COVID-19 on Current Hospital 
Readmissions Reduction Program Measures
a. Background
    On March 11, 2020, the WHO publicly declared COVID-19 a pandemic. 
On March 13, 2020, the President declared the COVID-19 pandemic a 
national emergency. On April 21, 2020, July 23, 2020, October 2, 2020, 
January 7, 2021, April 21, 2021, and July 19, 2021, the Secretary 
renewed the January 31, 2020 determination that a PHE for COVID-19 
exists and has existed since January 27, 2020. The Secretary may renew 
the PHE every 90 days until such time as the Secretary determines that 
a PHE no longer exists.
    In response to the PHE for COVID-19, we have conducted analyses on 
the six current Hospital Readmissions Reduction Program measures to 
determine whether and how COVID-19 may have impacted the validity of 
these condition/procedure-specific readmission measures. For the 
reasons discussed in this section of this rule, we have concluded that 
COVID-19 has significantly impacted the validity of the Hospital 30-
Day, All-Cause, Risk-Standardized Readmission Rate (RSRR) following 
Pneumonia Hospitalization measure (NQF #0506) (hereafter referred to as 
the CMS 30-Day Pneumonia Readmission Measure (NQF #0506)), such that we 
cannot fairly assess this measure. The FY 2022 CMS 30-Day Pneumonia 
Readmission Measure (NQF #506) applicable period is July 1, 2017 
through June 30, 2020. However, in the September 2020 IFC, we noted 
that we would except the use of any first or second quarter CY 2020 
claims data from our calculation of performance for the applicable 
fiscal years (85 FR 54833). With this exception, the FY 2022 applicable 
period for this measure would only be affected by a shortened 
performance period (July 1, 2017 through December 1, 2019) that does 
not use data from the COVID-19 PHE. Therefore, we have determined that 
it is not necessary to suppress this measure for the FY 2022 program 
year. However,

[[Page 45254]]

given the ongoing status of the PHE and the impact of COVID-19 on this 
measure data, we proposed to temporarily suppress this measure for the 
FY 2023 program year (86 FR 25462 through 25464).
    We stated in the FY 2022 PPS/LTCH PPS proposed rule that although 
COVID-19 has also impacted the five remaining condition/procedure-
specific measures, we have concluded that this impact is less severe 
overall and can be further mitigated by updating the measure 
specifications to exclude Medicare beneficiaries with a secondary 
diagnosis of COVID-19 (86 FR 25462). Therefore, we did not propose to 
suppress the five remaining condition/procedure-specific measures for 
the FY 2023 program year \764\ but are updating their specifications 
instead (86 FR 25464). The measures are as follows:
---------------------------------------------------------------------------

    \764\ In the FY 2022 IPPS/LTCH PPS proposed rule (86 FR 25462), 
we indicated that we were updating the five remaining condition/
procedure-specific measures for the FY 2022 program year. However, 
as noted in our discussion above, in the September 2020 IFC we noted 
that we would except the use of any first or second quarter CY 2020 
claims data from our calculation of performance for the applicable 
fiscal years (85 FR 54833). With this exception, the FY 2022 
applicable period for these condition/procedure-specific readmission 
measures would only be affected by a shortened performance period 
(July 1, 2017 through December 1, 2019) that does not use data from 
the COVID-19 PHE. Therefore, we are updating in this final rule that 
we are modifying these condition/procedure-specific readmission 
measure specifications for the FY 2023 program year.
---------------------------------------------------------------------------

     Hospital 30-Day All-Cause Risk-Standardized Readmission 
Rate (RSRR) Following Acute Myocardial Infarction (AMI) Hospitalization 
(NQF #0505);
     Hospital 30-Day, All-Cause, Unplanned, Risk-Standardized 
Readmission Rate (RSRR) Following Coronary Artery Bypass Graft (CABG) 
Surgery (NQF #2515);
     Hospital 30-Day, All-Cause, Risk-Standardized Readmission 
Rate (RSRR) Following Chronic Obstructive Pulmonary Disease (COPD) 
Hospitalization (NQF #1891);
     Hospital 30-Day, All-Cause, Risk-Standardized Readmission 
Rate (RSRR) Following Heart Failure Hospitalization (NQF #0330); and
     Hospital-Level 30-Day, All-Cause Risk-Standardized 
Readmission Rate (RSRR) Following Elective Primary Total Hip 
Arthroplasty (THA) and/or Total Knee Arthroplasty (TKA) (NQF #1551).
    As discussed more fully later in this section of this final rule, 
we are modifying these five condition/procedure-specific measures to 
exclude COVID-19 patients from the measures as technical updates to the 
measure specifications.
b. Suppression of the CMS 30-Day Pneumonia Readmission Measure (NQF 
#0506) for the FY 2023 Program Year
    We refer readers to the FY 2012 IPPS/LTCH PPS final rule (76 FR 
51664 through 51666), the FY 2014 IPPS/LTCH PPS final rule (78 FR 50649 
through 50676), the FY 2015 IPPS/LTCH PPS final rule (79 FR 50024 
through 50048), and the FY 2016 IPPS/LTCH PPS final rule (80 FR 24490 
through 24492) for information on our policies that relate to 
refinement of the readmissions measures and related methodology for the 
current applicable conditions/procedures.
    In the FY 2022 IPPS/LTCH PPS proposed rule (86 FR 25462 through 
25464), we proposed to suppress temporarily the CMS 30-Day Pneumonia 
Readmission Measure (NQF #0506) for the FY 2023 program year under 
proposed Measure Suppression Factor 2, clinical proximity of the 
measure's focus to the relevant disease or pathogen, particularly for a 
novel disease or pathogen of unknown origin, due to the COVID-19 PHE. 
COVID-19 is caused by the SAR-CoV-2 virus, which begins when 
respiratory droplets containing the virus enter an individual's upper 
respiratory tract.\765\ Pneumonia has been identified as a typical 
characteristic of individuals infected with COVID-19,\766\ and our 
analysis based on data from CY 2020 and early CY 2021 shows that a 
substantial portion of the CMS 30-Day Pneumonia Readmission Measure 
(NQF #0506) cohort includes admissions with a COVID-19 diagnosis. In 
addition, almost all of the patient admissions with a COVID-19 
diagnosis have a principal diagnosis of sepsis; observed mortality 
rates for these admissions are extremely high and are substantially 
higher than admissions without a COVID-19 diagnosis. We are concerned 
that these higher mortality rates may also potentially distort 
readmissions data for the CMS 30-Day Pneumonia Readmission Measure (NQF 
#0506) cohort. Based on the currently available data for this measure, 
there is a substantial proportion of Medicare beneficiaries with a 
secondary diagnosis of COVID-19 in the measure cohort during CY 2020 
and early CY 2021.
---------------------------------------------------------------------------

    \765\ CDC. ``How COVID-19 Spreads''. Available at: https://www.cdc.gov/coronavirus/2019-ncov/prevent-getting-sick/how-covid-spreads.html.
    \766\ CDC. ``Interim Clinical Guidance for Management of 
Patients with Confirmed Coronavirus Disease (COVID-19)''. Updated 
February 16, 2021. Available at: https://www.cdc.gov/coronavirus/2019-ncov/hcp/clinical-guidance-management-patients.html.
---------------------------------------------------------------------------

    In accordance with the previously discussed measure suppression 
policy, we would weight the CMS 30-Day Pneumonia Readmission Measure 
(NQF #0506) at zero percent in the Hospital Readmissions Reduction 
Program payment methodology such that claims data for this measure 
would not be used to assess that hospital's performance. Additionally, 
we would continue to monitor the claims that form the basis for this 
measure's calculations to evaluate the effect of the circumstances on 
quality measurement and to determine the appropriate policies in the 
future. We would also continue to provide feedback reports to hospitals 
as part of program activities to ensure that they are made aware of the 
changes in performance rates that are observed and to inform quality 
improvement activities.
    As previously discussed, the CMS 30-Day Pneumonia Readmission 
Measure (NQF #0506) FY 2022 applicable period is July 1, 2017 through 
June 30, 2020. However, in the September 2020 IFC, we noted that we 
would not use any first or second quarter CY 2020 claims data to assess 
performance for the applicable fiscal years (85 FR 54833). With this 
exception, the FY 2022 applicable period for this measure would only be 
affected by a shortened performance period (July 1, 2017 through 
December 1, 2019) that does not use data impacted by the COVID-19 PHE. 
Therefore, we have decided that it is not necessary to suppress this 
measure for the FY 2022 program year. However, given the ongoing status 
of the PHE and the impact of COVID-19 on this measure's data, we 
proposed to temporarily suppress this measure for the FY 2023 program 
year.
    Our analysis of the CMS 30-Day Pneumonia Readmission Measure (NQF 
#0506) claims data showed that a higher proportion of patients had a 
secondary diagnosis of COVID-19 than other readmission measures and 
that these patients have a higher risk of mortality than the remainder 
of the admissions in the pneumonia measure cohort.

[[Page 45255]]

[GRAPHIC] [TIFF OMITTED] TR13AU21.257

    Data from September 2020 showed that although admission volumes for 
this cohort were substantially lower compared to admission volumes in 
September 2019, the observed readmission rates were statistically 
significantly higher compared to the observed readmission rates for 
this cohort during the same period in 2019.
[GRAPHIC] [TIFF OMITTED] TR13AU21.258

    Our analyses performed with available data demonstrated that COVID-
19 patients captured in the pneumonia readmission measure cohort likely 
represent a distinct, severely ill group of patients for whom it may be 
difficult to adequately ascertain appropriate risk adjustment. We want 
to ensure that the measure reflects care provided by the hospital to 
Medicare beneficiaries admitted with pneumonia and we are concerned 
that excluding a significant proportion of all eligible patients may 
not accurately reflect the care provided, particularly given the 
unequal distribution of COVID-19 patients across hospitals over time. 
Suppressing this measure for the FY 2023 program year would address 
this concern.
    As part of our analysis, we also evaluated the impact of 
suppressing the CMS 30-Day Pneumonia Readmission Measure (NQF #0506) on 
hospital eligibility, program calculations, and payment for the FY 2023 
program year. We noted that we used data from the most recently 
completed performance period, FY 2021, to simulate removal of the CMS 
30-Day Pneumonia Readmission Measure (NQF #0506) as compared to the 
baseline data.\767\ We found that the suppression of the CMS 30-Day 
Pneumonia Readmission Measure (NQF #0506) resulted in about a 1 percent 
decrease in eligibility for hospitals with at least 25 eligible 
discharges for any of the readmission measures under the Hospital 
Readmissions Reduction Program; the number of hospitals receiving a 
payment reduction was reduced by 5.17 percent; the penalty as a share 
of payments, or the weighted average payment reduction decreased by .13 
percentage points; and the estimated Medicare savings decreased by 
22.20%. Therefore, we believe that suppressing the CMS 30-Day Pneumonia 
Readmission Measure (NQF #0506) measure would have a minimal negative 
impact on eligibility for the Hospital Readmissions Reduction Program, 
and the number of hospitals receiving payment reductions. Although we 
noted that suppressing the CMS 30-Day Pneumonia Readmission Measure 
(NQF #0506) measure would have larger impacts on the weighted average 
payment reduction and the estimated Medicare savings under the Hospital 
Readmissions Reduction Program, the reduction in penalty as a share of 
payments and estimated Medicare savings are expected based on the 
program methodology in which each measure contributes to the payment 
reduction additively, increasing the size of the payment reduction.
---------------------------------------------------------------------------

    \767\ We note that, for purposes of this analysis, we removed 
the pneumonia readmission measure from program results calculated 
using a 29-month performance period.
---------------------------------------------------------------------------

    We sought comments on our proposal to suppress the current CMS 30-
Day Pneumonia Readmission Measure (NQF #0506) for FY 2023. The comments 
we received and our responses are set forth in this section of this 
rule.
    Comment: Many commenters expressed support for our proposal to 
suppress the CMS 30-Day Pneumonia Readmission Measure (NQF #0506) for 
FY 2023. Several commenters noted that this suppression would help 
address the significant impact of the COVID-19 PHE

[[Page 45256]]

and the close clinical proximity of pneumonia to COVID-19, both of 
which could distort hospital performance on the measure. Several 
commenters also expressed support for not including the suppressed 
readmission measure in payment reduction calculations.
    Response: We thank the commenters for their support.
    Comment: Several commenters encouraged CMS to continue analyzing 
data from 2020 and 2021 to determine if suppression is necessary in 
future fiscal years due to the ongoing impact of the pandemic. A 
commenter noted that although they support suppression of the measure 
due to the COVID-19 PHE, the measures are intended to promote 
improvements in critical patient safety and quality of care metrics. 
For this reason, the commenter stressed the importance of resuming full 
implementation of hospital quality programs as soon as sufficiently 
reliable data are available.
    Response: We thank the commenters for their feedback. We agree that 
the effects of the COVID-19 pandemic are ongoing and we will continue 
to monitor the claims that form the basis for this measure's 
calculations to evaluate the effect of the circumstances on quality 
measurement and to determine the appropriate policies in the future. We 
agree that it is important to continue tracking the impact of the 
COVID-19 PHE on the CMS 30-Day Pneumonia Readmission Measure (NQF 
#0506), as these data will inform our considerations regarding whether 
future measure suppression is necessary beyond FY 2023. We also agree 
that the measure is important to improving patient safety and quality 
of care, and will continue to monitor measure data to determine when it 
may be considered sufficiently reliable such that resuming full 
implementation of the CMS 30-Day Pneumonia Readmission Measure (NQF 
#0506) is appropriate.
    Comment: Some commenters expressed concern regarding the public 
reporting of suppressed data, suggesting that data unfit to determine 
payments should not be publicly reported. A few commenters stated that 
such information should not be publicly reported because it would not 
be sufficiently accurate to support informed decision-making by 
beneficiaries and other stakeholders.
    Response: We understand the commenters' concerns about publicly 
reporting measure data from during the PHE due to COVID-19. However, as 
noted previously in section V.G.5. of the preamble of this final rule, 
we will make clear in the public presentation of the data that the 
measure has been suppressed for purposes of scoring and payment 
adjustments because of the effects of the PHE due to COVID-19. 
Displaying this information will promote transparency on the impacts of 
the PHE due to COVID-19, and we will appropriately caveat the data in 
order to mitigate potential public confusion.
    Comment: A few commenters expressed support for our proposal to 
provide confidential performance feedback to hospitals on suppressed 
measures.
    Response: We thank the commenters for their support. We will 
provide confidential feedback reports to hospitals for the pneumonia 
readmission measure, with the current specifications. In these 
confidential reports, hospitals will be able to see which of their 
patients were readmitted to the hospital, and which of their patients 
were excluded from the measure denominators to inform hospital quality 
improvement initiatives.
    After consideration of the public comments we received, we are 
finalizing our proposal to suppress the CMS 30-Day Pneumonia 
Readmission Measure (NQF #0506) for FY 2023 as proposed, without 
modification.
c. Technical Measure Specification Update To Exclude COVID-19 Diagnosed 
Patients From All Other Condition/Procedure-Specific Readmission 
Measures Beginning With FY 2023
    In the FY 2015 IPPS/LTCH final rule, we finalized a subregulatory 
process to incorporate technical measure specification updates into the 
measure specifications we have adopted for the Hospital Readmissions 
Reduction Program (79 FR 50039). We reiterated this policy in the FY 
2020 IPPS/LTCH final rule, stating our continued belief that the 
subregulatory process is the most expeditious manner possible to ensure 
that quality measures remain fully up to date while preserving the 
public's ability to comment on updates that so fundamentally change a 
measure that it is no longer the same measure that we originally 
adopted (84 FR 42385). In the FY 2022 PPS/LTCH PPS proposed rule, we 
stated that due to the impact of the COVID-19 PHE on the measures used 
in the Hospital Readmissions Reduction Program, as described 
previously, we would be updating these five condition/procedure-
specific readmission measures to exclude COVID-19 diagnosed patients 
from the measure denominators (86 FR 25464). We also stated this 
technical update would modify these five condition/procedure-specific 
readmission measures to exclude certain ICD-10 Codes that represented 
patients with a secondary diagnosis of COVID-19 from the measure 
denominators, but would retain the measures in the program. Although in 
the proposed rule we stated that the technical update would modify the 
condition/procedure-specific readmission measures to exclude patients 
with a secondary diagnosis of COVID-19 (86 FR 25462), it is possible 
that certain procedure-specific readmission measures could include 
patients with a primary diagnosis of COVID-19 in the measure cohort as 
well. Therefore, we are updating our language in this final rule to 
reflect that the technical measure specification updates would exclude 
patients with primary or secondary COVID-19 diagnoses.
    We believe that excluding COVID-19 patients from the measure 
denominator will ensure that these five condition/procedure-specific 
readmission measures continue to account for readmissions as intended 
and meet the goals of the Hospital Readmissions Reduction Program. 
Additional resources about the current measure technical specifications 
and methodology for the Hospital Technical specification of the current 
readmission measures are provided at our website in the Measure 
Methodology Reports (available at: http://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/HospitalQualityInits/Measure-Methodology.html). Hospital Readmissions Reduction Program 
resources are located at the Resources web page of the QualityNet 
website (available at: https://www.qualitynet.org/dcs/ContentServer?c=Page&pagename=QnetPublic%2FPage%2FQnetTier3&cid=1228772412995).
    We received public comments on this technical measure specification 
update. The comments we received and our responses are set forth in 
this section of this rule.
    Comment: Many commenters expressed support for our technical 
measure specification updates removing COVID-19 patients from the 
denominator for the five remaining condition/procedure-specific 
readmission measures beginning in FY 2023. These commenters agreed that 
the COVID-19 public health emergency had a direct impact on the 
readmission measures as well as an indirect effect through 
complications and exacerbation of existing conditions. Several 
commenters noted that these technical updates to measure specifications

[[Page 45257]]

would help to mitigate the impact of the COVID-19 PHE on condition/
procedure-specific readmission measures. A few commenters noted the 
importance of keeping the measures in the program, while also 
accounting for the impact of COVID-19 patients on measure cohorts.
    Response: We thank the commenters for their support.
    Comment: Several commenters supported the technical specification 
updates to remove COVID-19 patients from the measure denominators, but 
also encouraged CMS to continue analyzing COVID-19's impact on quality 
measures. These commenters added that impacts on measure performance 
may stem from more than just COVID-19 diagnoses, such as closing of 
long-term care facilities, lack of visitors to understand aftercare 
instructions, and lower elective procedure rates.
    Response: We understand that the COVID-19 PHE is ongoing and may be 
impacting many aspects of the healthcare system and patient outcomes. 
We will continue to monitor the claims data that form the basis for 
these measure calculations to evaluate the effect of COVID-19 on 
quality measurement and to determine appropriate policies in the 
future.
    Comment: Several commenters expressed concern that the technical 
measure specification updates to exclude COVID-19 patients from the 
five condition/procedure-specific readmission measures may not 
adequately address the impacts of COVID-19 on those measures. Several 
commenters also sought clarification on whether the exclusion would 
apply to patients who contract COVID-19 between the index admission and 
readmission. A few commenters questioned CMS to specify the ICD-10 
codes that will be used to identify secondary diagnosis of COVID-19. A 
few commenters recommended additional exclusions to the measure 
specifications in order to account for those readmissions to ensure 
that CMS is not penalizing hospitals for readmissions due to COVID-19.
    Response: We thank the commenters for their feedback. We share 
commenters' concerns regarding whether the exclusions discussed in the 
proposed rule adequately capture all COVID-19 readmissions. Therefore, 
we wish to clarify that we plan to remove any patients diagnosed with 
COVID-19, including a primary or secondary diagnosis of COVID-19, from 
both index admissions and readmissions in order to exclude from the 
measure cohort patients who are readmitted due to COVID-19 within the 
30-day readmission period. We would like to clarify that we will be 
removing index admissions (from the denominator) that have a principal 
or secondary diagnosis present on admission (POA), of COVID-19 using 
the COVID-19 specific ICD-10 code (U07.1). We are explicitly noting the 
exclusion of principal diagnoses given the possible, though likely 
rare, scenario in which a patient is admitted for a CABG or THA/TKA 
procedure with a principal diagnosis of COVID-19. We will continue to 
monitor the claims data and COVID-19 coding practices. Additionally, we 
will be removing from the numerator any readmissions within 30 days 
that have a principal or secondary diagnosis POA, of COVID-19 (U07.1).
    Comment: A few commenters expressed concern that the exclusions may 
not adequately adjust for the impacts of COVID-19 on the condition/
procedure-specific readmission measures and recommended that CMS 
consider additional suppression policies, noting that the COVID-19 PHE 
impacted measure data for a variety of reasons, including higher 
patient acuity, disruptions in care due to the COVID-19 PHE, as well as 
challenges with available resources. A few commenters requested that 
CMS consider the impact of the COVID-19 PHE and exclusion of COVID-19 
patients by modeling the potential impacts on hospital performance 
scores prior to finalizing these technical measure specification 
updates. A few commenters expressed concern that operational changes 
and fluctuations in volume may have unintended consequences on the 
calculation of performance scores.
    Response: We appreciate commenters' concerns that the exclusions 
may not capture the totality of the impacts of the COVID-19 PHE on 
condition/procedure-specific readmission measures, and will continue to 
evaluate data collected during the COVID-19 PHE to assess whether 
additional measure suppressions or further exclusions may be necessary. 
We have based our measurement and program changes announced in this 
final rule based upon analyses of the most recently available data. As 
additional months of data become available, we will continue to conduct 
analyses to understand the evolving circumstances of the COVID-19 
pandemic to inform future measurement approaches.
    Comment: A few commenters recommended that CMS provide confidential 
feedback reports to hospitals that include the entire measure cohort 
for each condition/procedure-specific readmission measure, including 
COVID-19 patients, in order to help hospitals and clinicians better 
understand the relationship between COVID-19 and patient outcomes for 
these condition/procedure-specific readmission measures.
    Response: We thank the commenters for their feedback, and will 
evaluate the feasibility of providing confidential feedback reports to 
hospitals that include condition/procedure-specific readmission measure 
data for patients with and without COVID-19 diagnoses. In these 
confidential reports, hospitals would be able to see which of their 
patients were excluded from the measures due to a qualifying COVID-19 
diagnosis to inform hospital quality improvement initiatives.
    Comment: A few commenters recommended that CMS continue to analyze 
COVID-19 PHE data to determine whether the technical measure 
specification updates should be extended beyond FY 2023 due to the 
continuing impact of COVID-19 on the condition/procedure-specific 
readmission measures.
    Response: We thank the commenters for their feedback. We agree with 
commenters that it is important to continue monitoring the PHE's 
ongoing effects on condition/procedure-specific readmission measures, 
as this will inform our considerations about whether to extend the 
exclusions beyond FY 2023.
    Comment: A few commenters expressed concern that removing patients 
with COVID-19 from the readmission measures would not adequately 
account for the effects of the PHE on the readmission measures, 
including for patients who did not contract COVID-19. These commenters 
requested that CMS consider suppression of the five readmission 
measures as the COVID-19 pandemic impacted hospital volume and 
operations.
    Response: Our analyses of available data to date have estimated 
only minimal impacts of COVID-19 on readmission measure results (for 
measures other than pneumonia readmission) for the FY 2023 program 
year. The proportion of admissions and readmissions with a principal or 
secondary diagnosis of COVID-19 were very small due to the cohort 
definitions and affected performance period.
    After consideration of the public comments we received, we are 
clarifying our technical measure specification update to remove any 
patients diagnosed with COVID-19, including a primary or secondary 
diagnosis POA of COVID-19, from both

[[Page 45258]]

index admissions and readmissions from the measure cohorts for these 
five condition/procedure-specific readmission measures.
7. Automatic Adoption of Applicable Periods for FY 2023 and Subsequent 
Years
    We refer readers to the FY 2012 IPPS/LTCH PPS final rule (76 FR 
51671) and the FY 2013 IPPS/LTCH PPS final rule (77 FR 53375) for 
discussion of our previously finalized policy for defining ``applicable 
period''. In the FY 2019 IPPS/LTCH PPS final rule (83 FR 41434 through 
41435) and the FY 2020 IPPS/LTCH PPS final rule (84 FR 42387), we 
finalized the ``applicable period'' consistent with the definition 
specified at 42 CFR 412.152, to calculate the readmission payment 
adjustment factor for FY 2022 as the 3-year time period of July 1, 2017 
through June 30, 2020.\768\
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    \768\ Although the FY 2022 applicable period is July 1, 2017 
through June 30, 2020, we note that first and second quarter data 
from CY 2020 is excluded from consideration for program calculation 
purposes due to the nationwide ECE that was granted in response to 
the COVID-19 PHE.
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    The ``applicable period'' is the 3-year period from which data are 
being collected in order to calculate excess readmission ratios (ERRs) 
and payment adjustment factors for the fiscal year; this includes 
aggregate payments for excess readmissions and aggregate payments for 
all discharges used in the calculation of the payment adjustment. The 
``applicable period'' for dually eligible beneficiaries is the same as 
the ``applicable period'' that we otherwise adopt for purposes of the 
Hospital Readmissions Reduction Program.
    In order to provide greater certainty around future applicable 
periods for the Hospital Readmissions Reduction Program, in the FY 2021 
IPPS/LTCH final rule (85 FR 58846), we finalized the automatic adoption 
of applicable periods for FY 2023 and all subsequent program years for 
the Hospital Readmissions Reduction Program. Beginning in FY 2023, the 
applicable period for the Hospital Readmissions Reduction Program will 
be the 3-year period beginning 1 year advanced from the previous 
program fiscal year's start of the applicable period. Under this 
policy, for all subsequent years, we will advance this 3-year period by 
1 year unless otherwise specified by the Secretary, which we would 
convey through notice and comment rulemaking. Similarly, the applicable 
period for dual eligibility will continue to correspond to the 
applicable period for the Hospital Readmissions Reduction Program, 
unless otherwise specified by the Secretary. We refer readers to the FY 
2021 IPPS/LTCH PPS final rule (85 FR 58845 through 58846) for a more 
detailed discussion of this topic. In the FY 2022 IPPS/LTCH PPS 
proposed rule (86 FR 25464), we did not propose any updates to this 
policy.
8. Identification of Aggregate Payments for Each Condition/Procedure 
and All Discharges for FY 2022
    When calculating the numerator (aggregate payments for excess 
readmissions), we determine the base operating DRG payment amount for 
an individual hospital for the applicable period for each condition/
procedure using Medicare inpatient claims from the MedPAR file with 
discharge dates that are within the applicable period. Under our 
established methodology, we use the update of the MedPAR file for each 
Federal fiscal year, which is updated 6 months after the end of each 
Federal fiscal year within the applicable period, as our data source.
    In identifying discharges for the applicable conditions/procedures 
to calculate the aggregate payments for excess readmissions, we apply 
the same exclusions to the claims in the MedPAR file as are applied in 
the measure methodology for each of the applicable conditions/
procedures. For the FY 2022 applicable period, this includes the 
discharge diagnoses for each applicable condition/procedure based on a 
list of specific ICD-10-CM and ICD-10-PCS code sets, as applicable, for 
that condition/procedure, because diagnoses and procedure codes for 
discharges occurring on or after October 1, 2015 (FY 2016) began 
reporting under the ICD-10-CM and ICD-10-PCS code sets as opposed to 
the previous ICD-9-CM code set.
    We identify Medicare fee-for-service (FFS) claims that meet the 
criteria as previously described for each applicable condition/
procedure to calculate the aggregate payments for excess readmissions. 
This means that claims paid for under Medicare Part C (Medicare 
Advantage) are not included in this calculation. This policy is 
consistent with the methodology to calculate ERRs based solely on 
admissions and readmissions for Medicare FFS patients. Therefore, 
consistent with our established methodology, for FY 2022, we proposed 
to continue to exclude admissions for patients enrolled in Medicare 
Advantage (MA), as identified in the Medicare Enrollment Database.
    In the FY 2022 IPPS/LTCH PPS proposed rule (86 FR 25464 through 
25465), for FY 2022, we proposed to determine aggregate payments for 
excess readmissions, and aggregate payments for all discharges using 
data from MedPAR claims with discharge dates that align with the FY 
2022 applicable period.\769\ As we stated in the FY 2018 IPPS/LTCH PPS 
final rule (82 FR 38232), we would determine the neutrality modifier 
using the most recently available full year of MedPAR data. However, we 
noted that, for the purpose of modeling the estimated FY 2022 
readmissions payment adjustment factors for this final rule, we would 
use the proportion of dually eligible beneficiaries, excess readmission 
ratios, and aggregate payments for each condition/procedure and all 
discharges for applicable hospitals from the FY 2022 Hospital 
Readmissions Reduction Program applicable period (July 1, 2017 through 
December 1, 2019).\770\ For the FY 2022 program year, applicable 
hospitals will have the opportunity to review and correct calculations 
based on the FY 2022 applicable period of July 1, 2017 to December 1, 
2019, before they are made public under our policy regarding reporting 
of hospital-specific information. Again, we reiterate that this period 
is intended to review the program calculations, and not the underlying 
data. For more information on the review and corrections process, we 
refer readers to the FY 2013 IPPS/LTCH PPS final rule (77 FR 53399 
through 53401).
---------------------------------------------------------------------------

    \769\ Although the FY 2022 applicable period is July 1, 2017 
through June 30, 2020, we note that first and second quarter data 
from CY 2020 is excluded from consideration for scoring purposes due 
to the nationwide ECE that was granted in response to the COVID-19 
PHE. Taking into consideration the 30-day window to identify 
readmissions, the period for calculating DRG payments would be 
adjusted to July 1, 2017 through December 1, 2019. Further 
information will be found in the FY 2022 Hospital Specific Report 
(HSR) User Guide located on QualityNet website at: https://qualitynet.cms.gov/inpatient/hrrp/reports that is anticipated to 
become available in August 2021.
    \770\ We note that in the FY 2022 IPPS/LTCH PPS proposed rule 
(86 FR 25465), we used data from the FY 2021 Hospital Readmissions 
Reduction Program applicable period to estimate payment adjustment 
factors. We are updating these estimates in this final rule with 
data from the FY 2022 applicable period.
---------------------------------------------------------------------------

    In the proposed rule, we also proposed to continue to use MedPAR 
data corresponding to the applicable period for identifying discharges 
for the applicable conditions/procedures to calculate the aggregate 
payments for excess readmissions for the Hospital Readmissions 
Reduction Program. We proposed to use the update of the MedPAR file for 
each Federal FY, which is updated 6 months after the end of each 
Federal FY within the applicable period, as our data source.
    We welcomed public comment on this proposal to identify aggregate 
payments for each condition/procedure

[[Page 45259]]

and all discharges for the FY 2022 applicable period using 
corresponding MedPAR data. The comments we received and our responses 
are set forth in this section of this rule.
    Comment: A few commenters expressed support for our proposal to 
determine aggregate payments for excess readmissions, and aggregate 
payments for all discharges using data from MedPAR claims with 
discharge dates that align with the FY 2022 applicable period.
    Response: We thank these commenters for their support.
    Comment: A few commenters expressed support for the use of MedPAR 
data based on the FY 2022 applicable period of July 1, 2017 through 
December 1, 2019, which was modified due to the nationwide ECE granted 
in response to the COVID-19 PHE.
    Response: We thank these commenters for their support.
    After consideration of the public comments we received, we are 
finalizing our policy to identify aggregate payments for each 
condition/procedure and all discharges for the FY 2022 applicable 
period using corresponding MedPAR data as proposed, without 
modification.
9. Automatic Adoption of the Use of MedPAR Data Corresponding to the 
Applicable Period Beginning in FY 2023
    We refer readers to the FY 2013 IPPS/LTCH PPS final rule (77 FR 
53387 through 53390) for discussion of our previously finalized policy 
for the use of MedPAR claims data as our data source for determining 
aggregate payments for each condition/procedure and aggregate payments 
for all discharges during applicable periods. Most recently, in the FY 
2021 IPPS/LTCH PPS final rule (85 FR 58846), we finalized our policy on 
the continued use of the MedPAR data corresponding to the applicable 
period for the Hospital Readmissions Reduction Program calculations for 
the FY 2021 applicable period. We also finalized our policy to use the 
update of the MedPAR file for each Federal FY, which is updated 6 
months after the end of each Federal FY within the applicable period, 
as our data source to identify discharges within the FY 2021 applicable 
period during that fiscal year. Similarly, in section V.G.8 of this 
final rule, we are finalizing our proposal to use MedPAR data 
corresponding to the applicable period for the Hospital Readmissions 
Reduction Program calculations for the FY 2022 applicable period, and 
to use the update of the MedPAR file for each Federal FY, which is 
updated 6 months after the end of each Federal FY within the applicable 
period, as our data source.
    We continue to believe that the use of MedPAR claims data is the 
appropriate source for identifying aggregate payments for each 
condition/procedure and all discharges during the corresponding 
applicable period for the Hospital Readmissions Reduction Program. In 
order to provide greater certainty around future applicable periods for 
the Hospital Readmissions Reduction Program, in the FY 2021 IPPS/LTCH 
final rule (85 FR 58845 through 58846), we finalized the automatic 
adoption of applicable periods for FY 2023 and all subsequent program 
years for the Hospital Readmissions Reduction Program. Under this 
policy, the 3-year applicable period will automatically advance by 1 
year beginning in FY 2023. Because the MedPAR data used for the 
Hospital Readmissions Reduction Program calculations corresponds to the 
applicable period, we believe that the automatic adoption of the use of 
MedPAR data corresponding to the applicable period for Hospital 
Readmissions Reduction Program calculations each year will similarly 
streamline the process and provide additional clarity and consistency 
to the program.
    Therefore, in the FY 2022 IPPS/LTCH proposed rule (86 FR 25465), we 
proposed to automatically adopt the use of MedPAR data corresponding to 
the applicable period for Hospital Readmissions Reduction Program 
calculations for FY 2023 and all subsequent program years. We proposed 
that, beginning in FY 2023, the MedPAR data used to calculate aggregate 
payments for each condition/procedure and for all discharges will be 
the 3-year period beginning 1 year advanced from the previous program 
fiscal year's MedPAR data corresponding to the applicable period for 
Hospital Readmissions Reduction Program calculations. Under this 
proposal, for all subsequent years, we would advance this 3-year period 
by 1 year unless otherwise specified by the Secretary, which we would 
convey through notice and comment rulemaking. We also proposed to 
automatically adopt the use of the update of the MedPAR file for each 
Federal FY, which is updated 6 months after the end of each Federal FY 
within the applicable period, as our data source, and to similarly 
advance this by 1 year from the previous program fiscal year.
    We welcomed public comment on this proposal. The comment we 
received and our response are set forth in this section of this rule.
    Comment: A commenter expressed support for the proposal to 
automatically adopt the use of MedPAR data to its corresponding 
applicable period beginning in FY 2023 program year and all subsequent 
program years.
    Response: We thank the commenter for its support.
    After consideration of the public comment we received, we are 
finalizing our policy to automatically adopt the use of MedPAR data 
corresponding to the applicable period for Hospital Readmissions 
Reduction Program calculations for FY 2023 and all subsequent program 
years as proposed, without modification.
10. Calculation of Payment Adjustment Factors for FY 2022
    As we discussed in the FY 2018 IPPS/LTCH PPS final rule (82 FR 
38226), section 1886(q)(3)(D) of the Act requires the Secretary to 
group hospitals and apply a methodology that allows for separate 
comparisons of hospitals within peer groups, based on the proportion of 
dually eligible beneficiaries served by each hospital, in determining a 
hospital's adjustment factor for payments applied to discharges 
beginning in FY 2019. Section 1886(q)(3)(D) also states that this 
methodology could be replaced through the application of subclause 
(E)(i), which states that the Secretary may take into account the 
studies conducted and the recommendations made by the reports required 
by section 2(d)(1) of the IMPACT Act of 2014 (Pub. L. 113-185; 42 
U.S.C. 1395 note) with respect to risk adjustment methodologies. On 
June 29, 2020,\771\ the second Report to Congress by the Department's 
Office of the Assistant Secretary for Planning and Evaluation (ASPE) on 
social risk and Medicare's value-based purchasing programs came out. We 
are continuing our review of these recommendations and will address 
them as appropriate in future rulemaking.
---------------------------------------------------------------------------

    \771\ Department of Health and Human Services Office of the 
Assistant Secretary for Planning and Evaluation (ASPE), ``Report to 
Congress: Social Risk Factors and Performance in Medicare's Value-
Based Purchasing Program.'' March 2020. Available at: https://aspe.hhs.gov/system/files/pdf/263676/Second-IMPACT-SES-Report-to-Congress.pdf.
---------------------------------------------------------------------------

    We refer readers to the FY 2018 IPPS/LTCH PPS final rule (82 FR 
38226 through 38237) for a detailed discussion of the payment 
adjustment methodology. We did not propose any changes to this payment 
adjustment calculation methodology for FY 2022 in the proposed rule (86 
FR 25466).

[[Page 45260]]

11. Calculation of Payment Adjustment for FY 2022
    Section 1886(q)(3)(A) of the Act defines the payment adjustment 
factor for an applicable hospital for a fiscal year as ``equal to the 
greater of: (i) the ratio described in subparagraph (B) for the 
hospital for the applicable period (as defined in paragraph (5)(D)) for 
such fiscal year; or (ii) the floor adjustment factor specified in 
subparagraph (C).'' Section 1886(q)(3)(B) of the Act, in turn, 
describes the ratio used to calculate the adjustment factor. 
Specifically, it states that the ratio is equal to 1 minus the ratio of 
aggregate payments for excess readmissions to aggregate payments for 
all discharges, scaled by the neutrality modifier. The calculation of 
this ratio is codified at 42 CFR 412.154(c)(1) and the floor adjustment 
factor is codified at 42 CFR 412.154(c)(2). Section 1886(q)(3)(C) of 
the Act specifies the floor adjustment factor at 0.97 for FY 2015 and 
subsequent fiscal years.
    Consistent with section 1886(q)(3) of the Act, codified in our 
regulations at 42 CFR 412.154(c)(2), for FY 2022, the payment 
adjustment factor will be either the greater of the ratio or the floor 
adjustment factor of 0.97. Under our established policy, the ratio is 
rounded to the fourth decimal place. In other words, for FY 2022, a 
hospital subject to the Hospital Readmissions Reduction Program would 
have an adjustment factor that is between 1.0 (no reduction) and 0.9700 
(greatest possible reduction).
    For additional information on the FY 2022 payment calculation, we 
refer readers to the Hospital Readmissions Reduction Program 
information and resources available on our QualityNet website. We did 
not propose any changes to our calculation of payment methodology in 
the proposed rule (86 FR 25466).
12. Overall Hospital Quality Star Ratings
    In the CY 2021 OPPS/ASC final rule with comment period and interim 
final rule with comment period (85 FR 86193 through 86236), we 
finalized a methodology to calculate the Overall Hospital Quality Star 
Ratings (Overall Star Ratings). The Overall Star Ratings utilize data 
collected on hospital inpatient and outpatient measures that are 
publicly reported on a CMS website, including data from the Hospital 
Readmissions Reduction Program. We refer readers to section XVI. of the 
CY 2021 OPPS/ASC final rule for details (85 FR 86193 through 86236). We 
did not propose any changes to our calculation of the Overall Star 
Ratings.
13. Extraordinary Circumstance Exception (ECE) Policy for the Hospital 
Readmissions Reduction Program
a. Background
(1) Previously Established Extraordinary Circumstance Exception (ECE) 
Policy Under the Hospital Readmissions Reduction Program
    We refer readers to the FY 2016 IPPS/LTCH PPS final rule (80 FR 
49542 through 49543) and the FY 2018 IPPS/LTCH PPS final rule (82 FR 
38239 through 38240) for discussion of our Extraordinary Circumstances 
Exception (ECE) policy. In the FY 2016 IPPS/LTCH PPS final rule (80 FR 
49542 through 49543), we adopted an ECE policy for the Hospital 
Readmissions Reduction Program, which recognized that there may be 
periods of time during which a hospital is not able to submit data 
(from which readmission measures data are derived) in an accurate or 
timely fashion due to an extraordinary circumstance beyond its control. 
When adopting this policy, we noted that we considered the feasibility 
and implications of excluding data for certain measures for a limited 
period of time from the calculations for a hospital's excess 
readmission ratios for the applicable performance period. By minimizing 
the data excluded from the program, the policy enabled affected 
hospitals to continue to participate in the Hospital Readmissions 
Reduction Program for a given fiscal year if they otherwise continued 
to meet applicable measure minimum threshold requirements. We expressed 
the belief that this approach would help alleviate the burden for a 
hospital that might be adversely impacted by a natural disaster or 
other extraordinary circumstance beyond its control, while enabling the 
hospital to continue to participate in the Hospital Readmissions 
Reduction Program. We further observed that section 1886(q)(5)(D) of 
the Act permits the Secretary to determine the applicable period for 
readmissions data collection, and we interpreted the statute to allow 
us to determine that the period not include times when hospitals may 
encounter extraordinary circumstances. This policy was similar to the 
ECE policy for the Hospital Inpatient Quality Reporting (IQR) Program, 
as initially adopted in the FY 2012 IPPS/LTCH PPS final rule (76 FR 
51651) and modified in the FY 2014 IPPS/LTCH PPS final rule (78 FR 
50836) and the FY 2015 IPPS/LTCH PPS final rule (79 FR 50277). We also 
considered how best to align an extraordinary circumstance exception 
policy for the Hospital Readmissions Reduction Program with existing 
extraordinary circumstance exception policies for other IPPS quality 
reporting and payment programs, such as the Hospital Value-Based 
Purchasing (VBP) Program, to the extent feasible.
    In the FY 2018 IPPS/LTCH PPS final rule (82 FR 38239), we modified 
the requirements for the Hospital Readmissions Reduction Program ECE 
policy to further align with the processes used by other quality 
reporting and VBP programs for requesting an exception from program 
reporting due to an extraordinary circumstance not within a provider's 
control.
(2) Extraordinary Circumstance Exception (ECE) Granted in Response to 
the COVID-19 Public Health Emergency
    On March 22, 2020, in response to COVID-19, we announced relief for 
clinicians, providers, hospitals, and facilities participating in 
Medicare quality reporting and value-based purchasing programs.\772\ 
Specifically, we announced that we were excluding data for the first 
and second quarters of CY 2020. On March 27, 2020, we published a 
supplemental guidance memorandum that described the scope and duration 
of the ECEs we were granting under each Medicare quality reporting and 
VBP program.\773\ For the Hospital Readmissions Reduction Program, we 
stated that qualifying claims will be excluded from the measure 
calculations for January 1, 2020-March 31, 2020 (Q1 2020) and April 1, 
2020-June 30, 2020 (Q2 2020) from the readmission measures.
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    \772\ CMS, Press Release, CMS Announces Relief for Clinicians, 
Providers, Hospitals and Facilities Participating in Quality 
Reporting Programs in Response to COVID-19 (Mar. 22, 2020), https://www.cms.gov/newsroom/press-releases/cms-announces-relief-clinicians-providers-hospitals-and-facilities-participating-quality-reporting.
    \773\ CMS, Exceptions and Extensions for Quality Reporting 
Requirements for Acute Care Hospitals, PPS-Exempt Cancer Hospitals, 
Inpatient Psychiatric Facilities, Skilled Nursing Facilities, Home 
Health Agencies, Hospices, Inpatient Rehabilitation Facilities, 
Long-Term Care Hospitals, Ambulatory Surgical Centers, Renal 
Dialysis Facilities, and MIPS Eligible Clinicians Affected by COVID-
19 (Mar. 27, 2020), https://www.cms.gov/files/document/guidance-memo-exceptions-and-extensions-quality-reporting-and-value-based-purchasing-programs.pdf.
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(3) Updated Application of the ECE Granted in Response to COVID-19
    On September 2, 2020, we published the Interim Final Rule with 
comment period (IFC), ``Medicare and Medicaid Programs, Clinical 
Laboratory Improvement Amendments (CLIA), and Patient Protection and 
Affordable Care Act; Additional Policy and Regulatory Revisions in 
Response to the COVID-19

[[Page 45261]]

Public Health Emergency'' (85 FR 54820). The IFC updated the ECE we 
granted in response to the PHE for COVID-19, for the Hospital 
Readmissions Reduction Program and several other quality reporting 
programs (85 FR 54827 through 54838).
    In the IFC, we updated the previously announced application of our 
ECE policy for the Hospital Readmissions Reduction Program (85 FR 54832 
through 54833) to the COVID-19 PHE to exclude any data submitted 
regarding care provided during the first and second quarters of CY 2020 
from our calculation of performance for FY 2022, FY 2023, and FY 2024. 
We expressed concern that excess readmission ratios calculated using 
excepted claims data could affect the national comparability of these 
data due to the geographic differences of COVID-19 incidence rates and 
hospitalizations along with different impacts resulting from different 
State and local law and policy changes implemented in response to 
COVID-19, and therefore may not provide a nationally comparable 
assessment of performance in keeping with the program goal of national 
comparison.
    In the IFC, we welcomed public comments on our policy to exclude 
any data submitted regarding care provided during first and second 
quarter of CY 2020 from our calculation of performance for FY 2022, FY 
2023, and FY 2024. We are responding to those public comments in this 
FY 2022 IPPS/LTCH PPS final rule.
    In the September 2, 2020 IFC, we also announced that if, due to 
ECEs related to the COVID-19 PHE, we do not have enough data to 
reliably measure national performance, we may propose to not assess 
hospitals based on such limited data or make temporary payment 
adjustments to facilities under the Hospital Readmissions Reduction 
Program for the affected program year. We stated that, if circumstances 
warranted, we could propose to suspend prospective application of 
program penalties or payment adjustments through the annual IPPS/LTCH 
PPS proposed rule. We also stated that, in the interest of time and 
transparency, we would provide subregulatory advance notice of our 
intentions to suspend such penalties and adjustments through routine 
communication channels to facilities, vendors, and QIOs. The 
communications could include memos, emails, and notices on the public 
QualityNet website (https://www.qualitynet.cms.gov/).\774\
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    \774\ We note that the QualityNet website (previously at 
QualityNet.org) has transitioned to a QualityNet.cms.gov.
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    We received public comments on our policy to exclude any data 
submitted regarding care provided during first and second quarter of CY 
2020 from our calculation of performance for FY 2022, FY 2023, and FY 
2024. The comments we received and our responses are set forth in this 
section of this rule.
    Comment: Several commenters supported CMS' updated application of 
the ECE granted in response to the PHE due to COVID-19. A few 
commenters also agreed with CMS' concerns regarding the national 
comparability of data from Q1 and Q2 of CY 2020 and noted that the 
integrity and validity of any measurement calculations associated with 
these data could be compromised. A commenter encouraged CMS to continue 
accepting data for purposes of evaluating the impact of COVID-19 on 
hospitals' outcomes.
    Response: We thank commenters for their support.
    Comment: A commenter encouraged CMS to consider excluding the 
remainder of CY 2020 data from use in payment determinations.
    Response: We thank the commenter for this feedback. Although we are 
not expanding the ECE we granted in response to the COVID-19 to exclude 
data for the remainder of CY 2020 data from use in the Hospital 
Readmissions Reduction Program, we refer readers to sections V.G.5 and 
V.G.6 for further discussion of policies that we are adopting in 
response to the impact of the COVID-19 PHE on measure data used in 
payment determinations.
    Comment: A commenter recommended that CMS consider factors which 
may impact hospital performance in the Hospital Readmissions Reduction 
Program besides the quantity of data submitted in deciding whether or 
not to assess hospitals, expressing concern regarding the reliability 
of the data that would be used to measure national performance. The 
commenter recommended that CMS should not impose penalties under the 
Hospital Readmissions Reduction Program for the affected program year.
    Response: We thank commenter for this feedback. We refer readers to 
our measure suppression policy in V.G.5, in which we consider factors 
which may impact the reliability and comparability of the measure data 
used to assess hospital performance in the Hospital Readmissions 
Reduction Program due to the COVID-19 PHE. Under this policy, we are 
suppressing the CMS 30-Day Pneumonia Readmission Measure (NQF #0506) 
for FY 2023 due to the potential impact of COVID-19 diagnoses on the 
reliability of the data that would be used to measure national 
performance on that measure. We are also updating the technical 
specifications for the remaining five condition/procedure-specific 
measures to exclude COVID-19 diagnoses from the measure cohorts to 
address the potential impact of COVID-19 on measure data quality. We 
note that due to our policy to exclude any data submitted regarding 
care provided during first and second quarter of CY 2020, the FY 2022 
applicable period for the Hospital Readmissions Reduction Program will 
not include measure data impacted by the COVID-19 PHE.
    As established in the September 2020 IFC, we have finalized our 
updated application of the ECE granted in response to the COVID-19 PHE.
b. General Clarifications to Hospital Readmissions Reduction Program 
ECE Policy
    After the nationwide ECE granted in response to the COVID-19 PHE 
ended, we received several requests from hospitals for individual ECEs 
under the Hospital Readmissions Reduction Program, due to extraordinary 
circumstances resulting from the continuing impact of the PHE. In the 
FY 2022 IPPS/LTCH PPS proposed rule (86 FR 25467 through 25468), we 
clarified our ECE policy to highlight that an ECE granted under the 
Hospital Readmissions Reduction Program would exclude claims data 
during the corresponding ECE period. Although we have considered the 
feasibility and implications of excluding data under the ECE policy for 
the Hospital Readmissions Reduction Program, we have never specified 
the types of data that would be excluded under an ECE granted to an 
individual hospital. Considering that the Hospital Readmissions 
Reduction Program only uses claims data, we would like to clarify our 
ECE policy to specify that claims data will be excluded from 
calculations of measure performance under an approved ECE for the 
Hospital Readmissions Reduction Program.
    The FY 2016 IPPS/LTCH final rule specifies that we may waive 
reporting requirements for the Hospital Readmissions Reduction Program 
in response to ECE requests, in alignment with the Hospital Inpatient 
Quality Reporting (IQR) policy (80 FR 49542). Although the Hospital 
Readmissions Reduction Program and the Hospital IQR Program use 
different sources of data and have different requirements

[[Page 45262]]

depending on the type of measure, the ECE policy applies to both 
programs. Therefore, in the FY 2022 IPPS/LTCH proposed rule, we 
clarified that although an approved ECE for the Hospital Readmissions 
Reduction Program would exclude excepted data from Hospital 
Readmissions Reduction Program payment reduction calculations, we did 
not propose to waive the data submission requirements of a hospital for 
claims data (86 FR 25467). For example, for claims data, we require a 
hospital to submit claims to receive payments for the services they 
provided to patients. Although an individual ECE approval under the 
Hospital Readmissions Reduction Program would except data submitted by 
a hospital from Hospital Readmissions Reduction Program calculations, a 
hospital would still need to submit its claims in order to receive 
payment outside the scope of the Hospital Readmissions Reduction 
Program for services provided.
    We have also received a few requests from hospitals for ECEs under 
the Hospital Readmissions Reduction Program, in which the hospitals 
requested an exception from the Hospital Readmissions Reduction Program 
payment reduction. The ECE policy for the Hospital Readmissions 
Reduction Program is intended to provide relief for a hospital that has 
been negatively impacted as a direct result of experiencing a 
significant disaster or other extraordinary circumstance beyond the 
hospital's control by excepting data from the period during which 
performance was impacted. The hospital would still be evaluated for the 
remainder of the applicable period during which performance was not 
impacted. The ECE policy is not intended to extend to payment 
reductions. Therefore, we clarify that, although an approved ECE for 
the Hospital Readmissions Reduction Program would exclude excepted data 
from Hospital Readmissions Reduction Program payment reduction 
calculations, it does not exempt hospitals from payment reductions 
under the Hospital Readmissions Reduction Program. Instead of relying 
upon our ECE policy, we are relying upon our authority under subsection 
1886(q)(5)(A)(i) of the Act to determine the scope of ``applicable 
conditions'', including the Secretary's authority to utilize his own 
criteria to select measures to be used to calculate the excess 
readmission measure.
c. Clarification of the Impact of ECE Excluded Data for the Hospital 
Readmissions Reduction Program
    In the FY 2022 IPPS/LTCH PPS proposed rule (86 FR 25468), we 
clarified the impact of data which had been excluded from the Hospital 
Readmissions Reduction Program due to the nationwide ECE that was 
granted in response to COVID-19 on upcoming Hospital Readmissions 
Reduction Program calculations. In order to determine and evaluate what 
kind of impact the nationwide ECE might have on the Hospital 
Readmissions Reduction Program, we conducted analyses to simulate the 
impact of an altered performance period on program eligibility and the 
resulting payment impacts to hospitals using pre-COVID-19 data from the 
FY 2020 Hospital Readmissions Reduction Program year. This analysis was 
intended to evaluate what patterns we might observe in Hospital 
Readmissions Reduction Program eligibility and payment as a result of 
excluding 6 months of data due to the ECE granted in response to the 
PHE for COVID-19. Our analysis found that there would be a minimal 
impact on hospitals if 6 months of data were removed from Hospital 
Readmissions Reduction Program calculations. We are performing 
additional analyses as CY 2020 data becomes available, and we will 
provide updated analyses as necessary when it becomes available.
    Although the FY 2022 applicable period is July 1, 2017 through June 
30, 2020, due to the first and second quarter CY 2020 claims exception 
period and the 30-day window to identify readmissions, the period for 
calculating ERRs would be adjusted to July 1, 2017 through December 1, 
2019. The period for calculating DRG payments would similarly be 
adjusted to July 1, 2017 through December 1, 2019 to align with the 
period to calculate ERRs. We would also note that CY 2019 data would be 
used to calculate the Neutrality Modifier, as that would be the most 
recent full year of data (since Q1 and Q2 CY 2020 data are excluded 
from FY 2020 data under the nationwide ECE). Finally, we note that each 
of the readmission measures uses claims data for the 12 months prior to 
the index hospitalization as well as index hospitalization claims for 
risk adjustment (76 FR 51672). Due to the nationwide ECE that was 
granted in response to the COVID-19 PHE, the condition/procedure-
specific measures will use less than 12 months of data for risk 
adjustment for admissions between July 1, 2020 and June 30, 2021 during 
the FY 2023 applicable period. For example, if not for the COVID-19 PHE 
and subsequent nationwide ECE, an admission on July 1, 2020 would have 
included 12 months of prior claims data--a lookback period of July 2, 
2019 through June 30, 2020--for risk adjustment. Because claims data 
from January 1, 2020 through June 30, 2020 are excluded under the 
nationwide ECE, an admission on July 1, 2020 will have a shorter 
lookback period of July 2, 2019 through December 31, 2019. 
Comorbidities from the index admission will continue to be used for all 
admissions.
    In the FY 2020 IPPS/LTCH PPS final rule, we finalized our policy to 
adopt a subregulatory process to make nonsubstantive updates to payment 
adjustment factor components to facilitate the program's operation when 
minor changes are required, but do not substantively impact the 
program's previously finalized policies (84 FR 42385 through 42387). 
Although these changes are substantive, they do not substantially 
impact the outcomes in comparison to the Hospital Readmissions 
Reduction Program's previously finalized policies. Implementation of 
this temporary policy will be addressed through the subregulatory 
process. For more details on these subregulatory updates, we refer 
readers to the Hospital Specific Report (HSR) User Guide located on 
QualityNet website at: https://qualitynet.cms.gov/inpatient/hrrp/reports.
14. Request for Public Comment on Possible Future Stratification of 
Results by Race and Ethnicity for Condition/Procedure-Specific 
Readmission Measures
    We are committed to achieving equity in health care outcomes for 
our beneficiaries by supporting providers in quality improvement 
activities to reduce health inequities, enabling them to make more 
informed decisions, and promoting provider accountability for health 
care disparities.\775\ As described in the FY 2022 IPPS/LTCH PPS 
proposed rule (86 FR 25554 through 25561), in response to statute and 
policy reports from the Assistant Secretary for Planning and Evaluation 
(ASPE) of HHS and the National Academies of Science, Engineering and 
Medicine to better account for social risk factors in the Medicare 
program,\776\ we have created

[[Page 45263]]

two complementary methods to calculate disparities in condition/
procedure-specific readmission measures (the CMS Disparity Methods). 
The first method (the Within-Hospital disparity method) promotes 
quality improvement by calculating differences in outcome rates among 
patient groups within a hospital while accounting for their clinical 
risk factors. This method also allows for a comparison of those 
differences, or disparities, across hospitals, so hospitals could 
assess how well they are closing disparity gaps compared to other 
hospitals. The second methodological approach (the Across-Hospital 
method) is complementary and assesses hospitals' outcome rates for 
subgroups of patients across hospitals, allowing for a comparison among 
hospitals on their performance caring for their patients with social 
risk factors. We refer readers to the technical report describing the 
CMS Disparity Methods in detail as well as the FY 2018 IPPS/LTCH PPS 
final rule (82 FR 38405 through 38407) and the posted Disparity Methods 
Updates and Specifications Report posted on the QualityNet website. The 
CMS Disparity Methods have thus far focused on dual eligibility, a 
proxy for social risk factors, as the main stratification variable for 
reporting disparity results. These stratified data are provided in 
confidential Hospital Specific Reports (HSRs) for six condition/
procedure-specific readmission measures and not publicly reported at 
this time. The disparity methods were designed to accommodate 
additional types of stratification variables, such as race and 
ethnicity, language preference, and disability status.
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    \775\ https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/QualityInitiativesGenInfo/Downloads/CMS-Quality-Strategy.pdf.
    \776\ ASPE, Report to Congress: Social Risk Factors and 
Performance Under Medicare's Value-Based Purchasing Programs (2016), 
https://aspe.hhs.gov/system/files/pdf/253971/ASPESESRTCfull.pdf. For 
more information, see National Academies of Sciences, Engineering, 
and Medicine, Accounting for Social Risk Factors in Medicare 
Payment: Identifying Social Risk Factors (2016), https://doi.org/10.17226/21858. See also, Improving Medicare Post-Acute Care 
Transformation Act of 2014 (2014), https://www.govinfo.gov/content/pkg/BILLS-113hr4994enr/pdf/BILLS-113hr4994enr.pdf.
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    As described in the proposed rule (86 FR 25557 through 25560), we 
sought comment on potentially expanding our methods for stratified 
reporting of the Disparity Methods to better illuminate social 
disparities in populations served by Medicare-participating hospitals. 
As described in the proposed rule, studies have shown that among 
Medicare beneficiaries, racial and ethnic minority persons often 
experience worse health outcomes, including more frequent hospital 
readmissions and procedural complications. We are, in particular, 
exploring the significance of racial and ethnic inequities, as well as 
other social factors such as language preference and disability status, 
in outcomes in the Hospital Readmissions Reduction Program.\777\ 
Expanding the disparity methods to include stratified results by both 
dual eligibility and race and ethnicity, as well as language preference 
and disability status, may enable a more comprehensive assessment of 
health equity and support initiatives to close the equity gap. We 
believe that hospitals will be able to use the results from the 
disparity methods to identify and develop strategies to promote health 
equity.
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    \777\ For example, see the RIT Race Code, available at https://www.resdac.org/cms-data/variables/research-triangle-institute-rti-race-code. See also, Health Serv Res. 2019 Feb; 54(1):13-23. doi: 
10.1111/1475-6773.13099. Epub 2018 Dec 3.
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    More specifically, we sought comment on expanding our efforts to 
provide hospital-level results of both the Within- and Across-Hospital 
Disparity Methods, as described in the proposed rule (86 FR 25557 
through 25560), using indirectly estimated race and ethnicity, as well 
as additional social factors, such as language preference and 
disability status. Indirect estimation relies on a statistical 
imputation method for inferring a missing variable or improving an 
imperfect administrative variable using a related set of information 
that is more readily available.\778\ Imputed data are most commonly 
used at the population level, where aggregated results form a more 
accurate description of the population than existing, imperfect data 
sets. The proposed rule also summarized the existing challenges in 
accurately determining race and ethnicity in our administrative data, 
the need for using advanced statistical methods for indirectly 
estimating race and ethnicity, and the previous algorithms developed to 
indirectly estimate race and ethnicity in our data. The expanded 
methods would be reported at the hospital-level, and provided to 
hospitals in confidential HSRs for six condition/procedure-specific 
readmission measures, stratified by both dual eligibility and race/
ethnicity: (1) Hospital 30-Day, All-Cause, Risk-Standardized 
Readmission Rate (RSRR) Following Acute Myocardial Infarction (AMI) 
Hospitalization (NQF #0505); (2) Hospital 30-Day, All-Cause, Risk-
Standardized Readmission Rate (RSRR) Following Coronary Artery Bypass 
Graft (CABG) Surgery (NQF #2515); (3) Hospital 30-Day, All-Cause, Risk-
Standardized Readmission Rate (RSRR) Following Chronic Obstructive 
Pulmonary Disease (COPD) Hospitalization (NQF #1891); (4) Hospital 30-
Day, All-Cause, Risk-Standardized Readmission Rate (RSRR) Following 
Heart Failure (HF) Hospitalization (NQF #0330); (5) Hospital-Level 30-
Day, All-Cause, Risk-Standardized Readmission Rate (RSRR) Following 
Elective Primary Total Hip Arthroplasty (THA) and/or Total Knee 
Arthroplasty (TKA) (NQF #1551); and (6) Hospital 30-Day, All-Cause, 
Risk-Standardized Readmission Rate (RSRR) Following Pneumonia 
Hospitalization (NQF #0506), for groups where results are technically 
feasible, adequately representative, and statistically reliable.\779\
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    \778\ IOM. 2009. Race, Ethnicity, and Language Data: 
Standardization for Health Care Quality Improvement. Washington, DC: 
The National Academies Press.
    \779\ Although we proposed to suppress the CMS 30-Day Pneumonia 
Readmission Measure (NQF #0506) in section V.G.6 of the proposed 
rule, we note that the measure is not being proposed for removal and 
is therefore still considered one of the six condition/procedure-
specific readmission measures included in the Hospital Readmissions 
Reduction Program.
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    To allow stakeholders an opportunity to become more familiar with, 
and gain comfort in interpreting stratified results using indirect 
estimation of race and ethnicity as described in the proposed rule, 
hospitals would receive confidential HSRs containing results for the 
six condition/procedure-specific readmission measures, stratified by 
both dual eligibility and race/ethnicity in Spring 2022, prior to 
anticipated future publication of results in Spring 2023. Any proposal 
to publicly display stratified quality measure data for these six 
condition/procedure-specific readmission measures as previously 
described on the Care Compare website, or expand stratified reporting 
to additional social risk factors, would be made through future 
rulemaking.
    We invited public comment on the following: (1) The possibility of 
confidentially reporting in HSRs stratified results using indirectly 
estimated race and ethnicity in addition to the currently reported 
results stratified using dual eligibility, for the six condition/
procedure-specific readmission measures, and by expansion of 
standardized data collection to additional social factors, such as 
language preference and disability status; (2) the possibility of 
publicly reporting stratified results using both indirectly estimated 
race and ethnicity, and dual eligibility, publicly on Care Compare, 
after at least one year of confidential reporting and further 
rulemaking, for the six condition/procedure-specific measures; and (3) 
possible mechanisms of incorporating other demographic characteristics 
into analysis that address and advance

[[Page 45264]]

health equity, such as the potential to include administrative and 
self-reported data to measure co-occurring disability status.
    Comment: Several commenters supported the creation and 
dissemination of measures stratified by dual eligibility status, 
imputed race/ethnicity, and other demographic and social risk factors. 
Some commenters explicitly supported stratification by imputed race and 
ethnicity for readmission measures. A commenter noted imputed race 
could be used as a way to expand the collection of additional social 
risk factors. Others noted that publicly reporting stratified results 
could build trust and transparency with patients and communities; help 
understand potential patterns in access and outcomes for patients with 
social risk factors; identify patient populations that would benefit 
from quality improvement strategies; and develop quality improvement 
strategies targeted to specific populations.
    Response: We thank the commenters for their feedback. We also 
anticipate that stratified hospital-level reporting by dual eligibility 
status, indirectly estimated race/ethnicity, and other demographic and 
social factors, even if confidential, has the potential to support 
quality improvement activities to improve quality of care and reduce 
disparities in hospital outcomes. We intend to begin confidential 
reporting of the six condition-specific readmission measures using both 
dual eligibility and indirect estimation of race and ethnicity. We will 
continue to evaluate the validity of the readmission measures 
stratified by indirect estimation during the confidential reporting 
period. We plan to report results confidentially to hospitals in Spring 
2022 where results are technically feasible, meaningful, and 
statistically reliable. Any potential future proposal to publicly 
display the disparity results on Care Compare would be made through 
future rulemaking.
    Comment: Several other commenters that supported public reporting 
of stratified results shared some concerns and suggestions for how to 
report the data. Several commenters stated that stratified results 
should only be publicly available for dual eligibility and self-
reported race and ethnicity. Some commenters were concerned about using 
imputed data for stratification by race and ethnicity and explained 
that reporting this information publicly could have unintended 
consequences such as confusion for consumers and the public. Some 
commenters recommended using indirect methods of calculating race and 
ethnicity for the purposes of stratifying measures for confidential 
reporting only. Many commenters noted concern about the lack of 
accuracy of imputed data. They recommended against using imputed data 
in programs that affect payment adjustments.
    Response: We are sensitive to the concerns raised by stakeholders 
about indirect estimation. As we summarized in the proposed rule (86 FR 
25558), the Medicare program does not directly collect information from 
beneficiaries on race and ethnicity, instead relying on data collected 
by the Social Security Administration. A number of barriers contribute 
to this information being insufficiently accurate to examine hospital-
level disparities. For example, prior to 1980, only three categories 
(White, Black, and Other) were available for individuals to self-report 
race, and respondents were not able to indicate Asian, American Indian/
Alaska Native, Hispanic, or Pacific Islander identities. As a result of 
these constrained response options, many current beneficiaries may not 
have had the opportunity to accurately self-report their race and 
ethnicity. Although we have undertaken significant efforts to update 
incorrect race and ethnicity information many inaccuracies remain 
limiting our ability to measure disparities.
    As summarized in the proposed rule (86 FR 25558), in recent years 
we have sponsored the development of two indirect estimation 
algorithms, both intended to correct and improve administrative 
information on race and ethnicity. Indirect estimation methods such as 
these can generally be used in two different ways: (a) To estimate 
race/ethnicity in the absence of self-reported data; or (b) to improve 
administrative data in which beneficiaries provided a self-report of 
race/ethnicity but were not permitted a full set of response options 
(post-1980). While there is evidence supporting the validity of both 
approaches,\780\ accuracy and performance is particularly high in 
situation (b), where indirect estimation allows the administrative 
variables to better match the responses people would give when 
permitted a full set of response options. The approach for indirect 
estimation we intend to apply is situation (b), which uses an algorithm 
to augment existing data to allow a constrained administrative self-
reported variable to better match what Medicare beneficiaries 
themselves may have chosen when given a comprehensive set of response 
options on race and ethnicity.
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    \780\ Dembosky JW, Haviland AM, Haas A, Hambarsoomian K, Weech-
Maldonado R, Wilson-Frederick SM, Gaillot S, Elliott MN. Indirect 
Estimation of Race/Ethnicity for Survey Respondents Who Do Not 
Report Race/Ethnicity. Med Care. 2019 May;57(5):e28-e33. doi: 
10.1097/MLR.0000000000001011. PMID: 30520838. Available at: https://pubmed.ncbi.nlm.nih.gov/30520838/.
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    The Medicare Bayesian Improved Surname Geocoding Version 2.1 (MBISG 
2.1) uses the original beneficiary self-report, but uses additional 
information supplied by Medicare beneficiaries and information about 
neighborhood composition, to make this variable better match what 
Medicare beneficiaries themselves self-report when given a full set of 
response options. With respect to Asian and Pacific Islander, Black, 
Hispanic, and White Medicare beneficiaries, the improved version of the 
administrative variable has 96-99% concordance with what Medicare 
beneficiaries themselves report when allowed a full set of response 
options,\781\ matching much better than the original self-reported 
variable in which most Medicare beneficiaries were not allowed to 
indicate Asian, American Indian/Alaska Native, Hispanic, or Pacific 
Islander identities. The MBISG 2.1 also offers distinct advantages 
because it generates probabilities of identification in each racial and 
ethnic group for each beneficiary.
---------------------------------------------------------------------------

    \781\ Ibid.
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    The MBISG 2.1 incorporates multiple sources of information to 
develop racial and ethnic probabilities. In addition to the information 
on race and ethnicity which that person reported to the SSA, the model 
also considers the person's first and last name, the composition of the 
census block group where they live, and other demographic information 
that Medicare beneficiary shared. Through such a holistic approach, the 
MBISG 2.1 can make accurate comparisons between groups of Medicare 
beneficiaries regarding the quality of care received, including people 
whose surnames are common among several racial and ethnic groups, and 
people who changed their surnames upon marriage. The MBISG 2.1 is also 
designed to consider those who identify as Multiracial and allows 
measurement in Census categories that distinguish those who chose 
single or multiple racial identity, as well as considering endorsement 
of Hispanic ethnicity separately. Notably, we only intend to use the 
MBISG 2.1 to make inferences about aggregated groups at the hospital 
level, and do not intend to use it to make inferences about any single 
individual, validation studies indicate that these aggregate estimates

[[Page 45265]]

further improve upon the higher predictive accuracy of the model.\782\
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    \782\ MBISG 2.1 validation results performed under contract #GS-
10F-0012Y/HHSM-500-2016- 00097G. Pending public release of the 2021 
Part C and D Performance Data Stratified by Race, Ethnicity, and 
Gender Report, available at: https://www.cms.gov/About-CMS/Agency-Information/OMH/research-and-data/statistics-and-data/stratified-reporting.
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    We believe that use of statistical imputation models, such as the 
MBISG 2.1 will permit us to provide more accurate, less biased 
information on disparities in hospital outcomes when reported 
confidentially. We plan to report results confidentially to hospitals 
in Spring 2022 where results are technically feasible, meaningful, and 
statistically reliable. Any potential future proposal to publicly 
display the disparity results on Care Compare would be made through 
future rulemaking. We are sensitive to the concerns raised by 
stakeholders and will continue to evaluate the validity of the 
readmission measures when stratified by indirect estimation during the 
confidential reporting period.
    Comment: Some commenters shared concerns about data privacy and 
raised doubt about the actionability of indirectly estimating race and 
ethnicity data for stratified measures.
    Response: We prioritize the privacy of the personal information of 
our beneficiaries and are sensitive to concerns raised by commenters 
about privacy and the use of data algorithms to infer potentially 
sensitive information about individuals. We are also sensitive to the 
need for hospitals to receive transparent information on health care 
quality measures, including the opportunity to review measure 
calculations and lists of potentially eligible patients. Notably, we 
only intend to use the MBISG 2.1 to make inferences about aggregated 
groups at the hospital level, and do not intend to use it to make 
inferences about any single individual, validation studies indicate 
that these aggregate estimates further improve upon the high predictive 
accuracy of the MBISG 2.1. At this time, we do not intend to share the 
individual-level race and ethnicity estimations or probabilities with 
hospitals during the confidential reporting period. We look forward to 
opportunities to address this issue with stakeholders in the future.
    Comment: Several commenters raised concerns about the reliability 
of disparity results. Specifically, they noted that groups of 10 
patients may be too small to produce reliable disparity estimates at 
the hospital level and highlighted the need to analyze the stability of 
the random effect model.
    Response: We agree that achieving statistical reliability of 
measure results is important to provide more accurate, less biased 
information on disparities in hospital outcomes. We will apply the same 
reliability standards to reporting of disparities results as we do for 
other measures that are publicly or confidentially reported. For 
measures that rely on a random effect model we will assess model 
stability and random effect variance prior to deriving any results, and 
reporting thresholds will be adjusted based on model results.
    Results will only be provided to hospitals where results are 
technically feasible, meaningful, and statistically reliable. 
Additional technical materials on minimum sample size thresholds will 
be posted on the QualityNet website.
    Comment: Commenters suggested that new reporting mechanisms may be 
necessary. Several commenters suggested that public reporting should 
occur only after enough time has passed to allow for testing messaging, 
conducting focus groups, and other techniques to ensure public data are 
comprehensible. A commenter suggested including text to aid 
interpretation of publicly reported results. Others suggested public 
reporting should occur after several years of confidential reporting to 
ensure there is enough time to develop, test, and implement data review 
and correction mechanisms.
    Response: We thank the commenters for their feedback. We are 
sensitive to the concerns raised by stakeholders about the need for 
enough time to allow for testing of the new methods prior to any future 
public reporting. As part of initial confidential reporting, we will 
provide information on the QualityNet website which aids users in 
interpretation of the methods and results during the confidential 
reporting period. Any potential future proposal to publicly display the 
disparity results on Care Compare would be made through future 
rulemaking with opportunity for additional public feedback.
    Comment: A commenter shared a concern about comparing disparity 
results across all hospitals and recommended comparing results only 
across hospitals with similar patient populations and communities.
    Response: We thank the commenter for their feedback. We will 
continue to evaluate the validity of the readmission measures 
stratified by indirect estimation, including examining for differences 
in hospital performance based on hospital characteristics and patient 
and community composition, during the confidential reporting period.
    Comment: Several commenters noted the need to stratify results 
beyond dual eligibility and race/ethnicity to help hospitals close the 
equity gap. They supported the collection and use of additional equity-
related predictor variables such as language, disability status, 
financial strain, housing status, LGBTQ status, and ``evidence-based 
social determinants''. A commenter recommended exploring methods to use 
additional demographic characteristics in analyses. Another commenter 
suggested that the Quality Reporting Document Architecture files would 
have the necessary information for Within- and Across-Hospital 
Disparity Methods their use would limit provider burden.
    Response: We appreciate the feedback provided by the commenters 
regarding stratification by other demographic characteristics in order 
to further address and advance health equity. We agree with commenters 
that many variables impact health equity, and note that this request 
for public comment is just a first step in addressing the equity gap. 
We will investigate the suggested predictor variables for use in future 
reports in this program and across our programs. We agree that Quality 
Reporting Document Architecture files and use of Certified Electronic 
Health Record Technology would limit provider burden on any future data 
collection efforts for future consideration. We will continue to take 
all concerns, comments, and suggestions into account in future 
policies.
    Comment: Several commenters supported standardizing data sources to 
capture social risk factors. A commenter highlighted that data used for 
stratification should be complete and accurate. Another commenter 
suggested that health information technology standards and guidance are 
needed to standardize data collection processes. Another commenter 
recommends that CMS should use existing data resources as a starting 
point for building a health equity framework instead of requiring 
hospitals to report additional data.
    Response: We appreciate the feedback provided by the commenters 
regarding approaches for incorporating other demographic 
characteristics into analyses that address and advance health equity. 
When considering future policy development, we agree that CMS would 
conduct any future collection of demographic and social data in a 
manner that minimizes provider reporting burden. We will take 
commenters' feedback into consideration in future policy development.

[[Page 45266]]

    Comment: Many commenters expressed overall support of CMS' goals to 
improve health care outcomes for Medicare beneficiaries and supported 
the stratification of measures in the Hospital Readmissions Reduction 
Program to identify and understand disparities. They noted that 
providing stratified measures could help hospitals identify gaps and 
advance equity but had concerns about the timeline and process of 
reporting the data. Some commenters recommended that if stratification 
is used to support disparity identification, then there should be clear 
statements around the intended use of the stratification variables. 
Several commenters also recommended updates to the Hospital 
Readmissions Reduction Program to better address health equity issues. 
For example, a commenter noted the need to risk adjust readmission 
measures by social risk factors, while another commenter suggested that 
the Hospital Readmissions Reduction Program should be streamlined into 
a more comprehensive program to better incorporate and address health 
equity.
    Response: We appreciate the feedback provided by the commenters 
regarding measuring health equity in our hospital quality measurement 
programs, including the Hospital Readmissions Reduction Program. We 
will continue to take all concerns, comments, and suggestions into 
account in our future policies.
15. Regulatory Updates (42 CFR 412.154)
    We proposed to update the references to CMS resources in regulation 
text (86 FR 25470). First, we note that we renamed our Hospital Compare 
website. It is now referred to as Care Compare and is available at: 
https://www.medicare.gov/care-compare. We proposed to revise our 
regulations for the Hospital Readmissions Reduction Program at 42 CFR 
412.154(f)(4) to reflect the new website name. We proposed to amend CFR 
412.154(f)(4), by adding the phrase ``or successor website'' so that 
the text reads ``Hospital Compare website or successor website.'' \783\
---------------------------------------------------------------------------

    \783\ While the statute refers to Hospital Compare, the name has 
been changed to Care Compare. Now called Care Compare, the website 
continues to serve the purpose of displaying quality data submitted 
for the Hospital Readmissions Reduction Program.
---------------------------------------------------------------------------

    We invited public comment on our proposal. The comment we received 
and our response are set forth in this section of this rule.
    Comment: A commenter expressed support for the update to the 
regulatory text that reflects the renaming of Hospital Compare to Care 
Compare.
    Response: We thank this commenter for its support.
    After consideration of the public comment we received, we are 
finalizing our proposal to update the regulatory text at 42 CFR 
412.154(f)(4) as proposed, without modification.

H. Hospital Value-Based Purchasing (VBP) Program: Policy Changes

    Section 1886(o) of the Act requires the Secretary to establish a 
hospital value-based purchasing program (the Hospital VBP Program) 
under which value-based incentive payments are made in a fiscal year 
(FY) to hospitals that meet performance standards established for a 
performance period for such fiscal year. Both the performance standards 
and the performance period for a fiscal year are to be established by 
the Secretary.
    For more of the statutory background and descriptions of our 
current policies for the Hospital VBP Program, we refer readers to our 
codified requirements for the Hospital VBP Program at 42 CFR 412.160 
through 412.168.
1. Flexibilities for the Hospital VBP Program in Response to the Public 
Health Emergency (PHE) Due to COVID-19
a. Measure Suppression Policy for the Duration of the PHE for COVID-19
    In previous rules, we have identified the need for flexibility in 
our quality programs to account for the impact of changing conditions 
that are beyond participating hospitals' control. We identified this 
need because we would like to ensure that participants in our programs 
are not affected negatively when their quality performance suffers not 
due to the care provided, but due to external factors.
    A significant example of the type of external factor that may 
affect quality measurement is the COVID-19 public health emergency 
(PHE), which has had, and continues to have, significant and ongoing 
effects on the provision of medical care in the country and around the 
world. The COVID-19 pandemic and associated PHE has impeded effective 
quality measurement in many ways. Changes to clinical practices to 
accommodate safety protocols for medical personnel and patients, as 
well as unpredicted changes in the number of stays and facility-level 
case mixes, have affected the data used in quality measurement and the 
resulting quality scores. Measures used in the Hospital VBP Program 
need to be evaluated to determine whether their specifications need to 
be updated to account for new clinical guidelines, diagnosis or 
procedure codes, and medication changes that we have observed during 
the PHE. Additionally, because COVID-19 prevalence is not consistent 
across the country, hospitals located in different areas have been 
affected differently at different times throughout the pandemic. Under 
those circumstances, we remain significantly concerned that Hospital 
VBP Program quality measure scores that are calculated using data 
submitted during the PHE for COVID-19 are distorted and will result in 
skewed payment incentives and inequitable payments, particularly for 
hospitals that have treated more COVID-19 patients than others.
    It is not our intention to penalize hospitals based on measure 
scores that we believe are distorted by the COVID-19 PHE and, thus, not 
reflective of the quality of care that the measures in the Hospital VBP 
Program were designed to assess. As previously discussed, the COVID-19 
PHE has had, and continues to have, significant and enduring effects on 
health care systems around the world, and affects care decisions, 
including those made on clinical topics covered by the Hospital VBP 
Program's measures. As a result of the COVID-19 PHE, hospitals could 
provide care to their patients that meets the underlying clinical 
standard but results in worse measured performance, and by extension, 
lower incentive payments in the Hospital VBP Program. We are also 
concerned that regional differences in COVID-19 prevalence during the 
performance periods for the FY 2022 and FY 2023 Hospital VBP Programs, 
which include CY 2020 data, have directly affected hospitals' measure 
scores for the FY 2022 and FY 2023 Hospital VBP program years. Although 
these regional differences in COVID-19 prevalence rates do not reflect 
differences in the quality of care furnished by hospitals, they 
directly affect the value-based incentive payments that these hospitals 
are eligible to receive and could result in an unfair and inequitable 
distribution of those incentives. These inequities could be especially 
pronounced for hospitals that have treated a large number of COVID-19 
patients.
    Therefore, we proposed to adopt a policy for the duration of the 
PHE for COVID-19 that would enable us to suppress the use of data for a 
number of measures if we determine that circumstances caused by the 
COVID-19 PHE have affected those measures and the resulting Total 
Performance Scores significantly (86 FR 25470). We also proposed, as 
described more fully in

[[Page 45267]]

section V.H.1.b. of this final rule, to suppress all of the measures in 
the Person and Community Engagement, Safety, and Efficiency and Cost 
Reduction Domains for the FY 2022 program year because we have 
determined that circumstances caused by the COVID-19 PHE have affected 
those measures significantly, and to adopt a special scoring and 
payment rule for that program year. Under this special rule for FY 
2022, which we would codify in our regulations at Sec.  412.168, we 
would calculate measure rates for all measures, including the measures 
we proposed to suppress, but would only calculate achievement and 
improvement scores for the measures in the Clinical Outcomes Domain, 
which we did not propose to suppress for FY 2022. We would also 
calculate domain scores for the Clinical Outcomes Domain but because 
that domain is only weighted at 25 percent of the TPS and we would have 
no other domain scores, we would not calculate total performance scores 
(TPSs) for hospitals. Finally, we would reduce each hospital's base-
operating DRG payment amount by 2 percent, as required under section 
1886(o)(7)(B) of the Act, but because no hospital would receive a TPS 
for FY 2022, we would assign to each hospital a value-based incentive 
payment percentage that results in a value-based incentive payment 
amount that matches the 2 percent reduction to the base operating DRG 
payment amount. The net result of these payment adjustments would be 
neutral for hospitals. That is, a hospital's base operating DRG payment 
amount would remain unchanged for FY 2022.
    We would still provide confidential feedback reports to hospitals 
on their FY 2022 measure rates on all measures to ensure that they are 
made aware of the changes in performance rates that we have observed. 
We would also publicly report Q3 and Q4 2020 data with appropriate 
caveats noting the limitations of the data due to the PHE for COVID-19. 
We noted that, due to operational complications associated with 
extended deadlines for Q3 2020 data submissions for the HCAHPS and HAI 
measures granted in response to the system issues as well as the 
proposed changes in the FY 2022 scoring methodology,\784\ and in order 
to allow enough time for the appropriate notice and comment period 
process, we may not be able to provide hospitals with the feedback 
reports for FY 2022 until after August 1, 2021. We intend to provide 
hospitals with these feedback reports for FY 2022 as soon as possible 
and estimate that we will be able to provide reports before the end of 
2021.
---------------------------------------------------------------------------

    \784\ All Programs (IQR, OQR, PCH, Validation, VBP, eCQM, HACRP, 
ESRD QIP) Subject: Q3 2020 Data Submission Deadline Extension for 
Certain Medicare Quality Reporting and Value-Based Purchasing 
Programs, available at: https://www.cms.gov/files/document/2020-12-inpatient-quarter-3-2020-extension-listserve-final.pdf.
---------------------------------------------------------------------------

    For the FY 2023 program year, we proposed to suppress only one 
measure, MORT-30-PN because we have determined that circumstances 
caused by the COVID-19 PHE have affected this measure significantly, 
but we did not propose to adopt a special scoring and payment rule for 
that program year (86 FR 25470). Instead, the scoring and payment rules 
we previously adopted at Sec.  412.160 through 412.165 would apply. The 
FY 2024 and FY 2025 program years also use CY 2020 data, but we did not 
propose to suppress the MORT-30-PN measure in the FY 2024 and FY 2025 
program years at this time. We will continue to analyze this data and 
will address suppression of MORT-30-PN for additional program years in 
future rulemaking.
    In developing the measure suppression provision, we considered what 
circumstances caused by the PHE for COVID-19 would affect a quality 
measure significantly enough to warrant its suppression in the Hospital 
VBP Program (86 FR 25471). We stated our belief that significant 
deviation in measured performance that can be reasonably attributed to 
the PHE is a significant indicator of changes in clinical conditions 
that affect quality measurement. Similarly, we stated our belief that a 
measure may be focused on a clinical topic or subject that is proximal 
to the disease, pathogen, or other health impacts of the PHE. As has 
been the case during the COVID-19 pandemic, we stated our belief that 
rapid or unprecedented changes in clinical guidelines and care 
delivery, potentially including appropriate treatments, drugs, or other 
protocols, may affect quality measurement significantly and should not 
be attributed to the participating facility positively or negatively. 
We also noted that scientific understanding of a particular disease or 
pathogen may evolve quickly during an emergency, especially in cases of 
new disease or conditions. Finally, we stated our belief that, as 
evidenced during the COVID-19 pandemic, national or regional shortages 
or changes in health care personnel, medical supplies, equipment, 
diagnostic tools, and patient case volumes or facility-level case mix 
may result in significant distortions to quality measurement.
    Based on these considerations, we developed a number of Measure 
Suppression Factors that we believe should guide our determination of 
whether to propose to suppress a Hospital VBP Program measure for one 
or more program years where the baseline or performance period of the 
measure overlaps with the PHE for COVID-19. We proposed to adopt these 
Measure Suppression Factors for use in the Hospital VBP Program and, 
for consistency, the following other value-based purchasing programs: 
Hospital Readmissions Reduction Program, HAC Reduction Program, and 
Skilled Nursing Facility Value-Based Purchasing Program. We stated our 
belief that these Measure Suppression Factors will help us evaluate the 
Hospital VBP Program's measures and that their adoption in the other 
value-based purchasing programs, as previously noted, will help ensure 
consistency in our measure evaluations across programs. The proposed 
Measure Suppression Factors are as follows:
     Significant deviation in national performance on the 
measure during the PHE for COVID-19, which could be significantly 
better or significantly worse compared to historical performance during 
the immediately preceding program years.
     Clinical proximity of the measure's focus to the relevant 
disease, pathogen, or health impacts of the PHE for COVID-19.
     Rapid or unprecedented changes in--
    ++ Clinical guidelines, care delivery or practice, treatments, 
drugs, or related protocols, or equipment or diagnostic tools or 
materials; or
    ++ The generally accepted scientific understanding of the nature or 
biological pathway of the disease or pathogen, particularly for a novel 
disease or pathogen of unknown origin.
     Significant national shortages or rapid or unprecedented 
changes in--
    ++ Healthcare personnel;
    ++ Medical supplies, equipment, or diagnostic tools or materials; 
or
    ++ Patient case volumes or facility-level case mix.
    We also considered alternatives to this proposed policy that could 
fulfill our objective to not penalize hospitals for measure results 
that are distorted due to the PHE for COVID-19. As previously noted, 
the country continues to grapple with the effects of the COVID-19 PHE, 
and in March 2020, CMS issued a nationwide, blanket Extraordinary 
Circumstances Exception (ECE) for all hospitals and other facilities 
participating in our quality reporting and value-based purchasing 
programs in response to the COVID-19 PHE. This blanket ECE excepted 
data reporting requirements for Q1 and Q2

[[Page 45268]]

2020 data, including excepting the use of claims data, HCAHPS survey 
data, and data collected through the CDC's web-based surveillance 
system for this data period. Quality data collection resumed on July 1, 
2020. We considered extending this blanket ECE for Q3 and Q4 2020. This 
alternative would have protected hospitals from having their quality 
data used for quality scoring purposes if those data were affected 
significantly by the COVID-19 PHE. However, this option would have made 
hospital quality data collection and reporting to CMS no longer 
mandatory and would have left us with no comprehensive data available 
for use in providing confidential performance feedback to hospitals or 
monitoring for purposes of deciding whether programmatic changes are 
necessary to adequately respond to the PHE.
    As an alternative to the proposed quality measure suppression 
policy, we also considered not suppressing any measures under the 
Hospital VBP Program. However, this alternative would mean assessing 
hospitals using quality measure data that has been significantly 
affected by the COVID-19 PHE. Additionally, given the geographic 
disparities in the COVID-19 PHE's effects, we stated in the proposed 
rule that we believe that if we do not adopt a policy to suppress 
measures that have been significantly affected by the PHE for COVID-19, 
hospitals in regions that are more heavily impacted by the COVID-19 PHE 
will be at a disadvantage when compared to hospitals in regions that 
are either not as heavily impacted, or are heavily impacted at a 
different point in the pandemic.
    We viewed the measure suppression proposal as a necessity to ensure 
that the Hospital VBP Program does not reward or penalize hospitals 
based on circumstances caused by the PHE for COVID-19 that the 
Program's measures were not designed to accommodate. We intended for 
policy to provide short-term relief to hospitals when we have 
determined that one or more of the Measure Suppression Factors warrants 
the suppression of one or more of the Program's measures.
    We invited public comment on this provision for the adoption of a 
measure suppression policy for the Hospital VBP Program for the 
duration of the PHE for COVID-19, and also on the proposed Measure 
Suppression Factors that we developed for purposes of the proposed 
policy.
    We also invited comment on whether we should consider adopting a 
measure suppression policy in the situation of a future national PHE, 
and if so, whether under such a policy, we should have the flexibility 
to suppress certain measures without specifically proposing to do so in 
rulemaking. We also requested comment on whether we should in future 
years consider adopting any form of regional adjustment for the 
proposed measure suppression policy that could take into account any 
disparate effects of circumstances affecting hospitals around the 
country that would prompt us to suppress a measure. For example, COVID-
19 affected different regions of the country at different rates 
depending on factors like time of year, geographic density, State and 
local policies, and health care system capacity. In future years and 
for future PHEs, should they arise, we also requested commenters' 
feedback on whether we should, rather than suppress a measure 
completely for scoring and payment purposes, consider a suppression 
policy with more granular effects based on our assessment of the 
geographic effects of the circumstances, and if so, how region-based 
measure suppression could be accounted for within the program's scoring 
methodology.
    The comments we received on our proposals and other requests for 
comments, as well as our responses, are set forth below.
    Comment: Many commenters expressed support for our proposed measure 
suppression policy, agreeing with our stated goal of ensuring that 
hospitals are not rewarded or penalized for their quality performance 
based on non-representative data. Commenters encouraged us to consult 
with stakeholders on any subregulatory policy changes on this topic in 
the future, including any potential changes to the Measure Suppression 
Factors, and requested that we explain the effects of any changes to 
the Measure Suppression Factors in detail. Some commenters recommended 
that we ensure that the suppression policy does not unintentionally 
penalize hospitals.
    Response: We thank the commenters for their support. We acknowledge 
commenters' concern that the suppression policy should not 
unintentionally penalize hospitals. As discussed in the FY 2022 IPPS/
LTCH PPS proposed rule and section V.H.1.b of this final rule, we 
proposed to suppress measures for purposes of scoring and payment 
adjustments because of our concern that we could be unable to make 
fair, national comparisons of hospitals across the country.
    Comment: Some commenters expressed concerns about our proposed 
suppression policy. Several commenters argued that we should not 
publicly report suppressed data, suggesting that data unfit to 
determine payments should not be publicly reported, while others 
suggested that we should note clearly that any publicly reported data 
has been affected by the COVID-19 PHE.
    Response: We believe it is important to balance fairness in value-
based payments with the public's need for transparency. Therefore, we 
intend to make the data publicly available. We understand the 
commenters' concern about publicly reporting data that was gathered by 
hospitals during the COVID-19 PHE; however, we will make clear in the 
public presentation of any data on a suppressed measure that the 
measure has been suppressed for purposes of scoring and payment 
adjustments because of the effects of the COVID-19 PHE. We will 
appropriately caveat the data in order to mitigate public confusion and 
avoid misrepresenting quality of care.
    Comment: Some commenters suggested that we should limit this policy 
to the current PHE given the unique circumstances involved in the 
COVID-19 pandemic. A few commenters expressed concerns about CMS being 
empowered to implement scoring adjustments and payment changes outside 
of rulemaking, and worried that comparisons between suppressed and 
unsuppressed scores would be unfair.
    Response: We did not propose to apply this policy beyond the COVID-
19 PHE. Any scoring adjustments or payment changes that might address a 
different, future fiscal year of the program due to the COVID-PHE or 
another type of emergency would be proposed through rulemaking. We 
acknowledge the commenters' concerns about potentially unfair 
comparisons and will consider for future rulemaking any such issues we 
identify.
    Comment: A few commenters requested additional information 
regarding how CMS plans to refresh the Overall Hospital Quality Star 
Ratings and HCAHPS Star Ratings when only Q3 and Q4 of CY 2020 data are 
scheduled to be publicly reported.
    Response: We are continuing to evaluate the data impacts and will 
provide information on future refreshes to the Overall Hospital Star 
Ratings and HCAHPS Star Ratings when available. Information will be 
provided through the Overall Hospital Star Ratings' and HCAHPS Star 
Ratings' previously established communication channels.
    Comment: Several commenters recommended that we study the effects 
of the measure suppression policy and the Measure Suppression Factors 
to

[[Page 45269]]

inform any suppression policies for future PHEs and that we work with 
stakeholders before adopting additional measure suppression policies. A 
commenter recommended that we include more flexible language in our 
suppression factors to account for our evolving understanding of COVID-
19, while another commenter suggested that we continue monitoring the 
effects of COVID-19 on 2021 quality performance and consider updating 
measure specifications to exclude COVID-19 patients or change our risk 
adjustment models. Other commenters suggested that we monitor the 
shorter performance periods carefully, as well as the effects of the 
policy on future benchmarking, and that we assess the indirect effects 
that the COVID-19 PHE has had on all aspects of medical care delivery.
    Response: We share commenters' concerns about the potential long-
term effects of the measure suppression policy, including the Measure 
Suppression Factors. While we appreciate the commenter's suggestion 
that we incorporate more flexibility into the Measure Suppression 
Factors, we believe the specificity with which we proposed them was 
necessary to provide hospitals and other members of the stakeholder 
community with clear insight into the decision-making process that we 
employed in response to the COVID-19 PHE. We agree with commenters that 
we should monitor the PHE's ongoing effects carefully and we will work 
with measure developers to refine measure specifications as 
circumstances warrant. We will also assess performance periods, 
benchmarks, and other effects of the COVID-19 PHE carefully and welcome 
stakeholders' continuing feedback as we continue responding to the PHE.
    Comment: Some commenters recommended that we refine our proposed 
Measure Suppression Factors. Some commenters suggested that we define 
them more precisely to be fully transparent with the factors' terms and 
effects, arguing that we have not defined what we consider to be 
``significant'' deviation in national performance on a measure during a 
PHE. A commenter also argued that the Measure Suppression Factors 
should be focused on effects on Medicare beneficiaries, not on 
providers or circumstances within the control of providers. A commenter 
suggested that we consider suppressing measures for individual 
hospitals where performance may have deviated significantly from past 
performance, while another commenter recommended that we ensure that 
the Measure Suppression Factors do not assess provider organizations' 
quality per se, but rather, the PHE at issue.
    Response: We thank the commenters for this feedback. We believe 
that some level of discretion is necessary in the face of evolving 
circumstances like those that have confronted us in the COVID-19 PHE. 
In deciding which measures to suppress, and as discussed further in 
section VI.H.1.b. of this final rule, we examined each measure and 
determined that the evidence showed significant deviation in the 
individual measure performance data associated with the COVID-19 PHE. 
We believe providing the evidence for the measure suppressions is 
transparent and provides sufficient explanation for our rationales. We 
note further that we designed several of the Measure Suppression 
Factors to account for circumstances that could affect the health and 
safety of patients and healthcare personnel, and we believe that 
situations like personal protective equipment (PPE) shortages do affect 
the care provided to Medicare beneficiaries. We recommend that any 
individual hospitals believing that they have faced extraordinary 
circumstances that affect their quality performance, but that have not 
been addressed by the suppression policy, consider seeking an 
Extraordinary Circumstances Exception.\785\
---------------------------------------------------------------------------

    \785\ For more information regarding Extraordinary Circumstances 
Exceptions requests under the Hospital VBP Program, please see: 
https://qualitynet.cms.gov/inpatient/hvbp/participation.
---------------------------------------------------------------------------

    Comment: Some commenters supported regional adjustments to the 
measure suppression policy, suggesting that we should account for 
disparate effects of circumstances like the COVID-19 pandemic around 
the country. Commenters requested that we seek stakeholders' feedback 
before adopting more granular suppression policies in the future. A 
commenter cautioned against regional adjustments, suggesting that such 
adjustments would not account for differences in PHE prevalence at 
safety-net hospitals that take on leading roles during PHEs.
    Response: We thank the commenters for their feedback and will 
consider it for future rulemaking. We share the commenter's concern 
that adjustments to account for regional differences in a PHE's effects 
may not fully capture those differences.
    Comment: Several commenters expressed support for our proposal to 
provide confidential performance feedback to hospitals on suppressed 
measures.
    Response: We thank the commenters for their support.
    After consideration of the public comments we received, we are 
finalizing our proposal to adopt a measure suppression policy and the 
measure suppression factors described above for the duration of the 
COVID-19 PHE.
b. Suppression of Specific Measures for the FY 2022 or FY 2023 Program 
Year
(1) Background
    We have conducted analyses on all Hospital VBP Program measures 
with the exception of the CMS PSI 90 measure to determine whether and 
how COVID-19 has impacted the validity of these measures. Our findings 
from these analyses are discussed below in the following sections. We 
did not conduct an analysis to determine the impact of COVID-19 on the 
CMS PSI 90 measure performance because the CMS PSI 90 measure would not 
be included in TPS calculations until FY 2023, and we proposed to 
remove this measure from the Hospital VBP Program beginning with FY 
2023. Based on those analyses, we proposed to suppress the following 
measures for the FY 2022 program year:

 Hospital Consumer Assessment of Healthcare Provides and 
Systems (HCAHPS) (NQF #0166)
 Medicare Spending Per Beneficiary--Hospital (NQF #2158)
 National Healthcare Safety Network (NHSN) Catheter-Associated 
Urinary Tract Infection (CAUTI) Outcome Measure (NQF #0138)
 National Healthcare Safety Network (NHSN) Central Line-
Associated Bloodstream Infection (CLABSI) Outcome Measure (NQF #0139)
 American College of Surgeons--Centers for Disease Control and 
Prevention Harmonized Procedure Specific Surgical Site Infection (SSI) 
Outcome Measure (NQF #0753)
 National Healthcare Safety Network (NHSN) Facility-wide 
Inpatient Hospital-onset Methicillin-resistant Staphylococcus aureus 
(MRSA) Bacteremia Outcomes Measure (NQF #1716)
 National Healthcare Safety Network (NHSN) Facility-wide 
Inpatient Hospital-onset Clostridium difficile Infection (CDI) Outcome 
Measure (NQF #1717)

    We additionally proposed to suppress the Hospital 30-Day, All 
Cause, Risk Standardized Mortality Rate Following Pneumonia (PN) 
Hospitalization measure (NQF #0468) (MORT-30-PN) for the FY 2023 
program year. Our proposals are described in more detail in this final 
rule. (2) Suppression of the Hospital Consumer Assessment of Healthcare 
Providers and Systems

[[Page 45270]]

(HCAHPS) Survey Measure (NQF #0166) for the FY 2022 Hospital VBP 
Program Year.
    We proposed to suppress the HCAHPS measure for the FY 2022 program 
year under proposed Measure Suppression Factor 1, significant deviation 
in national performance on the measure during the PHE for COVID-19, 
which could be significantly better or significantly worse as compared 
to historical performance during the immediately preceding program 
years (86 FR 25472 through 25473). We would calculate hospitals' HCAHPS 
measure rates, but we would not use these measure rates to generate 
achievement or improvement points for this measure. Additionally, 
because the HCAHPS measure is the only measure included in the Person 
and Family Engagement domain, we would not calculate hospitals' FY 2022 
domain scores for the Person and Family Engagement domain. 
Participating hospitals would continue to report the measure's data to 
CMS so that we can monitor the effect of the circumstances on quality 
measurement and determine the appropriate policies in the future. We 
would also continue to provide confidential feedback reports to 
hospitals as part of program activities to allow hospitals to track the 
changes in performance rates that we observe. We also intend to 
publicly report 2020 Q3 and Q4 2020 measure rate data where feasible 
and appropriately caveated.
    Based on our analysis of HCAHPS data from Q1 2018 to Q3 2020, we 
have observed a notable decline in hospital-level HCAHPS scores. This 
decline is associated with the COVID-19 PHE in 2020. HCAHPS measure 
results are publicly reported as ``top-box,'' ``bottom-box,'' and 
``middle-box'' scores, with ``top-box'' being the most positive 
response to HCAHPS Survey items.\786\
---------------------------------------------------------------------------

    \786\ https://www.hcahpsonline.org/en/summary-analyses/.
---------------------------------------------------------------------------

    In order to detect the possible impact of the COVID-19 PHE on 
patients' experience of hospital care, we conducted an ``apples-to-
apples'' analysis in which we compared hospitals' HCAHPS measure top-
box scores for each quarter between Q1 2019 and Q3 2020 to their top-
box scores for each of the same quarters one year earlier. For example, 
scores from Q1 2019 were compared to scores from Q1 2018, and scores 
from Q3 2020 (the most recent data available) were compared to scores 
from Q3 2019. The pre-COVID-19 quarters reveal the trend in HCAHPS 
scores prior to the onset of the pandemic. Each of these comparisons 
shown in Table V.H-1 includes the following:
     Official HCAHPS top-box scoring that adjusts for survey 
mode and patient mix.
     Restriction to hospitals with at least 25 completed 
surveys in each of the two matched quarters, so that the same types of 
hospitals that achieve 100 completes over four quarters for the 
Hospital VBP Program were used.
     Comparison was restricted to the same hospitals one year 
earlier, so that differential participation of hospitals during the 
excepted reporting period (Q1 and Q2 2020) did not distort results.
     Comparisons of parallel quarters were used, for example Q1 
to Q1, to neutralize any seasonal effects.
[GRAPHIC] [TIFF OMITTED] TR13AU21.259

    Results show that for Q1 2019 to Q4 2019, scores generally 
increased compared to the same quarter one year earlier, with changes 
of <1 top-box point. During the first COVID-19 impacted quarter, Q1 
2020, score differences were mixed, with top-box scores sometimes >1 
top-box point compared to a year earlier. That is, changes between Q1 
2019 and Q1 2020 were both positive and negative, with some changes 
exceeding 1 top-box point.
    During the COVID-19 impacted quarters of Q2 2020 and Q3 2020, 
scores were almost always lower than a year earlier, generally by 1-3 
top-box points except in the Q2 2020 vs. Q2 2019 comparison where 
scores increased to 0.54. These changes are statistically significant 
in all but one instance, often with p<0.0001, meaning that changes were 
too large to occur by chance more than one time in 10,000. These 
changes stand in sharp contrast to the patterns of small improvement 
prior to Q2 2020 discharges.
    We note that, in accordance with the ECE granted in response to the 
COVID-19 PHE discussed more fully in section V.H.7 of this final rule, 
submission of Q1 and Q2 CY 2020 HCAHPS data was optional. However, as 
previously mentioned, comparisons are based on hospitals with at least 
25 completed surveys in each of the two matched quarters. We do not 
believe that such a significant change in hospital

[[Page 45271]]

performance from the immediately preceding years for this measure would 
exist in the absence of the PHE for COVID-19.
    Additionally, in the September 2020 IFC, we noted that we would not 
use any Q1 or Q2 CY 2020 data to calculate a participating hospital's 
TPS for the applicable fiscal years (85 FR 54835). Because the FY 2022 
performance period for the HCAHPS measure is January 1, 2020 through 
December 31, 2020, we would only have 6 months of data (July 1, 2020 
through December 31, 2020) to calculate hospital performance on this 
measure. We believe that the third and fourth CY 2020 data would 
continue to demonstrate a deviation in national performance such that 
scoring this measure would not be representative of national or 
individual hospital quality of care.
    We also believe that suppressing this measure for the FY 2022 
program year will address concerns about the potential unintended 
consequences of penalizing hospitals that treated COVID-19 diagnosed 
patients. Therefore, we believe it is appropriate to suppress the 
HCAHPS measure for the FY 2022 Hospital VBP program year.
    We welcomed public comment on our proposal to suppress the HCAHPS 
measure for the FY 2022 program year.
    Comment: Many commenters expressed support for the proposal to 
suppress the HCAHPS measure for the FY 2022 program year due to the 
impacts of the COVID-19 PHE. The commenters agreed that hospital 
performance would likely be non-representative of individual hospital 
quality and they appreciate the stability that this suppression policy 
provides. Additionally, the commenters supported CMS' decision to not 
generate improvement or performance points for this measure.
    Response: We thank commenters for their support.
    Comment: A few commenters did not support the public reporting of 
HCAHPS measure data because the data are significantly impacted by the 
COVID-19 pandemic. The commenters asserted that displaying this 
information is likely to cause confusion or misinterpretation of 
quality among consumers. A commenter suggested that CMS should provide 
hospitals with the option to opt-in to public reporting as part of 
their confidential feedback review.
    Response: While we acknowledge commenters' concerns about publicly 
reporting data from the COVID-19 PHE, we disagree with the comment that 
we should not publicly report HCAHPS measure information for FY 2022. 
As noted above in section V.H.1. of this final rule, we place 
significant value on being as transparent as possible with the 
performance information that we collect, and we will make clear that 
that performance information was affected by the COVID-19 PHE. Further, 
we disagree with the suggestion to allow hospitals the option to opt-in 
to public reporting. We believe this may cause confusion and would 
provide an incomplete picture of the impact of COVID-19 on performance 
data.
    After consideration of the public comments we received, we are 
finalizing our proposal to suppress the HCAHPS measure for FY 2022 as 
proposed.
(3) Suppression of the Medicare Spending Per Beneficiary (MSPB) Measure 
(NQF #2158) for the FY 2022 Hospital VBP Program Year
    Pursuant to the measure suppression policy discussion in section 
V.H.1 of this final rule, we proposed to suppress the MSPB measure for 
the FY 2022 program year under proposed Measure Suppression Factor 4, 
significant national shortages or rapid or unprecedented changes in: 
(i) Healthcare personnel; (ii) medical supplies, equipment, or 
diagnostic tools or materials; or (iii) patient case volumes or 
facility-level case mix (86 FR 25473 through 25474. Based on our 
analysis, we have found that hospitalizations involving COVID-19 
overall tend to have higher mortality rates, longer lengths of stay, 
and higher observed, payment-standardized costs than hospitalizations 
without COVID-19. Based on our analysis, we believe that these rapid 
changes in patient case mix have significantly affected the MSPB 
measure. Under this proposal, we would calculate hospitals' MSPB 
measure rates, but we would not use these measure rates to generate 
achievement or improvement points for this measure. Additionally, 
because the MSPB measure is the only measure included in the Efficiency 
and Cost Reduction domain, we would not calculate hospitals' FY 2022 
Efficiency and Cost Reduction domain scores. Participating hospitals 
would continue to report the measure's data to CMS so that we can 
monitor the effect of the circumstances on quality measurement and 
determine the appropriate policies in the future. We would also 
continue to provide confidential feedback reports to hospitals as part 
of program activities to ensure that they are made aware of the changes 
in performance rates that we observe. We also intend to publicly report 
Q3 and Q4 2020 data where feasible and appropriately caveated.
    We note that in the September 2020 IFC, we stated that we would not 
use any first or second quarter CY 2020 data to calculate TPSs for the 
applicable fiscal years (85 FR 54835). We also note that the MSPB 
Hospital measure requires a 90-day lookback period to risk adjust the 
data appropriately. Third quarter CY 2020 data would require a lookback 
period of April 1, 2020 through July 1, 2020 for risk adjustments, but 
this period would fall within the excepted second quarter CY 2020 data. 
Therefore, for the FY 2022 program year, if we were to not suppress 
this measure, we would only be able to use hospital admissions data 
from Q4 of CY 2020 to calculate hospital scores for this measure.
    We conducted an analysis to assess the impact of COVID-19 on 
hospitalizations and several specific components of the MSPB measure, 
including length of stay, cost of inpatient stay, and proxy MSPB 
hospital episode costs (all costs from 3 days prior to admission to 30 
days post-discharge). This analysis used available data from January 1, 
2020 through November 22, 2020. We focused on MS-DRGs as the unit of 
analysis and comparison to examine the impact of COVID-19 generally on 
hospitalizations. We applied several data processing steps to ensure 
data completeness: we restricted the study population to beneficiaries 
with continuous enrollment in Parts A and B and with Medicare as 
primary payer, and who had data from three days prior to the inpatient 
hospital admission through 30 days post-hospital discharge during the 
study period. The analysis also required inpatient claims with a valid 
discharge date and a positive standard allowed amount to ensure that 
only claims that were paid under Medicare Parts A and B were captured. 
These data processing steps ensured the appropriate beneficiary 
population and data validity.
    During the study period, we observed significant impacts to patient 
case mix due to COVID-19. The majority of hospitals (67 percent) had at 
least one COVID-19 hospitalization, defined as the presence of a 
principal or secondary diagnosis for COVID-19 on the inpatient claim. 
There were nearly 250,000 COVID-19 hospitalizations, representing 
around 4 percent of all hospitalizations during the study period. As 
the study period ended in November 2020, our analysis does not capture 
increases in COVID-19 hospitalizations over the winter period. The MS-
DRG with the highest share of COVID-19 hospitalizations was MS-DRG 177 
for Respiratory Infections and Inflammations with Major Complication

[[Page 45272]]

or Comorbidity (MCC), with over 70 percent of those admissions 
involving COVID-19. The effect of COVID-19 was not limited to 
respiratory care; in fact, we observed COVID-19 diagnoses across MS-
DRGs in 25 Major Diagnostic Categories (MDCs) out of a total of 26 
MDCs. The only MDC without any COVID-19 hospitalizations was MDC 15 for 
Newborns & Other Neonates with Conditions Originating in Perinatal 
Period. These results indicate that there were substantial changes to 
the patient case mix across the full range of care provided by 
hospitals due to the influx of patients with COVID-19.
    Beyond the prevalence of COVID-19 amongst the hospital inpatient 
population, we tested the extent to which hospitalizations with COVID-
19 appeared different from those without COVID-19. We found that the 
mean and median lengths of stays where patients were diagnosed with 
COVID-19 were longer compared to patients not diagnosed with COVID-19 
(mean of 10 days compared to 7 days, respectively and median of 7 days 
compared to 5 days, respectively). We also examined various cost 
metrics, using payment-standardized amounts which remove the effect of 
the increased DRG payment weighting for hospitalizations with a COVID-
19 diagnosis on the inpatient claim. The mean cost of hospitalizations 
with a COVID-19 diagnosis on the inpatient claim was 44 percent greater 
than the mean cost of hospitalizations without a COVID-19 diagnosis 
($21,939 compared to $15,203). Our analysis was limited to examining 
inpatient hospitalizations, rather than the MSPB measure, as we focused 
on gaining a broader understanding of the changes to healthcare due to 
COVID-19. However, we did conduct some analyses to understand the post-
discharge period as the MSPB measure includes a 30-day post discharge 
period. We compared the cost of a proxy episode by looking at the costs 
from 3 days prior to admission, the hospitalization, and 30 days after 
discharge for patients with and without a COVID-19 diagnosis on the 
inpatient claim. The mean cost for patients diagnosed with COVID-19 was 
27 percent more than a hospital episode where the patient was not 
diagnosed with COVID-19 ($37,217 compared to $29,309). These results 
indicate that the differences in the cost of hospitalizations with and 
without COVID-19 extend to the post-discharge period. We believe that 
suppressing this measure for the FY 2022 program year would mitigate 
concerns about the impact of the significant changes in facility-level 
case mix and costs due to the PHE for COVID-19 on hospital performance 
and national comparability for this measure. Therefore, we believe it 
is appropriate to suppress the MSPB measure for the FY 2022 program 
year.
    We welcomed public comment on our proposal to suppress the MSPB 
measure for the FY 2022 program year.
    Comment: Many commenters supported CMS' proposal to suppress the 
MSPB measure and to not calculate improvement and achievement scores 
for FY 2022 under the Hospital VBP Program. Likewise, commenters 
supported not calculating Efficiency and Cost Reduction domain scores 
for FY 2022. A few commenters expressed gratitude for the stability 
provided by this proposal.
    Response: We thank commenters for their support.
    Comment: Several commenters did not support publicly reporting the 
MSPB measure data for FY 2022 because the data are significantly 
impacted by the COVID-19 PHE. Commenters noted that displaying this 
information will have limited value and is likely to cause confusion or 
misinterpretation of quality among consumers. A commenter suggested 
that CMS should provide hospitals with the option to opt-in to public 
reporting as part of their confidential feedback review.
    Response: We believe it is important to balance fairness in value-
based payments with the public's need for transparency. Therefore, we 
intend to make the data publicly available. We understand the 
commenters' concern about publicly reporting data from during the 
COVID-19 PHE; however, we will make clear in the public presentation of 
the data that the measure has been suppressed for purposes of scoring 
and payment adjustments because of the effects of the COVID-19 PHE. We 
will appropriately caveat the data in order to mitigate public 
confusion and avoid misrepresenting quality of care.
    After consideration of the public comments we received, we are 
finalizing our proposal to suppress the MSPB measure for FY 2022 as 
proposed.
(4) Suppression of the Five Healthcare-Associated Infection (HAI) 
Safety Measures for the FY 2022 Hospital VBP Program Year
    In the FY 2022 IPPS/LTCH PPS proposed rule (86 FR 25474 through 
25475), we proposed to suppress the five HAI Safety measures (CAUTI, 
CLABSI, Colon and Hysterectomy SSI, MRSA, and CDI) for the FY 2022 
program year under proposed Measure Suppression Factor 1, significant 
deviation in national performance on the measures, which could be 
significantly better or significantly worse compared to historical 
performance during the immediately preceding program years. We are 
concerned that the COVID-19 PHE affected measure performance on the 
current HAI measures such that we will not be able to score hospitals 
fairly or reliably. We would calculate hospitals' five HAI measure 
rates, but we would not use these measure rates to generate achievement 
or improvement points for these measures. Additionally, because these 
five measures make up the entirety of the Safety domain, we would not 
calculate hospitals' FY 2022 Safety domain score. Participating 
hospitals would continue to report the measure data to the CDC and CMS 
so that we can monitor the effect of the circumstances on quality 
measurement and determine the appropriate policies in the future. We 
would continue to provide confidential feedback reports to hospitals as 
part of program activities to ensure that they are made aware of the 
changes in performance rates that we observe. We also intend to 
publicly report CY 2020 Q3 and Q4 data where feasible and appropriately 
caveated.
    The previously established FY 2022 performance period for the HAI 
measures was January 1, 2020 through December 31, 2020. We note that in 
the September 2020 IFC, we stated that we would not use any first or 
second quarter CY 2020 data to calculate TPSs for the applicable fiscal 
years because we were concerned with the national comparability of 
these data due to the geographic differences of COVID-19 incidence 
rates and hospitalizations along with different impacts resulting from 
different State and local law and policy changes implemented in 
response to COVID-19 (85 FR 54835). However, we continue to be 
concerned about measure performance and the national comparability of 
such performance during the third and fourth quarter of CY 2020.
    The CDC conducted an analysis which found that the CLASBI, CAUTI, 
and MRSA measures had statistically significant measure rate increases 
during the third and fourth quarter of CY 2020 as compared to the third 
and fourth quarter of CY 2019. We believe that this distortion in 
measure performance may be due to circumstances unique to the effects 
of the pandemic such as staffing shortages and turnover, patients that 
are more susceptible to infections due to increased hospitalization 
stays, and longer indwelling catheters and central lines. In a March 
comparison run

[[Page 45273]]

between Q4 2019 and Q4 2020 data for hospitals that submitted complete 
data for both quarters, there was a national percent change in the 
standardized infection ratio (SIR), or the primary summary measure used 
by the NHSN to track healthcare associated infections, of 48.1 percent 
for CLABSI, 18.8 percent for CAUTI and 33.8 percent for MRSA. For the 
SSI and CDI measures, neither measure had a statistically significant 
increase or decrease during the third and fourth quarter of CY 2020 as 
compared to the third and fourth quarter of CY 2019. For the SSI 
measure, the low reporting volume is due to the decrease in surgeries 
during the pandemic, while the CDI measure has historically been 
declining. Though the pandemic may not have the same clinical impact on 
the SSI and CDI measures, we believe that due to the low reporting 
volume of these two measures and for maintaining consistency of the 
full CDC NHSN HAI measure set, all five CDC NHSN HAI measures should be 
suppressed instead of just 3 of them. We are also concerned that if we 
were to suppress three measures in the Safety domain while continuing 
to score hospitals on the remaining two measures in the Safety domain, 
the Safety domain scores may be significantly better or significantly 
worse than in immediately preceding years. Therefore, we believe it is 
appropriate to suppress all five HAI measures in the Safety domain to 
ensure an accurate and reliable national comparison of performance on 
hospital safety.
    In determining how to address the impact of the COVID-19 PHE on the 
five HAI measures, we also considered extending the FY 2022 performance 
periods for the five HAI measures so that they would include 1 full 
year of measure data. However, because the performance period for the 
FY 2022 program year began on January 1, 2020, we believe that changing 
the performance period after January 1, 2020 would be unfair and 
confusing for hospitals. Using data from CY 2019 would require us to 
score hospitals on data on which they have already been scored in the 
FY 2021 program year. Additionally, using data from CY 2021 would 
require us to change the performance periods for all future program 
years in order to avoid using the same data twice. Scoring hospitals on 
the same data for multiple program years may cause hospitals that have 
improved on their performance to be penalized more than once or allow 
hospitals that have not improved to be rewarded on their performance 
more than once. Further, changing the performance periods for these 
measures could create administrative costs for hospitals that would be 
required to change their reporting systems and workflows.
    We also considered making no modifications to the program and 
suppressing no measure data from CY 2020 for assessing FY 2022 HAI 
measure scores as an additional alternative to using the measure 
suppression policy. This alternative would be operationally easier to 
implement but would mean assessing participating hospitals using 
quality measure data that has been impacted by the COVID-19 PHE without 
additional adjustments to the measures. Additionally, given the 
geographic disparities in the COVID-19 PHE's effects, this policy could 
place hospitals in regions that were hit harder by the pandemic at a 
disadvantage. Ultimately, we believe that our proposal to suppress the 
HAI measure data from CY 2020 more fairly addresses the impact of the 
COVID-19 PHE on participating hospitals. Therefore, in order to 
maintain program consistency and avoid scoring hospitals on the same 
data for more than one program year, we proposed to suppress all five 
HAI measures in the Safety domain for the entire FY 2022 program year.
    We welcomed public comment on our proposal to suppress the five HAI 
measures for the FY 2022 program year.
    Comment: Many commenters expressed support for suppressing the HAI 
measures in the Hospital VBP Program. A commenter believed that the 
impact of COVID-19 on hospitals differs across the country and the 
measures submitted during the PHE are distorted, unreliable, and not 
accurate indicators of hospital quality.
    Response: We thank commenters for their support.
    Comment: Several commenters supported the suppression of the HAI 
measures, but recommended that the measure data not be publicly 
reported. Commenters noted that displaying this information will have 
limited value and is likely to cause confusion or misinterpretation of 
quality among consumers.
    Response: We believe it is important to balance fairness in value-
based payments with the public's need for transparency. Therefore, we 
intend to make the data publicly available. We understand the 
commenters concern about publicly reporting data from during the COVID-
19 PHE; however, we will make clear in the public presentation of the 
data that the measures have been suppressed for purposes of scoring and 
payment adjustments because of the effects of the COVID-19 PHE. We will 
appropriately caveat the data in order to mitigate public confusion and 
avoid misrepresenting quality of care.
    Comment: A commenter did not support the proposal to suppress 
patient safety data related to HAIs, believing that removing any 
financial penalty was sufficient to address any difficulties in meeting 
value-based performance standards and recommended continued collection 
of the data.
    Response: We note that the measure suppression policy provides for 
the continued collection and use of HAI data to calculate hospitals' 
five HAI measure rates, because we believe patient safety and the 
continued monitoring and tracking of HAIs are high priorities, however, 
we will not use these measure rates to generate achievement or 
improvement points for these measures under the FY 2022 Hospital VBP 
Program. Participating hospitals will continue to report the measure's 
data to the CDC and CMS so that we can monitor the effect of the 
circumstances on quality measurement and determine the appropriate 
policies in the future. We will also continue to provide confidential 
feedback reports to hospitals through the previously established 
processes, including the information available to hospitals via the 
CDC's National Healthcare Safety Network, as part of program activities 
to ensure that hospitals are made aware of the changes in performance 
rates that we observe, and to make the information publicly available 
with appropriate caveats. As described more fully in section V.H.1.a. 
of this final rule, we have identified the need for flexibility in our 
quality programs to account for the impact of changing conditions that 
are beyond participating hospitals' control. We do not believe that 
removing the financial penalty alone for the FY 2022 program year is 
sufficient to address the difficulties in meeting value-based 
performance standards due to the impact of the COVID-19 pandemic on 
performance measurement for FY 2022 and instead believe that the 
measure suppression policy and the special scoring and payment rule for 
FY 2022 finalized in sections V.H.1.a and V.H.6.a. of this final rule 
provide the flexibility to determine if a specific measure or measures 
have been impacted by external factors for a program year in addition 
to not penalizing hospitals for performance on measures that may not 
reflect the quality of the care provided due to the COVID-19 pandemic. 
Therefore, we are finalizing our proposal to adopt a measure

[[Page 45274]]

suppression policy that provides for the application of measure 
suppression factors to help us evaluate the Hospital VBP Program's 
measures in section V.H.1.a. of this final rule as well as finalizing 
our special scoring and payment rule for FY 2022 in section V.H.6.a. We 
also believe that the adoption of the measure suppression policy in the 
other value-based purchasing programs will help ensure consistency in 
our measure evaluations across programs. For example, we note we are 
finalizing suppression of the five HAI measures in the HAC Reduction 
Program for the same portion of the performance period applicable to 
these measures; however, because the HAC Reduction Program typically 
uses a 2-year instead of 1-year performance period, there will be 
sufficient data not impacted by the COVID-19 PHE to calculate HAC 
Reduction Program payment adjustments for FY 2022.
    After consideration of these public comments, we are finalizing our 
proposal to suppress the five HAI measures for FY 2022 as proposed.
(5) Suppression of the Hospital 30-Day, All-Cause, Risk-Standardized 
Mortality Rate Following Pneumonia Hospitalization (MORT-30-PN) Measure 
(NQF #0468) for the FY 2023 Program Year
    In the FY 2022 IPPS/LTCH PPS proposed rule (86 FR 25475 through 
25477), we proposed to suppress the MORT-30-PN measure beginning with 
the FY 2023 program year under proposed Measure Suppression Factor 2, 
clinical proximity of the measure's focus to the relevant disease 
pathogen or health impacts of the national PHE. COVID-19 is caused by 
SARS-CoV-2, which begins when respiratory droplets containing the virus 
enter an individual's upper respiratory tract. Pneumonia has been 
identified as a typical characteristic of individuals infected with 
COVID-19,\787\ and our analysis based on data from CY 2020 shows that a 
substantial portion of the MORT-30-PN measure cohort includes 
admissions with either a principal or a secondary diagnoses of COVID-
19. In addition, almost all of the admissions with a COVID-19 diagnosis 
have a principal diagnosis of sepsis; observed mortality rates for 
these admissions are extremely high and are substantially higher than 
admissions without a COVID-19 diagnosis. Finally, observed mortality 
rates in admissions without a COVID-19 diagnosis (using data from April 
2020 through June 2020) are higher than observed mortality rates from 
the prior year. For the currently available data for this measure, 
there is a high percentage of Medicare beneficiaries with a secondary 
diagnosis of COVID-19 in the measure cohort during CY 2020. We would 
calculate hospitals' MORT-30-PN measure rates, but we would not use 
these measure rates to generate achievement and improvement points for 
this measure. We will continue to monitor the claims that form the 
basis for this measure's calculations to evaluate the effect of the 
circumstances on quality measurement and to determine the appropriate 
policies in the future. We would also continue to provide confidential 
feedback reports to hospitals as part of program activities to ensure 
that they are made aware of the changes in performance rates that we 
observe.
---------------------------------------------------------------------------

    \787\ 957 Zheng, Jun. SARS-CoV-2: An Emerging Coronavirus that 
Causes a Global Threat. Int J Biol Sci. 2020; 16(10): 1678-1685. 
Published online 2020 Mar 15. doi: 10.7150/ijbs.45053.
---------------------------------------------------------------------------

    As previously discussed, the FY 2022 MORT-30-PN performance period 
is September 1, 2017 through June 30, 2020. However, in the September 
2020 IFC, we noted that we would not use any first or second quarter CY 
2020 data to calculate TPSs for the applicable fiscal years (85 FR 
54835). With this exception, the FY 2022 performance period for this 
measure would only be affected by a shortened performance period 
(September 1, 2017 through December 31, 2019) that does not use data 
from the COVID-19 PHE. Therefore, we have decided that it is not 
necessary to suppress this measure for the FY 2022 program year. 
However, given the ongoing status of the PHE and the impact of COVID-19 
on this measure data, we proposed to suppress this measure for the FY 
2023 program year.
    Our analysis of the MORT-30-PN measure data showed that the MORT-
30-PN cohort had a higher proportion of patients with a secondary 
diagnosis of COVID-19 than the cohorts for the other condition-specific 
mortality measures used in the Hospital VBP Program, and that these 
patients have a higher risk of mortality than the remainder of the 
patients included in the pneumonia measure cohort.
BILLING CODE 4120-01-P
[GRAPHIC] [TIFF OMITTED] TR13AU21.260


[[Page 45275]]


[GRAPHIC] [TIFF OMITTED] TR13AU21.261

BILLING CODE 4120-01-C
    Data from September 2020 also showed that although admission 
volumes for the MORT-30-PN cohort were substantially lower compared to 
admission volumes for this cohort in September 2019, the observed 
mortality rates for this cohort were statistically significantly higher 
in September 2020 when compared to the observed mortality rates for 
this cohort during the same period in 2019.
    Our analyses also demonstrated that almost all of the COVID-19 
patients captured in the MORT-30-PN measure cohort likely represent a 
distinct, severely ill group of patients (with a mortality rate of 49.2 
percent as compared 23.8 percent for patients without a COVID-19 
diagnosis) for whom it may be difficult to adequately ascertain 
appropriate risk adjustment. In addition, our analyses found that the 
odds ratio of mortality for COVID-19 as a risk factor was very high 
(4.67, 95 percent confidence interval: 4.45-4.90) as compared to other 
diagnoses such as metastatic cancers, acute leukemia, and other severe 
cancers (2.16, 95 percent confidence interval: 2.05-2.28), protein-
calorie malnutrition (1.64, 95 percent confidence interval: 1.57-1.71), 
dementia or specified brain disorders (1.58, 95 percent confidence 
interval: 1.51-1.64), and chronic liver disease (1.50, 95 percent 
confidence interval: 1.37-1.64). We also calculated the Pearson 
correlation between the change in observed 30-day pneumonia mortality 
rate and Medicare COVID-19 burden (defined as COVID-19-related 
hospitalizations per Medicare beneficiary) for both a 3-months (March-
May) and 12-months (June-May) period. That is, we calculated the change 
in observed 30-day pneumonia mortality rates between March-May 2019 (3-
months) and March-May 2020, and also between June 2018-May 2019 and 
June 2019-May 2020 (12-months). We then assessed the correlation 
between these changes in observed pneumonia mortality rates and 
Medicare COVID-19 burden. Changes in observed 30-day pneumonia 
mortality rates were highly and statistically significantly correlated 
with Medicare COVID-19 burden when analyzing the 3-month and 12-month 
periods (Pearson correlation of 0.77 and 0.69, respectively).
    We considered whether we could exclude patients with a diagnosis of 
COVID-19 from the MORT-30-PN cohort, but we determined suppression will 
provide us with additional time and additional months of data 
potentially impacted by COVID-19 to more thoroughly evaluate a broader 
range of alternatives, given the month-to-month variation in the 
percent of COVID-19 diagnoses as shown in Table V.H-3. We want to 
ensure that the measure reflects care provided by the hospital to 
Medicare beneficiaries admitted with pneumonia and we are concerned 
that excluding a significant proportion of all eligible patients may 
not accurately reflect the care provided, particularly given the 
unequal distribution of COVID-19 patients across hospitals over time. 
We believe that suppressing this measure beginning with the FY 2023 
program year would address this concern.
    As part of our analysis, we also evaluated the impact of 
suppressing the MORT-30-PN measure on hospital eligibility, program 
scoring, and payment for FY 2023. We used data from the most recently 
completed program year, FY 2021, to simulate removal of the MORT-30-PN 
measure as compared to the baseline data.\788\ For purposes of this 
simulation, we assumed that all other measures in the Hospital VBP 
Program would remain in the program and that hospital performance on 
these measures would remain unchanged from their historical performance 
on these measures. Based on this simulation, we found that the 
suppression of the MORT-30-PN measure resulted in less than a one 
percent decrease in overall eligibility for the Hospital VBP Program; 
the average TPS for participating hospitals decreased by 0.4 points; 
and the number of hospitals receiving a payment increase was reduced by 
one percentage point. Therefore, we believe that suppressing the MORT-
30-PN measure minimizes negative impacts on the eligibility, scoring 
and payment distributions under the Hospital VBP Program and at this 
time we did not propose to make any changes to the FY 2023 scoring 
methodology as a result.
---------------------------------------------------------------------------

    \788\ We note that this analysis did not include the MORT-30-
CABG measure because it it not included in the Hospital VBP Program 
unitl FY 2022 (81 FR 56996 through 56998).
---------------------------------------------------------------------------

    We invited public comment on our proposal to suppress the MORT-30-
PN measure for the FY 2023 program year.
    Comment: Most commenters expressed support for suppressing the 
MORT-30-PN measure for the FY 2023 Hospital VBP program year and agreed 
that the clinical proximity of pneumonia to COVID-19 was significant 
enough to impact hospital performance.
    Response: We thank the commenters for their support.
    Comment: Several commenters encouraged CMS to continue to monitor 
claims data to evaluate the effect of the ongoing public health 
emergency on quality measurement and determine if there is a need for 
ongoing suppression of the MORT-30-PN measure in additional fiscal 
years.
    Response: We understand the COVID-19 PHE is ongoing and the effects 
may continue to impact this measure into the future. Although we are 
finalizing that we will suppress the MORT-30-PN measure for the FY 2023 
program year, we will continue to monitor claims used in the 
calculation of this measure to evaluate the effect on quality 
measurement and to consider whether there is a need to consider 
additional policies for this measure in future rulemaking.
    Comment: Some commenters expressed concern regarding public 
reporting of the MORT-30-PN measure. They noted that public reporting 
of the measure results may adversely impact hospital rankings and may 
not adequately support decision making.
    Response: We acknowledge the commenters' concerns about publicly 
reporting data from the COVID-19 PHE and agree that publicly reported 
measure information is important for stakeholder decision making as 
well as other purposes such as transparency. We will provide 
confidential feedback reports to hospitals for the MORT-30-PN measure 
as currently specified. In these confidential reports, hospitals will 
be able to see which of their patients died to inform hospital quality 
improvement initiatives. We believe it is

[[Page 45276]]

important to balance fairness in value-based payments with the public's 
need for transparency. Therefore, we intend to make the data publicly 
available. We understand the commenters concern about publicly 
reporting data from during the COVID-19 PHE; however, we will make 
clear in the public presentation of the data that the MORT-30-PN 
measure has been suppressed for purposes of scoring and payment 
adjustments because of the effects of the COVID-19 PHE. We will 
appropriately caveat the data in order to mitigate public confusion and 
avoid misrepresenting quality of care.
    After consideration of the public comments we received, we are 
finalizing our proposal to suppress the MORT-30-PN measure for FY 2023 
as proposed.
2. FY 2022 Program Year Payment Details
    Section 1886(o)(7)(B) of the Act instructs the Secretary to reduce 
the base operating DRG payment amount for a hospital for each discharge 
in a fiscal year by an applicable percent. Under section 1886(o)(7)(A) 
of the Act, the sum of these reductions in a fiscal year must equal the 
total amount available for value-based incentive payments for all 
eligible hospitals for the fiscal year, as estimated by the Secretary. 
We finalized details on how we would implement these provisions in the 
FY 2013 IPPS/LTCH PPS final rule (77 FR 53571 through 53573), and we 
refer readers to that rule for further details. We note that in section 
V.H.1. of this final rule, we are finalizing our proposal to suppress 
several measures in the Hospital VBP Program for the FY 2022 Program 
Year.
    Under section 1886(o)(7)(C)(v) of the Act, the applicable percent 
for the FY 2022 program year is two percent. Using the methodology, we 
adopted in the FY 2013 IPPS/LTCH PPS final rule (77 FR 53571 through 
53573), we estimate that the total amount available for value-based 
incentive payments for FY 2022 is approximately $1.9 billion, based on 
the December 2020 update of the FY 2020 MedPAR file.
    As finalized in the FY 2013 IPPS/LTCH PPS final rule (77 FR 53573 
through 53576), we utilize a linear exchange function to translate this 
estimated amount available into a value-based incentive payment 
percentage for each hospital, based on its Total Performance Score 
(TPS). We then calculate a value-based incentive payment adjustment 
factor to apply to the base operating DRG payment amount for each 
discharge occurring in FY 2022, on a per-claim basis. In the FY 2022 
IPPS/LTCH PPS proposed rule, we published the proxy value-based 
incentive payment adjustment factors in Table 16 associated with the 
proposed rule (which is available via the internet on the CMS website) 
(86 FR 25477 through 25478) using the previously established scoring 
methodology without any modifications based off our proposals. The TPSs 
from the FY 2021 program year are the basis for the proxy factors. 
These FY 2021 performance scores are the most recently available 
performance scores hospitals have been given the opportunity to review 
and correct. We note that the FY 2021 TPSs were calculated using 
measure data from before the COVID-19 PHE was declared. We refer 
readers to sections V.H.1. and V.H.6. of this final rule for additional 
information on the impacts of the COVID-19 PHE on the Hospital VBP 
Program.
    In the proposed rule, we stated that if our proposals to suppress 
measures and award each hospital a value-based payment amount that 
matches the reduction to the base operating DRG payment amount are 
finalized, we would not update Table 16 as Table 16A in the final rule 
(86 FR 25478 through 25478). We also noted that if those proposed 
provisions are not finalized, we would update this table as Table 16A 
in the final rule (which will be available on the CMS website) to 
reflect changes based on the March 2021 update to the FY 2020 MedPAR 
file. We would also update the slope of the linear exchange function 
used to calculate those updated proxy value-based incentive payment 
adjustment factors. The updated proxy value-based incentive payment 
adjustment factors for FY 2022 would continue to be based on historic 
FY 2021 program year TPSs because hospitals will not have been given 
the opportunity to review and correct their actual TPSs for the FY 2022 
program year before the FY 2022 IPPS/LTCH PPS final rule is published. 
Because we are finalizing our proposed measure suppression and scoring 
and payment policies in response to PHE due to COVID-19, we will not 
update Table 16 as Table 16A in this final rule.
    We stated in the FY 2022 IPPS/LTCH PPS proposed rule (86 FR 25478) 
that if our proposed provisions to suppress measures and award each 
hospital a value-based payment amount that matches the reduction to the 
base operating DRG payment amount are finalized, we would also not post 
Table 16B (which we typically do to display the actual value-based 
incentive payment adjustment factors, exchange function slope, and 
estimated amount available for the applicable program year, after 
hospitals have been given an opportunity to review and correct their 
actual TPSs). Because we are finalizing our proposed measure 
suppression and scoring and payment policies in response to the COVID-
19 PHE, we will not post a Table 16B.
    We received public comments on our proposed payment policy to 
suppress measures and award each hospital a value-based payment amount 
that matches the reduction to the base operation DRG payment amount for 
FY 2022.
    Comment: Several commenters expressed support for the FY 2022 
special payment policy to avoid unfairly penalizing hospitals that were 
impacted by the COVID-19 PHE. A commenter noted that providing bonuses 
or penalties based on measure data that may be skewed would be 
inappropriate. A commenter also expressed appreciation for the 
stability provided by a budget-neutral solution for hospitals. A 
commenter noted that applying neutral payment adjustments for FY 2022 
is both appropriate and well within CMS' statutory discretion.
    Response: We thank commenters for their support.
    Comment: A few commenters noted that awarding all hospitals a net-
neutral payment adjustment may be penalizing hospitals that have 
historically performed well under the Hospital VBP Program. A few 
commenters noted that many hospitals rely on bonuses from the Hospital 
VBP Program as part of their budgets.
    Response: We appreciate commenters concerns, however, the proposed 
flexibilities are intended to best mitigate the unprecedented effects 
of the COVID-19 PHE on hospitals participating in the Hospital VBP 
Program and our concern in the ability to make fair, national 
comparisons of hospitals across the country. A we noted in section 
V.H.1. of this final rule, we remain significantly concerned that 
Hospital VBP Program quality measure scores that are calculated using 
data submitted during the PHE for COVID-19 are distorted due to the 
impact of the COVID-19 PHE and will result in skewed payment incentives 
and inequitable payments. Though we recognize that some hospitals that 
may have otherwise received a positive payment incentive during a 
regular program year without the unexpected occurrence of the COVID-19 
PHE would receive a net neutral adjustment under the proposed payment 
policy, we do not believe it is appropriate to penalize any hospitals 
with negative payment adjustments based on measure scores that we 
believe are distorted by the COVID-19 PHE and, thus, not reflective

[[Page 45277]]

of the quality of care that the measures in the Hospital VBP Program 
were designed to assess. As discussed in section V.H.1. of this final 
rule, we considered alternative approaches, but determined that the 
proposed approach would best serve the Hospital VBP Program and its 
participants as a whole to provide short-term relief when we have 
determined that one or more of the Measure Suppression Factors warrants 
the suppression of the majority of the Hospital VBP Program's measures. 
We view the measure suppression proposal as a necessity to ensure that 
the Hospital VBP Program does not reward or penalize hospitals based on 
circumstances caused by the PHE for COVID-19 that the Program's 
measures were not designed to accommodate.
    After consideration of the public comments we received, we are 
finalizing the FY 2022 special payment policy as proposed and codifying 
this policy at Sec.  412.168.
3. Retention and Removal of Quality Measures
a. Retention of Previously Adopted Hospital VBP Program Measures and 
Relationship Between the Hospital IQR and Hospital VBP Program Measure 
Sets
    In the FY 2013 IPPS/LTCH PPS final rule (77 FR 53592), we finalized 
a policy to retain measures from prior program years for each 
successive program year, unless otherwise proposed and finalized. In 
the FY 2019 IPPS/LTCH PPS final rule (83 FR 41440 through 41441), we 
finalized a revision to our regulations at Sec.  412.164(a) to clarify 
that once we have complied with the statutory prerequisites for 
adopting a measure for the Hospital VBP Program, the statute does not 
require that the measure continue to remain in the Hospital IQR 
Program. We did not propose any changes to these policies.
b. Measure Removal Factors for the Hospital VBP Program
    In the FY 2019 IPPS/LTCH PPS final rule (83 FR 41441 through 
41446), we finalized measure removal factors for the Hospital VBP 
Program, and we refer readers to that final rule for details. We did 
not propose any changes to these policies.
c. Removal of the CMS Patient Safety and Adverse Events Composite (CMS 
PSI 90) (NQF #0531) Beginning With the FY 2023 Program Year
    We proposed to remove the CMS Patient Safety and Adverse Events 
Composite (CMS PSI 90) measure (NQF #0531) from the Hospital VBP 
Program under removal Factor 8--the costs associated with the measure 
outweigh the benefit of its use in the program (86 FR 25478 through 
25479). Factor 8 is a measure removal factor finalized in the FY 2019 
IPPS/LTCH PPS final rule (83 FR 41441 through 41446).
    We adopted the CMS PSI 90 composite measure (NQF #0531) in the FY 
2018 IPPS/LTCH PPS final rule (82 FR 38251 through 38256) beginning 
with the FY 2023 program year to encourage improvement in patient 
safety for all hospitals, and we also adopted a performance period for 
that program year that runs from July 1, 2019 through June 30, 2021. We 
continue to consider patient safety a high priority, but because the 
CMS PSI 90 measure is also used in the HAC Reduction Program, we 
believe removing this measure from the Hospital VBP Program will reduce 
the provider and clinician costs associated with tracking duplicative 
measures across programs. We noted in prior rulemaking that we would 
continue to monitor the HAC Reduction Program and Hospital VBP Program 
and analyze the impact of our measure selection, including any 
unintended consequences with having a measure in more than one program, 
and would revise the measure set in one or both programs if needed (82 
FR 38255). Since then, we have considered the impact of having the CMS 
PSI 90 measure in both the HAC Reduction Program and the Hospital VBP 
Program. We note that the modified version of the CMS PSI 90 measure 
was adopted for use in the FY 2018 HAC Reduction Program as finalized 
in the FY 2017 IPPS/LTCH PPS final rule (81 FR 57020). While both 
programs will require reporting on the same measure beginning in FY 
2023, we have reconsidered whether the differences in the scoring 
methodologies for measuring performance in these two programs presents 
unneeded complexity in tracking duplicative measures while accounting 
for differences in applicability. For example, the scoring methodology 
for the CMS PSI 90 measure for the Hospital VBP Program includes 
comparing an individual hospital's performance during the performance 
period to all hospitals' performance during an established baseline 
period and a hospital can be awarded improvement points by comparing an 
individual hospital's performance during the performance period to that 
same individual hospital's performance from the baseline period; the 
HAC Reduction Program assesses performance using an equally weighted 
average of scores across measures included in the program and does not 
require a baseline period for scoring purposes. Hospitals may also 
incur additional cost to monitor measure performance and potential 
payment impact in two programs, given that each program has a different 
scoring methodology that applies to the same measure. We also believe 
removing the CMS PSI 90 measure from the Hospital VBP Program is 
appropriately responsive to feedback from stakeholders who have noted 
that using the same measure in different programs creates additional 
administrative costs to hospitals rather than further incentivizing 
improved performance. We have noted in previous years that we believe 
costs are multifaceted and include not only the burden associated with 
reporting, but also the costs CMS incurs to implement and maintain the 
measure in the program (83 FR 41442). Maintaining this measure in both 
the HAC Reduction Program and the Hospital VBP Program and applying two 
different scoring methodologies requires CMS to expend resources for 
analyzing performance and developing duplicative feedback reports for 
its use in both programs. For example, due to the differences in 
scoring methodologies between the HAC Reduction Program and the 
Hospital VBP Program, CMS may be required to utilize and maintain 
multiple versions of the CMS PSI software used to calculate PSIs and 
the composite measure across the two programs. Further, since 2017, we 
have worked to reduce regulatory burden on hospitals, lower health care 
costs, and enhance patient care by streamlining the quality reporting 
and value-based purchasing programs through the Meaningful Measures 
Framework. We refer readers to the FY 2019 IPPS/LTCH PPS final rule for 
a broader discussion of the Meaningful Measures Framework (83 FR 
41147). Two of the primary objectives of the Meaningful Measures 
Framework are to include quality measures for which there is 
significant opportunity for improvement and to minimize the level of 
burden for providers. We recognize that the Hospital VBP Program 
currently uses five other patient safety-focused measures (CAUTI, 
CLABSI, CDI, MRSA, and SSI) that are also used under the HAC Reduction 
Program. As noted in prior rulemaking, we continue to monitor and 
analyze measures that are in both the HAC Reduction Program and 
Hospital VBP Program to assess the impact of having a measure in more 
than one program and to revise the measure set in one or both programs 
if needed (82 FR 38255). We focused our initial analysis on the impact 
of the CMS PSI 90 measure in the Hospital

[[Page 45278]]

VBP Program rather than the other five patient safety-focused measures 
because we believe it would be least burdensome to remove now, before 
hospitals are required to begin reporting on the measure for the FY 
2023 Hospital VBP program year. Furthermore, as previously noted, the 
Hospital VBP Program requires that the software used to calculate 
measure scores between the baseline and performance period must match, 
whereas the HAC Reduction Program does not include baseline periods and 
can therefore more easily implement measure scoring. At this time, we 
believe there is significant opportunity for the remaining five patient 
safety-focused measures to continue encouraging improvement in patient 
safety in both the Hospital VBP Program and the HAC Reduction Program 
and will continue to monitor and analyze the impact of these measures 
and assess the need for revisions in future rulemaking. We note that 
the Hospital VBP Program uses the same processes adopted by the HAC 
Reduction Program for hospitals to review and correct data for the CDC 
NHSN HAI measures and relies on HAC Reduction Program validation to 
ensure the accuracy of CDC NHSN HAI measure data used in the Hospital 
VBP Program.
    Accordingly, for the previously discussed reasons, we proposed to 
remove the CMS PSI 90 measure from the Hospital VBP Program beginning 
with the FY 2023 program year.
    We welcomed public comment on this proposal to remove the CMS PSI 
90 measure beginning with FY 2023.
    Comment: Many commenters expressed support for the removal of the 
CMS PSI 90 measure. Many commenters expressed agreement with the 
removal of the CMS PSI 90 measure under removal Factor 8, the costs 
associated outweigh the benefit to the program, believing the measure's 
duplicative reporting increases burden and administrative costs; it 
does not incentivize or improve quality care; and is a composite 
measure that does not readily identify individual components for 
improvement. A commenter noted that the CMS PSI 90 measure is a flawed 
measure. A commenter expressed significant concerns about the measure's 
construction and its ability to provide actionable information to 
providers. A commenter expressed concerns that some components of the 
CMS PSI 90 measure focus on surgical care which can disadvantage 
hospitals with larger volumes of surgical care.
    A few commenters recommended removal of the CMS PSI 90 measure from 
other quality programs, including the HAC Reduction Program and all 
other quality programs. A commenter specifically supported the 
measure's removal in the Hospital VBP Program and retention in the HAC 
Reduction Program.
    Response: We thank the commenters for their support. We note that 
we did not propose to remove the CMS PSI 90 measure in the HAC 
Reduction or other quality programs in the FY 2022 IPPS/LTCH PPS 
proposed rule and believe that maintaining the CMS PSI 90 measure in 
the HAC Reduction Program is necessary to continue tracking hospital 
quality on important patient safety and adverse event outcomes and to 
maintain a strong financial incentive focused on patient safety.
    Comment: Many commenters did not support the removal of the CMS PSI 
90 measure. A few commenters stated that the CMS PSI 90 measure is 
directly tied to safety by providing a representative picture of 
hospital safety and driving the focus of safety, and therefore, the 
measure should be retained to continue prioritizing patient safety.
    Response: We appreciate the commenters concerns and note that we 
continue to consider patient safety a high priority. We agree that the 
CMS PSI 90 measure is an important measure and note that it remains in 
use in the HAC Reduction Program where it accounts for 16 percent of 
the Total HAC Score as one of the six equally-weighted measures that 
comprise the HAC Reduction Program measure set. We note the equal 
weighting scoring methodology in the HAC Reduction Program allows for 
the CMS PSI 90 measure to have greater weight in the calculation of the 
Total HAC Score compared to the weight of the CMS PSI 90 measure in 
Hospital VBP Program. In addition, under the HAC Reduction Program, if 
a hospital does not have sufficient data to score one or more of the 
five HAI measures, the CMS PSI 90 measure could be assigned an even 
greater portion of the Total HAC Score. In comparison, under the 
Hospital VBP Program, the CMS PSI 90 measure is one of 14 measures and 
is included in the Safety domain, which is weighted at 25 percent of 
the TPS, along with five HAI measures, which results in the CMS PSI 90 
measure accounting for approximately 4 percent of the TPS. This 
potentially allows a hospital to not perform well on the CMS PSI 90 
measure and the Safety domain, and still do well in the Hospital VBP 
Program if they perform well relative to other hospitals on the other 
measures and domains in the program We believe the greater weight 
attributed to the CMS PSI 90 measure in the HAC Reduction Program, and 
the risk of a hospital ranking within the worst-performing quartile of 
hospitals under the HAC Reduction Program by not performing well on the 
CMS PSI 90 measure, will continue to promote and prioritize patient 
safety for hospitals. Furthermore, under the HAC Reduction Program's 
payment methodology, because the penalty is applied to the worst-
performing quartile of hospitals after ranking them based on their 
respective Total HAC Scores, if a hospital which did not receive a 
penalty does not continue to improve their performance on the measures 
while other hospitals continue to make improvements, over time such a 
hospital will worsen in rank and be at risk for falling within the 
worst-performing quartile and being penalized. Additionally, with only 
six measures in the HAC Reduction Program, improvement on a single 
measure, such as the CMS PSI 90 measure, can have a greater impact on 
whether a hospital receives a penalty under the HAC Reduction Program. 
That is, a hospital that may receive a penalty under the HAC Reduction 
Program can improve their performance on the CMS PSI 90 measure and 
increase their chances of not receiving a penalty under the HAC 
Reduction Program more so than the impact on their TPS under the 
Hospital VBP Program. In addition, hospitals' performance on the CMS 
PSI 90 measure will continue to be publicly reported on the Care 
Compare website and be used in the Overall Hospital Star Ratings.
    We also believe there is significant opportunity for the remaining 
five patient safety-focused measures in the Hospital VBP Program to 
continue encouraging improvement in patient safety in both the Hospital 
VBP Program and the HAC Reduction Program along with the continued use 
of the CMS PSI 90 measure in the HAC Reduction Program and public 
reporting of hospital performance information on the Care Compare 
website. In addition, as part of our commitment to patient safety, we 
are developing new digital quality measures that use data from hospital 
EHRs that would assess various aspects of patient safety in the 
inpatient care setting. For example, two recently developed measures, 
Hospital Harm-Severe Hyperglycemia eCQM (NQF #3533e) and Hospital Harm-
Severe Hypoglycemia eCQM (NQF #3503e) have been proposed and are being 
finalized for the Hospital IQR Program, as discussed in the FY 2022 
IPPS/LTCH PPS proposed rule (86 FR 25076) and in

[[Page 45279]]

section X.C.5.d and IX.C.5.e of this final rule. In addition to 
finalizing the Severe Hyperglycemia and Severe Hypoglycemia patient 
safety measures in this rulemaking cycle, we will also consider a 
composite harm measure which includes several patient safety and harm 
measures when all other harm measures such as pressure injury, falls 
with injury, acute kidney injury, and medication related bleeding are 
fully developed.
    Comment: A commenter noted there are multi-faceted benefits to 
retaining measures in multiple value-based purchasing programs. A 
commenter stated that the measure should be retained because there are 
important differences between the Hospital VBP Program and HAC 
Reduction Program.
    Response: We believe removing the CMS PSI 90 measure from the 
Hospital VBP Program is appropriately responsive to feedback from 
stakeholders who have noted that using the same measure in different 
programs including different software versions of the measure has 
created additional administrative costs to hospitals rather than 
further incentivizing improved performance. We also note, as discussed, 
the difference in CMS PSI 90 measure weight in the HAC Reduction 
Program compared to the Hospital VBP Program, and we believe that 
retaining the measure in the HAC Reduction Program where the CMS PSI 90 
measure is weighted at approximately 16 percent of the Total HAC Score, 
as well as continued public reporting of hospitals' CMS PSI 90 
performance, will continue to incentivize hospitals to maintain a 
strong focus on patient safety even after removal of the measure from 
the Hospital VBP Program.
    Comment: A commenter disagreed with the removal of the CMS PSI 90 
measure and the rationale CMS uses under Factor 8--the costs associated 
outweigh the benefit to the program--to propose removal of CMS PSI 90 
believing that the costs of maintaining the CMS PSI 90 measure in two 
programs is minimal compared to serious harms, errors, and preventable 
death, and considering the overall financial costs to CMS and families. 
A commenter recommended that CMS retain the CMS PSI 90 measure, and, 
alternatively, if CMS removes the CMS PSI 90 measure, then CMS should 
adopt the PSI-03 pressure ulcer rate measure as a stand-alone measure.
    Response: We remain committed to patient safety as a high priority 
and believe that Factor 8 is applicable and appropriate in this 
situation because costs are multifaceted and include not only the 
burden associated with reporting, with which hospitals have expressed 
concerns for several years, but also the costs CMS incurs to implement 
and maintain the measure in the program. We have evaluated having 
duplicative measures in these two programs and believe removing this 
measure from the Hospital VBP Program will reduce the provider and 
clinician costs associated with tracking duplicative measures, while 
continued use of the measure in the HAC Reduction Program and through 
public reporting of hospital performance information retains the focus 
on patient safety. We also note that maintaining the CMS PSI 90 measure 
in the HAC Reduction Program aligns with our interests in promoting 
patient safety with the scoring methodology of the HAC Reduction 
Program weighting the CMS PSI 90 measure at approximately 16 percent of 
the total performance score and believe this will help drive hospital 
behavior focused on reducing complications. While we did not propose to 
adopt the PSI-03 pressure ulcer rate measure in the FY 2022 IPPS/LTCH 
PPS proposed rule, we agree that this is an important topic and are 
working with a measure developer to develop the Hospital Harm-Pressure 
Injury electronic clinical quality measure (eCQM) for potential future 
use. As noted, in addition to finalizing the Severe Hyperglycemia and 
Severe Hypoglycemia patient safety eCQMs in this final rule, we will 
also consider a composite measure which includes several patient safety 
and harm measures when all other harm measures such as pressure injury, 
falls with injury, acute kidney injury, and medication related bleeding 
are fully developed.
    After consideration of the public comments we received, we are 
finalizing the removal of the CMS PSI 90 measure beginning with FY 
2023.
d. Updates to the Specifications of Four Condition-Specific Mortality 
Measures and One Procedure-Specific Complication Measure Beginning With 
the FY 2023 Program Year To Exclude Patients Diagnosed With COVID-19
    We are updating the following four condition-specific mortality 
measures and one procedure-specific complication measure to exclude 
patients with either principal or secondary diagnoses of COVID-19 from 
the measure denominators beginning with the FY 2023 program year.

 Hospital 30-Day, All-Cause, Risk-Standardized Mortality Rate 
Following Acute Myocardial Infarction (AMI) Hospitalization (NQF #0230)
 Hospital 30-Day, All-Cause, Risk-Standardized Mortality Rate 
Following Coronary Artery Bypass Graft (CABG) Surgery (NQF #2558)
 Hospital 30-Day, All-Cause, Risk-Standardized Mortality Rate 
Following Chronic Obstructive Pulmonary Disease (COPD) Hospitalization 
(NQF #1893)
 Hospital 30-Day, All-Cause, Risk-Standardized Mortality Rate 
Following Heart Failure Hospitalization (NQF #0229)
 Hospital-Level Risk-Standardized Complication Rate Following 
Elective Primary Total Hip Arthroplasty (THA) and/or Total Knee 
Arthroplasty (TKA) (NQF #1550)

    We note that we do not need to update these measures for the FY 
2022 program year because the only data that would have been affected 
by the PHE for COVID-19 is from the first and second quarters of CY 
2020, which are excluded under the ECE we granted in response to the 
PHE for COVID-19.
    The measures we have adopted for the Hospital VBP Program are not 
currently specified to account for how patients with a COVID-19 
diagnosis might impact the quality of care assessed by those measures. 
To determine this impact, we analyzed the relationship between COVID-19 
and the measure cohorts for each of the applicable conditions/
procedures for the Hospital VBP Program measures, as previously listed 
(86 FR 25479 through 25480). For these measures, we calculated the 
Pearson correlation between changes in observed 30-day mortality rates 
and Medicare COVID-19 burden (defined as COVID-19-related 
hospitalizations per Medicare beneficiary) for both a 3-month (March-
May) and 12-month (June-May) period. That is, we calculated the change 
in observed 30-day mortality rates between March-May 2019 (3-months) 
and March-May 2020, and also between June 2018-May 2019 and June 2019-
May 2020 (12-months). We then assessed the correlation between these 
changes in observed mortality rates and Medicare COVID-19 burden. 
Changes in observed 30-day mortality rates showed no or modest but 
statistically significant correlation with Medicare COVID-19 burden 
when analyzing a 3-month period for the non-pneumonia measures in the 
Hospital VBP Program; however, there was no significant correlation for 
the non-pneumonia measures when analyzing the 12-month period. Because 
the performance periods for these measures are each three years and 
there is no

[[Page 45280]]

significant correlation between the change in mortality with Medicare 
COVID-19 burden over a 12-month period (using COVID-impacted data 
through May 2020), we believe these measure scores will be valid and 
equitable for use in the Hospital VBP Program.
    In the FY 2015 IPPS/LTCH PPS final rule, we finalized a technical 
updates policy which included a subregulatory process to incorporate 
technical measure specification updates into the measure specifications 
we have adopted for the Hospital VBP Program (79 FR 50077 through 
50079). We stated that these non-substantive updates might include 
exclusions to a measure (citing as an example the addition of a hospice 
exclusion to the 30-day mortality measures) (79 FR 50078). Due to the 
impact of the COVID-19 PHE on the mortality and complications measures 
used in the Hospital VBP Program, as described previously, we are 
updating the MORT-30-AMI, MORT-30-CABG, MORT-30 COPD, MORT-30-HF, and 
COMP-HIP-KNEE measures to exclude admissions with either a principal or 
secondary diagnosis of COVID-19 from the measure denominators. This 
technical update will modify these four condition-specific mortality 
measures and one procedure-specific complication measure to exclude 
certain ICD-10 Codes that identify patients with a principal or 
secondary diagnosis of COVID-19 from the measure denominators but will 
retain the measures in the program.
    We believe that excluding COVID-19 patients from the measure 
denominator beginning with the FY 2023 program year and subsequent 
years will ensure that these four condition-specific mortality measures 
and one procedure-specific complication measure continue to account for 
mortality and complication rates as intended and meet the goals of the 
Hospital VBP Program. Technical specifications of the Hospital VBP 
Program measures are provided on our website under the Measure 
Methodology Reports section (available at: http://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/HospitalQualityInits/Measure-Methodology.html). Additional resources 
about the measure technical specifications and methodology for the 
Hospital VBP Program are on the QualityNet website (available at: 
https://qualitynet.cms.gov/inpatient/hvbp).
    Comment: Most commenters expressed support for our technical 
measure specification updates removing patients diagnosed with COVID-19 
from the denominators of the Hospital 30-Day, All-Cause, Risk-
Standardized, Mortality Rate Following Acute Myocardial Infarction 
(AMI) Hospitalization, Coronary Artery Bypass Graft (CABG) Surgery, 
Chronic Obstructive Pulmonary Disease (COPD) Hospitalization, Heart 
Failure Hospitalization, and Elective Primary Total Hip Arthroplasty 
(THA) and/or Total Knee Arthroplasty (TKA) complication measures 
beginning with the FY 2023 program year. Exclusion of these patients 
from the measure denominators will ensure that patient populations in 
these measures remain consistent with patient populations in prior year 
assessments within the three-year performance period.
    Response: We thank the commenters for their support of the removal 
of admissions with a principal or secondary diagnosis POA of COVID-19 
from the denominators of these measures.
    Comment: Several commenters supported excluding patients diagnosed 
with COVID-19 from the denominators of the four mortality measures and 
the complications measure, but also encouraged CMS to continue 
monitoring the data to assess the full impact of COVID-19 on hospital 
operations and quality measures and determine if future exclusions or 
suppressions after FY 2023 may be necessary.
    Response: We understand the COVID-19 PHE is ongoing and may be 
impacting many aspects of the healthcare system and patient outcomes. 
We will continue to monitor the claims data that form the basis for 
these measure calculations to evaluate the effect of COVID-19 on 
quality measurement and to determine appropriate policies in the 
future.
    Comment: Commenters expressed concern that removal of patients 
diagnosed with COVID-19 from the measure denominators may not 
sufficiently address the impact of COVID-19 on the health care system 
during the public health emergency. There are many reasons data may 
show a decrease in quality, including hospitals seeing a smaller and 
more acute population, general disruptions in care practices during the 
pandemic, and challenges with available resources. They encouraged CMS 
to consider suppression for these mortality and complication measures 
starting in FY 2023.
    Response: Our analyses of available data to date have estimated 
only minimal impacts of COVID-19 on mortality and complications measure 
results (for measures other than pneumonia mortality) for the FY 2023 
program year due to the cohort definitions. Additionally, these 
measures are typically three-year measures and will additionally not 
include six months of data (January 1, 2020 through June 30, 2020) that 
we excluded from measure calculations under the ECE we granted for the 
Hospital VBP Program in March, 2020.
    Comment: Commenters noted that the mortality and complications 
measures could provide valuable information on the clinical effects of 
COVID-19 on these conditions and procedures. For this reason, they 
requested that CMS consider providing confidential reports that are 
inclusive of COVID-19 patients for learning and monitoring purposes.
    Response: We agree that measure results from the complications and 
mortality measures provide important information for understanding the 
impact of COVID-19 and improving quality. We will provide hospital 
specific reports (HSRs) to hospitals for the five measure with the 
specifications modified to remove from the denominator any principal or 
secondary POA of COVID index admissions. In these HSRs, hospitals will 
be able to see which of their patients were excluded from the measures 
due to a qualifying COVID-19 diagnosis to inform hospital quality 
improvement initiatives.
    Comment: Commenters expressed concern that the proposed approach of 
removing patients diagnosed with COVID-19 may result in the incomplete 
exclusion of COVID-19 patients from the measures as the approach does 
not account for patients whose COVID-19 infections occur after hospital 
discharge, but within the 30-day time window of the measures.
    Response: Any publicly reported measures will exclude data from 
January 1, 2020 through June 30, 2020 as announced in the COVID-19 
public health emergency ECE. Outside of this timeframe, we are 
excluding index admissions (from the denominator) that have a principal 
or secondary diagnosis present on admission (POA), of COVID-19 using 
the COVID-19 specific ICD-10 code (U07.1). To align with changes for 
the readmission measures in the Hospital Readmissions Reduction Program 
(see section V.G.6.c of this final rule), and in response to the public 
comments received, we will also remove numerator events for 
readmissions related to COVID-19 for the four medical complications 
that are part of the outcome inclusion criteria for the COMP-HIP-KNEE 
measure. The four medical complication outcomes that this applies to 
are: (1) Acute myocardial infarction (AMI) during a subsequent 
inpatient admission that occurs within seven days from the start of the 
index admission; (2) pneumonia or other acute

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respiratory complication during a subsequent inpatient admission that 
occurs within seven days from the start of the index admission, (3) 
sepsis/septicemia/shock during a subsequent inpatient admission that 
occurs within seven days from the start of the index admission, and (4) 
pulmonary embolism during the index admission or a subsequent inpatient 
admission within 30 days from the start of the index admission. In 
these cases, readmissions with a principal or secondary diagnosis POA 
of COVID-19 (U07.1) will be removed from the numerator. We appreciate 
the commenters suggestion to remove post-discharge mortality events due 
to COVID-19, however, the data sources that are used to identify the 
outcome do not specify the cause of death.
    Comment: Some commenters did not support removal of COVID-19 
patients from the denominators of the mortality and complications 
measures unless the only cases that are excluded are those cases where 
the COVID-19 diagnosis was present on admission (POA). The commenters 
believe hospitals should be accountable for the transmission of COVID-
19 and for deaths of patients who were infected while in the hospital. 
Although the commenters expressed recognition of the many challenges 
hospitals have endured, they felt hospitals' ability to prevent the 
spread of COVID-19 infection within their walls is of enormous 
importance to the public and to health care workers.
    Response: We agree with the commenters and note that almost all of 
the admissions with a COVID-19 diagnosis within the cohorts for the 
mortality and complication measures in the Hospital VBP Program 
represent COVID-19 as a secondary diagnosis present on admission (POA). 
We are clarifying here that patients who contract COVID-19 in the 
hospital (that is, patients who do not have a COVID-19 diagnosis POA, 
but subsequently receive a COVID-19 diagnosis during their hospital 
stay) and die represent a quality signal that the hospital should have 
taken steps to prevent the spread of COVID-19 infection within their 
facility, and therefore these patients will be included in the measure. 
In rare cases, due to the MORT-30-CABG and COMP-HIP-KNEE procedural 
measures' cohort definitions based upon procedure codes, an admission 
with a COVID-19 principal diagnosis may theoretically be within the 
cohort. We are therefore clarifying that we are removing index 
admissions with a principal, or secondary COVID-19 diagnosis POA.
e. Summary of Previously Adopted Measures for FY 2022 Through FY 2025 
Program Years
    We refer readers to the FY 2021 IPPS/LTCH PPS final rule (85 FR 
58849 through 58850) for summaries of previously adopted measures for 
the FY 2023 and FY 2024 program years, and to the tables in this 
section showing summaries of previously adopted measures for the FY 
2023, FY 2024, and FY 2025 program years. We proposed to remove the CMS 
PSI 90 measure from the Hospital VBP Program beginning with the FY 2023 
program year. We also proposed to suppress the HCAHPS, MSPB, and HAI 
measures for the FY 2022 program year, and to suppress the MORT-30-PN 
measure for FY 2023. We did not propose to add new measures at this 
time. Because these measure proposals are being finalized as proposed, 
the Hospital VBP Program measure set for the FY 2022, FY 2023, FY 2024 
and FY 2025 program years would contain the following measures:
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4. Previously Adopted Baseline and Performance Periods
a. Background
    Section 1886(o)(4) of the Act requires the Secretary to establish a 
performance period for the Hospital VBP Program that begins and ends 
prior to the beginning of such fiscal year. We refer readers to the FY 
2017 IPPS/LTCH PPS final rule (81 FR 56998 through 57003) for a 
previously finalized schedule for all future baseline and performance 
periods for previously adopted measures. We refer readers to the FY 
2018 IPPS/LTCH PPS final rule (82 FR 38256 through 38261), the FY 2019 
IPPS/LTCH PPS final rule (83 FR 41466 through 41469), the FY 2020 IPPS/
LTCH PPS final rule (84 FR 42393 through 42395), and the FY 2021 IPPS/
LTCH PPS final rule (85 FR 58850 through 58854) for additional 
previously adopted baseline and performance periods for the FY 2023 and 
subsequent program years. As discussed in the FY 2022 IPPS/LTCH PPS 
proposed rule, we proposed to remove the CMS PSI 90 measure and to 
suppress the MORT-30-PN measure for the FY 2023 program year (86 FR 
25478 through 25479; 86 FR 25475 through 25477).
b. Updated Baseline Periods for Certain Measures Due to the 
Extraordinary Circumstances Exception Granted in Response to the COVID-
19 PHE
(1) Background
    We previously finalized baseline and performance periods for the FY 
2023, 2024, 2025, 2026, and 2027 program years for all the measures 
included in the Hospital VBP Program, and we refer the reader to Table 
V.H-5 for those previously adopted baseline and performance periods. 
However, subsequent to finalizing those baseline periods, and as 
described further in section V.H.7. of this final rule, we granted an 
ECE in response to the COVID-19 PHE and stated that we will not use any 
first or second quarter of CY 2020 measure data that was voluntarily 
submitted for scoring purposes under the Hospital VBP Program.
    If we simply removed the first and second quarter of CY 2020 
measure data from the previously finalized baseline periods for the FY 
2024 program year the baseline period for certain measures included in 
the Hospital VBP Program would only be 6 months, which is too short for 
purposes of calculating reliable baseline period scores.
    Accordingly, to ensure that we have a sufficient quantity of data 
for baselining purposes, we proposed and are finalizing several updates 
to the baseline periods in this final rule for the FY 2024 program year 
and we refer readers to section V.H.4.b. of this final rule for further 
discussion of these updates. We believe that the previously established 
baseline periods for FY 2022, FY 2025, and FY 2026 program years are 
not impacted. There are also measures whose quantity of data for 
baselining purposes would be impacted by the ECE for the FY 2027 
program year. However, for these measures, we believe 30 and 33-month 
baseline periods still provide enough data to reliably calculate 
baseline scores.
(2) Updated FY 2024 Baseline Period for the Person and Community 
Engagement Domain Measure (HCAHPS Survey)
    For the Person and Community Engagement Domain Measure (HCAHPS 
Survey), we finalized that the baseline period for the FY 2024 program 
year would be January 1, 2020 through December 31, 2020, but the 
removal of the January-June data would only leave us with 6 months of 
data (86 FR 25483). We believe that using at least a full year for data 
collection provides high levels of data accuracy and reliability for 
scoring hospitals on this measure (76 FR 2458). Therefore, we proposed 
to use a baseline period of January 1, 2019 through December 31, 2019 
so that we have a full year of data (86 FR 25483). This baseline period 
would be paired with the previously finalized performance period of 
January 1, 2022 through December 31, 2022. We believe using data from 
this period will provide sufficiently reliable data for evaluating 
hospital performance that can be used for FY 2024 scoring. We selected 
this

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revised data period because it would provide the most consistency for 
hospitals in terms of the comparable length to previous program years 
and the performance period, and it would capture a full year of data, 
including any seasonal effects.
    We noted that this new proposed baseline period would not include 
the third or fourth quarters of 2020, even though those quarters were 
not included in the ECE. However, our internal analyses indicated that 
the average number of completed surveys, and thus average reliability 
of the measure as a whole, is higher when based on four consecutive 
quarters as opposed to two quarters of HCAHPS data. In addition, 
because hospitals must report at least 100 completed surveys for a 
performance period to receive an HCAHPS measure score, reducing the 
baseline period from 12 to 6 months would result in fewer hospitals, 
especially smaller hospitals, being able to report 100 surveys for the 
performance period. We estimated that 11 percent of the hospitals that 
would be able to achieve 100 completed surveys over four quarters would 
be unable to do so in two quarters. As a result, we believe using four 
consecutive quarters of data for the baseline period will provide a 
higher level of data accuracy and reliability for scoring hospitals on 
the HCAHPS Survey.
(3) Updated FY 2024 Baseline Period for the Safety Domain Measures
    In the FY 2017 IPPS/LTCH PPS final rule (81 FR 57000), we finalized 
the performance period for all measures in the Safety domain to run on 
the calendar year two years prior to the applicable program year and a 
baseline period that runs on the calendar year four years prior to the 
applicable program year for the FY 2019 program year and subsequent 
program years. For FY 2024, the baseline period for the Safety Domain 
Measures would be January 1, 2020 through December 31, 2020, but the 
removal of data impacted by the ECE from January to June of 2020 would 
only leave us with 6 months of data. We believe that using at least a 
full year for data collection provides high levels of data accuracy and 
reliability for scoring hospitals on measures (76 FR 2458). Therefore, 
we proposed to update the FY 2024 baseline period for the Safety domain 
measures from January 1, 2020 through December 31, 2020 to January 1, 
2019 through December 31, 2019 so that we have a full year of data (86 
FR 25483). We believe using data from this period will provide 
sufficiently reliable data for evaluating hospital performance that can 
be used for FY 2024 scoring. We selected this data period because it 
would provide the most consistency for hospitals in terms of the 
comparable length to previous program years and the performance period, 
and it would capture a full year of data, including any seasonal 
effects.
(4) Updated FY 2024 Baseline Period for the Efficiency and Cost 
Reduction Domain Measure
    In the FY 2017 IPPS/LTCH PPS final rule (81 FR 56998), we finalized 
a 12-month performance period for the MSPB measure that runs on the 
calendar year two years prior to the applicable program year and a 12-
month baseline period that runs on the calendar year four years prior 
to the applicable program year for the FY 2019 program year and 
subsequent years. For FY 2024, the baseline period for the MSPB measure 
would be January 1, 2020 through December 31, 2020, but the removal of 
data impacted by the ECE from January to June of 2020 would only leave 
us with 6 months of data. We believe that using at least a full year 
for data collection provides high levels of data accuracy and 
reliability for scoring hospitals on measures (76 FR 2458). Therefore, 
we proposed to update the FY 2024 baseline period for the MSPB measure 
from January 1, 2020 through December 31, 2020 to January 1, 2019 
through December 31, 2019 so that we have a full year of data (86 FR 
25483 through 25484). We believe using data from this period will 
provide sufficiently reliable data for evaluating hospital performance 
that can be used for FY 2024 scoring. We selected this data period 
because it would provide the most consistency for hospitals in terms of 
the comparable length to previous program years and the performance 
period, and it would capture a full year of data, including any 
seasonal affects.
    We welcomed public comment on our proposals to update the FY 2024 
baseline periods for the measures included in the Person and Community 
Engagement, Safety, and Efficiency and Cost Reduction domains.
    Comment: Many commenters supported CMS' proposal to change the FY 
2024 baseline periods for the Person and Community Engagement, Safety, 
and Efficiency and Cost Reduction Domains. Commenters agreed with the 
approach of using a full year of 2019 data rather than 6 months of 2020 
data for the purposes of data accuracy and reliability.
    Response: We thank commenters for their support.
    Comment: A few commenters recommended that CMS should continue to 
monitor CY 2021 performance to determine whether there is a fair and 
valid comparison to pre-pandemic baseline periods or if further policy 
updates are needed to better compare performance and improvement 
scores.
    Response: We thank commenters for their recommendation and note 
that we plan to continue monitoring the impacts of the COVID-19 PHE on 
performance data to evaluate whether any additional flexibilities or 
updates are needed.
    After consideration of the public comments we received, we are 
finalizing the updates to the FY 2024 baseline periods for measures 
included in the Person and Community Engagement, Safety, and Efficiency 
and Cost Reduction domains as proposed.
c. Summary of Previously Adopted and Newly Updated Baseline and 
Performance Periods for the FY 2023 Through FY 2027 Program Years
    The following tables summarize the previously adopted and newly 
updated baseline and performance periods.
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BILLING CODE 4120-01-C
5. Performance Standards for the Hospital VBP Program
a. Background
    We refer readers to sections 1886(o)(3)(A) through 1886(o)(3)(D) of 
the Act for the performance standard requirements under the Hospital 
VBP Program. We refer readers to the Hospital Inpatient VBP Program 
final rule (76 FR 26511 through 26513) for further discussion of 
achievement and improvement standards under the Hospital VBP Program. 
We refer readers to the FY 2013, FY 2014, and FY 2015 IPPS/LTCH PPS 
final rules (77 FR 53599 through 53605; 78 FR 50694 through 50699; and 
79 FR 50077 through 50081, respectively) for a more detailed discussion 
of the general scoring methodology used in the Hospital VBP Program. We 
refer readers to the FY 2021 IPPS/LTCH PPS final rule (85 FR 58856 
through 58857) for previously established performance standards for the 
FY 2023 program year. We note that the measure suppression proposals 
for the FY 2022 and FY 2023 program years, discussed more fully in 
section V.H.1. of this final rule, will not affect the performance 
standards for the FY 2022 or FY 2023 program year. However, as 
discussed in section V.H.6. of this final rule, we are finalizing our 
proposal to not generate achievement or improvement points for any 
suppressed measures for FY 2022.
    We refer readers to the FY 2021 IPPS/LTCH PPS final rule for 
further discussion on performance standards for which the measures are 
calculated with lower values representing better performance (85 FR 
58855).
b. Previously Established and Estimated Performance Standards for the 
FY 2024 Program Year
    In the FY 2019 IPPS/LTCH PPS final rule (83 FR 41472), we 
established performance standards for the FY 2023 program year for the 
Clinical Outcomes domain measures (MORT-30-AMI, MORT-30-HF, MORT-30-PN 
(updated cohort), MORT-30-COPD, MORT-30-CABG, and COMP-HIP-KNEE) and 
for the Efficiency and Cost Reduction domain measure (MSPB). In the FY 
2019 IPPS/LTCH PPS final rule (83 FR 41471 through 41472), we 
established, for the FY 2023 program year, the performance standards 
for the Safety domain measure, CMS PSI 90. However, as discussed in 
section V.H.3.c. of this final rule, we are finalizing our proposal to 
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the Hospital VBP Program beginning with the FY 2023 program year. For 
this reason, we did not provide the estimated performance standards for 
this measure in the proposed rule. We note that the performance 
standards for the MSPB measure are based on performance period data. 
Therefore, we are unable to provide numerical equivalents for the 
standards at this time. As discussed in section V.H.4.b. of this final 
rule, we are finalizing our proposal to update the FY 2024 program year 
baseline periods for the measures included in the Safety, Person and 
Community Engagement, and Efficiency and Cost Reduction domains. Since 
this proposal is being finalized, according to our established 
methodology for calculating performance standards, we will use data 
from January 1, 2019 through December 31, 2019 to calculate performance 
standards for the FY 2024 program year for these measures.
    In accordance with our methodology for calculating performance 
standards discussed more fully in the Hospital Inpatient VBP Program 
final rule (76 FR 26511 through 26513) and codified at 42 CFR 412.160, 
we are estimating additional performance standards for the FY 2024 
program year. We noted in the FY 2022 IPPS/LTCH PPS proposed rule (86 
FR 25489) that the numerical values for the performance standards for 
the Safety and Person and Community Engagement domains for the FY 2024 
program year in the following tables are estimates based on the most 
recently available data, and that we intended to update the numerical 
values in the FY 2022 IPPS/LTCH PPS final rule. The updated numerical 
values are in Table V.H-11.
    The previously established and newly updated performance standards 
for the measures in the FY 2024 program year are set out in the 
following tables.
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    The HCAHPS Base Score is calculated using the eight dimensions of 
the HCAHPS measure\.\ For each of the eight dimensions, Achievement 
Points (0-10 points) and Improvement Points (0-9 points) are 
calculated, the larger of which is then summed across the eight 
dimensions to create the HCAHPS Base Score (0-80 points). Each of the 
eight dimensions is of equal weight; therefore, the HCAHPS Base Score 
ranges from 0 to 80 points. HCAHPS Consistency Points are then 
calculated, which range from 0 to 20 points. The Consistency Points 
take into consideration the scores

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of all eight Person and Community Engagement dimensions. The final 
element of the scoring formula is the summation of the HCAHPS Base 
Score and the HCAHPS Consistency Points, which results in the Person 
and Community Engagement Domain score that ranges from 0 to 100 points. 
As discussed in section V.H.4.b. of this final rule, we are finalizing 
our proposal to update the FY 2024 program year baseline period for the 
measure included in the Person and Community Engagement domain. Since 
this proposal is finalized, according to our established methodology 
for calculating performance standards, we will use data from January 1, 
2019 through December 31, 2019 to calculate performance standards for 
the FY 2024 program year for this measure.
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c. Previously Established Performance Standards for Certain Measures 
for the FY 2025 Program Year
    We have adopted certain measures for the Safety domain, Clinical 
Outcomes domain, and Efficiency and Cost Reduction domain for future 
program years in order to ensure that we can adopt baseline and 
performance periods of sufficient length for performance scoring 
purposes. In the FY 2020 IPPS/LTCH PPS final rule (84 FR 42398 through 
42399), we established performance standards for the FY 2025 program 
year for the Clinical Outcomes domain measures (MORT-30-AMI, MORT-30-
HF, MORT-30-PN (updated cohort), MORT-30-COPD, MORT-30-CABG, and COMP-
HIP-KNEE) and the Efficiency and Cost Reduction domain measure (MSPB). 
In the FY 2021 IPPS/LTCH PPS final rule (85 FR 58858), we established, 
for the FY 2025 program year, the performance standards for the Safety 
domain measure, CMS PSI 90. However, as discussed in section V.H.3.c. 
of this final rule, we are finalizing our proposal to remove the CMS 
PSI 90 measure from the Hospital VBP Program starting with the FY 2023 
program year. For this reason, we are not including performance 
standards for this measure in this final rule. We note that the 
performance standards for the MSPB measure are based on performance 
period data. Therefore, we are unable to provide numerical equivalents 
for the standards at this time. The previously established and newly 
established performance standards for these measures are set out in the 
following table.

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d. Previously Established Performance Standards for Certain Measures 
for the FY 2026 Program Year
    We have adopted certain measures for the Safety domain, Clinical 
Outcomes domain, and the Efficiency and Cost Reduction domain for 
future program years in order to ensure that we can adopt baseline and 
performance periods of sufficient length for performance scoring 
purposes. In the FY 2021 IPPS/LTCH PPS final rule (85 FR 58858 through 
588589), we established performance standards for the FY 2026 program 
year for the Clinical Outcomes domain measures (MORT-30-AMI, MORT-30-
HF, MORT-30-PN (updated cohort), MORT-30-COPD, MORT-30-CABG, and COMP-
HIP-KNEE) and the Efficiency and Cost Reduction domain measure (MSPB). 
We note that the performance standards for the MSPB measure are based 
on performance period data. Therefore, we are unable to provide 
numerical equivalents for the standards at this time.
    The previously established performance standards for these measures 
are set out in the following table.

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e. Newly Established Performance Standards for Certain Measures for the 
FY 2027 Program Year
    As discussed previously, we have adopted certain measures for the 
Clinical Outcomes domain (MORT-30-AMI, MORT-30-HF, MORT-30-PN (updated 
cohort), MORT-30-COPD, MORT-30-CABG, and COMP-HIP-KNEE) and the 
Efficiency and Cost Reduction domain (MSPB) for future program years in 
order to ensure that we can adopt baseline and performance periods of 
sufficient length for performance scoring purposes. In accordance with 
our methodology for calculating performance standards discussed more 
fully in the Hospital Inpatient VBP Program final rule (76 FR 26511 
through 26513), which is codified at 42 CFR 412.160, we are 
establishing the following performance standards for the FY 2027 
program year for the Clinical Outcomes domain and the Efficiency and 
Cost Reduction domain. We note that the performance standards for the 
MSPB measure are based on performance period data. Therefore, we are 
unable to provide numerical equivalents for the standards at this time. 
The newly established performance standards for these measures are set 
out in the following table.

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BILLING CODE 4120-01-C
6. Scoring Methodology and Data Requirements
a. Scoring Methodology for the FY 2022 Program Year Due to the PHE for 
COVID-19
    As described in section V.H.1. of this final rule, we are 
finalizing our proposal to suppress seven measures in the Hospital VBP 
Program for FY 2022 and to use a special rule for FY 2022 scoring. As 
previously discussed, we are finalizing that we would calculate measure 
rates for all measures in the FY 2022 program year. For measures that 
we proposed to suppress, we would not use the measure rates to generate 
achievement and improvement points within the Hospital VBP Programs 
current scoring methodology. We further proposed under this special 
rule that we would only calculate achievement and improvement points, 
as well as a domain score, for the Clinical Outcomes Domain and that, 
because no other domains receive scores for the FY 2022 Program year, 
we would not award TPSs to any hospital for FY 2022.
    Because no hospital would receive a TPS for FY 2022, we further 
proposed that we would reduce each hospital's base-operating DRG 
payment amount by 2 percent, as required under section 1886(o)(7)(B) of 
the Act, and then assign to each hospital a value-based incentive 
payment amount that matches the 2 percent reduction to the base 
operating DRG payment amount. The net result of these payment 
adjustments would be neutral for hospitals. We have stated that value-
based payment systems should rely on a mix of standards, processes, 
outcomes, and patient experience measures (76 FR 26491). As such, the 
Hospital VBP Program scoring methodology was developed to be used with 
several measures across multiple domains and aims to score hospitals on 
their overall achievement relative to national benchmarks. However, as 
discussed in the measure suppression proposals in section V.H.1. of 
this final rule, the data from several measures is significantly 
impacted by the COVID-19 PHE. Awarding negative or positive incentive 
payment adjustment percentages using TPSs calculated using the current 
scoring methodology would not provide a representative score of a 
hospital's overall performance in providing quality of care during a 
pandemic.
    In order to ensure that hospitals are aware of changes in their 
performance rates that we have observed, we proposed to provide FY 2022 
confidential feedback reports that contain the measure rates we have 
calculated for the FY 2022 program year, along with achievement and 
improvement scores for the measures in the Clinical Outcomes Domain and 
a Clinical Outcomes Domain score. However, as previously discussed, we 
proposed that the measure rates and Clinical Outcome Domain performance 
scores would not be used to calculate TPSs for the purpose of adjusting 
hospital payments under the FY 2022 Hospital VBP Program.
    We invited public comment on these scoring proposals for FY 2022.
    Comment: Several commenters supported CMS' proposal to not 
calculate a total performance score to avoid unfairly penalizing 
hospitals that have been impacted by the COVID-19 PHE. A few commenters 
urged CMS to finalize the FY 2022 special scoring policy to account for 
the significant impact COVID-19 had on hospitals. A commenter noted 
that CMS is best situated to understand the effect of COVID-19 on 
program outcomes. A commenter noted appreciation that CMS will 
calculate and report measure scores where feasible and appropriate 
given the value of these data to hospitals for performance improvement 
initiatives now and for future PHEs.
    Response: We thank commenters for their support and agree that the 
FY 2022 special scoring policy is an appropriate approach to unfairly 
penalizing hospitals and account for the impact of the COVID-19 PHE on 
hospitals.
    Comment: A few commenters sought clarification on how the FY 2022 
special scoring policy would affect other programs such as the Merit-
based

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Incentive Payment System (MIPS) that use Hospital VBP Program measures. 
Commenters expressed concern that the FY 2022 special scoring policy 
would negatively impact facility-based clinicians participating in the 
MIPS.
    Response: We understand that the FY 2022 special scoring policy has 
implications for the MIPS program. Under the facility-based measurement 
option within MIPS, clinicians eligible for facility-based measurement, 
as described Sec.  414.1380(e)(2), may have their MIPS quality and cost 
performance category scores based on the Total Performance Score of 
their affiliated hospital from the Hospital VBP Program as determined 
by the requirements at Sec.  414.1380(e)(5). As described at Sec.  
414.1380(e)(1)(ii) and in the CY 2019 PFS final rule, the scoring 
methodology applicable for MIPS eligible clinicians scored with 
facility-based measurement is the Total Performance Score methodology 
adopted for the Hospital VBP Program, for the fiscal year for which 
payment begins during the applicable MIPS performance period. Thus, for 
the CY 2021 MIPS performance period/CY 2023 MIPS payment year, the 
Total Performance Score for FY 2022 would be applied. If a hospital 
does not have a Total Performance Score, facility-based measurement is 
not available for the MIPS eligible clinicians affiliated with that 
hospital. Since no hospitals will have a FY 2022 Total Performance 
Score, the clinicians who are normally assessed through facility-based 
measurement will need to identify another method of participating in 
MIPS for the CY 2021 MIPS performance period/CY 2023 MIPS payment year 
or submit an application for reweighting a performance category or 
categories, if applicable.
    Comment: A commenter suggested that CMS establish alternative 
performance periods for the FY 2022 program year, noting this approach 
would recognize investments in and on-going costs of quality 
infrastructure made by hospitals that maintained strong performance on 
measures prior to the pandemic. A commenter suggested a more equitable 
way to administer the program would be to average hospitals' scores 
over the last two years to determine TPSs and payment incentive 
multipliers for FY 2022.
    Response: We encourage hospitals to continue investing in and 
developing quality infrastructure to provide beneficiaries with high 
quality care, whether or not they are receiving a positive payment 
adjustment for a given fiscal year. In assessing approaches for 
mitigating the impact of the COVID-19 PHE on our quality payment 
programs, we considered establishing alternative performance periods. 
However, if we were to establish alternative performance periods for 
the Hospital VBP Program measures, we would be limited to data that has 
already been used to determine incentive payments in the past. Our 
preference is to avoid, where feasible, using the same data as a 
previous performance period in multiple program years. Hospitals that 
maintained strong performance on measures prior to the pandemic have 
been recognized through positive payment incentives distributed in 
prior program years, and we believe our proposed approach provides 
relief to hospitals impacted by the COVID-19 PHE while avoiding 
unfairly adjusting hospital payments.
    Comment: A commenter suggested CMS should score hospitals in FY 
2022 and provide positive payment adjustments for hospitals that 
receive a TPS that exceeds 1.0 while those hospitals that score below 
1.0 be held harmless.
    Response: As discussed in section V.H.1., we do not believe it 
would be appropriate to score hospitals and distribute incentive 
payments based on data that have been significantly impacted by the 
COVID-19 PHE. We believe that the COVID-19 pandemic has impeded 
effective quality measurement and because COVID-19 prevalence is not 
consistent across the country, hospitals located in different areas 
have been affected differently at different times throughout the 
pandemic. Under those circumstances, we remain significantly concerned 
that Hospital VBP Program quality measure scores that are calculated 
using data submitted during the PHE for COVID-19 are distorted. 
Therefore, we believe that scoring hospitals and providing a positive 
payment adjustment to any hospital would require us to provide positive 
payment incentives based on unreliable or potentially inaccurate TPSs, 
which could still penalize hospitals that were affected by holding them 
harmless when they might otherwise receive a positive payment 
adjustment in the absence of the PHE due to COVID-19. Additionally, 
implementing the suggested approach would be logistically infeasible to 
implement as the funds to pay for positive payment adjustments would 
need to come from the reduction of payments to other participating 
hospitals. Otherwise, the positive payment adjustments would be 
deducted from the Medicare trust fund, which could threaten the 
stability and sustainability of the Hospital VBP Program as well as 
other programs funded by the Medicare trust fund.
    Comment: A commenter urged CMS to use the previously established 
scoring methodology to score hospitals for FY 2022 because monitoring 
and tracking key measures using pandemic data is an important component 
of understanding an organization's ability to serve its patients.
    Response: We agree that it is important to continue tracking key 
metrics during the COVID-19 PHE. As part of the measure suppression 
policy, we proposed that hospitals would continue to collect and submit 
measure data to monitor quality and so that we are able to provide 
hospitals with confidential feedback reports and publicly report these 
data with appropriate caveats. We believe we are capable of monitoring 
and tracking key measures through this continued data collection and 
calculation of measure rates. Additionally, because the data will be 
publicly reported, other stakeholders will also be able to monitor and 
track these measures.
    After consideration of the public comments we received, we are 
finalizing the FY 2022 Hospital VBP Program scoring policies as 
proposed.
b. Domain Weighting for the FY 2023 Program Year and Subsequent Years 
for Hospitals That Receive a Score on All Domains
    In the FY 2018 IPPS/LTCH PPS final rule (82 FR 38266), we finalized 
our proposal to retain the equal weight of 25 percent for each of the 
four domains in the Hospital VBP Program for the FY 2020 program year 
and subsequent years for hospitals that receive a score in all domains. 
We did not propose any changes to these policies.
c. Domain Weighting for the FY 2023 Program Year and Subsequent Years 
for Hospitals Receiving Scores on Fewer Than Four Domains
    In the FY 2015 IPPS/LTCH PPS final rule (79 FR 50084 through 50085) 
we adopted a policy that hospitals must receive domain scores on at 
least three of four quality domains in order to receive a TPS, for the 
FY 2017 program year and subsequent years. Hospitals with sufficient 
data on only three domains will have their TPSs proportionately 
reweighted (79 FR 50084 through 50085). We did not propose any changes 
to these policies.
d. Minimum Numbers of Measures for Hospital VBP Program Domains
    We refer readers to the 2018 IPPS/LTCH PPS final rule (82 FR 38266) 
for our previously finalized requirements

[[Page 45297]]

for the minimum numbers of measures for hospitals to receive domain 
scores. We did not propose any changes to these policies.
e. Minimum Numbers of Cases for Hospital VBP Program Measures
(1) Background
    Section 1886(o)(1)(C)(ii)(IV) of the Act requires the Secretary to 
exclude for the fiscal year hospitals that do not report a minimum 
number (as determined by the Secretary) of cases for the measures that 
apply to the hospital for the performance period for the fiscal year. 
For additional discussion of the previously finalized minimum numbers 
of cases for measures under the Hospital VBP Program, we refer readers 
to the Hospital Inpatient VBP Program final rule (76 FR 26527 through 
26531); the CY 2012 OPPS/ASC final rule (76 FR 74532 through 74534); 
the FY 2013 IPPS/LTCH PPS final rule (77 FR 53608 through 53610); the 
FY 2015 IPPS/LTCH PPS final rule (79 FR 50085 through 50086); the FY 
2016 IPPS/LTCH PPS final rule (80 FR 49570); the FY 2017 IPPS/LTCH PPS 
final rule (81 FR 57011); the FY 2018 IPPS/LTCH PPS final rule (82 FR 
38266 through 38267); the FY 2019 IPPS/LTCH PPS final rule (83 FR 41465 
through 41466); the FY 2020 IPPS/LTCH PPS final rule (84 FR 42399 
through 42400; and the FY 2021 IPPS/LTCH PPS final rule (85 FR 58859 
through 58860). We did not propose any changes to these policies.
(2) Summary of Previously Adopted Minimum Numbers of Cases
    The previously adopted minimum numbers of cases for these measures 
are set forth in the following table.
[GRAPHIC] [TIFF OMITTED] TR13AU21.277

f. Summary of Previously Adopted Administrative Policies for NHSN 
Healthcare-Associated Infection (HAI) Measure Data
    In the FY 2020 IPPS/LTCH PPS final rule (84 FR 42400 through 
42402), we finalized our proposal to use the same data to calculate the 
CDC NHSN HAI measures for the Hospital VBP Program that the HAC 
Reduction Program uses for purposes of calculating the measures under 
that program, beginning on January 1, 2020 for CY 2020 data collection, 
which would apply to the Hospital VBP Program starting with data for 
the FY 2022 program year performance period. In the FY 2020 IPPS/LTCH 
PPS final rule (84 FR 42402), we also finalized our proposal for the 
Hospital VBP Program to use the same processes adopted by the HAC 
Reduction Program for hospitals to review and correct data for the CDC 
NHSN HAI measures and to rely on HAC Reduction Program validation to 
ensure the accuracy of CDC NHSN HAI measure data used in the Hospital 
VBP Program. We did not propose any changes to these policies.
7. Extraordinary Circumstance Exception (ECE) Policy for the Hospital 
VBP Program
a. Background
(1) Previously Established Extraordinary Circumstance Exception (ECE) 
Policy Under the Hospital VBP Program
    We refer readers to the FY 2014 IPPS/LTCH PPS final rule (78 FR 
50704 through 50707) for discussion of our Extraordinary Circumstance 
Exception (ECE) policy. In the FY 2014 IPPS/LTCH PPS final rule (78 FR 
50704 through 50707), we adopted an ECE policy for the Hospital VBP 
Program, which recognized that there may be periods of time during 
which a hospital is affected by an extraordinary circumstance beyond 
its control. When adopting the policy, we stated that upon a hospital's 
request, we will consider providing an exception from the Hospital VBP 
Program requirements to hospitals affected by natural disasters or 
other extraordinary circumstances (78 FR 50704 through 50706). 
Specifically, we stated that we interpreted the minimum number of cases 
and measures requirement in sections 1886(o)(1)(C)(ii)(III) and (IV) of 
the Act to not include any measures or cases for which a hospital has 
submitted data during a performance period for which the hospital has 
been granted a Hospital VBP Program ECE. We expressed belief that this 
approach would help alleviate the reporting burden for a hospital that 
is adversely impacted by a natural disaster or other extraordinary 
circumstance beyond its control, while enabling the hospital to 
continue to participate in the Hospital VBP Program.
    On May 8, 2020, we published an Interim Final Rule with public 
comment (IFC) titled ``Medicare and Medicaid Programs, Basic Health 
Program, and Exchanges; Additional Policy and Regulatory Revisions in 
Response to the COVID-19 Public Health Emergency and Delay of Certain 
Reporting Requirements for the Skilled Nursing Facility Quality 
Reporting Program,'' in response to the PHE for COVID-19

[[Page 45298]]

(hereafter referred to as the ``May 2020 IFC'') (85 FR 27550), where we 
modified the Hospital VBP Program's ECE policy to allow us to grant ECE 
exceptions to hospitals which have not requested them when we determine 
that an extraordinary circumstance that is out of their control, such 
as an act of nature (for example, a hurricane) or PHE (for example, the 
COVID-19 pandemic), affects an entire region or locale, in addition to 
retaining the individual ECE request policy (85 FR 27597 through 
27598). We stated that if we grant an ECE to hospitals located in an 
entire region or locale under this revised policy and, as a result of 
granting that ECE, one or more hospitals located in that region or 
locale does not report the minimum number of cases and measures 
required to enable us to calculate a TPS for that hospital for the 
applicable program year, the hospital will be excluded from the 
Hospital VBP Program for the applicable program year. We also stated 
that a hospital that does not report the minimum number of cases or 
measures for a program year will not receive a two percent reduction to 
its base operating diagnosis-related group (DRG) payment amount for 
each discharge in the applicable program year and will also not be 
eligible to receive any value-based incentive payments for the 
applicable program year. We refer readers to sections V.H.6.d. and 
V.H.6.e. of this final rule for the minimum number of measures and 
cases that we currently require hospitals to report in order to receive 
a TPS for a program year under the Hospital VBP Program.
    In the May 2020 IFC, we welcomed public comments on our policy to 
modify the Hospital VBP Program's ECE policy to allow us to grant ECE 
exceptions to hospitals which have not requested them when we determine 
that an extraordinary circumstance that is out of their control.
    Comment: Some commenters supported CMS in updating the Hospital VBP 
Program ECE policy to grant ECEs to hospitals which have not requested 
them. A few commenters noted that they appreciate CMS moving toward 
consistency of ECE policies across hospital reporting and performance 
programs. A commenter appreciated that this updated ECE policy helps 
alleviate the burden to hospital administration in filing an individual 
ECE request.
    Response: We thank commenters for their support and agree that it 
is important to align with other reporting and performance programs 
where possible. We also agree that our updated Hospital VBP Program ECE 
policy will help alleviate burden for providers in future extraordinary 
circumstances.
    As established in the May 2020 IFC, we have finalized our updated 
ECE policy for the Hospital VBP Program.
(2) Extraordinary Circumstance Exception (ECE) Granted in Response to 
the PHE for COVID-19
    On March 22, 2020, in response to COVID-19, we announced relief for 
clinicians, providers, hospitals, and facilities participating in 
Medicare quality reporting and VBP programs.\789\ Specifically, we 
announced that we were granting ECEs for certain data reporting 
requirements and submission deadlines for the first and second quarters 
of CY 2020. On March 27, 2020, we published a supplemental guidance 
memorandum that described the scope and duration of the ECEs we were 
granting under each Medicare quality reporting and VBP program.\790\ 
For the Hospital VBP Program, we stated that qualifying claims will be 
excluded from the measure calculations for January 1, 2020-March 31, 
2020 (Q1 2020) and April 1, 2020-June 30, 2020 (Q2 2020) from the 
claims-based complication, mortality, and CMS PSI 90 measures. The ECEs 
also relieved providers and facilities of their obligation to report 
HCAHPS survey data and CDC NHSN HAI data for the fourth quarter 
calendar year (CY) 2019, first quarter CY 2020, and second quarter CY 
2020.
---------------------------------------------------------------------------

    \789\ CMS, Press Release, CMS Announces Relief for Clinicians, 
Providers, Hospitals and Facilities Participating in Quality 
Reporting Programs in Response to COVID-19 (Mar. 22, 2020), https://www.cms.gov/newsroom/press-releases/cms-anounces-relief-clinicians-providers-hospitals-and-facilities-participating-quality-reporting.
    \790\ CMS, Exceptions and Extensions for Quality Reporting 
Requirements for Acute Care Hospitals, PPS-Exempt Cancer Hospitals, 
Inpatient Psychiatric Facilities, Skilled Nursing Facilities, Home 
Health Agencies, Hospices, Impatient Rehabilitation Facilities, 
Long-Term Care Hospitals, Ambulatory Surgical Centers, Renal 
Dialysis Facilities, and MIPS Eligible Clinicians Affected by COVID-
19 (Mar. 27, 2020), https://www.cms.gov/files/document/guidance-memo-exceptions-and-extensions-quality-reporting-and-value-based-purchasing-programs-pdf.
---------------------------------------------------------------------------

    Because the May 2020 IFC was published after these exceptions were 
granted, we also clarified the specific guidance and exceptions for the 
Hospital VBP Program in that IFC. We welcomed public comment on these 
exceptions granted in response to the COVID-19 PHE.
    Comment: A few commenters urged CMS to extend the ECE granted in 
response to the COVID-19 PHE for the remainder of 2020 in future 
rulemaking, and a few commenters urged CMS to suspend its hospital 
quality performance programs or hold hospitals harmless under these 
programs during the PHE.
    Response: We refer readers to section V.H.1. of this final rule for 
our finalized flexibilities in response to the COVID-19 PHE. We note 
that while we did not extend the ECE we granted in response to the 
COVID-19 PHE, we are finalizing in this final rule a number of other 
policies, including measure suppressions and a special scoring and 
payment policy for FY 2022, which are intended to mitigate any negative 
impacts of the COVID-19 PHE on hospitals participating in the Hospital 
VBP Program.
    Comment: A commenter recommended that CMS maintain clear 
communication with hospitals to avoid duplicative filing.
    Response: We believe the policies finalized in this final rule will 
clearly communicate the Hospital VBP Program's FY 2022 requirements. We 
also refer readers to QualityNet.cms.gov for additional resources. 
Readers may also sign up for email updates on QualityNet.cms.gov/listserv-signup to receive news, information, announcements, and 
educational offerings/events regarding the Hospital VBP Program
    Comment: A few commenters noted that, despite CMS excepting 
requirements for NHSN reporting of HAI measures for Q4 of CY 2019 and 
Q1 and Q2 of CY 2020, state regulations may continue to require this 
reporting. These commenters were concerned that hospitals located in 
these states would be unable to voluntarily withhold reporting and that 
their performance on these measures will be scored under the Hospital 
VBP and HAC Reduction Programs, which may cause bias in the scoring if 
hospitals in other states do not report on these measures during the 
impacted reporting periods.
    Response: We refer readers to section V.H.1. of the final rule, 
where we finalize our proposal to suppress seven Hospital VBP Program 
measures for FY 2022, including the five NHSN HAI measures, as well as 
our proposal to assign each hospital a value-based incentive payment 
percentage that results in a value-based incentive payment amount that 
matches the 2 percent reduction to the base operating DRG payment 
amount. The net result of these payment adjustments would be neutral 
for hospitals and a hospital's base operating DRG payment amount would 
remain unchanged for FY 2022. Therefore, the NHSN HAI data for 
hospitals in states that requires reporting of the NHSN HAI measures 
will not negatively impact their scores or payment for FY 2022. We also 
refer

[[Page 45299]]

readers to section IX.I.3.d. of this final rule where we are finalizing 
the suppression of third and fourth quarters of CY 2020 (that is, July 
1, 2020 through September 30, 2020 (Q3 2020) and October 1, 2020 
through December 31, 2020 (Q4 2020)) CDC NHSN HAI and CMS PSI 90 data 
from the HAC Reduction Program's performance calculations for FY 2022 
and FY 2023.
    Comment: A commenter requested that CMS consider publishing a 
clarification to the Hospital VBP Program ECE policy. Specifically, 
this commenter sought clarification on whether all hospitals will be 
excluded from the Hospital VBP Program for FY 2022 and FY 2023.
    Response: We refer readers to the September 2020 IFC as well as 
section V.H.7. of this final rule for clarifications on the application 
of the ECE granted in response to the COVID-19 PHE and additional 
finalized policies that suppress several measures in the Hospital VBP 
Program and result in neutral payment adjustments for all hospitals 
participating in the Hospital VBP Program for FY 2022. We note that we 
have finalized the suppression of one measure for the FY 2023 Program, 
and we will continue to evaluate the impact of COVID-19 on the Hospital 
VBP Program measures to determine the best approach for scoring and 
payment in FY 2023.
    As established in the May 2020 IFC, we have finalized exceptions 
for qualifying claims for January 1, 2020-March 31, 2020 (Q1 2020) and 
April 1, 2020-June 30, 2020 (Q2 2020) from the claims-based 
complication, mortality, and CMS PSI 90 measures as well as provider 
obligations to report HCAHPS survey data and CDC NHSN HAI data for the 
fourth quarter calendar year (CY) 2019, first quarter CY 2020, and 
second quarter CY 2020.
(3) Updated Application of the ECE Granted in Response to the PHE for 
COVID-19
    On September 2, 2020, we published a separate IFC, titled 
``Medicare and Medicaid Programs, Clinical Laboratory Improvement 
Amendments (CLIA), and Patient Protection and Affordable Care Act; 
Additional Policy and Regulatory Revisions in Response to the COVID-19 
Public Health Emergency'' (hereafter referred to as the ``September 
2020 IFC'') (85 FR 54820). The September 2020 IFC updated the ECE we 
granted in response to the PHE for COVID-19, for the Hospital VBP 
Program and several other quality reporting programs (85 FR 54827 
through 54838).
    In the September 2020 IFC, we updated the ECE that we granted for 
the Hospital VBP Program (85 FR 54833 through 54835) and stated that we 
will not use any first or second quarter CY 2020 measure data that was 
voluntarily submitted for scoring purposes under the Hospital VBP 
Program. We expressed concern with the national comparability of the 
Hospital VBP Program data due to the geographic differences of COVID-19 
incidence rates and hospitalizations along with different impacts 
resulting from different State and local law and policy changes 
implemented in response to COVID-19.
    In the September 2020 IFC, we welcomed public comments on our 
policy to not use any first or second quarter CY 2020 measure data that 
was voluntarily submitted for scoring purposes under the Hospital VBP 
Program. We stated that we would respond to those public comments in 
the FY 2022 IPPS/LTCH PPS final rule. We received some general comments 
that applied to the Hospital VBP, HAC Reduction, and Hospital 
Readmissions Reduction Programs:
    Comment: Several commenters supported CMS' general updated 
application of the ECE granted in response to the COVID-19 PHE. A few 
commenters also agreed with CMS' concerns regarding the national 
comparability of data from Q1 and Q2 of CY 2020 and noted that the 
integrity and validity of any measurement calculations associated with 
this data could be compromised. A commenter encouraged CMS to continue 
accepting data for purposes of evaluating the impact of COVID-19 on 
hospitals' outcomes.
    Response: We thank commenters for their support.
    Comment: A commenter encouraged CMS to consider excluding the 
remainder of CY 2020 data from use in payment determinations.
    Response: We thank commenter for this feedback. Although we are not 
expanding the ECE we granted in response to the COVID-19 to except 
submission requirements for the remainder of CY 2020 data from use in 
our VBP programs, we refer readers to our measure suppression policy 
and the Hospital VBP Program's special scoring and payment policy for 
FY 2022 in sections V.H.1., V.H.2 and V.H.6.a of this final rule for 
further discussion of policies that we are adopting in response to the 
impact of the COVID-19 PHE on measure data used in payment 
determinations.
    We also received one comment specifically aimed at the policies 
established for the Hospital VBP Program.
    Comment: A commenter supported CMS' revised application of the ECE 
granted for the COVID-19 PHE for the Hospital VBP Program. This 
commenter noted its appreciation for CMS' clarification of how it plans 
to use reported data for future program years.
    Response: We thank this commenter for its support.
    As established in the September 2020 IFC, we have finalized our 
updated application of the ECE granted in response to the COVID-19 PHE.
8. Provision To Revise Existing Code of Federal Regulations (CFR) 
Language by Replacing the Term ``System Administrator'' With the Term 
``Security Official''
    We proposed to replace the term ``QualityNet System Administrator'' 
with ``QualityNet security official'' in Sec.  412.167(b)(5) of our 
regulations. This update will align the terminology used for this 
program with the terminology we proposed in the FY 2022 IPPS/LTCH PPS 
proposed rule (86 FR 25495) to use for the Hospital IQR Program. This 
official is one of hospital's contact people for purposes of the appeal 
process under Sec.  412.167(b).
    We welcomed public comment on this proposal to replace the term 
``QualityNet System Administrator'' with ``QualityNet security 
official'' in our regulation text.
    We did not receive public comments and are finalizing this policy 
to replace the term ``QualityNet System Administrator'' with 
``QualityNet security official'' at Sec.  412.167(b)(5) as proposed.
9. Provision To Update References to QualityNet and Hospital Compare 
for the Hospital VBP Program
    There are currently several codified requirements for the Hospital 
VBP Program in our regulations. However, in the FY 2022 IPPS/LTCH PPS 
proposed rule (86 FR 25495), we proposed to update regulation text to 
reflect changes made to CMS resources. Specifically, we proposed to 
revise regulations in two places:
     At 42 CFR 412.163 in paragraph (d) and at 42 CFR 412.164 
at paragraph (b) to update the text to indicate that the Hospital 
Compare website is now available on the Care Compare site at: https://www.medicare.gov/care-compare.
     At 42 CFR 412.165 in paragraphs (c)(2) and (c)(4) to 
update the URL for our QualityNet website from QualityNet.org to 
QualityNet.cms.gov. We note that we launched the redesigned QualityNet 
website in November 2020.

[[Page 45300]]

    We welcomed public comment on this proposal to update references to 
CMS resources in our regulation text.
    We did not receive public comments and are finalizing our proposal 
to update references to CMS resources in our regulation text at Sec.  
412.163(d), Sec.  412.164(b), and Sec.  412.165(c)(2) and (c)(4) as 
proposed.
10. Overall Hospital Quality Star Ratings
    In the CY 2021 OPPS/ASC final rule with comment period and interim 
final rule with comment period (85 FR 86193 through 86236), we 
finalized a methodology to calculate the Overall Hospital Quality Star 
Ratings (Overall Star Ratings). The Overall Star Ratings utilize data 
collected on hospital inpatient and outpatient measures that are 
publicly reported on a CMS website, including data from the Hospital 
VBP Program. We refer readers to section XVI. of the CY 2021 OPPS/ASC 
final rule for details (85 FR 86193 through 86236).
11. References to Additional Requests for Information
    We refer readers to section IX.A. of this final rule, which 
describes our request for information on potential actions and priority 
areas that would enable the continued transformation of our quality 
measurement enterprise toward greater digital capture of data and use 
of the FHIR standard. We also refer readers to section IX.B. of this 
final rule, which describes our request for information on our Equity 
Plan for Improving Quality in Medicare, which outlines our commitment 
to closing the health equity gap through improved data collection to 
better measure and analyze disparities across programs and policies.

I. Hospital-Acquired Condition (HAC) Reduction Program: Updates and 
Changes (42 CFR 412.170)

1. Regulatory Background
    We refer readers to the FY 2014 IPPS/LTCH PPS final rule (78 FR 
50707 through 50708) for a general overview of the HAC Reduction 
Program and to the same final rule (78 FR 50708 through 50709) for a 
detailed discussion of the statutory basis for the Program. For 
additional descriptions of our previously finalized policies for the 
HAC Reduction Program, we also refer readers to the following final 
rules:
     The FY 2014 IPPS/LTCH PPS final rule (78 FR 50707 through 
50729);
     The FY 2015 IPPS/LTCH PPS final rule (79 FR 50087 through 
50104);
     The FY 2016 IPPS/LTCH PPS final rule (80 FR 49570 through 
49581);
     The FY 2017 IPPS/LTCH PPS final rule (81 FR 57011 through 
57026);
     The FY 2018 IPPS/LTCH PPS final rule (82 FR 38269 through 
38278);
     The FY 2019 IPPS/LTCH PPS final rule (83 FR 41472 through 
41492);
     The FY 2020 IPPS/LTCH PPS final rule (84 FR 42402 through 
42411); and
     The FY 2021 IPPS/LTCH PPS final rule (85 FR 58860 through 
58865).
    We have also codified certain requirements of the HAC Reduction 
Program at 42 CFR 412.170 through 412.172.
2. Overview of Updates to the HAC Reduction Program and Requests for 
Information
    In section IX.I.3.c. of the proposed rule, we proposed to adopt a 
cross-program measure suppression policy (86 FR 25497 through 25499) 
and in section IX.I.3.d. of the proposed rule we proposed to suppress 
third and fourth quarter CY 2020 CMS PSI 90 and CDC NHSN HAI measure 
data from the HAC Reduction Program (86 FR 25499 through 25500). In 
section IX.I.7. of the proposed rule, we clarified some aspects of the 
Extraordinary Circumstances Exception (ECE) policy (86 FR 25501 through 
25502). In section IX.I.9. of the proposed rule, we proposed to revise 
our regulations for the HAC Reduction Program at 42 CFR 412.172(f)(4) 
to add the phrase ``or successor website'' to reflect the change in the 
CMS website name from Hospital Compare to Care Compare (86 FR 25502).
    We also refer readers to section IX.B. of the proposed rule (86 FR 
25554 through 25561) and of this final rule, Closing the Health Equity 
Gap in CMS Quality Programs--A Request for Information, where we 
requested information on our Equity Plan for Improving Quality in 
Medicare, which sets out our commitment to closing the health equity 
gap through improved data collection to better measure and analyze 
disparities across programs and policies. The request for information 
asks for public comment regarding the potential stratification of 
quality measure results by race and ethnicity and the potential 
creation of a hospital equity score in CMS quality reporting and value-
based purchasing programs, including the HAC Reduction Program.
    We also refer readers to section IX.A. of the proposed rule (86 FR 
25549 through 25554) and of this final rule, where we requested 
information on potential actions and priority areas that would enable 
the continued transformation of our quality measurement enterprise 
toward greater digital capture of data and use of the FHIR standard (as 
described in that section). This request for information supports our 
goal of moving fully to digital quality measurement in CMS quality 
reporting and value-based purchasing programs, including the HAC 
Reduction Program, by 2025.
3. Measures for FY 2022 and Subsequent Years
    We refer readers to the FY 2019 IPPS/LTCH PPS final rule (83 FR 
41472 through 41474) for more information about how the HAC Reduction 
Program supports our goal of bringing quality measurement, 
transparency, and improvement together with value-based purchasing to 
the hospital inpatient care setting through the Meaningful Measures 
Framework.
a. Current Measures
    The HAC Reduction Program has adopted six measures to date. In the 
FY 2014 IPPS/LTCH PPS final rule (78 FR 50717), we finalized the use of 
five CDC NHSN HAI measures: (1) CAUTI; (2) CDI; (3) CLABSI; (4) Colon 
and Abdominal Hysterectomy SSI; and (5) MRSA bacteremia. In the FY 2017 
IPPS/LTCH PPS final rule (81 FR 57014), we finalized the use of the CMS 
PSI 90 measure. These previously finalized measures, with their full 
measure names, are shown in this table.

[[Page 45301]]

[GRAPHIC] [TIFF OMITTED] TR13AU21.278

    Technical specifications for the CMS PSI 90 measure can be found on 
the QualityNet website at: https://qualitynet.cms.gov/inpatient/measures/psi/resources. Technical specifications for the CDC NHSN HAI 
measures can be found at CDC's NHSN website at: http://www.cdc.gov/nhsn/acute-care-hospital/index.html. Both websites provide measure 
updates and other information necessary to guide hospitals 
participating in the collection of HAC Reduction Program data.
    In the proposed rule, we did not propose to add or remove any 
measures.
b. Measure Removal Factors Policy
    We refer readers to the FY 2020 IPPS/LTCH PPS final rule (84 FR 
42404 through 42406) for information about our measure removal and 
retention factors for the HAC Reduction Program. In the proposed rule, 
we did not propose any measure removal and retention factor policy 
changes.
c. Flexibility for Changes That Affect Quality Measures During a 
Performance or Measurement Period in the HAC Reduction Program
    In previous rules, we have identified the need for flexibility in 
our quality programs to account for the impact of changing conditions 
that are beyond participating facilities' or practitioners' control. We 
identified this need because we would like to ensure that participants 
in our programs are not affected negatively when their quality 
performance suffers not due to the care provided, but due to external 
factors.
    A significant example of the type of external factor that may 
affect quality measurement is the COVID-19 public health emergency 
(PHE), which has had, and continues to have, significant and ongoing 
effects on the provision of medical care in the country and around the 
world. The COVID-19 pandemic and associated PHE impedes effective 
quality measurement in many ways. Changes to clinical practices to 
accommodate safety protocols for medical personnel and patients, as 
well as unpredicted changes in the number of stays and facility-level 
case mixes, have affected the data used in quality measurement and the 
resulting quality scores. New clinical guidelines, diagnosis or 
procedure codes, and medications take time to be incorporated into 
quality measures, and once incorporated, those changes affect measure 
calculations. Additionally, COVID-19 prevalence is not identical across 
the country, meaning that the medical provider community has been 
affected differently at different times throughout the calendar year. 
Under those circumstances, we remain significantly concerned that 
quality measurement is distorted, which would result in skewed payment 
incentives and inequitable payments, particularly for hospitals or 
other providers that have treated more COVID-19 patients than others.
    It is not our intention to penalize hospitals for performance on 
measures that are affected significantly by global events like the 
COVID-19 PHE. As previously discussed, the COVID-19 PHE had, and 
continues to have, significant and enduring effects on health care 
systems around the world, and affects care decisions, including those 
that may result in HACs as measured by the HAC Reduction Program. As a 
result of the PHE, hospitals could provide care to their patients that 
meets the underlying clinical standard but results in worse measured 
performance, and by extension, lower payment adjustments in the HAC 
Reduction Program. We are also concerned that regional and temporal 
differences in COVID-19 prevalence during the FY 2022, FY 2023, and FY 
2024\791\ performance periods, which include data collected during the 
PHE, may directly affect hospitals' HAC measure performance for the FY 
2022, FY 2023, and FY 2024 program years. Although these regional and 
temporal differences in COVID-19 prevalence rates do not reflect 
differences in the quality of care furnished by hospitals, they 
directly affect the value-based payment adjustments that these 
hospitals are eligible to receive and could result in an unfair and 
inequitable distribution of those assessment of penalties for excess 
hospital acquired conditions. These inequities could be especially 
pronounced for hospitals that have treated a large number of COVID-19 
patients.
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    \791\ In the proposed rule, we referred only to the FY 2022 and 
FY 2023 performance periods (86 FR 25497). However, as discussed 
further in this final rule, we believe that the suppression of third 
and fourth quarter CY 2020 data from FY 2024 HAC Reduction Program 
is a logical outgrowth from our proposal to suppress such quarters 
and comments received from the public.
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    Therefore, we proposed to adopt a policy for the duration of the 
PHE for COVID-19 that would enable us to suppress a number of measures 
from the FY 2022 and FY 2023 Total HAC Score calculations for the HAC 
Reduction Program if we determine that circumstances caused by the PHE 
for COVID-19 have affected these measures and the resulting Total HAC 
Scores significantly (86 FR 25497 through

[[Page 45302]]

25499). Under the proposed policy, if we determine that the suppression 
of a HAC Reduction Program measure is warranted for a program year, we 
would propose to calculate measure rates for that program year but then 
suppress the use of those rates to generate Total HAC Scores. We would 
instead assign each hospital a zero percent weight for any suppressed 
measures in the Total HAC Score calculation. In the proposed rule, we 
stated that we would also provide confidential feedback reports to 
hospitals on their FY 2022, FY 2023, and FY 2024 performance to ensure 
that they are made aware of the changes in performance rates that we 
have observed. For CMS NHSN HAI measures, feedback regarding the 
suppressed data will be provided within NHSN. For the CMS PSI 90 
measures, feedback regarding the suppressed data will be provided in 
public reporting CMS PSI 90 hospital-specific reports (HSRs) prior to 
publication. We would also publicly report the FY 2022, FY 2023, and FY 
2024 data with appropriate caveats noting the limitations of the data 
due to the PHE for COVID-19, on the Provider Data Catalog, available at 
https://data.cms.gov/provider-data/. Data from Q3 and Q4 CY 2020 will 
be included in public reporting on Care Compare and will also include 
appropriate caveats.
    In developing this proposed policy, we considered what 
circumstances caused by the PHE for COVID-19 would affect a quality 
measure significantly enough to warrant its suppression in a value-
based purchasing program. We stated our belief that significant 
deviation in measured performance that can be reasonably attributed to 
a PHE is a significant indicator of changes in clinical conditions that 
affect quality measurement. Similarly, we stated our belief that a 
measure may be focused on a clinical topic or subject that is proximal 
to the disease, pathogen, or other health impacts of the PHE. As has 
been the case during the COVID-19 PHE, we stated our belief that rapid 
or unprecedented changes in clinical guidelines and care delivery, 
potentially including appropriate treatments, drugs, or other protocols 
may affect quality measurement significantly and should not be 
attributed to the participating facility positively or negatively. We 
also noted that scientific understanding of a particular disease or 
pathogen may evolve quickly during an emergency, especially in cases of 
new disease or conditions. Finally, we stated our belief that, as 
evidenced during the COVID-19 PHE, national or regional shortages or 
changes in health care personnel, medical supplies, equipment, 
diagnostic tools, and patient case volumes or facility-level case mix 
may result in significant distortions to quality measurement.
    Based on these considerations, we developed a number of Measure 
Suppression Factors that we believe should guide our determination of 
whether to propose to suppress HAC Reduction Program measures for one 
or more program years that overlap with the PHE for COVID-19. We 
proposed to adopt these Measure Suppression Factors for use in the HAC 
Reduction Program, and for consistency, the following other value-based 
purchasing programs: Hospital Value-Based Purchasing, Hospital 
Readmissions Reduction Program, Skilled Nursing Facility Value-Based 
Purchasing Program, and End-Stage Renal Disease Quality Incentive 
Program. We stated our belief that these Measure Suppression Factors 
will help us evaluate the HAC Reduction Program's measures and that 
their adoption in the other value-based purchasing programs, as 
previously noted, will help ensure consistency in our measure 
evaluations across programs. The proposed Measure Suppression Factors 
are as follows:
     Significant deviation in national performance on the 
measure during the PHE for COVID-19, which could be significantly 
better or significantly worse compared to historical performance during 
the immediately preceding program years.
     Clinical proximity of the measure's focus to the relevant 
disease, pathogen, or health impacts of the PHE for COVID-19.
     Rapid or unprecedented changes in--
    ++ Clinical guidelines, care delivery or practice, treatments, 
drugs, or related protocols, or equipment or diagnostic tools or 
materials; or
    ++ The generally accepted scientific understanding of the nature or 
biological pathway of the disease or pathogen, particularly for a novel 
disease or pathogen of unknown origin.
     Significant national shortages or rapid or unprecedented 
changes in--
    ++ Healthcare personnel;
    ++ Medical supplies, equipment, or diagnostic tools or materials; 
or
    ++ Patient case volumes or facility-level case mix.
    We also considered alternatives to this proposed policy that could 
fulfill our objective to not hold facilities accountable for distorted 
measure results under the FY 2022 and FY 2023 Programs. As previously 
noted, the country continues to grapple with the effects of the COVID-
19 PHE, and in March 2020, CMS issued a nationwide, blanket ECE for all 
hospitals and other facilities participating in our quality reporting 
and value-based purchasing programs in response to the COVID-19 PHE. 
This blanket ECE waived all data reporting requirements for Q1 and Q2 
2020 data, including waiving the use of claims data and data collected 
through the CDC's web-based surveillance system for this data period. 
Quality data collection resumed on July 1, 2020. This blanket ECE is 
likely to affect our quality programs significantly, especially in 
future years as CY 2020 measurement forms the basis for performance 
assessments in our value-based purchasing programs. We considered 
extending the blanket ECE that we issued for Q1 and Q2 2020 for Q3 and 
Q4 2020. This alternative would protect providers and suppliers from 
having their quality data used for quality scoring purposes while those 
data are likely to have been affected significantly by the PHE for 
COVID-19. However, this option would leave no comprehensive data 
available for us to provide confidential performance feedback to 
providers nor for monitoring and to inform decision-making for 
potential future programmatic changes, particularly as the PHE is 
extended.
    As an alternative to the proposed quality measure suppression 
policy, we also considered not making any further changes to the 
Program or measures and using Q3 and Q4 2020 quality measurement data 
that we previously specified for the HAC Reduction Program. However, 
this alternative would mean assessing hospitals and other providers and 
suppliers using quality measure data that could be affected 
significantly by the COVID-19 PHE. Additionally, given the geographic 
disparities in the COVID-19 PHE's effects, we stated in the proposed 
rule that we believed that implementation of the FY 2022, FY 2023, and 
FY 2024 HAC Reduction Programs as previously finalized would place 
hospitals in regions that were more heavily affected by the pandemic in 
Q3 and Q4 of 2020 at a disadvantage compared to hospitals in regions 
that were more heavily affected during the first two quarters of CY 
2020, for which we are not using HAC Reduction Program data to 
calculate the Program's measures.
    We stated in the proposed rule that we view this measure 
suppression proposal as necessary to ensure that the FY 2022 and FY 
2023 HAC Reduction Programs do not reward or penalize facilities based 
on factors that the Program's measures were not designed to 
accommodate. We intended for this proposed policy to provide short-term

[[Page 45303]]

relief to hospitals when we have determined that one or more of the 
Measure Suppression Factors warrants the suppression of one or more of 
the HAC Reduction Program's measures.
    We invited public comments on this proposal for the adoption of a 
measure suppression policy for the FY 2022 and FY 2023 HAC Reduction 
Program years, as previously described, and also on the proposed 
Measure Suppression Factors that we developed for purposes of this 
proposed policy. As discussed further in the following subsection of 
this final rule, we note that our proposal to suppress Q3 and Q4 CY 
2020 data also impacts the applicable period for the CMS PSI 90 measure 
in the FY 2024 HAC Reduction Program. We believe that the suppression 
of Q3 and Q4 CY 2020 from the FY 2024 HAC Reduction Program is a 
logical outgrowth of the proposal to suppress such quarters from the 
Program and comments received from the public.
    We also invited comment on whether we should consider adopting a 
measure suppression policy that would apply in a future national PHE, 
and if so, whether under such a policy, we should have the flexibility 
to suppress certain measures without specifically proposing to do so in 
rulemaking. We also requested comment on whether we should in future 
years consider adopting any form of regional adjustment for the 
proposed measure suppression policy that could take into account any 
disparate effects of circumstances affecting hospitals around the 
country that would prompt us to suppress a measure. For example, the 
COVID-19 PHE affected different regions of the country at different 
rates depending on factors like time of year, geographic density, State 
and local policies, and health care system capacity. In future years 
and for future PHEs, should they arise, we also requested commenters' 
feedback on whether we should, rather than suppress a measure 
completely, consider a suppression policy with more granular effects 
based on our assessment of the geographic effects of the circumstances, 
and if so, how region-based measure suppression could be accounted for 
within the program's scoring methodology.
    The comments we received and our responses are set forth below.
    Comment: Many commenters expressed support for our proposed measure 
suppression policy, agreeing with our stated goal of ensuring that 
hospitals are not rewarded or penalized for their quality performance 
based on non-representative data. Some commenters recommended that we 
ensure that the suppression policy does not unintentionally penalize 
hospitals.
    Response: We thank the commenters for their support. We acknowledge 
commenters' concern that the suppression policy should not 
unintentionally penalize hospitals. We note that we proposed the 
suppression policy due to the impacts of the COVID-19 PHE because of 
our concern in the ability to make fair, national comparisons of 
hospitals around the country.
    Comment: Some commenters expressed concerns about our proposed 
suppression policy. Some commenters suggested that we should limit this 
policy to the current PHE given the unique circumstances involved in 
the COVID-19 pandemic. A few commenters expressed concerns about CMS 
being empowered to implement scoring adjustments and payment changes 
outside of rulemaking, and worried that comparisons between suppressed 
and unsuppressed scores would be unfair.
    Response: We did not propose to apply this policy beyond the COVID-
19 PHE. Any scoring adjustments or payment changes that might address a 
different, future fiscal year of the program due to the COVID-19 PHE or 
another type of emergency would be proposed through rulemaking. We 
acknowledge the commenters' concerns about potentially unfair 
comparisons and will consider for future rulemaking any such issues we 
identify.
    Comment: Several commenters argued that we should not publicly 
report suppressed data, suggesting that data unfit to determine 
payments adjustments should not be publicly reported, while others 
suggested that we should note clearly that any publicly-reported data 
has been affected by the COVID-19 PHE.
    Response: We understand the commenters concern about publicly 
reporting measure data during the PHE due to COVID-19. However, as 
noted previously in section IX.I.3.c. of the preamble of this final 
rule, we will make clear in the public presentation of the data that 
the measure has been suppressed for purposes of scoring and payment 
adjustments because of the effects of the PHE due to COVID-19. 
Displaying this information will promote transparency on the impacts of 
the PHE due to COVID-19, and we will appropriately caveat the data in 
order to mitigate public confusion.
    Comment: Several commenters recommended that we study carefully the 
effects of the measure suppression policy and the measure suppression 
factors to inform any suppression policies for future PHEs. Several 
commenters recommended that we work with stakeholders before adopting 
additional measure suppression policies or any subregulatory policy 
changes on this topic in the future, including any potential changes to 
the Measure Suppression Factors, and requested that we explain the 
effects of any changes to the Suppression Factors in detail. A 
commenter suggested that we continue monitoring the effects of COVID-19 
on 2021 quality performance and consider updating measure 
specifications to exclude COVID-positive patients or change our risk 
adjustment models. Other commenters suggested that we monitor the 
shorter performance periods carefully, as well as the effects of the 
policy on future benchmarking, and that we assess the indirect effects 
that the COVID-19 PHE has had on all aspects of medical care delivery.
    Response: We share commenters' concerns about the potential long-
term effects of the measure suppression policy, including the measure 
suppression factors. We agree with commenters that we should monitor 
the PHE's ongoing effects carefully and we will work with measure 
developers to refine measure specifications as feasible for future 
rulemaking. We will also assess performance periods, benchmarks, and 
other effects of the COVID-19 PHE carefully, and we will monitor the 
policy's effects carefully as we implement it. We welcome stakeholders' 
continuing feedback as we continue responding to the PHE.
    Comment: Some commenters expressed support for the proposed Measure 
Suppression Factors, while others suggested that we include more 
flexibility in the Suppression Factors, particularly to account for 
future PHEs, and that we consult with stakeholders when applying these 
factors in the future. A commenter recommended that we explicitly 
include flexibility in our suppression factors to account for our 
evolving understanding of COVID-19.
    Response: We thank the commenters for this feedback. While we 
appreciate the commenter's suggestion that we incorporate more 
flexibility into the current Measure Suppression Factors, we believe 
the specificity with which we proposed them was necessary to provide 
hospitals, patients/consumers, and other stakeholders with clear 
insight into the decision-making process that we employed in response 
to the COVID-19 PHE. However, we will also engage with stakeholders 
when developing and implementing these Suppression Factors for future 
PHEs.
    Comment: Some commenters recommended that we refine our

[[Page 45304]]

proposed Measure Suppression Factors. Some commenters suggested that we 
define them more precisely to be fully transparent with the factors' 
terms and effects, arguing that we have not defined what we consider to 
be ``significant'' deviation in national performance on a measure 
during a PHE. A commenter also argued that the Suppression Factors 
should be focused on effects on Medicare beneficiaries, not on 
providers or circumstances within the control of providers. A commenter 
suggested that we consider suppressing measures for individual 
hospitals where performance may have deviated significantly from past 
performance, while another commenter recommended that we ensure that 
the Suppression Factors do not assess provider organizations' quality 
per se, but rather, the PHE at issue.
    Response: We thank the commenters for this feedback. We believe 
that some level of discretion is necessary in the face of evolving 
circumstances like those that have confronted us in the form of the 
COVID-19 PHE. In deciding which measures to suppress, and as discussed 
further in section VI.H.1.b. of this final rule, we examined each 
measure and determined that the evidence showed deviation in the 
individual measure performance data associated with the COVID-19 PHE. 
We believe providing the evidence for the measure suppressions included 
in this final rule is transparent and provides sufficient explanation 
for our rationales. We note further that we designed several of the 
measure suppression factors to account for circumstances that could 
affect the health and safety of patients and healthcare personnel, and 
we believe that situations like personal protective equipment (PPE) 
shortages affect the care provided to Medicare beneficiaries. We 
recommend that any individual hospitals believing that they have faced 
extraordinary circumstances that affect their quality performance, but 
that have not been addressed by the suppression policy, consider 
seeking an Extraordinary Circumstances Exception.\792\
---------------------------------------------------------------------------

    \792\ For more information regarding Extraordinary Circumstances 
Exceptions requests under the HAC Reduction Program, please see: 
https://qualitynet.cms.gov/inpatient/hac/participation#tab2.
---------------------------------------------------------------------------

    Comment: Some commenters supported regional adjustments to the 
measure suppression policy, suggesting that we should account for 
disparate effects of circumstances like the COVID-19 pandemic around 
the country. Commenters requested that we seek stakeholders' feedback 
before adopting more granular suppression policies in the future. A 
commenter cautioned against regional adjustments, suggesting that such 
adjustments would not account for differences in PHE prevalence at 
safety-net hospitals that take on leading roles during PHEs.
    Response: We thank the commenters for their feedback and will 
consider it for future rulemaking. We share the commenter's concern 
that adjustments to account for regional differences in a PHE's effects 
may not fully capture those differences.
    Comment: Several commenters expressed support for our proposal to 
provide confidential performance feedback to hospitals on suppressed 
measures.
    Response: We thank the commenters for their support. In the HAC 
Reduction Program, information regarding performance on CDC NHSN HAI 
data will be available within NHSN. For the CMS PSI 90 measures, 
feedback regarding suppressed data will be provided in public reporting 
CMS PSI 90 HSRs.
    After consideration of the public comments we received, we are 
finalizing our proposal to adopt a measure suppression policy and 
measure suppression factors described above for the FY 2022, and FY 
2023 HAC Reduction Program years, without modification. Further, as 
discussed above, and as a logical outgrowth of the proposed policy and 
of public comments, we are finalizing a policy to suppress Q3 and Q4 CY 
2020 data from the FY 2024 HAC Reduction Program.
d. Provision To Suppress Third and Fourth Quarter CY 2020 Data From the 
FY 2022, FY 2023, and FY 2024 HAC Reduction Program \793\
---------------------------------------------------------------------------

    \793\ The corresponding section title in the proposed rule did 
not include FY 2024 (86 FR 25499). However, as discussed further in 
this final rule, we believe that the suppression of third and fourth 
quarter CY 2020 data from FY 2024 HAC Reduction Program is a logical 
outgrowth from our proposal to suppress such quarters and comments 
received from the public.
---------------------------------------------------------------------------

    In section IX.I.3.c. of the proposed rule, we proposed to adopt a 
measure suppression policy (86 FR 25497 through 25499). In section 
IX.I.3.d. of the proposed rule, we proposed to suppress the third and 
fourth quarters of CY 2020 (that is, July 1, 2020 through September 30, 
2020 (Q3 2020) and October 1, 2020 through December 31, 2020 (Q4 2020)) 
CDC NHSN HAI and CMS PSI 90 data from our performance calculations for 
FY 2022 and FY 2023 under the proposed Measure Suppression Factor (1) 
``significant deviation in national performance on the measure, which 
could be significantly better or significantly worse compared to 
historical performance during the immediately preceding program 
years;'' and the Measure Suppression Factor (4) subfactor, 
``significant national or regional shortages or rapid or unprecedented 
changes in patient case volumes or case mix'' (86 FR 25499 through 
25500). Although Q3 and Q4 2020 data would be suppressed from the Total 
HAC Score calculation, hospitals would still be required to submit such 
data and such data would be used for public reporting purposes.
    The proposal to suppress Q3 and Q4 CY 2020 data also impacts the 
applicable period for the CMS PSI 90 measure in the FY 2024 HAC 
Reduction Program. We believe that the suppression of Q3 and Q4 CY 2020 
data from the FY 2024 HAC Reduction Program is a logical outgrowth of 
the proposal to suppress such quarters from the Program and comments 
received from the public.
    As described in more detail in section IX.B.7.a. of this final 
rule, through memoranda released in March 2020 and an IFC published in 
September 2020 (85 FR 54827 through 54828), in response to the COVID-19 
PHE, we excluded, by application of our ECE policy, all data submitted 
regarding care provided during the first and second quarters of CY 2020 
from our performance calculations for FY 2022 and FY 2023. We excluded 
such data because of our concerns about the national comparability of 
these data due to the geographic differences of COVID-19 incidence 
rates and hospitalizations, along with different impacts resulting from 
different State and local laws and policy changes implemented in 
response to COVID-19.
    We continue to be concerned about measure performance and the 
national comparability of such performance during Q3 and Q4 2020 and 
therefore proposed to suppress Q3 2020 and Q4 2020 HAI and CMS PSI 90 
measure data from the calculation of the Total HAC Score. An analysis 
performed by the CDC found that CLABSI, CAUTI, and MRSA had 
statistically significant measure rate increases during Q3 and Q4 CY 
2020 as compared to Q3 and Q4 CY 2019. We stated our belief that the 
measure data may have been distorted due to circumstances unique to the 
effects of the COVID-19 PHE, such as staffing shortages and turnover, 
patients that are more susceptible to infections due to increased 
hospitalization stays, and longer indwelling catheters and central 
lines. As for the SSI and CDI measures, neither measure had a 
statistically significant increase or

[[Page 45305]]

decrease during Q3 and Q4 2020 as compared to Q3 and Q4 2019. For the 
SSI measure, the low reporting volume is due to the decrease in 
surgeries during the COVID-19 PHE, while the CDI measure has 
historically been declining. Though the COVID-19 PHE may not have the 
same clinical impact on the SSI and CDI measures, we stated in the 
proposed rule that we believe that due to the low reporting volume of 
these two measures and for maintaining consistency of the full CDC NHSN 
HAI measure set, all five CDC NHSN HAI measures should be suppressed 
instead of just three of them. Similarly, our analysis of CMS PSI 90 
measure suggested that comparability of performance on the measure has 
also been impacted by the PHE. Our analysis found a decrease in volume 
across all component Patient Safety Indicator (PSI) measures, 
especially those related to elective surgeries (postoperative acute 
kidney injury rate, postoperative respiratory failure rate, and 
postoperative sepsis rate). Our analysis also found increased risk-
adjusted rates for patients with COVID-19 compared to patients without 
COVID-19 as well as increased risk-adjusted rates for the three 
component PSI measures that include non-surgical patients (pressure 
ulcer rate, iatrogenic pneumothorax rate, and in-hospital fall with hip 
fracture rate) while the surgical-specific component PSI measures 
(perioperative hemorrhage and hematoma rate, postoperative acute kidney 
injury rate, postoperative respiratory failure rate, perioperative 
pulmonary embolism or deep vein thrombosis rate, postoperative sepsis 
rate, postoperative wound dehiscence rate, and unrecognized 
abdominopelvic accidental puncture/laceration rate) did not see 
substantial change in risk-adjusted rates.
    As previously noted, under this policy, participating hospitals 
would continue to report all HAC Reduction Program measures' data to 
CMS, and in the case of the CDC NHSN HAI measures, to CDC, so that we 
can monitor the effect of the circumstances on quality measurement and 
determine appropriate policies in the future. We would also use Q3 and 
Q4 2020 data in feedback reports to hospitals as part of program 
activities, including to inform their quality improvement activities, 
and to ensure that they are made aware of and have an opportunity to 
preview the changes in performance rates we observe and display via 
public reporting to ensure transparency.
    The proposed suppression of Q3 and Q4 2020 HAI and CMS PSI 90 
measure data would result in the following applicable periods for 
calculating Total HAC Scores for FY 2022, FY 2023, and FY 2024 HAC 
Reduction Programs. For the FY 2022 HAC Reduction Program, the 
applicable period used for scoring for the CMS PSI 90 measure would 
remain the same as resulted from the previously granted ECE, that is, 
the 18-month period from July 1, 2018 through December 31, 2019. For 
the CDC NHSN HAI measures, this further exclusion would result in an 
applicable period for FY 2022 of the 12-month period from January 1, 
2019 through December 31, 2019. For the FY 2023 HAC Reduction Program, 
the exclusion would result in a shortened applicable period, for the 
CMS PSI 90 measure, to the 12-month period from July 1, 2019 through 
December 31, 2019 and January 1, 2021 through June 30, 2021, and for 
the CDC NHSN HAI measures to the 12-month period from January 1, 2021 
through December 31, 2021. For the FY 2024 HAC Reduction Program, the 
exclusion would result in a shortened applicable period, for the CMS 
PSI 90 measure, to the 18-month period of January 1, 2021 through June 
30, 2022.
    We stated our belief that using data from the proposed periods will 
provide sufficiently reliable data for evaluating hospital performance 
that we can use for FY 2022, FY 2023, and FY 2024 scoring.\794\ In the 
FY 2017 IPPS/LTCH PPS final rule, we clarified that a hospital has 
complete data for the CMS PSI 90 measure if it has 12 months or more of 
data and three or more eligible discharges for at least one component 
PSI measure within the CMS PSI 90 composite measure (81 FR 57021). 
Further, as noted in that rule, NQF determined that the CMS PSI 90 
measure is reliable using 12 months of data (81 FR 57021). We have also 
determined that a 12-month performance period provides us with 
sufficient data on which to score hospital performance on NHSN measures 
in the Safety domain of the Hospital VBP Program (79 FR 50071). We also 
noted that 12-month performance periods are consistent with the 
reporting periods used for these measures under the Hospital VBP 
Program (79 FR 50071) and when the measures were previously in the 
Hospital IQR Program (78 FR 50689).
---------------------------------------------------------------------------

    \794\ Although the corresponding paragraph in the proposed rule 
did not include FY 2024 (86 FR 25499), as discussed further in this 
final rule, we believe that its inclusion is a logical outgrowth of 
our proposal to suppress Q3 and Q4 CY 2020 data and comments 
received from the public.
---------------------------------------------------------------------------

    In determining how to address the impact of the COVID-19 PHE on 
hospital performance and calculating Total HAC Scores for FY 2022 and 
FY 2023, we also considered as an alternative to suppressing all Q3 and 
Q4 2020 data, suppressing CDC NHSN HAI measure data while using the CMS 
PSI 90 measure data. This alternative would have focused on suppressing 
those measures most impacted by the COVID-19 PHE. An analysis revealed 
that smaller and rural hospitals would be more negatively impacted by 
suppressing data for those measures most impacted by the COVID-19 PHE. 
Additionally, as previously discussed, we still have concerns about the 
comparability of data for the CMS PSI 90 measure from Q3 and Q4 2020 
due to differences in the risk-adjusted rate of component PSI measures 
for COVID-positive patients.
    We also considered making no modifications to the program and 
suppressing no measure data from Q3 and Q4 2020 for assessing FY 2022 
and FY 2023 Total HAC Scores as an additional alternative to using the 
measure suppression policy. As discussed, when considering this 
previously discussed approach, this alternative would be operationally 
easier to implement, but would mean assessing participating hospitals 
using quality measure data that have been impacted by the COVID-19 PHE 
without additional adjustments to the measure. Additionally, given the 
geographic disparities in the COVID-19 PHE's effects, this policy could 
place hospitals in regions that were hit harder by the pandemic in Q3 
and Q4 of 2020 at a disadvantage compared to hospitals in regions that 
were more heavily affected earlier in CY 2020. Ultimately, we stated 
our belief that our proposal to suppress both CDC NHSN HAI and CMS PSI 
90 measure data from Q3 and Q4 2020 more fairly addresses the impact of 
the COVID-19 PHE on participating hospitals.
    We invited comments on our proposal to suppress third and fourth 
quarter CY 2020 CDC NHSN HAI and CMS PSI 90 measure data from the HAC 
Reduction Program.
    Comment: Many commenters supported our proposal to suppress third 
and fourth quarter CY 2020 data from the FY 2022 and FY 2023 HAC 
Reduction Program.
    Response: We thank the commenters for their support.
    Comment: A commenter supported the proposal but asked CMS to 
provide information regarding the number of hospitals likely to be 
eligible to participate in the program based on the suppression policy.
    Response: We thank the commenter for its support. With the 
suppression of Q3 and Q4 CY 2020 data, an estimated 3,066 hospitals 
will receive Total HAC

[[Page 45306]]

Scores in FY 2022. See Appendix A for additional information regarding 
the numbers of hospitals estimated to be eligible to participate in the 
program by type for FY 2022.
    Comment: Several commenters supported the proposal to suppress 
third and fourth quarter CY 2020 data from the HAC Reduction Program 
and agreed that the data should be suppressed for future performance 
periods. These commenters also requested that CMS continue to monitor 
and evaluate available data to determine whether additional quarters of 
data should be suppressed for future performance periods due to the 
ongoing impacts of the PHE. These commenters expressed concerns that 
first and second quarter CY 2021 data may still be affected by the 
pandemic and using those data may unfairly disadvantage hospitals in 
certain regions or that serve certain populations. A commenter 
requested that CMS consider updating measure specifications to exclude 
patients with primary and secondary diagnoses of COVID-19 from HAC 
Reduction Program measures or adjust our risk adjustment models to 
account for prior COVID-19 diagnoses and the impact of COVID-19 on CY 
2021 performance. Another commenter requested that CMS clarify how it 
is considering handling first and second quarter CY 2021 data.
    Response: We appreciate commenters' support to suppress third and 
fourth quarter CY 2020 data from future performance periods. We are 
suppressing this data from FY 2022 and FY 2023 HAC Reduction Programs, 
as proposed. We also will suppress the data from FY 2024 HAC Reduction 
Program as a logical outgrowth from the proposal to suppress such data 
and comments received from the public. We continue to monitor the 
impact of the PHE on program data, including on CY 2021 data, and will 
take commenters' concerns and recommendations under consideration in 
the future.
    Comment: A few commenters supported the proposal to suppress third 
and fourth quarter CY 2020 data from Total HAC Score calculations, but 
did not support public reporting of suppressed data, including in 
Overall Star Ratings. A commenter expressed concern that the current 
footnote structure on Care Compare is not designed for patient and/or 
layperson navigation and therefore would be insufficient to communicate 
the gravity of the impact that the pandemic had on quality measures. A 
commenter recommended that CMS provide appropriate caveats and 
education to clarify that publicly reported results are based on data 
from the PHE. Another commenter expressed concern that the information 
will not be accurate enough for stakeholder decision making and 
recommended CMS perform analyses to ensure the reliability and validity 
of the results of each measure before reporting them publicly. The 
commenter stated that if the data are used in public reporting, CMS 
should consider strategies to ensure the accuracy of the information 
provided to consumers such as using data from before the PHE, excluding 
data from 2020, and assessing performance changes to ensure new results 
track with historical performance.
    Response: We understand the commenters concern about publicly 
reporting data during the PHE due to COVID-19. However, we will make 
clear in the public presentation of the data that the measure has been 
suppressed for purposes of scoring and payment adjustments because of 
the effects of the PHE due to COVID-19. We will appropriately caveat 
the data in order to mitigate public confusion and avoid 
misrepresenting quality of care. Four quarters of data will be publicly 
available on Care Compare, while HAC Reduction Program performance data 
will be available on the Provider Data Catalog, available at https://data.cms.gov/provider-data/. CMS continues to evaluate the data impacts 
and will provide information on future refreshes of the Overall 
Hospital Star Ratings when available.
    Comment: A few commenters supported our proposal to suppress Q3 and 
Q4 2020 data from the CDC NHSN HAI measures but raised concerns 
regarding the suppression of those data from the CMS PSI 90 measure. A 
few commenters expressed concern as to whether the CMS PSI 90 measure 
remained reliable with a performance period of 12 months. Other 
commenters requested that CMS continue to analyze data regarding the 
reliability of using shortened periods and a commenter requested that 
CMS make the results of such analysis public.
    Response: We appreciate the commenters' feedback. As detailed 
above, we have concluded that the updated version of the CMS PSI 90 
measure currently adopted in the Program remains sufficiently reliable 
with a performance period of 12 months. As noted above, the proposal to 
suppress Q3 and Q4 CY 2020 data from the CMS PSI 90 measure impacts FY 
2023 and FY 2024. Because the applicable period for FY 2022 would 
remain the same as resulted from the previously granted ECE (the 18-
month period from July 1, 2018 through December 31, 2019) and use only 
data prior to the PHE, no additional suppression is required for FY 
2022.
    Comment: A few commenters supported the proposal to suppress Q3 and 
Q4 CY 2020 data from the Total HAC scores but were concerned that our 
policy required hospitals that submit such data due to state 
requirements to also submit an Extraordinary Circumstances Exception 
(ECE) in order to have the data suppressed. Those commenters urged CMS 
to adopt a streamlined approach to automatically exclude such data.
    Response: We clarify that all subsection (d) hospitals are still 
required to submit Q3 and Q4 CY 2020 CDC NHSN HAI and CMS PSI 90 data 
for the HAC Reduction Program. However, all such data will be 
automatically suppressed from Total HAC Score calculations for FY 2022, 
FY 2023, and FY 2024 and no ECE is required to suppress those data. If 
a hospital wishes to request to not submit such data, an ECE would be 
required.
    Comment: A commenter requested that CMS empirically test whether 
the pandemic significantly changed risk-standardized rates of hospital 
outcomes, including HACs and patient safety indicators. The commenter 
requested that CMS specify the statistical methodology used for 
determining whether circumstances caused by the PHE affected HAC 
scores. The commenter also suggested that patients and consumers may 
need relevant information on which hospitals were able to provide high-
quality clinical outcomes despite circumstances beyond their control, 
as this may indicate pre-existing excellence in hospital processes and 
structures which are known to be associated with better outcomes.
    Response: We thank the commenter for its response. As stated in the 
proposed rule (86 FR 25499), an analysis performed by the CDC found 
that CLABSI, CAUTI, and MRSA had statistically significant measure rate 
increases in Q3 and Q4 CY 2020 as compared to Q3 and Q4 CY 2019. 
Similarly, our analysis of CMS PSI 90 measure suggested that 
comparability of performance on the measure has also been impacted by 
the PHE. We agree with the commenter that patients, consumers, and 
other stakeholders may find information regarding how hospitals 
performed during the PHE relevant, and that is why we will be using Q3 
and Q4 CY 2020 data in public reporting. As we have discussed in 
response to other comments, we believe that we should be as transparent 
as possible with the performance information that we collect.

[[Page 45307]]

    Comment: Several commenters expressed concern that the truncated 
applicable periods will in effect double-penalize hospitals that were 
in the worst quartile in FY 2021. Specifically, these commenters are 
concerned that by reusing only 2019 data, these hospitals may remain in 
the worst quartile even if they implemented policy and operational 
changes to improve their performance in 2020.
    Response: We appreciate commenters' concern. Since publication of 
the proposed rule, we have analyzed the removal of CY 2020 data from 
the FY 2022 HAC Reduction Program and found a change in worst-
performing quartile status for 17.2 percent of hospitals relative to 
their FY 2021 worst-performing quartile status, with 8.6 percent moving 
into the worst-performing quartile and 8.6 percent moving out, which is 
consistent with the proportion of hospitals that change their worst-
performing quartile status in previous years. We therefore do not 
believe that hospitals will be unfairly double penalized due to the 
suppression of data. We refer readers to Appendix A for additional 
information regarding the estimated numbers of hospitals in the worst-
performing quartile by hospital characteristic for FY 2022.
    Comment: A commenter did not support the proposal to suppress Q3 
and Q4 CY 2020 data and recommended that CMS risk-adjust for COVID-19 
as a patient-level risk factor instead. The commenter expressed 
concerns that having a 12-month applicable period and an overlapping 
18-month applicable period for CMS PSI 90 used in Care Compare at the 
same time would cause confusion and that risk-adjusting would allow for 
the same length of applicable period. Some commenters also recommended 
that CMS consider excluding COVID-19 patients from the CMS PSI 90 
measure calculations instead of suppressing the measure.
    Response: We appreciate the commenter's feedback. In determining 
how to address the impact of the COVID-19 PHE on hospital performance 
and calculating Total HAC Scores for FY 2022, FY 2023, and FY 2024, we 
considered risk-adjusting for COVID-19 as a patient-level risk factor. 
We ultimately determined that the measure suppression policy was 
preferable due to implementation concerns associated with making 
substantive changes to quality measure specifications that would 
necessitate NQF approval and rulemaking. We will continue to consider 
the best treatment of the CMS PSI 90 measure and monitor the data, and 
may revisit this approach in future rulemaking for future fiscal years. 
We will include appropriate information and caveats when publicly 
reporting the resulting performance data.
    Comment: A commenter stated its belief that CMS' proposal to 
suppress two quarters of data indicated that CMS can exempt certain 
hospitals from HAC Reduction Program calculations. This commenter 
specifically believed that Indian health providers are at an unfair 
disadvantage under the HAC Program and should be exempted from the 
program's calculations.
    Response: We appreciate and share the commenter's concerns 
regarding the impact of the COVID-19 PHE on Indian health providers. 
Under section 1886(p) of the Act, we are required to include all 
subsection (d) hospitals in the HAC Reduction Program unless exempt per 
section 1886(p)(2)(C) of the Act. We note that the measure suppression 
policy we are finalizing and its application to the HAC Reduction 
Program to suppress Q3 and Q4 CY 2020 data from Total HAC Score 
calculations is intended to be a limited approach to address in the 
short-term the COVID-19 PHE, which was an unanticipated event on a 
national and global scale. The focus of the measure suppression policy 
is to address the impact of the COVID-19 PHE on the quality measure 
data and the national comparability of such data, but it does not 
change hospital eligibility and participation requirements of the 
Program. Regarding the performance of Indian health providers under the 
HAC Program, we take the commenter's concerns seriously and will take 
them into consideration as we continue to monitor the impact of the 
program on various types of hospitals.
    Comment: A few commenters did not support the proposal to suppress 
Q3 and Q4 CY 2020 data and requested that CMS not enforce the one-
percent payment reduction for FY 2022 because reliable comparisons 
cannot be made due to the PHE.
    Response: We appreciate commenters concerns. However, under section 
1886(p) of the Act, we are required to impose a 1-percent payment 
reduction on the quartile of subsection (d) hospitals with the highest 
Total HAC Scores. As discussed in this section and section I.3.c., we 
considered various options for accounting for the impact of the PHE, 
and we believe that the measure suppression policy is the best solution 
with the data available that balances maintaining the HAC Reduction 
Program to continue incentivizing quality of care related to patient 
safety and adverse events while addressing the immediate impact of the 
COVID-19 PHE on the national comparability and reliability of the data 
that are used in the Program.
    After consideration of the public comments we received, we are 
finalizing our proposal to suppress Q3 and Q4 CY 2020 data from the FY 
2022 and FY 2023 HAC Reduction Programs, without modification. Further, 
as discussed above, and as a logical outgrowth of the proposed policy 
and of public comments, we are finalizing a policy to suppress Q3 and 
Q4 CY 2020 data from the FY 2024 HAC Reduction Program.
4. HAC Reduction Program Scoring Methodology and Scoring Review and 
Corrections Period
    In FY 2019 IPPS/LTCH PPS final rule (83 FR 41484 through 41489), we 
adopted the Equal Measure Weights approach to scoring and clarified the 
Scoring Calculations Review and Correction Period (83 FR 41484) for the 
HAC Reduction Program. Hospitals must register for a QualityNet 
website's secure portal account in order to access their annual 
hospital-specific reports. We will continue using this scoring 
methodology and the Scoring Calculations Review and Correction Period 
process in FY 2021 and for subsequent years. In the proposed rule, we 
did not propose any changes to the HAC Reduction Program scoring 
methodology or Scoring Calculations Review and Corrections Period.
5. Validation of HAC Reduction Program Data
    In the FY 2019 IPPS/LTCH PPS final rule (83 FR 41478 through 
41484), we adopted processes to validate the CDC NHSN HAI measure data 
used in the HAC Reduction Program, because the Hospital IQR Program 
finalized its proposals to remove CDC NHSN HAI measures from its 
program. In the FY 2020 IPPS/LTCH PPS final rule (84 FR 42406 through 
42410), we provided additional clarification to the validation 
selection and scoring methodology. We also refer readers to the 
QualityNet website for more information regarding chart-abstracted data 
validation of measures. In the FY 2020 IPPS/LTCH PPS final rule (85 FR 
58862 through 58865), we finalized our policy to align the HAC 
Reduction Program validation process with that of the Hospital IQR 
Program. Specifically, we aligned the hospital selection and submission 
quarters beginning with FY 2024 Hospital IQR and HAC Reduction Programs 
validation so that we only require one pool of hospitals to submit data 
for validation. Additionally, we finalized a policy requiring hospitals 
to submit digital files when submitting

[[Page 45308]]

medical records for validation of HAC Reduction Program measures, for 
the FY 2024 program year and subsequent years.
    In the FY 2021 IPPS/LTCH PPS final rule (85 FR 58862 through 
58865), we finalized our policy that for the FY 2024 program year and 
subsequent years, we will use measure data from all of CY 2021 for both 
the HAC Reduction Program and the Hospital IQR Program, which must be 
reported using the following validation schedule.
[GRAPHIC] [TIFF OMITTED] TR13AU21.279

    We  did not propose any changes to the policies regarding measure 
validation in the proposed rule.
---------------------------------------------------------------------------

    \795\ The CMS Clinical Data Abstraction Center (CDAC) performs 
the validation.
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6. Overall Hospital Quality Star Ratings
    In the CY 2021 OPPS/ASC final rule with comment period and interim 
final rule with comment period (85 FR 86193 through 86236), we 
finalized a methodology to calculate the Overall Hospital Quality Star 
Ratings (Overall Star Ratings). The Overall Star Ratings utilizes data 
collected on hospital inpatient and outpatient measures that are 
publicly reported on a CMS website, including data from the HAC 
Reduction Program. We refer readers to section XVI. of the CY 2021 
OPPS/ASC final rule for details. We did not propose any changes to this 
policy in the proposed rule.
7. Extraordinary Circumstances Exception (ECE) Policy for the HAC 
Reduction Program
a. Background
(1) Previously Established Extraordinary Circumstance Exception (ECE) 
Policy Under the HAC Reduction Program
    We refer readers to the FY 2016 IPPS/LTCH PPS final rule (80 FR 
49579 through 49581) and the FY 2018 IPPS/LTCH PPS (82 FR 38276 through 
38277) for discussion of our Extraordinary Circumstances Exception 
(ECE) policy. In the FY 2016 IPPS/LTCH PPS final rule (80 FR 49579 
through 49581), we adopted an ECE policy for the HAC Reduction Program, 
which recognized that there may be periods of time during which a 
hospital is affected by an extraordinary circumstance beyond its 
control. When adopting the policy, we noted that we considered the 
feasibility and implications of excluding data for certain measures for 
a limited period of time from the calculations for a hospital's measure 
results or Total HAC Score for the applicable performance period. By 
minimizing the data excluded from the program, the policy enabled 
affected hospitals to continue to participate in the HAC Reduction 
Program for a given fiscal year if they otherwise continued to meet 
applicable measure minimum threshold requirements. We expressed the 
belief that this approach would help alleviate the burden for a 
hospital that might be adversely impacted by a natural disaster or 
other extraordinary circumstance beyond its control, while enabling the 
hospital to continue to participate in the HAC Reduction Program. In 
developing this policy, we considered a policy and process similar to 
that for the Hospital IQR Program, as finalized in the FY 2012 IPPS/
LTCH PPS final rule (76 FR 51651), modified by the FY 2014 IPPS/LTCH 
PPS final rule (78 FR 50836) (designation of a non-CEO hospital 
contact), and further modified in the FY 2015 IPPS/LTCH PPS final rule 
(79 FR 50277) (amended Sec.  412.40(c)(2)) to refer to ``extension or 
exemption'' instead of the former ``extension or waiver''). We also 
considered how best to align an extraordinary circumstance exception 
policy for the HAC Reduction Program with existing extraordinary 
circumstance exception policies for other IPPS quality reporting and 
payment programs, such as the Hospital Value-Based Purchasing (VBP) 
Program, to the extent feasible.
    In the FY 2018 IPPS/LTCH PPS final rule (82 FR 38276 through 
38277), we modified the requirements for the HAC Reduction Program ECE 
policy to further align with the process used by other quality 
reporting and value-based purchasing programs for requesting an 
exception from program reporting due to an extraordinary circumstance 
not within a provider's control.
(2) Extraordinary Circumstances Exception (ECE) Granted in Response to 
the COVID-19 Public Health Emergency
    On March 22, 2020, in response to COVID-19, we announced relief for 
clinicians, providers, hospitals, and facilities participating in 
Medicare quality reporting and value-based purchasing programs.\796\ 
Specifically, we announced that we were granting ECEs for certain data 
reporting requirements and submission deadlines for the first and 
second quarters of CY 2020. On March 27, 2020, we published a 
supplemental guidance memorandum that described the scope and duration 
of the ECEs we were granting under each Medicare quality reporting and 
value-based purchasing program.\797\ In that memorandum, we stated that 
qualifying

[[Page 45309]]

claims would be excluded from the measure calculations for the CMS PSI 
90 for the first and second quarters of calendar year (CY) 2020. The 
ECEs also relieved providers and facilities of their obligation to 
report CDC NHSN HAI data for the fourth quarter CY 2019, first quarter 
CY 2020 and second quarter CY 2020.
---------------------------------------------------------------------------

    \796\ CMS, Press Release, CMS Annouces Relief for Clinicians, 
Providers, Hospitals and Facilities Participating in Quality 
Reporting Programs in Response to COVID-19 (Mar. 22, 2020), https://www.cms.gov/newsroom/press-releases/cms-announces-relief-clinicians-providers-hospitals-and-facilities-participating-quality-reporting.
    \797\ CMS, Exceptions and Extensions for Quality Reporting 
Requirements for Acute Care Hospitals, PPS-Exempt Cancer Hospitals, 
Inpatient Psychiatric Facilities, Skilled Nursing Facilities, Home 
Health Agencies, Hospices, Inpatient Rehabilitation Facilities, 
Long-Term Care Hospitals, Ambulatory Surgical Centers, Rental 
Dialysis Facilities, and MIPS Eligible Clinicians Affected by COVID-
19 (Mar. 27, 2020), https://www.cms.gov/files/document/guidance-memo-exceptions-and-extensions-quality-reporting-and-value-based-purchasing-programs.pdf.
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(3) Updated Application of the ECE Granted in Response to the COVID-19 
PHE
    On September 2, 2020, we published the interim final rule with 
comment period (IFC) titled ``Medicare and Medicaid Programs, Clinical 
Laboratory Improvement Amendments (CLIA), and Patient Protection and 
Affordable Care Act; Additional Policy and Regulatory Revisions in 
Response to the COVID-19 Public Health Emergency'' (85 FR 54820). The 
IFC updated the ECE we granted in response to the PHE for COVID-19, for 
the HAC Reduction Program and several other quality reporting programs 
(85 FR 54827 through 54838).
    In the IFC, we updated the previously announced application of our 
ECE policy for the HAC Reduction Program (85 FR 54830 through 54832) to 
the COVID-19 PHE to exclude any CDC NHSN HAI data submitted regarding 
care provided during first and second quarter of CY 2020 from our 
calculation of performance for FY 2022 and FY 2023, even if optionally 
reported. We recognized that the chart-abstracted measures in the HAC 
Reduction Program are calculated based on data submitted to the CDC's 
NHSN and that because the CDC uses the same data for epidemiological 
surveillance, hospitals may have reporting requirements which are not 
affected by our ECE (for example, State requirements). We expressed 
concern with the national comparability of the HAC Reduction Program 
data due to the geographic differences of COVID-19 incidence rates and 
hospitalizations along with different impacts resulting from different 
State and local law and policy changes implemented in response to 
COVID-19.
    In the IFC, we welcomed public comments on our policy to exclude 
any data submitted regarding care provided during the first and second 
quarter of CY 2020 from our calculation of performance for the FY 2022 
and FY 2023 program years.
    In the September 2, 2020 IFC, we also announced that if due to ECEs 
related to the COVID-19 PHE, we do not have enough data to reliably 
measure national performance, we may propose to not score hospitals 
based on such limited data or make the associated payment adjustments 
to hospitals under the IPPS for the affected program year. We stated 
that, if circumstances warranted, we could propose to suspend 
prospective application of program penalties or payment adjustments 
through the annual IPPS/LTCH PPS proposed rule. We also stated that, in 
the interest of time and transparency, we may provide subregulatory 
advance notice of our intentions to suspend such penalties and 
adjustments through routine communication channels to facilities, 
vendors, and QIOs. The communications could include memos, emails, and 
notices on the public QualityNet website (https://www.qualitynet.cms.gov/).\798\
---------------------------------------------------------------------------

    \798\ We note that the QualityNet website (previously at 
QualityNet.org) has transitioned to a new uniform resource locator 
(URL) at QualityNet.cms.gov.
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    We received the following comments on the IFC.
    Comment: A commenter supported our policy to exclude any data 
submitted regarding care provided during the first and second quarter 
of CY 2020 from our calculation of performance for the FY 2022 and FY 
2023 program years and expressed agreement that data should not be 
utilized if hospital performance cannot be appropriately compared.
    Response: We thank the commenter for the support.
    Comment: A commenter did not support scoring optionally submitted 
CY 2019 fourth quarter data. The commenter argued that hospitals have 
faced significant financial challenges during the pandemic and that the 
decision to use the data, which were submitted by over 95 percent of 
hospitals, created additional uncertainty for hospitals because it is 
difficult for them to anticipate a payment reduction with nearly 5 
percent of hospitals not reporting data. The commenter concluded that 
given the financial toll of the pandemic, CMS should refrain from 
imposing the 1-percent payment reduction under the HAC Reduction 
Program.
    Response: We believe that because nearly all hospitals reported 
their Q4 2019 HAI data by the submission deadline and reporting rates 
for the quarter were similar to quarters prior to the PHE, the optional 
reporting for the relatively small number of hospitals that needed the 
flexibility at the beginning of the PHE did not create additional 
uncertainty for hospitals. We do not have concerns about the validity 
or reliability of the Q4 2019 reported data that reflects performance 
on a time period before the COVID-19 PHE. Additionally, although we 
appreciate the financial toll of the pandemic on hospitals, under 
section 1886(p)(1) of the Act, we are statutorily required to impose a 
1-percent payment reduction to the worst-performing quartile of all 
subsection (d) hospitals.
    In the IFC, we finalized the exclusion of any data submitted 
regarding care provided during the first and second quarter of CY 2020 
from our calculation of performance for the FY 2022 and FY 2023 program 
years. We noted that the inclusion of data optionally reported by 
hospitals for the fourth quarter of CY 2019 in calculating hospitals' 
Total HAC Scores was consistent with the policy stated in the March 27, 
2020 guidance memo.
    In section IX.I.3.d. of this final rule, we finalized our policy to 
suppress third and fourth quarter CY 2020 data from FY 2022, FY 2023, 
and FY 2024 Total HAC Scores using the measure suppression policy.
b. General Clarifications to HAC Reduction Program ECE Policy
    After the nationwide ECE granted in response to the COVID-19 PHE 
ended, we received several requests from hospitals for individual ECEs 
under the HAC Reduction Program, due to extraordinary circumstances 
resulting from the continuing impact of the pandemic. These individual 
ECE requests specifically requested clarity on whether CDC NHSN HAI 
measure data that hospitals submitted to the CDC NHSN because of State 
reporting requirements could be excluded from the HAC Reduction Program 
Total HAC Score calculations. In this final rule, we would like to 
clarify that an ECE granted under the HAC Reduction Program may allow 
an exception from quality data reporting requirements and/or may grant 
a request to exclude any data submitted (whether submitted for claims 
purposes or to the CDC NHSN) from the calculation of a hospital's 
measure results or Total HAC Score for the applicable period, depending 
on the exact circumstances under which the request was made.
    We have also received a few ECE requests from hospitals for an 
exception from the HAC Reduction Program payment reduction. The ECE 
policy for the HAC Reduction Program is intended to provide relief for 
a hospital that has been negatively impacted as a direct result of 
experiencing a significant disaster or other extraordinary circumstance 
beyond the hospital's control by excluding data and/or granting an 
exception with respect to data reporting requirements for the

[[Page 45310]]

period during which performance or ability to submit data was impacted. 
However, we also believe that the hospital should still be evaluated 
for the remainder of the applicable period during which performance 
and/or ability to timely submit data was not impacted (to the extent 
that enough data are available to ensure that the calculation is 
statistically sound). This policy is not intended to extend to payment 
reductions. Therefore, we would like to clarify that an approved ECE 
for the HAC Reduction Program does not exempt hospitals from payment 
reductions under the HAC Reduction Program.
c. Clarification of the Impact of ECE Excluded Data for the HAC 
Reduction Program
    In this final rule, we would also like to clarify the impact on 
upcoming HAC Reduction Program calculations of data excluded from the 
HAC Reduction Program due to the nationwide ECE. In order to determine 
and evaluate what kind of impact the PHE for COVID-19 might have on the 
HAC Reduction Program, we conducted analyses to simulate the impact of 
an altered performance period on program eligibility and the resulting 
payment impacts to hospitals using data for the FY 2020 HAC Reduction 
Program performance period. This analysis was intended to evaluate what 
patterns we might observe in HAC Reduction Program eligibility and 
payment as a result of excluding 6 months of data due to the ECE 
granted in response to the PHE for COVID-19. Our analysis for the 
proposed rule found that when 6 months of data are removed from HAC 
Reduction Program calculations, 12.2 percent of hospitals see a change 
in worst-performing quartile status, with 6.1 percent moving into the 
worst-performing quartile and 6.1 percent moving out. For context, in a 
typical year approximately 18 percent of hospitals experience a change 
in worst-performing quartile status from one year to the next. An 
analysis of FY 2022 data resulted in a change in worst-performing 
quartile status for 17.2 percent of hospitals relative to their FY 2021 
worst-performing quartile status. We refer readers to Appendix A for 
additional information regarding the estimated numbers of hospitals in 
the worst-performing quartile by hospital characteristic for FY 2022.
    As we stated in the FY 2015 IPPS/LTCH PPS final rule (79 FR 50100 
through 50101) and reiterated in the FY 2019 IPPS/LTCH PPS final rule 
(83 FR 41475), we will use a subregulatory process to make 
nonsubstantive updates to measure specifications to facilitate the 
program's operation when minor changes are required, but do not 
substantively impact the program's previously finalized policies (84 FR 
42385 through 42387). We believe that updates to measure inclusion 
criteria proposed by the measure developers in response to the COVID-19 
PHE are substantive and we have discussed and finalized them in this 
rulemaking. For more details, we refer readers to the Hospital Specific 
Report (HSR) User Guide located on QualityNet website at: https://qualitynet.cms.gov/inpatient/hac/reports.
8. Regulatory Updates (42 CFR 412.172)
    We proposed to update the references to CMS resources in regulation 
text. We note that we renamed our Hospital Compare website. It is now 
referred to as Care Compare and is available at: https://www.medicare.gov/care-compare. We proposed to revise our regulations 
for the HAC Reduction Program at 42 CFR 412.172(f)(4) to reflect the 
new website name. We also proposed to amend Sec.  412.172(f)(4), by 
adding the phrase ``or successor website'' so that the text reads 
``Hospital Compare website or successor website.'' \799\ We invited 
public comment on our proposal. We received no comments on this 
proposal. We are finalizing our proposal, without modification.
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    \799\ While the statute refers to Hospital Compare, the name has 
been changed to Care Compare. Now called Care Compare, the website 
continues to serve the purpose of displaying quality data submitted 
for the HAC Reduction Program.
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J. Payment for Indirect and Direct Graduate Medical Education Costs 
(Sec. Sec.  412.105 and 413.75 Through 413.83)

1. Background
    Section 1886(h) of the Act, as added by section 9202 of the 
Consolidated Omnibus Budget Reconciliation Act (COBRA) of 1985 (Pub. L. 
99-272) and as currently implemented in the regulations at 42 CFR 
413.75 through 413.83, establishes a methodology for determining 
payments to hospitals for the direct costs of approved graduate medical 
education (GME) programs. Section 1886(h)(2) of the Act sets forth a 
methodology for the determination of a hospital-specific base-period 
per resident amount (PRA) that is calculated by dividing a hospital's 
allowable direct costs of GME in a base period by its number of full-
time equivalent (FTE) residents in the base period. The base period is, 
for most hospitals, the hospital's cost reporting period beginning in 
FY 1984 (that is, October 1, 1983 through September 30, 1984). The base 
year PRA is updated annually for inflation. In general, Medicare direct 
GME payments are calculated by multiplying the hospital's updated PRA 
by the weighted number of FTE residents working in all areas of the 
hospital complex (and at nonprovider sites, when applicable), and the 
hospital's Medicare share of total inpatient days.
    Section 1886(d)(5)(B) of the Act provides for a payment adjustment 
known as the indirect medical education (IME) adjustment under the IPPS 
for hospitals that have residents in an approved GME program, in order 
to account for the higher indirect patient care costs of teaching 
hospitals relative to nonteaching hospitals. The regulations regarding 
the calculation of this additional payment are located at 42 CFR 
412.105. The hospital's IME adjustment applied to the DRG payments is 
calculated based on the ratio of the hospital's number of FTE residents 
training in either the inpatient or outpatient departments of the IPPS 
hospital to the number of inpatient hospital beds.
    The calculation of both direct GME payments and the IME payment 
adjustment is affected by the number of FTE residents that a hospital 
is allowed to count. Generally, the greater the number of FTE residents 
a hospital counts, the greater the amount of Medicare direct GME and 
IME payments the hospital will receive. In an attempt to end the 
implicit incentive for hospitals to increase the number of FTE 
residents, Congress, through the Balanced Budget Act of 1997 (Pub. L. 
105-33), established a limit on the number of allopathic and 
osteopathic residents that a hospital may include in its FTE resident 
count for direct GME and IME payment purposes. Under section 
1886(h)(4)(F) of the Act, for cost reporting periods beginning on or 
after October 1, 1997, a hospital's unweighted FTE count of residents 
for purposes of direct GME may not exceed the hospital's unweighted FTE 
count for direct GME in its most recent cost reporting period ending on 
or before December 31, 1996. Under section 1886(d)(5)(B)(v) of the Act, 
a similar limit based on the FTE count for IME during that cost 
reporting period is applied, effective for discharges occurring on or 
after October 1, 1997. Dental and podiatric residents are not included 
in this statutorily mandated cap.
    The Affordable Care Act made a number of statutory changes relating 
to the determination of a hospital's FTE resident limit for direct GME 
and IME

[[Page 45311]]

payment purposes and the manner in which FTE resident limits are 
calculated and applied to hospitals under certain circumstances.
    Section 5503(a)(4) of the Affordable Care Act added a new section 
1886(h)(8) to the Act to provide for the reduction in FTE resident caps 
for direct GME under Medicare for certain hospitals training fewer 
residents than their caps, and to authorize the redistribution of the 
estimated number of excess FTE resident slots to other qualified 
hospitals. In addition, section 5503(b) amended section 
1886(d)(5)(B)(v) of the Act to require the application of the section 
1886(h)(8) of the Act provisions in the same manner to the IME FTE 
resident caps. The policy implementing section 5503 of the Affordable 
Care Act was included in the November 24, 2010 CY 2011 OPPS/ASC final 
rule with comment period (75 FR 72147 through 72212) and the FY 2013 
IPPS/LTCH PPS final rule (77 FR 53424 through 53434). Section 5506(a) 
of the Affordable Care Act amended section 1886(h)(4)(H) of the Act to 
add a new clause (vi) that instructs the Secretary to establish a 
process by regulation under which, in the event a teaching hospital 
closes, the Secretary will permanently increase the FTE resident caps 
for hospitals that meet certain criteria up to the number of the closed 
hospital's FTE resident caps. The policy implementing section 5506 of 
the Affordable Care Act was included in the November 24, 2010 CY 2011 
OPPS/ASC final rule with comment period (75 FR 72212 through 72238), 
the FY 2013 IPPS/LTCH PPS final rule (77 FR 53434 through 53448), and 
the FY 2015 IPPS/LTCH final rule (79 FR 50122-50140).
2. Provisions of the Consolidated Appropriations Act, 2021
    The Consolidated Appropriations Act, 2021 (CAA), division CC, 
contained 3 provisions affecting Medicare direct GME and IME payments 
to teaching hospitals. Section 126 of the CAA makes available 1,000 new 
Medicare-funded GME positions (but not more than 200 new positions for 
a fiscal year), to be distributed beginning in fiscal year 2023, with 
priority given to hospitals in 4 statutorily-specified categories. 
Section 127 of the CAA makes statutory changes relating to the 
determination of both an urban and rural hospital's FTE resident limit 
for direct GME and IME payment purposes with regard to residents 
training in an accredited rural training track (RTT), and the 3-year 
rolling average set out at section 1886(h)(4)(G)(i) of the Act used to 
calculate payments for these hospitals. Section 131 of the CAA makes 
statutory changes to the determination of direct GME PRAs and direct 
GME and IME FTE resident limits of hospitals that hosted a small number 
of residents for a short duration. We provided detailed proposals for 
implementing these three CAA provisions in the FY 2022 IPPS/LTCH PPS 
proposed rule (86 FR 25502 through 25523).
    We continue to review the large number of comments on the proposed 
provisions relating to sections 126, 127 and 131 of division CC the 
Consolidated Appropriations Act, 2021 (CAA, 2021). Due to the number 
and nature of the comments that we received on our proposed policies, 
we intend to address the public comments in a separate document. We 
refer individuals interested in reviewing the background information 
and the discussion regarding these policies to the FY 2022 IPPS/LTCH 
PPS proposed rule (86 FR 25503 through 25523).
3. Proposal for Intern and Resident Information System (IRIS) Data
    Section 42 CFR 413.24(f)(5)(i) provides that a Medicare cost report 
for a teaching hospital is rejected for lack of supporting 
documentation if the cost report does not include a copy of the Intern 
and Resident Information System (IRIS) diskette. In accordance with 42 
CFR 413.78(b) for direct GME and 42 CFR 412.105(f)(1)(iii)(A) for IME, 
no individual may be counted as more than one full-time equivalent 
(FTE). A hospital cannot claim the time spent by residents training at 
another hospital; if a resident spends time in more than one hospital 
or in a non-provider setting, the resident counts as a partial FTE 
based on the proportion of time worked at the hospital to the total 
time worked. A part-time resident count as a partial FTE based on the 
proportion of total time worked compared to the total time necessary to 
fill a full-time internship or residency slot.
    In 1990, we established the IRIS, under the authority of sections 
1886(d)(5)(B) and 1886(h) of the Act, in order to facilitate proper 
counting of FTE residents who rotate to more than one site (that is, 
hospitals, non-provider settings). Teaching hospitals use the IRIS to 
collect and report information on residents training in approved 
residency programs. Section 42 CFR 413.24(f)(5)(i) requires teaching 
hospitals to submit the IRIS data along with their Medicare cost 
reports in order to have an acceptable cost report submission. As 
stated in the FY 2022 IPPS/LTCH PPS proposed rule (86 FR 25523), we are 
in the process of issuing a new Extensible Markup Language (XML)-based 
IRIS file format that captures FTE resident count data consistent with 
the manner in which FTEs are reported on the Medicare cost report.
    After receiving the IRIS data along with each teaching hospital's 
cost report, the contractors upload the data to a national database 
housed at CMS, which can be used to identify ``duplicates,'' that is, 
the same time period (for example, April 1 through April 3 of a given 
fiscal year) being claimed by more than one hospital in their GME/IME 
FTE resident count. If duplicates are identified, the contractors will 
make the hospitals that claimed the same time aware of this situation 
and will correct the duplicate reporting on the respective hospitals' 
cost reports for direct GME and IME payment purposes.
    Historically, we would collect the IRIS data from hospitals on a 
diskette, as referenced in 42 CFR 413.24(f)(5)(i). Because diskettes 
are no longer used by providers to furnish these data to contractors, 
in the FY 2022 IPPS/LTCH PPS proposed rule (86 FR 25523 through 25524), 
we proposed to remove the reference in the regulations to a diskette 
and instead reference ``Intern and Resident Information System data.'' 
Specifically, we proposed to amend 42 CFR 413.24(f)(5)(i) by adding a 
new paragraph (A) to include this proposed revised language.
    In addition, to enhance the contractors' ability to review 
duplicates and to ensure residents are not being double-counted, we 
stated in the proposed rule that we believe it is necessary and 
appropriate to require that the total weighted and unweighted FTE 
counts on the IRIS for direct GME and IME respectively, for all 
applicable allopathic, osteopathic, dental, and podiatric residents 
that a hospital may train, must equal the same total weighted and 
unweighted FTE counts for direct GME and IME reported on Worksheet E-4 
and Worksheet E, Part A of the filed Medicare cost report. The need to 
verify and maintain the integrity of the IRIS data has been the subject 
of reviews by the Office of the Inspector General (OIG) over the years. 
An August 2014 OIG report cited the need for CMS to develop procedures 
to ensure that no resident is counted as more than one FTE in the 
calculation of Medicare GME payments (OIG Report No. A-02-13-01014, 
August 2014). More recently, a July 2017 OIG report recommended that 
procedures be developed to ensure that no resident is counted as more 
than one FTE in the calculation of Medicare GME payments (OIG Report 
No. A-02-15-01027, July 2017).
    Therefore, effective for cost reporting periods beginning on or 
after October 1, 2021, in the FY 2022 IPPS/LTCH PPS

[[Page 45312]]

proposed rule (86 FR 25524), we proposed to add the requirement that 
IRIS data contain the same total counts of direct GME FTE residents 
(unweighted and weighted) and of IME FTE residents as the total counts 
of direct GME and IME FTE residents reported in the cost report. 
Specifically, we proposed to amend 42 CFR 413.24(f)(5)(i)(A) to state 
that, effective for cost reporting periods on or after October 1, 2021, 
the IRIS data must contain the same total counts of direct GME FTE 
residents (unweighted and weighted) and of IME FTE residents as the 
total counts of direct GME FTE and IME FTE residents reported in the 
hospital's cost report, or the cost report will be rejected for lack of 
supporting documentation.
    Providers would be required to use the new XML IRIS format for all 
cost reports with cost reporting periods beginning on or after October 
1, 2021. CMS does not have a free download of the new IRIS XML format; 
the providers should use their vendors' software to file their IRIS 
report with the Medicare Administrative Contractor.
    Comment: A commenter appreciated that the agency has worked with 
independent vendors to develop a new version of the IRIS software. 
However, the commenter stated that CMS expects teaching hospitals 
participating in the Medicare program to contract with private 
companies to comply with a Medicare requirement. According to the 
commenter, CMS should develop its own version of IRIS, make it freely 
available for download to Medicare-participating hospitals that train 
residents, and keep it updated. However, the commenter appreciated that 
many of the changes that they and their members suggested have been 
incorporated into the new versions of the software that the private 
vendors have developed. The commenter explained that they submitted 
comments on the IRIS update process to CMS in June 2018 and July 2019. 
According to the commenter, the general changes that have been under 
discussion are necessary and appropriate, and they look forward to 
seeing those changes finalized. However, the commenter understands that 
certain vendors have not made the changes yet and/or have not released 
new versions of their software. Thus, the commenter and other members 
of the public are being asked to comment on a software change that the 
teaching hospital members have not seen, and more importantly, have not 
been able to work with for any period of time. According to the 
commenter, teaching hospitals should be able to work with the new 
software format for a full cost reporting year and work through any 
system concerns and issues before being subject to a regulatory 
requirement that might result in the rejection of a hospital's Medicare 
cost report. Therefore, the commenter requested that CMS withdraw its 
proposed regulatory change until such time as the teaching hospital 
community has a full cost reporting year to work with the new software 
and work out any system problems encountered. The commenter also 
requested that CMS explain in more detail the process by and timeframe 
in which the contractor will make hospitals that claimed the same time 
aware of duplicates, and the expectations regarding the affected 
hospitals' resolutions of those duplicates.
    Response: CMS is validating vendor IRIS software to ensure that it 
meets the IRIS XML specifications. CMS is planning on releasing the 
list of all approved IRIS software vendors. We understand the 
commenter's concern about rejection of the cost report if the submitted 
IRIS GME and IME FTEs do match the related counts reported in the cost 
reports beginning on or after October 1, 2021. However, we maintain 
that in order to properly identify the IRIS duplicates, it is necessary 
that the IME and GME FTE counts in the submitted IRIS match the related 
FTEs reported on the cost report. Therefore, we are finalizing 
revisions responsive to this concern, which are discussed below. We are 
not planning on issuing free IRIS software. CMS will issue a list of 
all approved IRIS software vendors.
    The timeline for review and resolution of duplicates would be based 
the Medicare Administrative Contractors (MACs) schedule for reviewing 
of the affected cost reports. Also, the MACs would follow their 
established process for resolving the duplicate. Comment asking CMS to 
describe a detailed process for how the MACs will resolve the 
duplicates for hospitals that claimed the same time considered outside 
the scope of this rule.
    Comment: A few commenters suggested that CMS should ensure that the 
proposal for reporting GME FTEs on the Medicare cost report is 
consistent with children's hospitals Medicare cost reporting 's 
hospitals are not reimbursed under the IPPS, they do not receive IME 
payments and therefore do not complete Worksheet E, Part A of the 
Medicare cost report. Thus, these commenters have noted that they 
either cannot access the worksheet or their cost reports may be flagged 
for errors if they attempt to submit information in the worksheet. 
According to the commenters, if CMS were to finalize the proposed rule, 
CMS must either exempt children's hospitals from this requirement, or 
alternatively, CMS must provide guidance and ensure that the 
information technology systems are updated such that children's 
hospitals can complete the required sections.
    Response: The proposed rule that GME and IME FTEs (weighted and 
unweighted) reported on the IRIS data match the total FTEs reported on 
the Medicare cost report does not change the Medicare cost report 
rules. Children's hospitals and other provider types that are not 
reimbursed for IME are not required to report IME FTEs reported in FTEs 
on the Medicare cost reports. Therefore, there is no requirement that 
the total IME IRIS match the total IME FTEs reported in the cost report 
for providers that are not reimbursed for IME.
    Comment: Several commenters had various concerns with the rule's 
proposal to require the data reported in IRIS must match data 
information provided in the cost report, to which it relates. A 
commenter explained that while they are supportive of using new 
technology to collect the IRIS data, they oppose the CMS' proposal to 
reject a cost report that lacks supporting documentation unless the 
IRIS data contains the same total counts of direct GME FTE residents 
(unweighted and weighted) and of IME FTE residents as the total counts 
of direct GME and IME FTEs on the cost report. The commenter stated 
that they are concerned that hospitals may experience software issues 
with the new IRIS data collection system since it has not been used 
before. As a result, this commenter requested that the CMS consider 
these transition issues and not penalize hospitals for inadvertent 
errors that commonly arise due to the complications of recording 
resident rotations and that ultimately are corrected to ensure accurate 
Medicare payment.
    A commenter added that they believe IRIS will continue to catch 
inadvertent errors and those errors will continue to be fixed. 
Therefore, the commenter believes that there is no need to impose this 
requirement and hospitals should not be penalized for inadvertent 
errors that commonly arise due to the complications of recording 
resident rotations and that ultimately are corrected to ensure proper 
Medicare payment. According to the commenter, CMS acknowledges the way 
in which IRIS is used when it states, in part, that if duplicates are 
identified, the contractors will make the hospitals that claimed the 
same time aware of this

[[Page 45313]]

situation and will correct the duplicate reporting on the respective 
hospitals' cost reports for direct GME and IME payment purposes. The 
commenter also questioned whether CMS recognized the adoption of new 
software program may present a technical issue for hospitals that must 
transition to an application they have not used before. The commenter 
explained that as they have learned from experience, it is not unusual 
for new software to have issues that may cause unintended problems.
    Some of these other commenters also recommended that CMS delay this 
proposal to allow hospitals and MACs sufficient time to gain 
familiarity with this new software and address other potential process 
issues that could result in cost reports being inappropriately 
rejected.
    Response: As explained in the preamble, CMS is required to review 
the GME & IME FTEs to identify duplicates. In order to ensure that the 
IRIS is identifying appropriate duplicates that the provider is 
actually claiming, or not claiming, in the cost report, the IRIS total 
GME and IME FTE counts must match the total GME and IME FTE counts 
claimed in the cost report. For example, if the GME FTE count (weighted 
or unweighted) reported in the cost report is lower than the related 
GME count computed from the IRIS, any duplicate identified by the IRIS 
may not be valid because it is possible that the cost report count does 
not contain the rotation or rotations that resulted in the IRIS 
duplicate. On the other hand, if the GME FTE count (weighted or 
unweighted) reported in the cost report is higher than the related GME 
FTE count computed from the IRIS, it is possible that the IRIS is not 
identifying some duplicates which are reported on the cost report. 
Since we are aware that there might be some rounding errors between 
total FTEs reported on the cost report and the IRIS data, CMS will 
establish a tolerance threshold for variances between total GME and IME 
FTE reported on the cost report and the IRIS data to account for 
possible rounding variances.
    CMS is validating vendor IRIS software to ensure that it meets the 
IRIS XML specifications and will release the list of all approved IRIS 
software vendors. However, we agree with the commenters that we should 
delay the implementation of the new policy requiring MACs to reject 
cost reports where the total number of reported submitted IRIS GME and 
IME FTEs do not match the total IME and GME FTEs reported on the cost 
report.
    After consideration of the public comments we received, we are 
modifying 42 CFR 413.24(f)(5)(i)(A) to require that for cost reporting 
periods beginning on or after October 1, 2021, the GME weighted and 
unweighted) and IME FTE counts on the submitted IRIS must match the 
total GME and IME FTE counts reported on the cost report. However, for 
cost reporting periods beginning on or after October 1, 2021 and before 
October 1, 2022, the cost reports will not be rejected if the total IME 
and GME FTEs (weighted and unweighted) on the submitted IRIS do not 
match the total related FTEs reported on the cost report.
    We are also revising this sub-section to include a requirement that 
for cost reporting periods beginning on or after October 1, 2021, the 
IRIS data must be in the XML format.

L. Rural Community Hospital Demonstration Program

1. Introduction
    The Rural Community Hospital Demonstration was originally 
authorized by section 410A of the Medicare Prescription Drug, 
Improvement, and Modernization Act of 2003 (MMA) (Pub. L. 108-173). The 
demonstration has been extended three times since the original 5-year 
period mandated by the MMA, each time for an additional 5 years: These 
extensions were authorized by sections 3123 and 10313 of the Affordable 
Care Act (Pub. L. 111-148) (ACA), section 15003 of the 21st Century 
Cures Act (Pub. L. 114-255) (Cures Act), enacted in 2016, and most 
recently, by section 128 of the Consolidated Appropriations Act of 2021 
(Pub. L. 116-260) (CAA 2021). In this final rule, we are summarizing 
the status of the demonstration program, as well as the methodologies 
for continued implementation and budget neutrality under the extension 
authorized by section 128 of the Public Law 116-260.
2. Background
    Section 410A(a) of Public Law 108-173 required the Secretary to 
establish a demonstration program to test the feasibility and 
advisability of establishing rural community hospitals to furnish 
covered inpatient hospital services to Medicare beneficiaries. The 
demonstration pays rural community hospitals under a reasonable cost-
based methodology for Medicare payment purposes for covered inpatient 
hospital services furnished to Medicare beneficiaries. A rural 
community hospital, as defined in section 410A(f)(1), is a hospital 
that--
     Is located in a rural area (as defined in section 
1886(d)(2)(D) of the Act) or is treated as being located in a rural 
area under section 1886(d)(8)(E) of the Act;
     Has fewer than 51 beds (excluding beds in a distinct part 
psychiatric or rehabilitation unit) as reported in its most recent cost 
report;
     Provides 24-Hour emergency care services; and
     Is not designated or eligible for designation as a CAH 
under section 1820 of the Act.
3. Policies for Implementing the 5-Year Extension Period Authorized by 
Public Law 116-260
    Our policy for implementing the 5-year extension period authorized 
this year by Public Law 116-260 follows upon that for the previous 
extensions, under the ACA (Pub. L. 111-148) and the Cures Act (Pub. L. 
114-255).
    Section 410A of Public Law 108-173 (MMA) initially required a 5-
year period of performance. Subsequently, sections 3123 and 10313 of 
Public Law 111-148 (ACA) required the Secretary to conduct the 
demonstration program for an additional 5-year period, to begin on the 
date immediately following the last day of the initial 5-year period. 
Public Law 111-148 required the Secretary to provide for the continued 
participation of rural community hospitals in the demonstration program 
during this 5-year extension period, in the case of a rural community 
hospital participating in the demonstration program as of the last day 
of the initial 5-year period, unless the hospital made an election to 
discontinue participation. In addition, Public Law 111-148 limited the 
number of hospitals participating to no more than 30.
    Section 15003 of the Cures Act required the Secretary to conduct 
the demonstration for a 10-year extension period (in place of the 5-
year extension period required by Pub. L. 111-148 (ACA)). Specifically, 
section 15003 of Public Law 114-255 (Cures Act) amended section 
410A(g)(4) of Public Law 108-173 (MMA) to require that, for hospitals 
participating in the demonstration as of the last day of the initial 5-
year period, the Secretary would provide for continued participation of 
such rural community hospitals in the demonstration during the 10-year 
extension period, unless the hospital made an election, in such form 
and manner as the Secretary may specify, to discontinue participation. 
In addition, section 15003 of Public Law 114-255 added subsection 
(g)(5) to section 410A of Public Law 108-173 to require that, during 
the second 5 years of the 10-year extension period, the Secretary would 
apply the provisions of section 410A(g)(4) of Public Law 108-

[[Page 45314]]

173 to rural community hospitals not described in subsection (g)(4) but 
that were participating in the demonstration as of December 30, 2014, 
in a similar manner as such provisions apply to hospitals described in 
subsection (g)(4).
    In the FY 2018 IPPS/LTCH PPS final rule (82 FR 38280), we finalized 
our policy with regard to the effective date for the application of the 
reasonable cost-based payment methodology under the demonstration for 
those previously participating hospitals choosing to participate in the 
second 5-year extension period. According to our finalized policy, each 
previously participating hospital began the second 5 years of the 10-
year extension period and payment for services provided under the cost-
based payment methodology under section 410A of Public Law 108-173 (as 
amended by section 15003 of Pub. L. 114-255) on the date immediately 
after the period of performance ended under the first 5-year extension 
period.
    Seventeen of the 21 hospitals that completed their periods of 
participation under the extension period authorized by Public Law 111-
148 (ACA) elected to continue in the 5-year extension period authorized 
by Public Law 114-255 (Cures Act). Therefore, for these hospitals, this 
third 5-year period of participation started on dates ranging from May 
1, 2015 through January 1, 2017, depending on when they had initially 
started. On November 20, 2017, we announced that 13 additional 
hospitals had been selected to participate in the demonstration in 
addition to these 17 hospitals continuing participation from the first 
5-year extension period. (These two groups are referred to as ``newly 
participating'' and ``previously participating'' hospitals, 
respectively.) We announced that each of these newly participating 
hospitals would begin its 5-year period of participation effective with 
the start of the first cost-reporting period on or after October 1, 
2017. One of the newly participating hospitals withdrew from the 
demonstration program prior to beginning participation in the 
demonstration on July 1, 2018. In addition, one of the previously 
participating hospitals closed effective January 2019, and another 
withdrew effective October 1, 2019. Therefore, 27 hospitals were 
participating in the demonstration as of this date--15 previously 
participating and 12 newly participating.
    Each hospital has had its own end date applicable to this third 
five-year period for the demonstration. For four of the previously 
participating hospitals, this end date fell within FY2020, while for 11 
of the previously participating hospitals, the end date would fall 
within CY 2021. (One of the hospitals within this group chose in 
February of 2020 to withdraw effective September of the previous year). 
The newly participating hospitals were all scheduled to end their 
participation either at the end of FY 2022 or during FY 2023.
    Division CC, section 128 of CAA 2021 requires a 15-year extension 
period (that is, an additional five years beyond the current extension 
period), to begin on the date immediately following the last day of the 
initial 5-year period, instead of the 10-year extension period mandated 
by the Cures Act. In addition, the statute provides for continued 
participation for all hospitals participating in the demonstration 
program as of December 30, 2019. We, therefore, interpret the statute 
as providing for an additional 5-year period under the reasonable cost-
based reimbursement methodology for the demonstration for the hospitals 
that were participating as of this date.
    Given that four hospitals ended the 5-year period authorized by the 
Cures Act during FY 2020, we proposed to keep to the policy finalized 
for the previous extensions, and apply the cost-based reimbursement 
methodology to the date following the last day of this previous period 
for each hospital that elects to continue participation. Likewise, each 
of the 22 hospitals with a scheduled end date during 2021, 2022, or 
2023 and the hospital that withdrew in February 2020 would be eligible 
for an additional 5-year period starting from the day after the 
specified end date. Accordingly, the period of participation for the 
last hospital in the model under this most recent legislative 
authorization would extend until June 30, 2028.
4. Budget Neutrality
a. Statutory Budget Neutrality Requirement
    Section 410A(c)(2) of Public Law 108-173 requires that, in 
conducting the demonstration program under this section, the Secretary 
shall ensure that the aggregate payments made by the Secretary do not 
exceed the amount that the Secretary would have paid if the 
demonstration program under this section was not implemented. This 
requirement is commonly referred to as ``budget neutrality.'' 
Generally, when we implement a demonstration program on a budget 
neutral basis, the demonstration program is budget neutral on its own 
terms; in other words, the aggregate payments to the participating 
hospitals do not exceed the amount that would be paid to those same 
hospitals in the absence of the demonstration program. We note that the 
payment methodology for this demonstration, that is, cost-based 
payments to participating small rural hospitals, makes it unlikely that 
increased Medicare outlays will produce an offsetting reduction to 
Medicare expenditures elsewhere. Therefore, in the 12 IPPS final rules 
spanning the period from FY 2005 through FY 2016, we adjusted the 
national inpatient PPS rates by an amount sufficient to account for the 
added costs of this demonstration program, thus applying budget 
neutrality across the payment system as a whole rather than merely 
across the participants in the demonstration program. (A different 
methodology was applied for FY 2017.) As we discussed in the FYs 2005 
through 2017 IPPS/LTCH PPS final rules (69 FR 49183; 70 FR 47462; 71 FR 
48100; 72 FR 47392; 73 FR 48670; 74 FR 43922, 75 FR 50343, 76 FR 51698, 
77 FR 53449, 78 FR 50740, 77 FR 50145; 80 FR 49585; and 81 FR 57034, 
respectively), we believe that the statutory language of the budget 
neutrality requirements permits the agency to implement the budget 
neutrality provision in this manner.
b. General Budget Neutrality Methodology
    We have generally incorporated two components into the budget 
neutrality offset amounts identified in the final IPPS rules in 
previous years. First, we have estimated the costs of the demonstration 
for the upcoming fiscal year, generally determined from historical, 
``as submitted'' cost reports for the hospitals participating in that 
year. Update factors representing nationwide trends in cost and volume 
increases have been incorporated into these estimates, as specified in 
the methodology described in the final rule for each fiscal year. 
Second, as finalized cost reports became available, we determined the 
amount by which the actual costs of the demonstration for an earlier, 
given year differed from the estimated costs for the demonstration set 
forth in the final IPPS rule for the corresponding fiscal year, and 
incorporated that amount into the budget neutrality offset amount for 
the upcoming fiscal year. If the actual costs for the demonstration for 
the earlier fiscal year exceeded the estimated costs of the 
demonstration identified in the final rule for that year, this 
difference was added to the estimated costs of the demonstration for 
the upcoming fiscal year when determining the budget neutrality 
adjustment for the upcoming

[[Page 45315]]

fiscal year. Conversely, if the estimated costs of the demonstration 
set forth in the final rule for a prior fiscal year exceeded the actual 
costs of the demonstration for that year, this difference was 
subtracted from the estimated cost of the demonstration for the 
upcoming fiscal year when determining the budget neutrality adjustment 
for the upcoming fiscal year. We note that we have calculated this 
difference for FYs 2005 through 2015 between the actual costs of the 
demonstration as determined from finalized cost reports once available, 
and estimated costs of the demonstration as identified in the 
applicable IPPS final rules for these years.
c. Budget Neutrality Methodology for the Extension Period Authorized by 
CAA 2021
    For the newly enacted extension period, under CAA 2021, we proposed 
to continue upon the general budget neutrality methodology used in 
previous years, and specifically to follow upon the determinations for 
the previous extension period, under the Cures Act.
(1) Budget Neutrality Methodology for Previous Extension Period Under 
the Cures Act
    We finalized our budget neutrality methodology for periods of 
participation under this previous 5-year extension period in the FY 
2018 IPPS/LTCH PPS final rule (82 FR 38285 through 38287). Similar to 
previous years, we stated in this rule, as well as in the FY 2019 and 
FY 2020 IPPS/LTCH PPS proposed and final rules (83 FR 20444 and 41503, 
and 84 FR19452 and 42421, respectively) that we would incorporate an 
estimate of the costs of the demonstration, generally determined from 
historical, ``as submitted'' cost reports for the participating 
hospitals, and appropriate update factors, into a budget neutrality 
offset amount to be applied to the national IPPS rates for the upcoming 
fiscal year. In addition, we stated that we would continue to apply our 
general policy from previous years of including, as a second component 
to the budget neutrality offset amount, the amount by which the actual 
costs of the demonstration for an earlier, given year (as determined 
from finalized cost reports, when available) differed from the 
estimated costs for the demonstration set forth in the final IPPS rule 
for the corresponding fiscal year.
    In these proposed and final rules, we described several distinct 
components to the budget neutrality offset amount for the specific 
fiscal years of the extension period authorized by the Cures Act.
    We included a component to our overall methodology similar to 
previous years, according to which an estimate of the costs of the 
demonstration for both previously and newly participating hospitals for 
the upcoming fiscal year is incorporated into a budget neutrality 
offset amount to be applied to the national IPPS rates for the upcoming 
fiscal year. In the FY 2019 IPPS final rule (83 FR 41506), we included 
such an estimate of the costs of the demonstration for each of FYs 2018 
and 2019 into the budget neutrality offset amount for FY 2019. In the 
FY 2020 IPPS final rule (84 FR 42421), we included an estimate of the 
costs of the demonstration for FY 2020 for 28 hospitals. In the FY 2021 
IPPS final rule (85 FR 58873), we included an estimate of the costs of 
the demonstration for FY 2021 for the 22 hospitals for which the cost-
based reimbursement methodology was to apply for all or part of FY 
2021.
    Similar to previous years, we continued to implement the policy of 
determining the difference between the actual costs of the 
demonstration as determined from finalized cost reports for a given 
fiscal year and the estimated costs indicated in the corresponding 
year's final rule, and including that difference as a positive or 
negative adjustment in the upcoming year's final rule. (For each 
previously participating hospital that decided to participate in the 5-
year extension period under the Cures Act, the cost-based payment 
methodology under the demonstration began on the date immediately 
following the end date of its period of performance for the still 
previous extension period (under the ACA). In addition, for previously 
participating hospitals that converted to CAH status during the time 
period of the second 5-year extension period, the demonstration payment 
methodology was applied to the date following the end date of its 
period of performance for the first extension period to the date of 
conversion). In the FY 2020 final rule, we included the difference 
between the amount determined for the cost of the demonstration in each 
of FYs 2014 and 2015 and the estimated amount included in the budget 
neutrality offset in the final rule for each of these respective fiscal 
years. For FY 2016 and subsequent years, we have stated that will use 
finalized cost reports when available that detail the actual costs of 
the demonstration in these fiscal years and incorporate these amounts 
into the budget neutrality calculation.
(2) Methodology for Estimating Demonstration Costs for FY 2022
    We are using a methodology similar to previous years, according to 
which an estimate of the costs of the demonstration for the upcoming 
fiscal year is incorporated into a budget neutrality offset amount to 
be applied to the national IPPS rates for the upcoming fiscal year, 
that is, FY 2022. We are conducting this estimate for FY 2022 based on 
the 26 hospitals that will be continuing participation in the 
demonstration for the fiscal year. The methodology for calculating this 
amount for FY 2022 proceeds according to the following steps:
    Step 1: For each of these 26 hospitals, we identify the reasonable 
cost amount calculated under the reasonable cost-based methodology for 
covered inpatient hospital services, including swing beds, as indicated 
on the ``as submitted'' cost report for the most recent cost reporting 
period available. For each of these hospitals, the ``as submitted'' 
cost report is that with cost report period end date in CY 2019. We sum 
these hospital-specific amounts to arrive at a total general amount 
representing the costs for covered inpatient hospital services, 
including swing beds, across the total 26 hospitals eligible to 
participate during FY 2022.
    Then, we multiply this amount by the FYs 2020, 2021 and 2022 IPPS 
market basket percentage increases, which are calculated by the CMS 
Office of the Actuary. (We are using the final market basket percentage 
increase for FY 2022, which can be found at section V.A of the preamble 
to this final rule). The result for the 26 hospitals is the general 
estimated reasonable cost amount for covered inpatient hospital 
services for FY 2022.
    Consistent with our methods in previous years for formulating this 
estimate, we are applying the IPPS market basket percentage increases 
for FYs 2020 through 2022 to the applicable estimated reasonable cost 
amount (previously described) in order to model the estimated FY 2022 
reasonable cost amount under the demonstration. We believe that the 
IPPS market basket percentage increases appropriately indicate the 
trend of increase in inpatient hospital operating costs under the 
reasonable cost methodology for the years involved.
    Step 2: For each of the participating hospitals, we identify the 
estimated amount that would otherwise be paid in FY 2022 under 
applicable Medicare payment methodologies for covered inpatient 
hospital services, including swing beds (as indicated on the same set

[[Page 45316]]

of ``as submitted'' cost reports as in Step 1), if the demonstration 
were not implemented. We sum these hospital-specific amounts, and, in 
turn, multiply this sum by the FYs 2020, 2021 and 2022 IPPS applicable 
percentage increases. (For FY 2021, we are using the finalized 
applicable percentage increase, per section V.A of the preamble of this 
final rule).This methodology differs from Step 1, in which we apply the 
market basket percentage increases to the hospitals' applicable 
estimated reasonable cost amount for covered inpatient hospital 
services. We believe that the IPPS applicable percentage increases are 
appropriate factors to update the estimated amounts that generally 
would otherwise be paid without the demonstration. This is because IPPS 
payments constitute the majority of payments that would otherwise be 
made without the demonstration and the applicable percentage increase 
is the factor used under the IPPS to update the inpatient hospital 
payment rates.
    Step 3: We subtract the amount derived in Step 2 from the amount 
derived in Step 1. According to our methodology, the resulting amount 
indicates the total difference for the 26 hospitals (for covered 
inpatient hospital services, including swing beds), which will be the 
general estimated amount of the costs of the demonstration for FY 2022.
    For this final rule, the resulting amount is $65,779,803, which we 
are incorporating into the budget neutrality offset adjustment for FY 
2022. This estimated amount is based on the specific assumptions 
regarding the data sources used, that is, recently available ``as 
submitted'' cost reports and historical update factors for cost and 
payment. In the proposed rule, we stated that if updated data became 
available prior to the final rule, we would use them as appropriate to 
estimate the costs for the demonstration program for FY 2022 in 
accordance with our methodology for determining the budget neutrality 
estimate. Accordingly, we have used revised, finalized determinations 
for the market basket update and applicable percentage increase in 
formulating this estimate for the final rule.
(3) Reconciling Actual and Estimated Costs of the Demonstration for 
Previous Years
    As described earlier, we have calculated the difference for FYs 
2005 through 2015 between the actual costs of the demonstration, as 
determined from finalized cost reports once available, and estimated 
costs of the demonstration as identified in the applicable IPPS final 
rules for these years.
    In the FY 2021 proposed rule, we stated that if finalized cost 
reports for the entire set of hospitals that completed cost report 
periods under the demonstration payment methodology beginning in FY 
2016 were available by the time of the final rule, we would include in 
the final budget neutrality offset amount the difference between the 
actual cost as determined from these cost reports and the estimated 
amount in the FY 2016 final rule. When the complete set of finalized 
cost reports were not available for the FY 2021 final rule, we stated 
that we would aim to include this difference within the FY 2022 
proposed and final rules. At this time, for the FY 2022 final rule, all 
of the finalized cost reports are available for the 18 hospitals that 
completed cost report periods under the demonstration payment 
methodology beginning in FY 2016; these cost reports show the actual 
costs of the demonstration for this fiscal year to be $29,842,614. 
Comparing this amount to the estimated amount in the FY 2016 IPPS/LTCH 
final rule ($26,044,620) (80 FR 49590) shows that the actual cost 
exceeded the estimated cost by $3,797,994. In keeping with past 
practice, we are adding this amount to the estimate of the 
demonstration costs for FY 2022 in formulating the total budget 
neutrality offset amount for this upcoming fiscal year.
(4) Total Proposed Budget Neutrality Offset Amount for FY 2022
    Therefore, for this FY 2022 IPPS/LTCH PPS final rule, the budget 
neutrality offset amount for FY 2022 is based on the sum of two 
amounts:
    (a) the amount determined under section X.4.c (2) of the preamble 
of this final rule, representing the difference applicable to FY 2022 
between the sum of the estimated reasonable cost amounts that would be 
paid under the demonstration for covered inpatient services to the 26 
hospitals participating in the fiscal year and the sum of the estimated 
amounts that would generally be paid if the demonstration had not been 
implemented. This estimated amount is $65,779,803.
    (b) the amount determined under section X.4.c(3) of the preamble of 
this final rule, indicating the amount by which the actual costs of the 
demonstration in FY 2016 as shown by finalized cost reports from that 
fiscal year exceed the estimated amount identified in the FY 2016 final 
rule. The amount of this difference is $3,797,994.
    We will subtract the sum of these two amounts, or $69,577,797 from 
the national IPPS rates for FY 2022.
    We received three public comments, all of them supportive of 
continuing the Rural Community Hospital Demonstration. Each of the 
commenters in addition, suggests specific innovations to either the 
demonstration or rural health financing:
    Comment: A commenter requested that we use the demonstration to 
waive barriers under Title XVIII that prevent nurse practitioners from 
practicing to their full education and training.
    Response: The authorizing legislation only allows waiving Title 
XVIII provisions that are necessary for the purpose of carrying out the 
demonstration program. Since the demonstration program focuses on 
payment enhancements for a limited number of rural hospitals, such 
broad waivers would not be allowed.
    Comment: A commenter recommended that we use the first year of the 
extension period for each participating hospital as a new base year for 
cost-based reimbursement for the demonstration.
    Response: We appreciate the comment on this specific element of the 
payment methodology authorized by section 410A of Public Law 108-173. 
The requirement under the authorizing statute is for participating 
hospitals to be paid for hospital inpatient services during the first 
year of the authorized 5-year period according to the reasonable costs 
of providing those services. For each of the remaining four years, 
payment is determined according to a methodology that imposes the 
reasonable cost amount from the first year as a limiting factor. The 
statutory language governing the respective extensions of the Rural 
Community Hospital demonstration requires a new base year for the 5-
year extension period mandated by CCA 2021, and we will determine the 
hospital inpatient payment for participating hospitals accordingly.
    Comment: The parent company for two of the participating hospitals 
notes that the demonstration does not offer long-term financial 
sustainability needed to maintain health care access in rural areas. 
The commenter recommends that we continue to examine and develop an 
alternative separate and distinct payment structure for the portion of 
cost-based reimbursement that pays for costs associated with access in 
rural areas.
    Response: We appreciate the comment, and continue to explore 
alternatives for promoting access to care

[[Page 45317]]

in rural areas. We would like to highlight two current initiatives:
    The Community Health Access and Rural Transformation (CHART) Model 
offers an alternative payment model opportunity for rural communities, 
aiming to provide financial stability to rural providers and facilitate 
access to high-quality care for rural beneficiaries. CMS will announce 
award recipients in the CHART Community Transformation Track in fall 
2021.
    In addition, section 125 of CAA 2021 establishes a new provider 
type, Rural Emergency Hospitals, which will be required to furnish 
emergency department services and observation care, and may provide 
other outpatient medical and health services as specified by the 
Secretary through rulemaking. We have included a Request for 
Information (RFI) in the Calendar Year 2022 Outpatient Prospective 
Payment System and Ambulatory Surgical Center Payment System Proposed 
Rule to obtain feedback that will inform policy development for this 
new provider type.

L. Market-Based MS-DRG Relative Weight Policy--Repeal (Sec.  413.20)

1. Overview
    In the FY 2021 IPPS/LTCH PPS final rule, we finalized a requirement 
for a hospital to report on the Medicare cost report the median payer-
specific negotiated charge that the hospital has negotiated with all of 
its MA organization payers, by MS-DRG, for cost reporting periods 
ending on or after January 1, 2021 (85 FR 58873 through 58892); this 
data collection requirement is specified in 42 CFR 413.20(d)(3). We 
also finalized the use of this data in a new market-based methodology 
for calculating the IPPS MS-DRG relative weights to reflect relative 
market-based pricing, beginning in FY 2024. Specifically, we finalized 
that we will begin using the reported median payer-specific negotiated 
charge by MS-DRG for MA organizations in the market-based MS-DRG 
relative weight methodology beginning with the relative weights 
calculated for FY 2024.
2. Repeal of the Market-Based MS-DRG Relative Weight Data Collection 
and Market-Based Methodology for Calculating MS-DRG Relative Weights
    After further consideration of the many contract arrangements 
hospitals use to negotiate rates with MA organization payers, and the 
usefulness, for ratesetting purposes, of the market-based data as 
reported in accordance with the FY 2021 IPPS/LTCH PPS final rule, we 
proposed to repeal the requirement that a hospital report on the 
Medicare cost report the median payer-specific negotiated charge that 
the hospital has negotiated with all of its MA organization payers, by 
MS-DRG, for cost reporting periods ending on or after January 1, 2021. 
We also proposed to repeal the market-based MS-DRG relative weight 
methodology that was adopted effective for FY 2024, and to continue 
using the existing cost-based methodology for calculating the MS-DRG 
relative weights for FY 2024 and subsequent fiscal years. We stated in 
the proposed rule that comments received on the 60-day Paperwork 
Reduction Act (PRA) revision request of the existing information 
collection requirement (ICR) for cost reports, (OMB control number 
0938-0050, which was published on November 10, 2020 (85 FR 71653 and 
71654)), also provided further questions for us to examine regarding 
the usefulness of this data, and requested that we consider a delay or 
repeal of this policy. In light of these questions and for the reasons 
discussed, we proposed to repeal the market-based data collection 
requirement and MS-DRG relative weight methodology to allow for further 
consideration of these questions and possible alternative approaches.
    We also proposed to amend 42 CFR 413.20(d)(3) to reflect the 
proposed repeal of the market-based MS-DRG relative weight data 
collection requirement. Specifically, we proposed to amend 42 CFR 
413.20(d)(3) to remove the requirement at 42 CFR 413.20(d)(3)(i)(B) 
that a provider furnish the contractor its median payer-specific 
negotiated charge by MS-DRG for payers that are MA organizations, as 
applicable, and changes thereto as they are put into effect, and to 
renumber the existing provisions accordingly.
    We stated in the proposed rule that in light of the proposal to 
repeal the requirement for hospitals to report this median payer-
specific negotiated charge data on the cost report, we would revise the 
next proposed revision of the existing ICR for cost reports (OMB 
control number 0938-0050, expiration date March 31, 2022), accordingly.
    We invited public comment on our proposal to repeal the market-
based data collection requirement and market-based MS-DRG relative 
weight methodology. We also invited public comment on alternative 
approaches or data sources that could be used in Medicare fee-for-
service (FFS) ratesetting. In the proposed rule, we also discussed and 
invited public comments on an alternative to maintain the market-based 
data collection requirement but delay the implementation of the market-
based MS-DRG relative weight methodology to a date after FY 2024. We 
refer readers to 86 FR 25784 of the proposed rule for further 
discussion of this alternative.
    Comment: Many commenters, including MedPAC, supported the proposal 
to repeal the market-based MS-DRG relative weight data collection 
requirement and market-based MS-DRG relative weight methodology 
(referred herein as the market-based policy). These commenters also 
opposed the alternative to instead maintain the requirement that 
hospitals report the median payer-specific negotiated charge for MA 
organizations on the Medicare cost report, but delay implementing the 
use of this data in the market-based MS-DRG relative weight methodology 
beyond FY 2024. These commenters expressed several of the same 
questions and concerns we received on the 60-day Paperwork Reduction 
Act (PRA) revision request of the information collection requirement 
(ICR), (OMB control number 0938-0050, which was published on November 
10, 2020 (85 FR 71653 and 71654)). These concerns were regarding the 
accuracy of this data to represent hospital relative resource use, the 
impact reporting this data would have on market competition, the 
ability for the data to represent market-based prices given the 
relationship between MA organization and Medicare FFS rates, and the 
usefulness of the data generally.
    Several commenters supported the proposal to repeal the market-
based policy because they believed the policy to be unduly burdensome 
on hospitals, and argued that the current cost-based methodology for 
calculating the MS-DRG relative weights was functioning as intended.
    MedPAC supported the proposal and noted that MA plans almost always 
explicitly use Medicare FFS relative weights to set their payment 
rates, and that using MA plans' rates to set MS-DRG relative weights 
would be circular and would not bring true market-based payment rates 
into the Medicare hospital ratesetting process. Several other 
commenters supported the proposal to repeal the market-based policy 
because they believed the policy did not inform Medicare beneficiaries 
with cost and quality information that would promote choice or 
encourage cost-conscious decisions to lower overall health care costs. 
These commenters argued that the market-based policy would result in 
shifting payments from one service to another, rather than promoting 
price transparency and controlling overall costs. A commenter suggested 
that MA organizations, instead of hospitals, were

[[Page 45318]]

better suited to report the median payer-specific negotiated charge 
that hospitals have negotiated with all of their MA organization 
payers, by MS-DRG.
    Many other commenters urged CMS not to finalize the proposed repeal 
of the market-based policy. Several of these commenters stated that the 
market-based policy would help lower costs, improve competition and 
empower patients. These commenters also argued that by repealing the 
market-based policy, CMS would continue its reliance on the hospital 
chargemaster, which they believed rarely reflects true market costs. 
These commenters argued that the additional burden required to report 
this market-based data on the Medicare cost report was minimal and that 
repealing the policy was premature.
    Other commenters argued that by repealing this market-based policy, 
CMS would remove a significant enforcement mechanism to promote price 
transparency. These commenters expressed that by repealing this policy, 
CMS would convey its lack of commitment to price transparency. Another 
commenter argued that there was no basis for proposing to repeal this 
policy since the court system rejected many of the hospitals' primary 
objections to price transparency.
    Response: We appreciate the commenters' feedback on our proposed 
repeal of the market-based policy. We agree with commenters that we 
need to further consider the questions raised regarding the ability for 
this data to represent market-based pricing given the relationship 
between Medicare FFS and MA organization rates, and therefore the 
usefulness and appropriateness of this data for Medicare FFS 
ratesetting purposes.
    With respect to commenters who opposed repealing the market-based 
policy based on the belief that the policy would lower costs, we note 
that the market-based MS-DRG relative weight methodology, as finalized 
in the FY 2021 IPPS/LTCH PPS final rule, would be normalized by an 
adjustment factor so that the average case weight after recalibration 
would be equal to the average case weight before recalibration, as is 
the case under the current cost-based MS-DRG relative weight 
methodology. As stated in the FY 2021 IPPS/LTCH PPS final rule, the 
normalization adjustment is intended to help ensure that recalibration 
by itself neither increases nor decreases total payments under the 
IPPS, as required by section 1886(d)(4)(C)(iii) of the Act (85 FR 
58880). Further, as stated in the FY 2021 IPPS/LTCH PPS final rule, the 
purpose of the market-based data collection requirement was to collect 
market-based data so that the data may be used within Medicare payment 
calculations (85 FR 58883); the focus of this policy was not on 
lowering costs.
    With regard to commenters who opposed repealing the market-based 
policy because they believed repealing it would minimize CMS' 
commitment to, and remove a significant enforcement mechanism for, 
price transparency, we emphasize that we agree with commenters on the 
importance of price transparency for health care consumers. A repeal of 
the market-based policy would not affect the separate price 
transparency requirements CMS finalized under the Hospital Price 
Transparency final rule or the Transparency in Coverage final rule, nor 
do we believe it would signal a change in our commitment to price 
transparency. As stated in the FY 2021 IPPS/LTCH PPS final rule, 
however, the purpose of the market-based data collection requirement 
was not to promote transparency in health care prices but to collect 
market-based data for use in Medicare payment calculations (85 FR 
58883).
    The market-based MS-DRG relative weight data collection policy, as 
finalized in the FY 2021 IPPS final rule, is distinct from the 
requirements and penalties set forth under the Hospital Price 
Transparency Final Rule (84 FR 65524). As discussed more fully in the 
FY 2021 IPPS/LTCH PPS final rule, the market-based data collection 
requirement and MS-DRG relative weight methodology were finalized under 
the authority provided under sections 1815(a), 1833(e), 1886(d)(4)(A), 
1886(d)(4)(B), and 1886(d)(4)(C) of the Social Security Act. By 
contrast, the Hospital Transparency Final Rule relied on separate 
authority under section 2718(e) of the Public Health Service Act. 
Similarly, the market-based policy is distinct from other CMS price 
transparency efforts, such as the Transparency in Coverage final rule, 
which relied on other authority under section 2715A of the Public 
Health Service Act, as well as section 1311(e)(3) of the Patient 
Protection and Affordable Care Act.\800\
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    \800\ Public Law 111-148.
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    In regards to commenters' concern that CMS is not committed to 
initiatives that promote competition, on July 9, 2021, President Biden 
issued an Executive Order (E.O.) on Promoting Competition in the 
American Economy. This E.O. directed the Department of Health and Human 
Services to support existing price transparency initiatives for 
hospitals, other providers and issuers, along with any new price 
transparency initiatives or changes made necessary by the No Surprises 
Act (Pub. L. 116-260, 134 Stat. 2758) or any other statutes. As stated 
previously, the purpose of the market-based policy was to collect 
market-based data so that the data may be used within Medicare payment 
calculations and is separate from CMS price transparency initiatives. 
This E.O. further reiterates CMS' commitment to current and future 
price transparency initiatives.
    As noted, CMS previously finalized the Hospital Price Transparency 
final rule which, as of January 1, 2021, requires each hospital 
operating in the United States to provide clear, accessible pricing 
information about the items and services they provide in two ways: (1) 
Comprehensive machine-readable file with all items and services, and 
(2) display of shoppable services in a consumer-friendly format. 
Hospital price transparency helps Americans know what a hospital 
charges for the items and services it provides. We expect hospitals to 
comply with these legal requirements, and are enforcing these rules to 
ensure Americans know what a hospital charges for items and services. 
CMS began auditing hospital websites for compliance with the 
requirements of the Hospital Price Transparency final rule in January 
2021, and began issuing warning letters to hospitals in April 2021. We 
will continue our monitoring and enforcement activities to ensure 
compliance with the Hospital Price Transparency requirements.
    With regard to the commenters who opposed repealing the market-
based policy because they believed it would remove a significant 
enforcement mechanism for price transparency, we note that in the 
recently published CY 2022 OPPS/ASC proposed rule we proposed to 
improve our enforcement and compliance efforts by increasing the 
penalty for hospitals that do not comply with Hospital Price 
Transparency final rule. Specifically, CMS proposed to set a minimum 
civil monetary penalty of $300/day that would apply to smaller 
hospitals with a bed count of 30 or fewer, and apply a penalty of $10/
bed/day for hospitals with a bed count greater than 30, not to exceed a 
maximum daily dollar amount of $5,500. CMS takes seriously the concerns 
it has heard from consumers that hospitals are not making clear, 
accessible pricing information available online, as they have been 
required to do since January 1, 2021. The public is encouraged to 
submit complaints of noncompliance through our website: https://www.cms.gov/hospital-price-transparency/contact-us.

[[Page 45319]]

    Additionally, on December 27, 2020, the Consolidated Appropriations 
Act, 2021 was enacted.\801\ Title I (No Surprises Act) and Title II 
(Transparency) of Division BB of the CAA established new protections 
for consumers related to surprise billing and transparency in health 
care. On July 1, 2021, the Department of Treasury, the Department of 
Labor, the Office of Personnel Management, and the Department of Health 
and Human Services, released an interim final rule with comment (IFC) 
entitled, ``Requirements Related to Surprise Billing; Part I.'' \802\ 
This IFC implements provisions of Title I (No Surprises Act) of 
Division BB of the CAA and establishes new protections from surprise 
billing and excessive cost-sharing for consumers receiving health care 
items and services. CMS remains committed to implementing these 
statutory requirements to promote transparency in health care.
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    \801\ Public Law 116-260.
    \802\ 86 FR 36872 (July 13, 2021).
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    As a result of these price transparency initiatives, we believe 
consumers will have readily available access to health care pricing 
information that may empower patients and may help lower costs. For the 
reasons discussed, as evidenced by these rules, we disagree with 
commenters who stated that repealing this market-based policy would 
convey a lack of commitment by CMS to enforcing the price transparency 
requirements, enhancing competition, and promoting price transparency 
generally.
    After consideration of the comments received, and for the reasons 
discussed, we are finalizing our proposal to repeal this market-based 
data collection requirement and market-based MS-DRG relative weight 
methodology that was adopted effective for FY 2024, and to continue 
using the existing cost-based methodology for calculating the MS-DRG 
relative weights for FY 2024 and subsequent fiscal years. We will 
continue to consider these comments and questions in connection with 
any potential future proposed changes to the MS-DRG relative weight 
ratesetting process, as applicable.
    Comment: Several commenters commented on our request for 
alternative approaches or data sources that could be used in Medicare 
FFS ratesetting. These commenters encouraged CMS to consider 
alternative data sources that incentivize value-based care, reduce 
costs, improve care quality, account for various risk-based contracting 
arrangements, and counter the practice of charge compression, without 
creating undue burden on hospitals, especially rural hospitals. Other 
commenters requested that if CMS reduced its reliance on the hospital 
chargemaster, that CMS contemplate the other ways in which the 
chargemaster is used in other payment methodologies.
    A commenter requested that CMS exercise caution in changing the 
current MS-DRG relative weight methodology and further requested that 
CMS work closely with the stakeholder community to analyze the impact 
before making any potential change. Other commenters requested that CMS 
pursue potential improvements in the ratesetting process without 
exposing confidential negotiations with competing payers. Several other 
commenters stated that hospitals continue to combat the COVID-19 
pandemic, and requested that as CMS assesses alternative data sources 
that it recognizes that additional flexibilities may be necessary as 
hospitals continue to recover from the COVID-19 public health emergency 
(PHE).
    Response: We appreciate commenters' suggestions on alternative 
approaches and data sources that could be used in Medicare FFS 
ratesetting. We will continue to evaluate and consider these 
recommendations, including commenters' concerns regarding the impact of 
the COVID-19 PHE, as we consider these alternative approaches and data 
sources.
    Comment: Several commenters expressed opinions and concerns related 
to CMS price transparency efforts, including suggestions related to 
harmonizing the Hospital Price Transparency final rule and the No 
Surprises Act requirements.
    Response: As stated in the Hospital Price Transparency final rule, 
we remain open to revisiting in future rulemaking the hospital price 
transparency requirements should we find it necessary to make 
improvements in the display and accessibility of hospital standard 
charge information for the public (84 FR 65559). While we did not 
request comments in this proposed rule on either the requirements set 
forth in the Hospital Price Transparency final rule or related to the 
No Surprises Act, in the CY 2022 OPPS/ASC proposed rule we recently 
proposed revisions to the Hospital Price Transparency final rule 
policies (https://www.federalregister.gov/public-inspection/2021-15496/medicare-program-hospital-outpatient-prospective-payment-and-ambulatory-surgical-center-payment.).
    After consideration of the comments received, and for the reasons 
discussed, we are finalizing our proposal to repeal the requirement 
that a hospital report on the Medicare cost report the median payer-
specific negotiated charge that the hospital has negotiated with all of 
its MA organization payers, by MS-DRG, for cost reporting periods 
ending on or after January 1, 2021, without modification. We also are 
finalizing our proposal to repeal the market-based MS-DRG relative 
weight methodology that was adopted effective for FY 2024, and to 
continue using the existing cost-based methodology for calculating the 
MS-DRG relative weights for FY 2024 and subsequent fiscal years, 
without modification. We are also finalizing our proposed amendment to 
42 CFR 413.20(d)(3) to reflect the repeal of the market-based MS-DRG 
relative weight data collection requirement, without modification. We 
are not finalizing the alternative we considered to maintain the 
market-based data collection requirement but delay the implementation 
of the market-based MS-DRG relative weight methodology to a date after 
FY 2024.
    As discussed, we will continue to evaluate and consider the 
usefulness and appropriateness of market-based data for ratesetting 
purposes. This includes further consideration of the comments we 
received regarding potential alternative approaches and data sources 
for use in Medicare FFS ratesetting, which we will consider as 
applicable. As discussed, we remain committed to promoting transparency 
in health care prices and promoting competition in the American 
economy.

M. Payment Adjustment for CAR T-Cell Clinical Trial and Expanded Access 
Use Immunotherapy Cases (Sec. Sec.  412.85 and 412.312)

    As discussed in the FY 2021 IPPS/LTCH PPS final rule (85 FR 58599 
through 58600), we created MS-DRG 018 for cases that include procedures 
describing CAR T-cell therapies, which were reported using ICD-10-PCS 
procedure codes XW033C3 or XW043C3. We refer the reader to section 
II.D.2. of this final rule for discussion of the procedure codes for 
CAR T-cell and non-CAR T-cell therapies and other immunotherapies that 
we proposed and are finalizing for assignment to MS-DRG 018 for FY 
2022. In the FY 2021 IPPS/LTCH PPS final rule, we modified our relative 
weight methodology for MS-DRG 018 in order to develop a relative weight 
that is reflective of the typical costs of providing CAR T-cell 
therapies relative to other IPPS services. Specifically, we finalized 
to not include claims determined to be clinical trial claims that group 
to new MS-DRG 018

[[Page 45320]]

when calculating the average cost for new MS-DRG 018 that is used to 
calculate the relative weight for this MS-DRG, with the additional 
refinements that (a) when the CAR T-cell therapy product is purchased 
in the usual manner, but the case involves a clinical trial of a 
different product, the claim will be included when calculating the 
average cost for new MS-DRG 018 to the extent such claims can be 
identified in the historical data, and (b) when there is expanded 
access use of immunotherapy, these cases will not be included when 
calculating the average cost for new MS-DRG 018 to the extent such 
claims can be identified in the historical data (85 FR 58600).
    In the FY 2021 IPPS/LTCH PPS final rule, we also finalized an 
adjustment to the payment amount for applicable clinical trial and 
expanded access immunotherapy cases that would group to MS-DRG 018 (85 
FR 58842) using the same methodology that we used to adjust the case 
count for purposes of the relative weight calculations. Specifically, 
after consideration of public comments, we finalized our proposal to 
apply a payment adjustment to claims that group to new MS-DRG 18 and 
include ICD-10-CM diagnosis code Z00.6, with the modification that when 
the CAR T-cell therapy product is purchased in the usual manner, but 
the case involves a clinical trial of a different product, the payment 
adjustment will not be applied in calculating the payment for the case. 
We also finalized that when there is expanded access use of 
immunotherapy, the payment adjustment will be applied in calculating 
the payment for the case. We codified this payment adjustment at 42 CFR 
412.85 (for operating IPPS payments) and 42 CFR 412.312 (for capital 
IPPS payments), for claims appropriately containing Z00.6, as described 
previously, including to reflect that the adjustment will also be 
applied for cases involving expanded access use immunotherapy, and that 
the payment adjustment only applies to applicable clinical trial cases; 
that is, the adjustment is not applicable to cases where the CAR T-cell 
therapy product is purchased in the usual manner, but the case involves 
a clinical trial of a different product. We also finalized our 
regulations at 42 CFR 412.85(c) to reflect that the adjustment factor 
will reflect the average cost for cases to be assigned to MS DRG 018 
that involve expanded access use of immunotherapy or are part of an 
applicable clinical trial to the average cost for cases to be assigned 
to MS-DRG 018 that do not involve expanded access use of immunotherapy 
and are not part of a clinical trial. (85 FR 58844).
    Using the same methodology from the FY 2021 IPPS/LTCH PPS final 
rule, we proposed to apply an adjustment to the payment amount for 
clinical trial cases that would group to MS-DRG 018 (85 FR 58842), 
which is the same methodology we proposed to use to adjust the case 
count for purposes of the relative weight calculations:
     Calculate the average cost for cases to be assigned to MS-
DRG 018 that contain ICD-10-CM diagnosis code Z00.6 or contain 
standardized drug charges of less than $373,000.
     Calculate the average cost for cases to be assigned to MS-
DRG 018 that do not contain ICD-10-CM diagnosis code Z00.6 or 
standardized drug charges of at least $373,000.
     Calculate an adjustor by dividing the average cost 
calculated in step 1 by the average cost calculated in step 2.
     Apply this adjustor when calculating payments for clinical 
trial cases that group to MS-DRG 018 by multiplying the relative weight 
for MS-DRG 018 by the adjustor.
    Additionally, we are continuing our finalized methodology for 
calculating this payment adjustment, such that: (a) When the CAR T-cell 
therapy product is purchased in the usual manner, but the case involves 
a clinical trial of a different product, the claim will be included 
when calculating the average cost for cases not determined to be 
clinical trial cases and (b) when there is expanded access use of 
immunotherapy, these cases will be included when calculating the 
average cost for cases determined to be clinical trial cases. However, 
we continue to believe to the best of our knowledge there are no claims 
in the historical data (FY 2019 MedPAR) used in the calculation of the 
adjustment for cases involving a clinical trial of a different product, 
and to the extent the historical data contain claims for cases 
involving expanded access use of immunotherapy we believe those claims 
would have drug charges less than $373,000.
    Consistent with our calculation of the adjustor for the relative 
weight calculations, and our proposal to use the FY 2019 data for the 
FY 2022 ratesetting, we proposed to continue to calculate this adjustor 
based on the March 2020 update of the FY 2019 MedPAR file for purposes 
of establishing the FY 2022 payment amount. Specifically, we proposed 
to multiply the FY 2022 relative weight for MS-DRG 018 by an adjustor 
of 0.17 as part of the calculation of the payment for claims determined 
to be applicable clinical trial or expanded use access immunotherapy 
claims that group to MS-DRG 018, which under our proposal (as finalized 
elsewhere in this rule) includes CAR T-cell and non-CAR T-cell 
therapies and other immunotherapies. We refer the reader to section 
II.D.2. for a further discussion of MS-DRG 018. As discussed in section 
I.F. of this final rule, we also solicited comments on an alternative 
approach of using the same FY 2020 data that we would ordinarily use 
for purposes of the FY 2022 rulemaking, which we stated we may consider 
finalizing for FY 2022 based on consideration of comments received. We 
noted that using the methodology as finalized in the FY 2021 IPPS/LTCH 
PPS final rule, we calculated an adjustor of 0.25 based on this 
alternative approach of using the FY 2020 MedPAR file. As discussed in 
section I.F. of this final rule, after consideration of comments 
received and for the reasons discussed, CMS is finalizing the use of 
the FY 2019 MedPAR data to determine the MS-DRG relative weights for FY 
2022.
    Comment: Some commenters requested that we use the calculated 
adjustment of 0.25 developed from our alternative approach of using the 
FY 2020 MedPAR data.
    Response: As previously noted, CMS is finalizing the use of the FY 
2019 MedPAR data to determine the MS-DRG relative weights for FY 2022, 
including the relative weight for MS-DRG 018. Accordingly, we disagree 
that we should use the adjustment of 0.25 calculated from the FY 2020 
MedPAR data instead of the 0.17 adjustment calculated from the FY 2019 
MedPAR data. Given that under the IPPS, the relative weight assigned to 
each MS-DRG reflects the relative hospital resources used with respect 
to discharges classified within that group compared to discharges 
classified within other MS-DRGs, it would be inappropriate to use the 
FY 2019 MedPAR to approximate the relative resource use for each MS-
DRG, including the majority of MS-DRG 018 cases, but then a different 
data source (the FY 2020 MedPAR) to determine the relative resources 
required for MS-DRG 018 cases that are expanded access or clinical 
trial cases to calculate the adjustor.
    After consideration of comments received, we are finalizing our 
proposed adjustment of 0.17, which will be multiplied by the final FY 
2022 relative weight for MS-DRG 018 as part of the calculation of the 
payment for claims determined to be applicable clinical trial or 
expanded use access immunotherapy claims that group to MS-DRG 018.

[[Page 45321]]

VI. Changes to the IPPS for Capital-Related Costs

A. Overview

    Section 1886(g) of the Act requires the Secretary to pay for the 
capital-related costs of inpatient acute hospital services in 
accordance with a prospective payment system established by the 
Secretary. Under the statute, the Secretary has broad authority in 
establishing and implementing the IPPS for acute care hospital 
inpatient capital-related costs. We initially implemented the IPPS for 
capital-related costs in the FY 1992 IPPS final rule (56 FR 43358). In 
that final rule, we established a 10-year transition period to change 
the payment methodology for Medicare hospital inpatient capital-related 
costs from a reasonable cost-based payment methodology to a prospective 
payment methodology (based fully on the Federal rate).
    FY 2001 was the last year of the 10-year transition period that was 
established to phase in the IPPS for hospital inpatient capital-related 
costs. For cost reporting periods beginning in FY 2002, capital IPPS 
payments are based solely on the Federal rate for almost all acute care 
hospitals (other than hospitals receiving certain exception payments 
and certain new hospitals). (We refer readers to the FY 2002 IPPS final 
rule (66 FR 39910 through 39914) for additional information on the 
methodology used to determine capital IPPS payments to hospitals both 
during and after the transition period.)
    The basic methodology for determining capital prospective payments 
using the Federal rate is set forth in the regulations at 42 CFR 
412.312. For the purpose of calculating capital payments for each 
discharge, the standard Federal rate is adjusted as follows:
    (Standard Federal Rate) x (DRG Weight) x (Geographic Adjustment 
Factor (GAF) x (COLA for hospitals located in Alaska and Hawaii) x (1 + 
Capital DSH Adjustment Factor + Capital IME Adjustment Factor, if 
applicable).
    In addition, under Sec.  412.312(c), hospitals also may receive 
outlier payments under the capital IPPS for extraordinarily high-cost 
cases that qualify under the thresholds established for each fiscal 
year.

B. Additional Provisions

1. Exception Payments
    The regulations at 42 CFR 412.348 provide for certain exception 
payments under the capital IPPS. The regular exception payments 
provided under Sec.  412.348(b) through (e) were available only during 
the 10-year transition period. For a certain period after the 
transition period, eligible hospitals may have received additional 
payments under the special exceptions provisions at Sec.  412.348(g). 
However, FY 2012 was the final year hospitals could receive special 
exceptions payments. For additional details regarding these exceptions 
policies, we refer readers to the FY 2012 IPPS/LTCH PPS final rule (76 
FR 51725).
    Under Sec.  412.348(f), a hospital may request an additional 
payment if the hospital incurs unanticipated capital expenditures in 
excess of $5 million due to extraordinary circumstances beyond the 
hospital's control. Additional information on the exception payment for 
extraordinary circumstances in Sec.  412.348(f) can be found in the FY 
2005 IPPS final rule (69 FR 49185 and 49186).
2. New Hospitals
    Under the capital IPPS, the regulations at 42 CFR 412.300(b) define 
a new hospital as a hospital that has operated (under previous or 
current ownership) for less than 2 years and lists examples of 
hospitals that are not considered new hospitals. In accordance with 
Sec.  412.304(c)(2), under the capital IPPS, a new hospital is paid 85 
percent of its allowable Medicare inpatient hospital capital-related 
costs through its first 2 years of operation, unless the new hospital 
elects to receive full prospective payment based on 100 percent of the 
Federal rate. We refer readers to the FY 2012 IPPS/LTCH PPS final rule 
(76 FR 51725) for additional information on payments to new hospitals 
under the capital IPPS.
3. Payments for Hospitals Located in Puerto Rico
    In the FY 2017 IPPS/LTCH PPS final rule (81 FR 57061), we revised 
the regulations at 42 CFR 412.374 relating to the calculation of 
capital IPPS payments to hospitals located in Puerto Rico beginning in 
FY 2017 to parallel the change in the statutory calculation of 
operating IPPS payments to hospitals located in Puerto Rico, for 
discharges occurring on or after January 1, 2016, made by section 601 
of the Consolidated Appropriations Act, 2016 (Pub. L. 114-113). Section 
601 of Public Law 114-113 increased the applicable Federal percentage 
of the operating IPPS payment for hospitals located in Puerto Rico from 
75 percent to 100 percent and decreased the applicable Puerto Rico 
percentage of the operating IPPS payments for hospitals located in 
Puerto Rico from 25 percent to zero percent, applicable to discharges 
occurring on or after January 1, 2016. As such, under revised Sec.  
412.374, for discharges occurring on or after October 1, 2016, capital 
IPPS payments to hospitals located in Puerto Rico are based on 100 
percent of the capital Federal rate.

C. Annual Update for FY 2022

    The annual update to the national capital Federal rate, as provided 
for in 42 CFR 412.308(c), for FY 2022 is discussed in section III. of 
the Addendum to this FY 2022 IPPS/LTCH PPS final rule.
    In section II.C. of the preamble of this FY 2022 IPPS/LTCH PPS 
final rule, we present a discussion of the MS-DRG documentation and 
coding adjustment, including previously finalized policies and 
historical adjustments, as well as the adjustment to the standardized 
amount under section 1886(d) of the Act that we are making for FY 2022, 
in accordance with the amendments made to section 7(b)(1)(B) of Pubic 
Law 110-90 by section 414 of the MACRA. Because these provisions 
require us to make an adjustment only to the operating IPPS 
standardized amount, we are not making a similar adjustment to the 
national capital Federal rate (or to the hospital-specific rates).
    We also note that in section V.M. of the preamble of this final 
rule, we discuss our finalized adjustment to the payment amount for 
certain clinical trial or expanded access use immunotherapy cases that 
will group to MS-DRG 018 for both operating IPPS payments and capital 
IPPS payments. We refer readers to section V.M.D of this preamble for 
additional details on the payment adjustment for these cases.

VII. Changes for Hospitals Excluded From the IPPS

A. Rate-of-Increase in Payments To Excluded Hospitals for FY 2022

    Certain hospitals excluded from a prospective payment system, 
including children's hospitals, 11 cancer hospitals, and hospitals 
located outside the 50 States, the District of Columbia, and Puerto 
Rico (that is, hospitals located in the U.S. Virgin Islands, Guam, the 
Northern Mariana Islands, and American Samoa) receive payment for 
inpatient hospital services they furnish on the basis of reasonable 
costs, subject to a rate-of-increase ceiling. A per discharge limit 
(the target amount, as defined in Sec.  413.40(a) of the regulations) 
is set for each hospital based on the hospital's own cost experience in 
its base year, and updated annually by a rate-of-increase percentage. 
For each cost reporting

[[Page 45322]]

period, the updated target amount is multiplied by total Medicare 
discharges during that period and applied as an aggregate upper limit 
(the ceiling as defined in Sec.  413.40(a)) of Medicare reimbursement 
for total inpatient operating costs for a hospital's cost reporting 
period. In accordance with Sec.  403.752(a) of the regulations, 
religious nonmedical health care institutions (RNHCIs) also are subject 
to the rate-of-increase limits established under Sec.  413.40 of the 
regulations discussed previously. Furthermore, in accordance with Sec.  
412.526(c)(3) of the regulations, extended neoplastic disease care 
hospitals also are subject to the rate-of-increase limits established 
under Sec.  413.40 of the regulations discussed previously.
    As explained in the FY 2006 IPPS final rule (70 FR 47396 through 
47398), beginning with FY 2006, we have used the percentage increase in 
the IPPS operating market basket to update the target amounts for 
children's hospitals, the 11 cancer hospitals, and RNHCIs. Consistent 
with the regulations at Sec. Sec.  412.23(g) and 413.40(a)(2)(ii)(A) 
and (c)(3)(viii), we also have used the percentage increase in the IPPS 
operating market basket to update target amounts for short-term acute 
care hospitals located in the U.S. Virgin Islands, Guam, the Northern 
Mariana Islands, and American Samoa. In the FY 2018 IPPS/LTCH PPS final 
rule, we rebased and revised the IPPS operating basket to a 2014 base 
year, effective for FY 2018 and subsequent fiscal years (82 FR 38158 
through 38175), and finalized the use of the percentage increase in the 
2014-based IPPS operating market basket to update the target amounts 
for children's hospitals, the 11 cancer hospitals, RNHCIs, and short-
term acute care hospitals located in the U.S. Virgin Islands, Guam, the 
Northern Mariana Islands, and American Samoa for FY 2018 and subsequent 
fiscal years. As discussed in section IV. of the preamble of the FY 
2022 IPPS/LTCH PPS proposed rule, we proposed to rebase and revise the 
IPPS operating basket to a 2018 base year. Therefore, we proposed to 
use the percentage increase in the 2018-based IPPS operating market 
basket to update the target amounts for children's hospitals, the 11 
cancer hospitals, RNHCIs, and short-term acute care hospitals located 
in the U.S. Virgin Islands, Guam, the Northern Mariana Islands, and 
American Samoa for FY 2022 and subsequent fiscal years. Accordingly, 
for FY 2022, the rate-of-increase percentage to be applied to the 
target amount for these hospitals would be the FY 2022 percentage 
increase in the proposed 2018-based IPPS operating market basket.
    For the FY 2022 IPPS/LTCH PPS proposed rule, based on IGI's 2020 
fourth quarter forecast, we estimated that the proposed 2018-based IPPS 
operating market basket update for FY 2022 would be 2.5 percent (that 
is, the estimate of the market basket rate-of-increase). Based on this 
estimate, the FY 2022 rate-of-increase percentage that would be applied 
to the FY 2021 target amounts in order to calculate the FY 2022 target 
amounts for children's hospitals, the 11 cancer hospitals, RNCHIs, and 
short-term acute care hospitals located in the U.S. Virgin Islands, 
Guam, the Northern Mariana Islands, and American Samoa would be 2.5 
percent, in accordance with the applicable regulations at 42 CFR 
413.40. However, we proposed that if more recent data became available 
for the FY 2022 IPPS/LTCH PPS final rule, we would use such data, if 
appropriate, to calculate the final IPPS operating market basket update 
for FY 2022.
    For FY 2022, we are finalizing the rebased and revised 2018-based 
IPPS operating market basket without modification. However, as we 
proposed, we are incorporating more recent data available for this 
final rule. Based on IHS Global Inc.'s second-quarter 2021 forecast, 
the IPPS operating market basket update for FY 2022 is 2.7 percent.
    In addition, payment for inpatient operating costs for hospitals 
classified under section 1886(d)(1)(B)(vi) of the Act (which we refer 
to as ``extended neoplastic disease care hospitals'') for cost 
reporting periods beginning on or after January 1, 2015, is to be made 
as described in 42 CFR 412.526(c)(3), and payment for capital costs for 
these hospitals is to be made as described in 42 CFR 412.526(c)(4). 
(For additional information on these payment regulations, we refer 
readers to the FY 2018 IPPS/LTCH PPS final rule (82 FR 38321 through 
38322).) Section 412.526(c)(3) provides that the hospital's Medicare 
allowable net inpatient operating costs for that period are paid on a 
reasonable cost basis, subject to that hospital's ceiling, as 
determined under Sec.  412.526(c)(1), for that period. Under Sec.  
412.526(c)(1), for each cost reporting period, the ceiling was 
determined by multiplying the updated target amount, as defined in 
Sec.  412.526(c)(2), for that period by the number of Medicare 
discharges paid during that period. Section 412.526(c)(2)(i) describes 
the method for determining the target amount for cost reporting periods 
beginning during FY 2015. Section 412.526(c)(2)(ii) specifies that, for 
cost reporting periods beginning during fiscal years after FY 2015, the 
target amount will equal the hospital's target amount for the previous 
cost reporting period updated by the applicable annual rate-of-increase 
percentage specified in Sec.  413.40(c)(3) for the subject cost 
reporting period (79 FR 50197).
    For FY 2022, in accordance with Sec. Sec.  412.22(i) and 
412.526(c)(2)(ii) of the regulations, for cost reporting periods 
beginning during FY 2022, the proposed update to the target amount for 
extended neoplastic disease care hospitals (that is, hospitals 
described under Sec.  412.22(i)) is the applicable annual rate-of-
increase percentage specified in Sec.  413.40(c)(3) for FY 2022, which 
would be equal to the percentage increase in the hospital market 
basket, which was estimated to be the percentage increase in the 
proposed 2018-based IPPS operating market basket (that is, the estimate 
of the market basket rate-of-increase). Accordingly, the proposed 
update to an extended neoplastic disease care hospital's target amount 
for FY 2022 was 2.5 percent, which is based on IGI's 2020 fourth 
quarter forecast. Furthermore, we proposed that if more recent data 
became available for the FY 2022 IPPS/LTCH PPS final rule, we would use 
such data, if appropriate, to calculate the IPPS operating market 
basket update for FY 2022.
    For FY 2022, we are finalizing the rebased and revised 2018-based 
IPPS operating market basket without modification. However, as we 
proposed, we are incorporating more recent data available for this 
final rule. Based on IHS Global Inc.'s second-quarter 2021 forecast, 
the IPPS operating market basket update for FY 2022 is 2.7 percent.
    We received no comments in response to these proposals. As such, we 
are finalizing as we proposed. Incorporating more recent data available 
for this final rule, as we proposed, we are adopting a 2.7 percent 
update for FY 2022.

B. Report on Adjustment (Exception) Payments

    Section 4419(b) of Public Law 105-33 requires the Secretary to 
publish annually in the Federal Register a report describing the total 
amount of adjustment payments made to excluded hospitals and hospital 
units by reason of section 1886(b)(4) of the Act during the previous 
fiscal year.
    The process of requesting, adjusting, and awarding an adjustment 
payment is likely to occur over a 2-year period or longer. First, 
generally, an excluded hospital must file its cost report for the

[[Page 45323]]

fiscal year in accordance with Sec.  413.24(f)(2) of the regulations. 
The MAC reviews the cost report and issues a notice of provider 
reimbursement (NPR). Once the hospital receives the NPR, if its 
operating costs are in excess of the ceiling, the hospital may file a 
request for an adjustment payment. After the MAC receives the 
hospital's request in accordance with applicable regulations, the MAC 
or CMS, depending on the type of adjustment requested, reviews the 
request and determines if an adjustment payment is warranted. This 
determination is sometimes not made until more than 180 days after the 
date the request is filed because there are times when the request 
applications are incomplete and additional information must be 
requested in order to have a completed request application. However, in 
an attempt to provide interested parties with data on the most recent 
adjustment payments for which we have data, we are publishing data on 
adjustment payments that were processed by the MAC or CMS during FY 
2019.
    The table that follows includes the most recent data available from 
the MACs and CMS on adjustment payments that were adjudicated during FY 
2020. As indicated previously, the adjustments made during FY 2020 only 
pertain to cost reporting periods ending in years prior to FY 2020. 
Total adjustment payments made to IPPS-excluded hospitals during FY 
2020 are $5,088,002. The table depicts for each class of hospitals, in 
the aggregate, the number of adjustment requests adjudicated, the 
excess operating costs over the ceiling, and the amount of the 
adjustment payments.
[GRAPHIC] [TIFF OMITTED] TR13AU21.280

C. Critical Access Hospitals (CAHs)

1. Background
    Section 1820 of the Act provides for the establishment of Medicare 
Rural Hospital Flexibility Programs (MRHFPs), under which individual 
States may designate certain facilities as critical access hospitals 
(CAHs). Facilities that are so designated and meet the CAH conditions 
of participation under 42 CFR part 485, subpart F, will be certified as 
CAHs by CMS. Regulations governing payments to CAHs for services to 
Medicare beneficiaries are located in 42 CFR part 413.
2. Frontier Community Health Integration Project (FCHIP) Demonstration
a. Background and Overview
    As discussed in the FY 2021 IPPS/LTCH PPS final rule (85 FR 58894 
through 58896), section 123 of the Medicare Improvements for Patients 
and Providers Act of 2008 (Public Law 110-275), as amended by section 
3126 of the Affordable Care Act, authorized a demonstration project to 
allow eligible entities to develop and test new models for the delivery 
of health care services in eligible counties in order to improve access 
to and better integrate the delivery of acute care, extended care and 
other health care services to Medicare beneficiaries. The demonstration 
was titled ``Demonstration Project on Community Health Integration 
Models in Certain Rural Counties,'' and commonly known as the Frontier 
Community Health Integration Project (FCHIP) demonstration.
    The authorizing statute stated the eligibility criteria for 
entities to be able to participate in the demonstration. An eligible 
entity, as defined in section 123(d)(1)(B) of Public Law 110-275, as 
amended, is a Medicare Rural Hospital Flexibility Program (MRHFP) 
grantee under section 1820(g) of the Act (that is, a CAH); and is 
located in a State in which at least 65 percent of the counties in the 
State are counties that have 6 or less residents per square mile.
    The authorizing statute stipulated several other requirements for 
the demonstration. Section 123(d)(2)(B) of Public Law 110-275, as 
amended, limited participation in the demonstration to eligible 
entities in not more than 4 States. Section 123(f)(1) of Public Law 
110-275 required the demonstration project to be conducted for a 3-year 
period. In addition, section 123(g)(1)(B) of Public Law 110-275 
required that the demonstration be budget neutral. Specifically, this 
provision stated that, in conducting the demonstration project, the 
Secretary shall ensure that the aggregate payments made by the 
Secretary do not exceed the amount which the Secretary estimates would 
have been paid if the demonstration project under the section were not 
implemented. Furthermore, section 123(i) of Public Law 110-275 stated 
that the Secretary may waive such requirements of titles XVIII and XIX 
of the Act as may be necessary and appropriate for the purpose of 
carrying out the demonstration project, thus allowing the waiver of 
Medicare payment rules encompassed in the demonstration.
    In January 2014, we released a request for applications (RfA) for 
the FCHIP Demonstration. Using 2013 data from the U.S. Census Bureau, 
CMS identified Alaska, Montana, Nevada, North Dakota, and Wyoming as 
states meeting the statutory eligibility requirement for participation 
in the demonstration. The RfA solicited CAHs in these five States to 
participate in the demonstration, stating that participation would be 
limited to CAHs in four of the States. To apply, CAHs were required to 
meet the eligibility requirements in the authorizing legislation, and 
to describe a proposal to enhance health-related services that would 
complement those currently provided by the CAH and better serve the 
community's needs. In addition, in the RfA, CMS interpreted the 
eligible entity definition in the statute as meaning a CAH that 
receives funding through the MHRFP. The RfA identified four 
interventions, under which specific waivers of Medicare payment rules 
would allow for enhanced payment for telehealth, skilled nursing 
facility/nursing facility

[[Page 45324]]

beds, ambulance services, and home health services. These waivers were 
formulated with the goal of increasing access to care with no net 
increase in costs.
    Ten CAHs were selected for participation in the demonstration, 
which started on August 1, 2016, and concluded on July 31, 2019 
(referred to in this section as the ``initial period''). The selected 
CAHs were located in Montana, Nevada, and North Dakota, and 
participated in three of the four interventions identified in the FY 
2017 IPPS/LTCH PPS final rule (81 FR 57064 through 57065), the FY 2018 
IPPS/LTCH PPS final rule (82 FR 38294 through 38296), and the FY 2019 
IPPS/LTCH PPS final rule (83 FR 41516 through 41517), the FY 2020 IPPS/
LTCH PPS final rule (84 FR 42427 through 42428) and the FY 2021 IPPS/
LTCH PPS final rule (85 FR 58894 through 58896). Eight CAHs 
participated in the telehealth intervention, three CAHs participated in 
the skilled nursing facility/nursing facility bed intervention, and two 
CAHs participated in the ambulance services intervention. Each CAH was 
allowed to participate in more than one of the interventions. None of 
the selected CAHs were participants in the home health intervention, 
which was the fourth intervention included in the RfA.
b. Intervention Payment and Payment Waivers
    CMS waived certain Medicare rules for CAHs participating in the 
demonstration to allow for alternative reasonable cost-based payment 
methods in the three distinct intervention service areas: Telehealth 
services, ambulance services, and skilled nursing facility/nursing 
facility (SNF/NF) beds expansion. The payments and payment waiver 
provisions only applied if the CAH participated in the associated 
intervention. The FCHIP payment waivers consisted of the following:
(1) Telehealth Services Intervention Payments
    CMS waived section 1834(m)(2)(B) of the Social Security Act (the 
Act), which specifies the facility fee to the originating site (that 
is, the participating CAH where the eligible telehealth individual is 
located). CMS modified the facility fee payment specified under section 
1834(m)(2)(B) of the Act to allow for reasonable cost-based 
reimbursement to the participating CAH. CMS reimbursed the 
participating CAH serving as the originating site at 101 percent of its 
reasonable costs for overhead, salaries, fringe benefits, and the 
depreciation value of the telehealth equipment at the participating 
CAH. The Demonstration waiver did not fund or provide reimbursement for 
the participating CAHs to purchase new telehealth equipment. However, 
if a participating CAH purchases new equipment, CMS would continue to 
reimburse depreciation costs for that equipment. The payments to the 
distant site physician or practitioner were made as usual under the 
Medicare physician fee schedule. CMS did not waive any other provisions 
of section 1834(m) of the Act, including the scope of Medicare 
telehealth services as established under section 1834(m)(4)(F) of the 
Act.
(2) Ambulance Services Intervention Payments
    CMS waived 42 CFR 413.70(b)(5)(C), which provides that payment for 
ambulance services furnished by a CAH, or an entity owned and operated 
by a CAH, is 101 percent of the reasonable costs of the CAH or the 
entity in furnishing the ambulance services if the CAH or entity is the 
only provider or supplier of ambulance services located within a 35-
mile drive of the CAH. Under the demonstration, a participating CAH was 
paid 101 percent of reasonable costs for its ambulance services 
regardless of whether there was any other provider or supplier of 
ambulance services located within a 35-mile drive of the participating 
CAH or CAH-owned and operated entity. Cost-based payment was not 
allowed for any new capital expenditures (for example, vehicles) 
associated with ambulance services. This waiver did not modify any 
other Medicare rules affecting the provision of ambulance services.
(3) SNF/NF Beds Expansion Intervention Payments
    CMS waived 42 CFR 485.620(a) and 42 CFR 485.645(a)(2), which limit 
CAHs to maintaining no more than 25 inpatient beds, including beds 
available for acute inpatient or swing bed services. Through this 
waiver, CAHs participating in the SNF/NF intervention were allowed to 
keep up to 10 additional beds (for a total of up to 35 beds) available 
for acute inpatient or swing bed services; however, the participating 
CAHs were only to use these additional beds for nursing facility or 
skilled nursing facility level of care. SNF/NF services furnished in 
the additional beds were reimbursed according to the standard Medicare 
reimbursement principles for CAHs. Additional capital expenditures were 
not allowed under this waiver. No changes to the methodology for 
calculating Medicare payments for swing bed services at participating 
CAHs were allowed. The Conditions of Participation (CoPs) for certified 
critical access hospitals providing (SNF/NF) long term care services 
are at 42 CFR 485.645. Certification to participate in Medicare's swing 
bed program is a separate approval by CMS from the certification to 
operate as a CAH provider of services. The participating CAHs within 
the SNF/NF Beds Expansion intervention were required to receive 
approval from and be certified by CMS to participate in the 
Demonstration swing bed program.
c. Budget Neutrality Requirement
    In the FY 2017 IPPS/LTCH PPS final rule (81 FR 57064 through 
57065), we finalized a policy to address the budget neutrality 
requirement for the demonstration. We also discussed this policy in the 
FY 2018 IPPS/LTCH PPS final rule (82 FR 38294 through 38296), the FY 
2019 IPPS/LTCH PPS final rule (83 FR 41516 through 41517), the FY 2020 
IPPS/LTCH PPS final rule (84 FR 42427 through 42428) and the FY 2021 
IPPS/LTCH PPS final rule (85 FR 58894 through 58996), but did not make 
any changes to the policy that was adopted in FY 2017. As explained in 
the FY 2017 IPPS/LTCH PPS final rule, we based our selection of CAHs 
for participation in the demonstration with the goal of maintaining the 
budget neutrality of the demonstration on its own terms meaning that 
the demonstration would produce savings from reduced transfers and 
admissions to other health care providers, offsetting any increase in 
Medicare payments as a result of the demonstration. However, because of 
the small size of the demonstration and uncertainty associated with the 
projected Medicare utilization and costs, the policy we adopted in the 
FY 2017 IPPS/LTCH PPS final rule provides a contingency plan to ensure 
that the budget neutrality requirement in section 123 of Public Law 
110-275 is met. If analysis of claims data for Medicare beneficiaries 
receiving services at each of the participating CAHs, as well as from 
other data sources, including cost reports for the participating CAHs, 
shows that increases in Medicare payments under the demonstration 
during the 3-year period are not sufficiently offset by reductions 
elsewhere, we will recoup the additional expenditures attributable to 
the demonstration through a reduction in payments to all CAHs 
nationwide. Because of the small scale of the demonstration, we 
indicated that we did not believe it would be feasible to implement 
budget neutrality by reducing payments to only the participating CAHs. 
Therefore, in the

[[Page 45325]]

event that this demonstration is found to result in aggregate payments 
in excess of the amount that would have been paid if this demonstration 
were not implemented, we stated that we would comply with the budget 
neutrality requirement by reducing payments to all CAHs, not just those 
participating in the demonstration. We stated that we believe it is 
appropriate to make any payment reductions across all CAHs because the 
FCHIP Demonstration was specifically designed to test innovations that 
affect delivery of services by the CAH provider category. We explained 
our belief that the language of the statutory budget neutrality 
requirement at section 123(g)(1)(B) of Public Law 110-275 permits the 
agency to implement the budget neutrality provision in this manner. The 
statutory language merely refers to ensuring that aggregate payments 
made by the Secretary do not exceed the amount which the Secretary 
estimates would have been paid if the demonstration project was not 
implemented, and does not identify the range across which aggregate 
payments must be held equal.
    Based on actuarial analysis using cost report settlements for FYs 
2013 and 2014, the FCHIP Demonstration was projected to satisfy the 
budget neutrality requirement and likely yield a total net savings. In 
the FY 2017 IPPS/LTCH PPS (81 FR 57064 through 57065) final rule, we 
estimated that the total impact of the payment recoupment (if needed) 
would be no greater than 0.03 percent of CAHs' total Medicare payments 
(that is, Medicare Part A and Part B) within 1 fiscal year. We also 
explained that the final budget neutrality estimates for the FCHIP 
Demonstration would be based on costs incurred during the initial 
period of the demonstration from August 1, 2016, through July 31, 2019.
d. FCHIP Budget Neutrality Methodology and Analytical Approach
    As explained in the FY 2021 IPPS/LTCH PPS final rule, our goal was 
to maintain the budget neutrality of the demonstration on its own terms 
(that is, the demonstration would produce savings from reduced 
transfers and admissions to other health care providers, thus 
offsetting any increase in payments to the participating CAHs resulting 
from the demonstration). The analysis of budget neutrality identified 
both the costs related to providing the intervention services under the 
FCHIP Demonstration and any potential downstream effects of the 
intervention-related services, including any savings that may have 
accrued.
    The budget neutrality analytical approach incorporated two major 
data components: (1) Medicare cost reports; and (2) Medicare 
administrative claims. As described in the FY 2021 IPPS/LTCH PPS final 
rule (85 48432 through 59107), we computed the cost of the 
demonstration for each fiscal year of the demonstration period using 
Medicare cost reports for the participating CAHs, and Medicare 
administrative claims and enrollment data for beneficiaries who 
received demonstration intervention services.
e. General Analytical Approach
    The budget neutrality assessment sought to determine if the goal to 
maintain budget neutrality of the demonstration on its own terms was 
met. We examined the difference in expenditures for groups of 
beneficiaries who received intervention services at demonstration CAHs 
or at comparison CAHs that were not participating in the demonstration. 
The demonstration and comparison groups were composed of Medicare 
beneficiaries receiving an intervention service (that is, telehealth, 
SNF/NF or ambulance) at participating CAHs and non-participating CAHs, 
respectively. To ensure that there was no cross contamination between 
the two groups, the demonstration and comparison groups were mutually 
exclusive of each other, and beneficiaries who received intervention 
services at both participating and non-participating CAHs were included 
within the demonstration group only.
    Medicare reimbursement for the demonstration intervention services 
depended on the service provided. For the swing bed services, the 
demonstration CAH swing bed reimbursement was based on 101 percent of 
the reasonable cost of the SNF services furnished in the swing beds (as 
computed in the Medicare cost report). The CAHs were paid on an interim 
basis using a per diem rate for routine and ancillary costs. For the 
demonstration ambulance and telehealth services, CAH reimbursement was 
based on 101 percent of the reasonable cost of providing the services 
to Medicare patients (as computed in the Medicare cost report). The 
CAHs were paid on an interim basis using a percentage of Medicare 
charges. The applicable percentage of Medicare charges was calculated 
by dividing the overall allowable Medicare costs by the overall 
Medicare charges in order to determine the Medicare cost-to-charge 
ratio.
    The three intervention services were different, and each 
demonstration CAH had the option to implement one, two or all three 
interventions. Therefore, budget neutrality was analyzed for each 
demonstration intervention service separately. The basic approach to 
the analysis was similar for each intervention service, but some 
additional variables were incorporated based on the nature of the 
intervention and its expected impact. The findings for each 
intervention service were then combined at the end of the process to 
reach a single conclusion regarding budget neutrality for the initial 
period of the demonstration as a whole.
f. Data Elements
    Beginning with the cost report data, CMS conducted Medicare cost 
report audit reviews for the 10 participating CAHs over the course of 
the three-year initial period. The cost reports are a collection of 
worksheets that calculate the costs of a specific provider for 
supplying health care services to Medicare beneficiaries and when 
aggregated these cost reports furnish information used by researchers, 
actuaries and policy makers. All CAHs participating in the Medicare 
program are required to submit cost reports annually, with the 
reporting period based on the provider's accounting year. It should be 
noted the FCHIP Cost Report audits calculated budget neutrality as 
determined only by the change in the cost of providing services to 
Medicare beneficiaries through the Medicare cost report and excluded 
other factors that may also influence aggregate cost to the Medicare 
program, such as a shifting of essential services to CAHs from more 
expensive tertiary hospitals or other downstream cost impacts.
    The intervention services authorized under the demonstration may 
impact cost in several ways that can act to either increase or decrease 
expenditures. For example, the transition from a facility fee payment 
to the originating site to cost-based reimbursement under the 
telehealth services intervention would likely result in increased costs 
for those services. However, the Medicare administrative claims 
analysis anticipated and measured that telehealth intervention services 
furnished under the demonstration may also produce savings through 
better management of chronic conditions, reduction in air transports, 
and reduction in transfers to other and/or more expensive facilities. 
In general, the intervention services under the demonstration may 
affect access to services and referral patterns that, in turn, may 
affect utilization and therefore costs. In order to capture the full 
impact of the interventions, CMS developed a statistical modeling, 
Difference-in-Difference (DID) regression analysis to estimate

[[Page 45326]]

demonstration episode expenditures and compute the impact of 
expenditures on the intervention services by comparing cost data for 
the demonstration and non-demonstration groups using Medicare 
administrative claims across the 36-month period of performance under 
the initial period of demonstration. Analyses were conducted separately 
for each intervention service using regression-based methods that 
controlled for demographics, diagnostic conditions, hierarchical 
condition categories (HCC) risk scores, and other factors. Results were 
combined across the three intervention services to produce a summary 
conclusion regarding budget neutrality for the initial period of the 
demonstration as a whole.
    This general analytic approach involved the comparison of total 
episode expenditures for beneficiaries receiving intervention services 
from CAHs in the demonstration group to the expected expenditures 
absent the demonstration. The projection of expected expenditures 
absent the demonstration included an additional adjustment to reflect 
the statistical uncertainty of the predictions. If actual expenditures 
for the intervention services furnished by CAHs in the demonstration 
group exceeded the expected expenditures absent the demonstration (with 
the adjustment for statistical uncertainty), then budget neutrality 
could potentially be violated. CMS conducted a series of analytical 
steps as previously described to determine the budget neutrality 
outcome for the initial period of the demonstration.
g. Methodology for Estimating Demonstration Costs
    Step 1: The Medicare cost reports for CAHs participating in the 
FCHIP Demonstration were reviewed to verify reasonableness of reported 
expenses, revenues and statistics and to ensure the reported 
demonstration expenses were allowable and accurately allocated on the 
cost report. CMS performed a reasonableness analysis of the cost 
reports for each of the demonstration CAHs that focused on cost 
incurred by the CAH to determine whether the costs were necessary and 
proper for patient care under the demonstration. CMS also performed an 
allowability analysis for each demonstration CAH to determine which 
costs were directly related to the demonstration and to ensure all 
reported costs related to the intervention services were accounted for. 
In addition, each demonstration CAH's cost reports were audited to 
ensure the reported expenses were allowable and accurately allocated to 
each intervention service considering established Medicare regulations 
as modified by demonstration requirements. Demonstration costs that 
were unrelated to patient care were deemed not allowable. The cost 
report audit analysis included removal of any cost claimed by 
demonstration CAHs that was not specifically described in `(b) 
Intervention Payment and Payment Waivers', which describes the Medicare 
rules and payments methods that were actually made under the 
demonstration for each of the three interventions.
    For each of the 10 demonstration CAHs, we identified the reasonable 
cost amount calculated under the reasonable cost-based methodology for 
the demonstration covered inpatient hospital services and covered 
outpatient hospital services, including swing bed, telehealth, and 
ambulance services as indicated on the ``as submitted'' cost report for 
each hospital cost reporting period covering the initial period of 
performance for the demonstration from August 1, 2016, through July 31, 
2019. For each of the demonstration CAHs, these ``as submitted'' cost 
reports are those with cost report period end dates in Calendar Year 
(CY) 2016, 2017, 2018, 2019 and 2020. We note that among the 
demonstration CAHs with ``as submitted'' cost reports in CY 2020, the 
cost reporting period covered January 1, 2019, to December 31, 2019; 
March 1, 2019, to April 30, 2020; or July 1, 2019, to June 30, 2020.
    Step 2: CMS utilized Hospital 2552-10 Cost Report Data files to 
calculate the change in Medicare reimbursement for the initial period 
of performance. CMS calculated Medicare reimbursement costs under the 
demonstration versus Medicare reimbursement costs without the 
demonstration. ``Medicare reimbursement costs without the 
demonstration'' were defined as Medicare costs as determined using the 
Medicare payment methodologies that would have applied absent the 
demonstration and represented the baseline costs for each intervention 
service. ``Medicare reimbursement costs under the demonstration'' were 
defined as the costs as determined through the audited cost report 
after the application of the demonstration payment waiver 
methodologies. The difference between these costs represented the cost 
impact of the demonstration.
    For each of the participating CAHs, we identified the estimated 
amount that would otherwise be paid under applicable Medicare payment 
methodologies for covered intervention services (as indicated on the 
same set of ``as submitted'' cost reports as in Step 1), if the 
demonstration were not implemented. (Also, as indicated on the same set 
of ``as submitted'' cost reports as in Step 1), we identified the 
estimated amount that was paid for covered intervention services under 
the demonstration. To compute the aggregate change in cost due to the 
demonstration, we calculated the difference in the costs of 
intervention services between ``Medicare reimbursement costs without 
the demonstration'' versus ``Medicare reimbursement costs under the 
demonstration'' from the cost reports.
    Step 3: For each of the 10 CAHs, Medicare administrative claims and 
enrollment data for beneficiaries receiving demonstration intervention 
services were identified. The data were collected at the individual 
beneficiary level and included information on service type, service 
date, and reasonable cost payment amount calculated under the 
reasonable cost-based methodology for covered intervention services 
furnished under the demonstration. Codes indicating diagnosis and the 
specific procedure provided under the demonstration were also 
identified using the claims and enrollment data and were used in the 
analysis.
    Step 4: CMS defined ``episodes of care'' for the eligible CAHs. For 
each of the participating CAHs, using Medicare administrative claims, 
we identified costs related to providing demonstration intervention 
services. The demonstration CAHs submitted Medicare claims for the 
demonstration intervention services. These claims were consolidated by 
the Medicare Administrative Contractor (MAC) into interim payments, 
which were incorporated into an episode of care framework for purposes 
of the budget neutrality calculation. CMS defined an episode of care as 
all Medicare Parts A and B services furnished to a beneficiary 
receiving a demonstration intervention service during a specified 
period of time ranging from 30 to 60 days following the receipt of a 
demonstration intervention service. The specific timeframes for the 
episodes of care were chosen for each intervention based on observed 
expenditure patterns following an episode-triggering intervention 
service.
    Episode costs were defined as the cost of all Medicare Parts A and 
B services provided to the beneficiary during the episode. Next, CMS 
incorporated the claims and interim payment data into the episode of 
care framework.
    Step 5: CMS constructed Episode of Care Comparison groups and 
potential savings variables. We separated the episode of care Medicare 
Parts A and B

[[Page 45327]]

expenditures into two groups--expenditures for beneficiaries receiving 
intervention services from demonstration group CAHs and expenditures 
for beneficiaries receiving intervention services from non-
demonstration (comparison) group CAHs within the FCHIP eligible States 
(Montana, Nevada, and North Dakota). Then we compared episode of care 
expenditures for beneficiaries receiving intervention services from 
demonstration group CAHs to those for beneficiaries receiving 
intervention services from comparison group CAHs.
    Step 6: CMS conducted the Difference-in-Difference Analysis. Using 
the episode of care framework described in Step 4, the demonstration 
and comparison groups were used to measure the impact of the 
intervention services on episode expenditures through a DID analysis 
comparing baseline and performance period costs for the demonstration 
groups and comparison groups. The DID regression model was estimated 
using episode expenditures as the dependent variable. (The model's 
functional form was a generalized linear model with a log link and 
gamma distribution. This type of model is commonly used in analyzing 
health care expenditures and yields only positive predicted values.) 
All analyses were carried out separately for the three intervention 
services. Using the episode of care approach enabled us to identify 
downstream effects of the intervention services, including any savings 
that may have accrued. For each of the participating CAHs we identified 
cost-savings or reductions in transfers and admissions to other health 
care providers, offsetting any increase in Medicare payments that may 
have resulted from the use of intervention services. Results were 
combined across the ten CAH participants and across the three 
interventions to produce a summary conclusion regarding budget 
neutrality for the 36-month initial demonstration performance period.
    Step 7: Lastly, CMS performed a supplementary sensitivity analysis 
adjustment for statistical uncertainty. The DID analysis results 
obtained using the Medicare administrative claims data were then 
reconciled using data obtained from auditing the participating CAHs' 
Medicare cost reports. The Medicare cost reports provide another source 
of data related to demonstration expenditures beyond the information 
that is directly reported via Medicare administrative claims. The 
Medicare cost report audit findings were used to reconcile the 
directionality and outcome of the DID regression analysis results. The 
sensitivity analysis was calculated for the demonstration as a whole to 
ensure the budget neutrality conclusion via the DID analysis was not 
the result of random variation or statistical uncertainty of the 
predictions used in the analysis.
g. Budget Neutrality Conclusion
    Based on analysis of the Medicare administrative claims data and 
the Medicare cost report audit data from the 36 months of the initial 
demonstration performance period, there were no statistically 
significant findings that the FCHIP Demonstration resulted in 
additional expenditures. The DID analysis results were based on an 
episode of care point estimate threshold. If the actual episode 
expenditures of the demonstration exceeded the expected expenditures 
absent the demonstration (with the sensitivity analysis adjustment for 
statistical uncertainty) then the requirement for budget neutrality 
under section 123(g)(1)(B) of Public Law 110-275 could potentially be 
violated. CMS found in aggregate that the demonstration CAHs' episode 
of care expenditures during the initial period of the demonstration 
were lower than expenditures would have been absent the demonstration. 
In fact, when the sensitivity analysis (using a 95 percent confidence 
interval) was calculated it showed that total expenditures for the 10 
participating CAHs in the demonstration would need to cumulatively 
increase cost by more than 18 percent (which translated to $3,120 per 
episode, or a total of $3,529,039 for the three interventions combined) 
to exceed expenditures absent the demonstration. When we compared the 
total cost of Medicare episodes of care under the demonstration with 
the aggregate demonstration cost findings based on the audit of 
Medicare cost reports, we also found that the aggregate demonstration 
intervention services cost on the ``as submitted'' Medicare cost 
reports fell within the point estimate threshold--therefore, the FCHIP 
Demonstration did not result in additional expenditures during the 
initial period of the demonstration.
    Under the policy finalized in the FY 2017 IPPS/LTCH PPS final rule, 
in the event the demonstration is found not to have been budget 
neutral, any excess costs will be recouped over a period of 3 cost 
reporting years, beginning in CY 2020. In the FY 2021 IPPS/LTCH PPS 
final rule (85 FR 58895), we stated that based on the currently 
available data, the determination of budget neutrality results was 
preliminary and the amount of any reduction to CAH payments that would 
be needed in order to recoup excess costs under the demonstration 
remained uncertain. Therefore, we revised the policy originally adopted 
in the FY 2017 IPPS/LTCH PPS final rule, to delay the implementation of 
any budget neutrality adjustment and stated that we would revisit this 
policy in rulemaking for FY 2022, when we expected to have complete 
data for the demonstration period. Based on the data and actuarial 
analysis described previously, we have concluded that the initial 
period of the FCHIP Demonstration (covering the performance period 
August 1, 2016, to July 31, 2019) has satisfied the budget neutrality 
requirement described in section 123(g)(1)(B) of Public Law 110-275. 
Therefore, we did not propose to apply a budget neutrality payment 
offset to payments to CAHs in FY 2022. This policy will have no impact 
for any national payment system for FY 2022.
3. Provisions of the Consolidated Appropriations Act of 2021 (Pub. L. 
116-159)
    As stated earlier, section 123 of the Medicare Improvements for 
Patients and Providers Act of 2008 (Pub. L. 110-275), as amended by 
section 3126 of the Affordable Care Act, authorized the Secretary to 
conduct the Frontier Community Health Integration Project (FCHIP) 
demonstration for a 3-year period. Section 129 of the Consolidated 
Appropriations Act (Pub. L. 116-159) extends the FCHIP Demonstration by 
5 years. Specifically, the Consolidated Appropriations Act amended 
subsection (f) of section 123 of the Medicare Improvements for Patients 
and Providers Act of 2008 (42 U.S.C. 1395i-4 note) in paragraph (1), by 
striking ``3-year period beginning on October 1, 2009'' and inserting 
``3-year period beginning on August 1, 2016 (referred to in this 
section as the ``initial period''), and 5-year period beginning on July 
1, 2021 (referred to in this section as the ``extension period''). The 
Secretary is required to conduct the demonstration for an additional 5-
year period. Only the 10 CAHs that participated in the initial period 
of the FCHIP Demonstration are eligible to participate during the 
extension period. In the FY 2022 IPPS/LTCH PPS proposed rule, CMS 
explained the provisions of the Consolidated Appropriations Act of 2021 
(Pub. L. 116-159) and states the FCHIP Demonstration will resume on 
July 1, 2021. The eligible CAH participants have elected to change the 
number of interventions and payment waivers they would participate in 
during the extension period. CMS consideration of these updates 
requires a delay in the effective date for starting the extension 
period that was published

[[Page 45328]]

in the proposed rule. We are updating our date for starting the 
extension period of the demonstration from July 1, 2021 to January 1, 
2022. CAHs participating in the demonstration during the extension 
period shall begin their participation in the cost reporting year that 
begins on or after January 1, 2022. During the delay, CMS will complete 
several actions with the CAHs to develop and/or update the intervention 
payment waivers for the demonstration extension period. In addition, 
CMS will be issuing a new participation agreement outlying the 
demonstration terms and conditions for the participating CAHs new 
performance period that shall begin on or after January 1, 2022. CMS 
informed the CAHs participating in the extension period of the change 
and the CAHs have not expressed concerns about the revised effective 
date.
    While we expect to use the same methodology that was used to assess 
the budget neutrality of the FCHIP Demonstration during initial period 
of the demonstration to assess the financial impact of the 
demonstration during this extension period, based on the data available 
upon receiving data for the extension period, we may update and/or 
modify the FCHIP budget neutrality methodology and analytical approach 
to ensure that the full impact of the demonstration is appropriately 
captured. We will determine the budget neutrality approach for the 
FCHIP Demonstration extension period once data is available for the 
extension period.
    We received no comments on this proposal and therefore are 
finalizing this provision without modification.

VIII. Changes to the Long-Term Care Hospital Prospective Payment System 
(LTCH PPS) for FY 2022

A. Background of the LTCH PPS

1. Legislative and Regulatory Authority
    Section 123 of the Medicare, Medicaid, and SCHIP (State Children's 
Health Insurance Program) Balanced Budget Refinement Act of 1999 (BBRA) 
(Pub. L. 106-113), as amended by section 307(b) of the Medicare, 
Medicaid, and SCHIP Benefits Improvement and Protection Act of 2000 
(BIPA) (Pub. L. 106-554), provides for payment for both the operating 
and capital-related costs of hospital inpatient stays in long-term care 
hospitals (LTCHs) under Medicare Part A based on prospectively set 
rates. The Medicare prospective payment system (PPS) for LTCHs applies 
to hospitals that are described in section 1886(d)(1)(B)(iv) of the 
Act, effective for cost reporting periods beginning on or after October 
1, 2002.
    Section 1886(d)(1)(B)(iv)(I) of the Act originally defined an LTCH 
as a hospital that has an average inpatient length of stay (as 
determined by the Secretary) of greater than 25 days. Section 
1886(d)(1)(B)(iv)(II) of the Act also provided an alternative 
definition of LTCHs (``subclause II'' LTCHs). However, section 15008 of 
the 21st Century Cures Act (Pub. L. 114-255) amended section 1886 of 
the Act to exclude former ``subclause II'' LTCHs from being paid under 
the LTCH PPS and created a new category of IPPS-excluded hospitals, 
which we refer to as ``extended neoplastic disease care hospitals,'' to 
be paid as hospitals that were formally classified as ``subclause 
(II)'' LTCHs (82 FR 38298).
    Section 123 of the BBRA requires the PPS for LTCHs to be a ``per 
discharge'' system with a diagnosis-related group (DRG) based patient 
classification system that reflects the differences in patient resource 
use and costs in LTCHs.
    Section 307(b)(1) of the BIPA, among other things, mandates that 
the Secretary shall examine, and may provide for, adjustments to 
payments under the LTCH PPS, including adjustments to DRG weights, area 
wage adjustments, geographic reclassification, outliers, updates, and a 
disproportionate share adjustment.
    In the August 30, 2002 Federal Register, we issued a final rule 
that implemented the LTCH PPS authorized under the BBRA and BIPA (67 FR 
55954). For the initial implementation of the LTCH PPS (FYs 2003 
through FY 2007), the system used information from LTCH patient records 
to classify patients into distinct long-term care-diagnosis-related 
groups (LTCDRGs) based on clinical characteristics and expected 
resource needs. Beginning in FY 2008, we adopted the Medicare severity-
long-term care-diagnosis related groups (MS-LTC-DRGs) as the patient 
classification system used under the LTCH PPS. Payments are calculated 
for each MS-LTC-DRG and provisions are made for appropriate payment 
adjustments. Payment rates under the LTCH PPS are updated annually and 
published in the Federal Register.
    The LTCH PPS replaced the reasonable cost-based payment system 
under the Tax Equity and Fiscal Responsibility Act of 1982 (TEFRA) 
(Pub. L. 97248) for payments for inpatient services provided by an LTCH 
with a cost reporting period beginning on or after October 1, 2002. 
(The regulations implementing the TEFRA reasonable-cost-based payment 
provisions are located at 42 CFR part 413.) With the implementation of 
the PPS for acute care hospitals authorized by the Social Security 
Amendments of 1983 (Pub. L. 98-21), which added section 1886(d) to the 
Act, certain hospitals, including LTCHs, were excluded from the PPS for 
acute care hospitals and paid their reasonable costs for inpatient 
services subject to a per discharge limitation or target amount under 
the TEFRA system. For each cost reporting period, a hospital specific 
ceiling on payments was determined by multiplying the hospital's 
updated target amount by the number of total current year Medicare 
discharges. (Generally, in this section of the preamble of this final 
rule, when we refer to discharges, we describe Medicare discharges.) 
The August 30, 2002 final rule further details the payment policy under 
the TEFRA system (67 FR 55954).
    In the August 30, 2002 final rule, we provided for a 5-year 
transition period from payments under the TEFRA system to payments 
under the LTCH PPS. During this 5-year transition period, an LTCH's 
total payment under the PPS was based on an increasing percentage of 
the Federal rate with a corresponding decrease in the percentage of the 
LTCH PPS payment that is based on reasonable cost concepts, unless an 
LTCH made a one-time election to be paid based on 100 percent of the 
Federal rate. Beginning with LTCHs' cost reporting periods beginning on 
or after October 1, 2006, total LTCH PPS payments are based on 100 
percent of the Federal rate.
    In addition, in the August 30, 2002 final rule, we presented an in-
depth discussion of the LTCH PPS, including the patient classification 
system, relative weights, payment rates, additional payments, and the 
budget neutrality requirements mandated by section 123 of the BBRA. The 
same final rule that established regulations for the LTCH PPS under 42 
CFR part 412, subpart O, also contained LTCH provisions related to 
covered inpatient services, limitation on charges to beneficiaries, 
medical review requirements, furnishing of inpatient hospital services 
directly or under arrangement, and reporting and recordkeeping 
requirements. We refer readers to the August 30, 2002 final rule for a 
comprehensive discussion of the research and data that supported the 
establishment of the LTCH PPS (67 FR 55954).
    In the FY 2016 IPPS/LTCH PPS final rule (80 FR 49601 through 
49623), we implemented the provisions of the Pathway for Sustainable 
Growth Rate

[[Page 45329]]

(SGR) Reform Act of 2013 (Pub. L. 113-67), which mandated the 
application of the ``site neutral'' payment rate under the LTCH PPS for 
discharges that do not meet the statutory criteria for exclusion 
beginning in FY 2016. For cost reporting periods beginning on or after 
October 1, 2015, discharges that do not meet certain statutory criteria 
for exclusion are paid based on the site neutral payment rate. 
Discharges that do meet the statutory criteria continue to receive 
payment based on the LTCH PPS standard Federal payment rate. For more 
information on the statutory requirements of the Pathway for SGR Reform 
Act of 2013, we refer readers to the FY 2016 IPPS/LTCH PPS final rule 
(80 FR 49601 through 49623) and the FY 2017 IPPS/LTCH PPS final rule 
(81 FR 57068 through 57075).
    In the FY 2018 IPPS/LTCH PPS final rule, we implemented several 
provisions of the 21st Century Cures Act (``the Cures Act'') (Pub. L. 
114-255) that affected the LTCH PPS. (For more information on these 
provisions, we refer readers to 82 FR 38299.)
    In the FY 2019 IPPS/LTCH PPS final rule (83 FR 41529), we made 
conforming changes to our regulations to implement the provisions of 
section 51005 of the Bipartisan Budget Act of 2018 (Pub. L. 115-123), 
which extends the transitional blended payment rate for site neutral 
payment rate cases for an additional 2 years. We refer readers to 
section VII.C. of the preamble of the FY 2019 IPPS/LTCH PPS final rule 
for a discussion of our final policy. In addition, in the FY 2019 IPPS/
LTCH PPS final rule, we removed the 25-percent threshold policy under 
42 CFR 412.538.
    In the FY 2020 IPPS/LTCH PPS final rule (84 FR 42439), we further 
revised our regulations to implement the provisions of the Pathway for 
SGR Reform Act of 2013 (Pub. L. 113-67) that relate to the payment 
adjustment for discharges from LTCHs that do not maintain the requisite 
discharge payment percentage and the process by which such LTCHs may 
have the payment adjustment discontinued.
2. Criteria for Classification as an LTCH
a. Classification as an LTCH
    Under the regulations at Sec.  412.23(e)(1), to qualify to be paid 
under the LTCH PPS, a hospital must have a provider agreement with 
Medicare. Furthermore, Sec.  412.23(e)(2)(i), which implements section 
1886(d)(1)(B)(iv) of the Act, requires that a hospital have an average 
Medicare inpatient length of stay of greater than 25 days to be paid 
under the LTCH PPS. In accordance with section 1206(a)(3) of the 
Pathway for SGR Reform Act of 2013 (Pub. L. 113-67), as amended by 
section 15007 of Public Law 114-255, we amended our regulations to 
specify that Medicare Advantage plans' and site neutral payment rate 
discharges are excluded from the calculation of the average length of 
stay for all LTCHs, for discharges occurring in cost reporting period 
beginning on or after October 1, 2015.
b. Hospitals Excluded From the LTCH PPS
    The following hospitals are paid under special payment provisions, 
as described in Sec.  412.22(c) and, therefore, are not subject to the 
LTCH PPS rules:
     Veterans Administration hospitals.
     Hospitals that are reimbursed under State cost control 
systems approved under 42 CFR part 403.
     Hospitals that are reimbursed in accordance with 
demonstration projects authorized under section 402(a) of the Social 
Security Amendments of 1967 (Pub. L. 90-248) (42 U.S.C. 1395b-1), 
section 222(a) of the Social Security Amendments of 1972 (Pub. L. 92-
603) (42 U.S.C. 1395b1 (note)) (Statewide-all payer systems, subject to 
the rate-of increase test at section 1814(b) of the Act), or section 
3201 of the Patient Protection and Affordable Care Act (Pub. L. 111-
148) (42 U.S.C. 1315a).
     Nonparticipating hospitals furnishing emergency services 
to Medicare beneficiaries.
3. Limitation on Charges to Beneficiaries
    In the August 30, 2002 final rule, we presented an in-depth 
discussion of beneficiary liability under the LTCH PPS (67 FR 55974 
through 55975). This discussion was further clarified in the RY 2005 
LTCH PPS final rule (69 FR 25676). In keeping with those discussions, 
if the Medicare payment to the LTCH is the full LTC-DRG payment amount, 
consistent with other established hospital prospective payment systems, 
Sec.  412.507 currently provides that an LTCH may not bill a Medicare 
beneficiary for more than the deductible and coinsurance amounts as 
specified under Sec. Sec.  409.82, 409.83, and 409.87, and for items 
and services specified under Sec.  489.30(a). However, under the LTCH 
PPS, Medicare will only pay for services furnished during the days for 
which the beneficiary has coverage until the short-stay outlier (SSO) 
threshold is exceeded. If the Medicare payment was for a SSO case (in 
accordance with Sec.  412.529), and that payment was less than the full 
LTC-DRG payment amount because the beneficiary had insufficient 
coverage as a result of the remaining Medicare days, the LTCH also is 
currently permitted to charge the beneficiary for services delivered on 
those uncovered days (in accordance with Sec.  412.507). In the FY 2016 
IPPS/LTCH PPS final rule (80 FR 49623), we amended our regulations to 
expressly limit the charges that may be imposed upon beneficiaries 
whose LTCHs' discharges are paid at the site neutral payment rate under 
the LTCH PPS. In the FY 2017 IPPS/LTCH PPS final rule (81 FR 57102), we 
amended the regulations under Sec.  412.507 to clarify our existing 
policy that blended payments made to an LTCH during its transitional 
period (that is, an LTCH's payment for discharges occurring in cost 
reporting periods beginning in FYs 2016 through 2019) are considered to 
be site neutral payment rate payments.
4. Best Available Data
    In section I.F. of the preamble of this final rule, we discussed 
how claims data from the MedPAR files and cost report data from HCRIS 
are the primary sources of data used in IPPS and LTCH PPS ratesetting. 
(We use the term ``ratesetting'' to describe the methods and processes 
we follow in determining the annual LTCH PPS payment rates and 
factors.) We also stated that our goal is to always use the best 
available data overall for ratesetting. Ordinarily, the best available 
claims data for the LTCH PPS ratesetting is the MedPAR file that 
contains claims from discharges for the fiscal year that is 2 years 
prior to the fiscal year that is the subject of the rulemaking, because 
in general it is the most complete full fiscal year of claims data 
available at the time of development of the rule. Therefore, for FY 
2022 ratesetting, under ordinary circumstances, the best available 
claims data would be the FY 2020 MedPAR file. Similarly, the best 
available cost report data for LTCH PPS ratesetting is ordinarily from 
the HCRIS dataset containing cost reports beginning 3 years prior to 
the fiscal year that is the subject of the rulemaking, because in 
general it is the most complete full fiscal year of cost report data 
available at the time of development of the rule. Therefore, for FY 
2022 ratesetting, under ordinary circumstances, that would be the HCRIS 
dataset from FY 2019, which would primarily contain cost reports 
beginning during FY 2019 and ending during FY 2020, based on each 
LTCH's fiscal year. In the proposed rule, we discussed that the FY 2020 
MedPAR claims file and the FY 2019 HCRIS dataset, however, both contain 
data significantly impacted by the COVID-19 PHE, meaning primarily the 
utilization of LTCH services was

[[Page 45330]]

generally markedly different for certain types of services in FY 2020 
than would have been expected in the absence of the PHE. To determine 
whether these data are still the best available data for LTCH PPS 
ratesetting, we stated that it is important to evaluate whether these 
data would better approximate the FY 2022 LTCH experience than data 
from before the COVID-19 PHE.
    In section I.F. of the preamble of the FY 2022 IPPS/LTCH PPS 
proposed rule (86 FR 25087), we discussed our examination of COVID-19 
vaccination data from the CDC to help evaluate whether the FY 2020 data 
we ordinarily would use in ratesetting is appropriate for approximating 
the FY 2022 inpatient experience, including in LTCHs. The CDC data 
showed that as of April 15, the 7-day average number of administered 
vaccine doses reported to CDC per day was 3.3 million, a 10.3 percent 
increase from the previous week. As of April 15, 80 percent of people 
65 or older had received at least one dose of vaccine; 63.7 percent 
were fully vaccinated. Nearly one-half (48.3 percent) of people 18 or 
older had received at least one dose of vaccine; 30.3 percent were 
fully vaccinated. Nationally, COVID-19-related emergency department 
visits as well as both hospital admissions and current hospitalizations 
had risen among patients ages 18 to 64 years in recent weeks, but 
emergency department visits and hospitalizations among people ages 65 
years and older had decreased, likely demonstrating the important role 
vaccination plays in protecting against COVID-19.
    As indicated by the CDC, COVID-19 vaccines are effective at 
preventing COVID-19. For example, a CDC report on the effectiveness of 
the Pfizer-BioNTech and Moderna COVID-19 vaccines when administered in 
real-world conditions found that after being fully vaccinated with 
either of these vaccines a person's risk of infection is reduced by up 
to 90 percent. With respect to inpatient utilization in FY 2020, in the 
proposed rule we stated our belief that COVID-19 and the risk of 
disease were drivers of the different utilization patterns observed. 
Therefore, the continuing rapid increase in vaccinations coupled with 
the overall effectiveness of the vaccines led us to conclude based on 
the information available at the time of the proposed rule that there 
will be significantly lower risk of COVID-19 in FY 2022 and fewer 
hospitalizations for COVID-19 for Medicare beneficiaries in FY 2022 
than there were in FY 2020. We concluded that this trend called into 
question the applicability of inpatient hospital data from FY 2020 to 
the FY 2022 time period. We refer readers to section I.F. of the 
preamble of this final rule for the details on this analysis.
    In section I.F. of the preamble of the proposed rule, we also 
discussed CDC guidance to healthcare facilities during the COVID-19 PHE 
(see https://www.cdc.gov/coronavirus/2019-ncov/hcp/guidance-hcf.html). 
In its most recent guidance available at the time of the proposed rule, 
the CDC described how the COVID-19 pandemic has changed how health care 
is delivered in the United States, and has affected the operations of 
healthcare facilities. Effects cited by the CDC include increases in 
patients seeking care for respiratory illnesses, patients deferring and 
delaying non-COVID-19 care, disruptions in supply chains, fluctuations 
in facilities' occupancy, absenteeism among staff because of illness or 
caregiving responsibilities, and increases in mental health concerns.
    In the proposed rule, to investigate the effects cited by the CDC, 
we compared LTCH claims data from the FY 2020 MedPAR to the FY 2019 
MedPAR. Similar to the findings for IPPS claims data, we observed 
several of the changes cited by the CDC. Overall, in FY 2020 LTCH 
admissions of LTCH PPS standard Federal payment rate cases declined 13 
percent compared to FY 2019. However, LTCH PPS standard Federal payment 
rate cases for MS-LTC-DRG 177 (Respiratory infections and inflammations 
with MCC), one of the MS-LTC-DRGs most often associated with the 
treatment of COVID-19, increased by 47 percent. Its share of total LTCH 
PPS standard Federal payment rate cases increased from 2.0 percent in 
FY 2019 to 3.4 percent in FY 2020. We also calculated and compared the 
aggregate case-mix values for LTCH PPS standard Federal payment rate 
cases in FY 2019 and FY 2020. For FY 2019 we calculated a case-mix 
value of 1.257 and for FY 2020 we calculated a case-mix value of 1.283, 
a relatively large 1-year increase in total case-mix of 2.1 percent. We 
noted that these observed changes in the LTCH claims data also extend 
to the cost reports submitted by LTCHs that include the COVID-19 PHE 
time period, since those cost reports that extend into the COVID-19 PHE 
are based in part on the discharges that occurred during that time.
    After analyzing this issue, in the proposed rule we stated our 
belief that the utilization patterns reflected in the FY 2020 LTCH 
claims data were significantly altered by the COVID-19 PHE. We also 
stated our belief that data from before the COVID-19 PHE will better 
approximate the FY 2022 LTCH experience for the reasons discussed in 
section I.F. of the preamble of the proposed rule, including an 
increase in the number of individuals who are vaccinated against COVID-
19. Therefore, in the FY 2022 IPPS/LTCH PPS proposed rule (86 FR 
25537), we proposed to use the FY 2019 data for the FY 2022 LTCH PPS 
ratesetting in situations where the utilization patterns reflected in 
the FY 2020 data were significantly impacted by the COVID-19 PHE. For 
example, we proposed to use the FY 2019 MedPAR claims data and the FY 
2018 HCRIS file in situations where we ordinarily would have used the 
FY 2020 MedPAR and the FY 2019 HCRIS file, respectively.
    Comment: The vast majority of commenters were fully supportive of 
our proposal to use the FY 2019 data for the FY 2022 LTCH PPS 
ratesetting in situations where the utilization patterns reflected in 
the FY 2020 data were significantly impacted by the COVID 19 PHE. A 
commenter expressed concern that using FY 2019 cost information for 
establishing the proposed FY 2022 payment rates would lead to payment 
rates that do not appropriately account for additional costs that LTCHs 
had to absorb during the PHE and may continue to experience in future 
years.
    Response: We appreciate the commenters' support of our proposal to 
use the FY 2019 data for the FY 2022 LTCH PPS ratesetting in situations 
where the utilization patterns reflected in the FY 2020 data were 
significantly impacted by the COVID 19 PHE. In response to the 
commenter who expressed concerns with using FY 2019 cost information 
for establishing the proposed FY 2022 rates, we appreciate the 
feedback. However, we believe that the commenter may have 
misinterpreted what aspects of the FY 2022 ratesetting were impacted by 
our proposal to use FY 2019 data in situations where the utilization 
patterns reflected in the FY 2020 data were significantly impacted by 
the COVID 19 PHE. The mechanism that CMS uses to adjust the LTCH PPS 
standard Federal payment rate for input price inflation is the annual 
market basket update, determined by the Office of the Actuary (OACT). 
The market basket update values for FY 2022 and prior years were not 
impacted by our proposal to use FY 2019 data for FY 2022 ratesetting.
    Since the publication of the proposed rule, we have continued to 
monitor the vaccination and hospitalization data reported by the CDC 
(see https://www.cdc.gov/coronavirus/2019-ncov/covid-data/covidview/past-reports/07022021.html, accessed July 6, 2021).

[[Page 45331]]

As of July 1, 2021, 328.2 million vaccine doses have been administered. 
Overall, about 181.3 million people, or 54.6 percent of the U.S. 
population, have received at least one dose of vaccine as of this date. 
About 155.9 million people, or 47.0 percent of the U.S. population have 
been fully vaccinated. As of July 1, the 7-day average number of 
administered vaccine doses reported to CDC per day was 334,816, a 45.3 
percent decrease from the previous week. As of July 1, 88.2 percent of 
people 65 or older have received at least one dose of vaccine; 78.3 
percent are fully vaccinated. Two-thirds (66.7 percent) of people 18 or 
older have received at least one dose of vaccine; 57.7 percent are 
fully vaccinated. Nationally, the COVID-19-related 7-day moving average 
for new hospital admissions has been generally decreasing since 
publication of the proposed rule, demonstrating the important role 
vaccination is playing in protecting against COVID-19. As of July 3, 
2021 (the most recent date with data available at the time of writing), 
the 7-day moving average for new hospital admissions was 1,821, down 
significantly from the 7-day moving average peak of 16,492 recorded on 
January 9th, 2021 and the 7-day moving average of 5,075 recorded on 
April 27, 2021, the date the proposed rule was issued.\803\
---------------------------------------------------------------------------

    \803\ New Admissions of Patients with Confirmed COVID-19., 
available at https://covid.cdc.gov/covid-data-tracker-/#new-hospital-administrations (accessed July 3, 2021).
---------------------------------------------------------------------------

    In the proposed rule, we analyzed the large growth in real-case mix 
observed in the FY 2020 MedPAR claims data. This analysis was 
consistent with the observations in the CDC's guidance that COVID 19 
increased the number of patients seeking care for respiratory 
illnesses, and caused patients to defer and delay non-COVID-19 care. 
While we acknowledge that the rate of vaccination for the U.S. 
population has slowed considerably since we released the proposed rule, 
the total number of vaccines administered, especially for people 65 or 
older, along with the latest hospitalization trends, lead us to 
continue to believe that there will be a significantly lower risk of 
COVID-19 in FY 2022 and fewer hospitalizations for COVID-19 for 
Medicare beneficiaries in FY 2022 than there were in FY 2020. For these 
reasons, we continue to believe that FY 2020 is not the best overall 
approximation of the LTCH experience in FY 2022 and that FY 2019 as the 
most recent complete FY prior to the COVID-19 PHE is a better 
approximation of the FY 2022 LTCH experience.
    Therefore, after considering the comments received and evaluating 
the most recent vaccination and hospitalization data from the CDC, we 
are finalizing our proposal to use the FY 2019 data for the FY 2022 
LTCH PPS ratesetting in situations where the utilization patterns 
reflected in the FY 2020 data were significantly impacted by the COVID 
19 PHE. For example, we used the FY 2019 MedPAR claims data and the FY 
2018 HCRIS file in situations where we ordinarily would have used the 
FY 2020 MedPAR and the FY 2019 HCRIS file, respectively. This provision 
is consistent with the provision made for FY 2022 IPPS ratesetting in 
section I.F. of the preamble of this final rule, and we note that IPPS 
rates and factors are used in determining the IPPS comparable amount 
under the short-stay outlier (SSO) policy at Sec.  412.529 and the IPPS 
comparable amount under the site neutral payment rate at Sec.  412.522. 
We refer readers to section I.F. of the preamble of this final rule for 
further information on this provision.
    We note that we received several comments, many of which related to 
the ALOS requirement or requests for other potential revisions to the 
PPS, which were outside the scope of the proposed rule. We will keep 
these comments in mind for future rulemaking.

B. Medicare Severity Long-Term Care Diagnosis-Related Group (MS-LTC-
DRG) Classifications and Relative Weights for FY 2022

1. Background
    Section 123 of the BBRA required that the Secretary implement a PPS 
for LTCHs to replace the cost-based payment system under TEFRA. Section 
307(b)(1) of the BIPA modified the requirements of section 123 of the 
BBRA by requiring that the Secretary examine the feasibility and the 
impact of basing payment under the LTCH PPS on the use of existing (or 
refined) hospital DRGs that have been modified to account for different 
resource use of LTCH patients.
    When the LTCH PPS was implemented for cost reporting periods 
beginning on or after October 1, 2002, we adopted the same DRG patient 
classification system utilized at that time under the IPPS. As a 
component of the LTCH PPS, we refer to this patient classification 
system as the ``long-term care diagnosis-related groups (LTC-DRGs).'' 
Although the patient classification system used under both the LTCH PPS 
and the IPPS are the same, the relative weights are different. The 
established relative weight methodology and data used under the LTCH 
PPS result in relative weights under the LTCH PPS that reflect the 
differences in patient resource use of LTCH patients, consistent with 
section 123(a)(1) of the BBRA (Pub. L. 106-113).
    As part of our efforts to better recognize severity of illness 
among patients, in the FY 2008 IPPS final rule with comment period (72 
FR 47130), the MS-DRGs and the Medicare severity long-term care 
diagnosis-related groups (MS-LTC-DRGs) were adopted under the IPPS and 
the LTCH PPS, respectively, effective beginning October 1, 2007 (FY 
2008). For a full description of the development, implementation, and 
rationale for the use of the MS-DRGs and MS-LTC-DRGs, we refer readers 
to the FY 2008 IPPS final rule with comment period (72 FR 47141 through 
47175 and 47277 through 47299). (We note that, in that same final rule, 
we revised the regulations at Sec.  412.503 to specify that for LTCH 
discharges occurring on or after October 1, 2007, when applying the 
provisions of 42 CFR part 412, subpart O applicable to LTCHs for policy 
descriptions and payment calculations, all references to LTC-DRGs would 
be considered a reference to MS-LTC-DRGs. For the remainder of this 
section, we present the discussion in terms of the current MS-LTC-DRG 
patient classification system unless specifically referring to the 
previous LTC-DRG patient classification system that was in effect 
before October 1, 2007.)
    The MS-DRGs adopted in FY 2008 represent an increase in the number 
of DRGs by 207 (that is, from 538 to 745) (72 FR 47171). The MS-DRG 
classifications are updated annually. For FY 2022, there will be 767 
MS-DRG groupings based on the changes, as discussed in section II.E. of 
the preamble of the final rule. Consistent with section 123 of the 
BBRA, as amended by section 307(b)(1) of the BIPA, and Sec.  412.515 of 
the regulations, we use information derived from LTCH PPS patient 
records to classify LTCH discharges into distinct MS-LTC-DRGs based on 
clinical characteristics and estimated resource needs. Then we assign 
an appropriate weight to the MS-LTC-DRGs to account for the difference 
in resource use by patients exhibiting the case complexity and multiple 
medical problems characteristic of LTCHs.
    In this section of this final rule, we provide a general summary of 
our existing methodology for determining the FY 2022 MS-LTC-DRG 
relative weights under the LTCH PPS.

[[Page 45332]]

    As we proposed in the FY 2022 IPPS/LTCH PPS proposed rule (86 FR 
25538), in general, for FY 2022, we are continuing to use our existing 
methodology to determine the MS-LTC-DRG relative weights (as discussed 
in greater detail in section VII.B.3. of the preamble of this final 
rule). As we established when we implemented the dual rate LTCH PPS 
payment structure codified under Sec.  412.522, which began in FY 2016, 
as we proposed, the annual recalibration of the MS-LTC-DRG relative 
weights are determined: (1) Using only data from available LTCH PPS 
claims that would have qualified for payment under the new LTCH PPS 
standard Federal payment rate if that rate had been in effect at the 
time of discharge when claims data from time periods before the dual 
rate LTCH PPS payment structure applies are used to calculate the 
relative weights; and (2) using only data from available LTCH PPS 
claims that qualify for payment under the new LTCH PPS standard Federal 
payment rate when claims data from time periods after the dual rate 
LTCH PPS payment structure applies are used to calculate the relative 
weights (80 FR 49624). That is, under our current methodology, our MS-
LTC-DRG relative weight calculations do not use data from cases paid at 
the site neutral payment rate under Sec.  412.522(c)(1) or data from 
cases that would have been paid at the site neutral payment rate if the 
dual rate LTCH PPS payment structure had been in effect at the time of 
that discharge. For the remainder of this discussion, we use the phrase 
``applicable LTCH cases'' or ``applicable LTCH data'' when referring to 
the resulting claims data set used to calculate the relative weights 
(as described in greater detail in section VII.B.3.c. of the preamble 
of this final rule). In addition, for FY 2022, as we proposed, we are 
continuing to exclude the data from all-inclusive rate providers and 
LTCHs paid in accordance with demonstration projects, as well as any 
Medicare Advantage claims from the MS-LTC-DRG relative weight 
calculations for the reasons discussed in section VII.B.3.c. of the 
preamble of this final rule.
    Furthermore, for FY 2022, in using data from applicable LTCH cases 
to establish MS-LTC-DRG relative weights, as we proposed, we are 
continuing to establish low-volume MS-LTC-DRGs (that is, MS-LTC-DRGs 
with less than 25 cases) using our quintile methodology in determining 
the MS-LTC-DRG relative weights because LTCHs do not typically treat 
the full range of diagnoses as do acute care hospitals. Therefore, for 
purposes of determining the relative weights for the large number of 
low-volume MS-LTC-DRGs, we grouped all of the low-volume MS-LTC-DRGs 
into five quintiles based on average charges per discharge. Then, under 
our existing methodology, we accounted for adjustments made to LTCH PPS 
standard Federal payments for short-stay outlier (SSO) cases (that is, 
cases where the covered length of stay at the LTCH is less than or 
equal to five-sixths of the geometric average length of stay for the 
MS-LTC-DRG), and we made adjustments to account for nonmonotonically 
increasing weights, when necessary. The methodology is premised on more 
severe cases under the MS-LTC-DRG system requiring greater expenditure 
of medical care resources and higher average charges such that, in the 
severity levels within a base MS-LTC-DRG, the relative weights should 
increase monotonically with severity from the lowest to highest 
severity level. (We discuss each of these components of our MS-LTC-DRG 
relative weight methodology in greater detail in section VII.B.3.g. of 
the preamble of this final rule.)
2. Patient Classifications Into MS-LTC-DRGs
a. Background
    The MS-DRGs (used under the IPPS) and the MS-LTC-DRGs (used under 
the LTCH PPS) are based on the CMS DRG structure. As noted previously 
in this section, we refer to the DRGs under the LTCH PPS as MS-LTC-DRGs 
although they are structurally identical to the MS-DRGs used under the 
IPPS.
    The MS-DRGs are organized into 25 major diagnostic categories 
(MDCs), most of which are based on a particular organ system of the 
body; the remainder involve multiple organ systems (such as MDC 22, 
Burns). Within most MDCs, cases are then divided into surgical DRGs and 
medical DRGs. Surgical DRGs are assigned based on a surgical hierarchy 
that orders operating room (O.R.) procedures or groups of O.R. 
procedures by resource intensity. The GROUPER software program does not 
recognize all ICD-10-PCS procedure codes as procedures affecting DRG 
assignment. That is, procedures that are not surgical (for example, 
EKGs), or minor surgical procedures (for example, a biopsy of skin and 
subcutaneous tissue (procedure code 0JBH3ZX)) do not affect the MS-LTC-
DRG assignment based on their presence on the claim.
    Generally, under the LTCH PPS, a Medicare payment is made at a 
predetermined specific rate for each discharge that varies based on the 
MS-LTC-DRG to which a beneficiary's discharge is assigned. Cases are 
classified into MS-LTC-DRGs for payment based on the following six data 
elements:
     Principal diagnosis.
     Additional or secondary diagnoses.
     Surgical procedures.
     Age.
     Sex.
     Discharge status of the patient.
    Currently, for claims submitted using version ASC X12 5010 format, 
up to 25 diagnosis codes and 25 procedure codes are considered for an 
MS-DRG assignment. This includes one principal diagnosis and up to 24 
secondary diagnoses for severity of illness determinations. (For 
additional information on the processing of up to 25 diagnosis codes 
and 25 procedure codes on hospital inpatient claims, we refer readers 
to section II.G.11.c. of the preamble of the FY 2011 IPPS/LTCH PPS 
final rule (75 FR 50127).)
    Under the HIPAA transactions and code sets regulations at 45 CFR 
parts 160 and 162, covered entities must comply with the adopted 
transaction standards and operating rules specified in subparts I 
through S of part 162. Among other requirements, on or after January 1, 
2012, covered entities were required to use the ASC X12 Standards for 
Electronic Data Interchange Technical Report Type 3--Health Care Claim: 
Institutional (837), May 2006, ASC X12N/005010X223, and Type 1 Errata 
to Health Care Claim: Institutional (837) ASC X12 Standards for 
Electronic Data Interchange Technical Report Type 3, October 2007, ASC 
X12N/005010X233A1 for the health care claims or equivalent encounter 
information transaction (45 CFR 162.1102(c)).
    HIPAA requires covered entities to use the applicable medical data 
code set requirements when conducting HIPAA transactions (45 CFR 
162.1000). Currently, upon the discharge of the patient, the LTCH must 
assign appropriate diagnosis and procedure codes from the most current 
version of the International Classification of Diseases, 10th Revision, 
Clinical Modification (ICD-10-CM) for diagnosis coding and the 
International Classification of Diseases, 10th Revision, Procedure 
Coding System (ICD-10-PCS) for inpatient hospital procedure coding, 
both of which were required to be implemented October 1, 2015 (45 CFR 
162.1002(c)(2) and (3)). For additional information on the 
implementation of the ICD-10 coding system, we refer readers to section 
II.F.1. of the preamble of the FY 2017 IPPS/LTCH PPS final rule (81 FR 
56787

[[Page 45333]]

through 56790) and section II.E.1. of the preamble of this final rule. 
Additional coding instructions and examples are published in the AHA's 
Coding Clinic for ICD-10-CM/PCS.
    To create the MS-DRGs (and by extension, the MS-LTC-DRGs), base 
DRGs were subdivided according to the presence of specific secondary 
diagnoses designated as complications or comorbidities (CCs) into one, 
two, or three levels of severity, depending on the impact of the CCs on 
resources used for those cases. Specifically, there are sets of MS-DRGs 
that are split into 2 or 3 subgroups based on the presence or absence 
of a CC or a major complication or comorbidity (MCC). We refer readers 
to section II.D. of the preamble of the FY 2008 IPPS final rule with 
comment period for a detailed discussion about the creation of MS-DRGs 
based on severity of illness levels (72 FR 47141 through 47175).
    MACs enter the clinical and demographic information submitted by 
LTCHs into their claims processing systems and subject this information 
to a series of automated screening processes called the Medicare Code 
Editor (MCE). These screens are designed to identify cases that require 
further review before assignment into a MS-LTC-DRG can be made. During 
this process, certain cases are selected for further explanation (74 FR 
43949).
    After screening through the MCE, each claim is classified into the 
appropriate MS-LTC-DRG by the Medicare LTCH GROUPER software on the 
basis of diagnosis and procedure codes and other demographic 
information (age, sex, and discharge status). The GROUPER software used 
under the LTCH PPS is the same GROUPER software program used under the 
IPPS. Following the MS-LTC-DRG assignment, the MAC determines the 
prospective payment amount by using the Medicare PRICER program, which 
accounts for hospital-specific adjustments. Under the LTCH PPS, we 
provide an opportunity for LTCHs to review the MS-LTC-DRG assignments 
made by the MAC and to submit additional information within a specified 
timeframe as provided in Sec.  412.513(c).
    The GROUPER software is used both to classify past cases to measure 
relative hospital resource consumption to establish the MS-LTC-DRG 
relative weights and to classify current cases for purposes of 
determining payment. The records for all Medicare hospital inpatient 
discharges are maintained in the MedPAR file. The data in this file are 
used to evaluate possible MS-DRG and MS-LTC-DRG classification changes 
and to recalibrate the MS-DRG and MS-LTC-DRG relative weights during 
our annual update under both the IPPS (Sec.  412.60(e)) and the LTCH 
PPS (Sec.  412.517), respectively.
b. Changes to the MS-LTC-DRGs for FY 2022
    As specified by our regulations at Sec.  412.517(a), which require 
that the MS-LTC-DRG classifications and relative weights be updated 
annually, and consistent with our historical practice of using the same 
patient classification system under the LTCH PPS as is used under the 
IPPS, in this final rule, as we proposed, we updated the MS-LTC-DRG 
classifications effective October 1, 2021 through September 30, 2022 
(FY 2022), consistent with the changes to specific MS-DRG 
classifications presented in section II.F. of the preamble of this 
final rule. Accordingly, the MS-LTC-DRGs for FY 2022 presented in 
section II.F. of the preamble of this final rule are the same as the 
MS-DRGs that are being used under the IPPS for FY 2022. In addition, 
because the MS-LTC-DRGs for FY 2022 are the same as the MS-DRGs for FY 
2022, the other changes that affect MS-DRG (and by extension MS-LTC-
DRG) assignments under GROUPER Version 39 as discussed in section II.E. 
of the preamble of this final rule, including the changes to the MCE 
software and the ICD-10-CM/PCS coding system, also are applicable under 
the LTCH PPS for FY 2022.
3. Development of the FY 2022 MS-LTC-DRG Relative Weights
a. General Overview of the Development of the MS-LTC-DRG Relative 
Weights
    One of the primary goals for the implementation of the LTCH PPS is 
to pay each LTCH an appropriate amount for the efficient delivery of 
medical care to Medicare patients. The system must be able to account 
adequately for each LTCH's case-mix in order to ensure both fair 
distribution of Medicare payments and access to adequate care for those 
Medicare patients whose care is costlier (67 FR 55984). To accomplish 
these goals, we have annually adjusted the LTCH PPS standard Federal 
prospective payment rate by the applicable relative weight in 
determining payment to LTCHs for each case. In order to make these 
annual adjustments under the dual rate LTCH PPS payment structure, 
beginning with FY 2016, we recalibrate the MS-LTC-DRG relative 
weighting factors annually using data from applicable LTCH cases (80 FR 
49614 through 49617). Under this policy, the resulting MS-LTC-DRG 
relative weights would continue to be used to adjust the LTCH PPS 
standard Federal payment rate when calculating the payment for LTCH PPS 
standard Federal payment rate cases.
    The established methodology to develop the MS-LTC-DRG relative 
weights is generally consistent with the methodology established when 
the LTCH PPS was implemented in the August 30, 2002 LTCH PPS final rule 
(67 FR 55989 through 55991). However, there have been some 
modifications of our historical procedures for assigning relative 
weights in cases of zero volume and/or nonmonotonicity resulting from 
the adoption of the MS-LTC-DRGs, along with the change made in 
conjunction with the implementation of the dual rate LTCH PPS payment 
structure beginning in FY 2016 to use LTCH claims data from only LTCH 
PPS standard Federal payment rate cases (or LTCH PPS cases that would 
have qualified for payment under the LTCH PPS standard Federal payment 
rate if the dual rate LTCH PPS payment structure had been in effect at 
the time of the discharge). (For details on the modifications to our 
historical procedures for assigning relative weights in cases of zero 
volume and/or nonmonotonicity, we refer readers to the FY 2008 IPPS 
final rule with comment period (72 FR 47289 through 47295) and the FY 
2009 IPPS final rule (73 FR 48542 through 48550).) For details on the 
change in our historical methodology to use LTCH claims data only from 
LTCH PPS standard Federal payment rate cases (or cases that would have 
qualified for such payment had the LTCH PPS dual payment rate structure 
been in effect at the time) to determine the MS-LTC-DRG relative 
weights, we refer readers to the FY 2016 IPPS/LTCH PPS final rule (80 
FR 49614 through 49617). Under the LTCH PPS, relative weights for each 
MS-LTC-DRG are a primary element used to account for the variations in 
cost per discharge and resource utilization among the payment groups 
(Sec.  412.515). To ensure that Medicare patients classified to each 
MS-LTC-DRG have access to an appropriate level of services and to 
encourage efficiency, we calculate a relative weight for each MS-LTC-
DRG that represents the resources needed by an average inpatient LTCH 
case in that MS-LTC-DRG. For example, cases in an MS-LTC-DRG with a 
relative weight of 2 would, on average, cost twice as much to treat as 
cases in an MS-LTC-DRG with a relative weight of 1.

[[Page 45334]]

b. Development of the MS-LTC-DRG Relative Weights for FY 2022
    In this final rule, as we proposed in the FY 2022 IPPS/LTCH PPS 
proposed rule (86 FR 25540), we are continuing to use our current 
methodology to determine the MS-LTC-DRG relative weights for FY 2022, 
including the continued application of established policies related to: 
The hospital-specific relative value methodology, the treatment of 
severity levels in the MS-LTC-DRGs, low-volume and no-volume MS-LTC-
DRGs, adjustments for nonmonotonicity, the steps for calculating the 
MS-LTC-DRG relative weights with a budget neutrality factor, and only 
using data from applicable LTCH cases (which includes our policy of 
only using cases that would meet the criteria for exclusion from the 
site neutral payment rate (or, for discharges occurring prior to the 
implementation of the dual rate LTCH PPS payment structure, would have 
met the criteria for exclusion had those criteria been in effect at the 
time of the discharge)).
    In this section, we present our application of our existing 
methodology for determining the MS-LTC-DRG relative weights for FY 
2022, and we discuss the effects of our policies concerning the data 
used to determine the FY 2022 MS-LTC-DRG relative weights on the 
various components of our existing methodology in the discussion that 
follows.
    We generally provide the low-volume quintiles and no-volume 
crosswalk data previously published in Tables 13A and 13B for each 
annual proposed and final rule as one of our supplemental IPPS/LTCH PPS 
related data files that are made available for public use via the 
internet on the CMS website for the respective rule and fiscal year 
(that is, FY 2019 and subsequent fiscal years) at: http://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/AcuteInpatientPPS/index.html 
to streamline the information made available to the public that is used 
in the annual development of IPPS Table 11 and to make it easier for 
the public to navigate and find the relevant data and information used 
for the development of proposed and final payment rates or factors for 
the applicable payment year while continuing to furnish the same 
information the tables provided in previous fiscal years (83 FR 41522). 
We refer readers to the CMS website for the low-volume quintiles and 
no-volume crosswalk data previously furnished via Tables 13A and 13B.
c. Data
    Ordinarily, for this FY 2022 final rule, we would use FY 2020 
Medicare LTCH claims data for purposes of calculating the MS-LTC-DRG 
relative weights for FY 2022. As discussed in section VIII.A.4. of the 
preamble of this final rule, we believe the utilization patterns 
reflected in the FY 2020 LTCH claims data were significantly impacted 
by the COVID-19 PHE. Therefore, for the purposes of calculating the MS-
LTC-DRG relative weights for FY 2022, as we proposed in the FY 2022 
IPPS/LTCH PPS proposed rule (86 FR 25540), we used FY 2019 Medicare 
LTCH claims data from the March 2020 update of the FY 2019 MedPAR file, 
which we believe are the best available data at this time for the 
reasons discussed in section VIII.A.4. of the preamble of this final 
rule. Specifically, for this FY 2022 IPPS/LTCH PPS final rule, as we 
proposed, we obtained total charges from FY 2019 Medicare LTCH claims 
data from the March 2020 update of the FY 2019 MedPAR file and used 
Version 39 of the GROUPER to classify LTCH cases.
    To calculate the FY 2022 MS-LTC-DRG relative weights under the dual 
rate LTCH PPS payment structure, as we proposed, we continued to use 
applicable LTCH data, which includes our policy of only using cases 
that meet the criteria for exclusion from the site neutral payment rate 
(or would have met the criteria had they been in effect at the time of 
the discharge) (80 FR 49624). Specifically, we began by first 
evaluating the LTCH claims data in the March 2020 update of the FY 2019 
MedPAR file to determine which LTCH cases would meet the criteria for 
exclusion from the site neutral payment rate under Sec.  412.522(b) or 
had the dual rate LTCH PPS payment structure applied to those cases at 
the time of discharge. We identified the FY 2019 LTCH cases that were 
not assigned to MS-LTC-DRGs 876, 880, 881, 882, 883, 884, 885, 886, 
887, 894, 895, 896, 897, 945, and 946, which identify LTCH cases that 
do not have a principal diagnosis relating to a psychiatric diagnosis 
or to rehabilitation; and that either--
     The admission to the LTCH was ``immediately preceded'' by 
discharge from a subsection (d) hospital and the immediately preceding 
stay in that subsection (d) hospital included at least 3 days in an 
ICU, as we define under the ICU criterion; or
     The admission to the LTCH was ``immediately preceded'' by 
discharge from a subsection (d) hospital and the claim for the LTCH 
discharge includes the applicable procedure code that indicates at 
least 96 hours of ventilator services were provided during the LTCH 
stay, as we define under the ventilator criterion. Claims data from the 
FY 2019 MedPAR file that reported ICD-10-PCS procedure code 5A1955Z 
were used to identify cases involving at least 96 hours of ventilator 
services in accordance with the ventilator criterion. (We note that, 
for purposes of developing the MS-LTC-DRG relative weights we have 
previously addressed the treatment of cases that would have been 
excluded from the site neutral payment rate under the statutory 
provisions that provided for temporary exception from the site neutral 
payment rate under the LTCH PPS for certain spinal cord specialty 
hospitals or for certain severe wound care discharges from certain 
LTCHs provided by sections 15009 and 15010 of Public Law 114-255, 
respectively. The temporary exception from the site neutral payment 
rate for certain spinal cord specialty hospitals is effective for 
discharges in cost reporting periods beginning during FYs 2018 and 
2019, and the temporary exception from the site neutral payment rate 
for certain severe wound care discharges from certain LTCHs was 
effective for a discharge in cost reporting period beginning during FY 
2018. These statutory provisions will no longer be in effect for any 
discharges occurring in FY 2022. Therefore, consistent with our 
historical policy of only using cases that meet the criteria for 
exclusion from the site neutral payment rate, we excluded these cases 
in our development of the MS-LTC-DRG relative weights for FY 2022.)
    Furthermore, consistent with our historical methodology, we 
excluded any claims in the resulting data set that were submitted by 
LTCHs that were all-inclusive rate providers and LTCHs that are paid in 
accordance with demonstration projects authorized under section 402(a) 
of Public Law 90-248 or section 222(a) of Public Law 92-603. In 
addition, consistent with our historical practice and our policies, we 
excluded any Medicare Advantage (Part C) claims in the resulting data. 
Such claims were identified based on the presence of a GHO Paid 
indicator value of ``1'' in the MedPAR files. The claims that remained 
after these three trims (that is, the applicable LTCH data) were then 
used to calculate the MS-LTC-DRG relative weights for FY 2022
    In summary, in general, we identified the claims data used in the 
development of the FY 2022 MS-LTC-DRG relative weights in this final 
rule, as we proposed, by trimming claims data that were paid the site 
neutral payment rate or would have been paid the site neutral

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payment rate had the dual payment rate structure been in effect. 
Finally, as we proposed, we trimmed the claims data of all-inclusive 
rate providers reported in the March 2020 update of the FY 2019 MedPAR 
file and any Medicare Advantage claims data. There were no data from 
any LTCHs that are paid in accordance with a demonstration project 
reported in the March 2020 update of the FY 2019 MedPAR file, but, had 
there been any, we would have trimmed the claims data from those LTCHs 
as well, in accordance with our established policy. As we proposed, we 
used the remaining data (that is, the applicable LTCH data) to 
calculate the relative weights for FY 2022.
d. Hospital-Specific Relative Value (HSRV) Methodology
    By nature, LTCHs often specialize in certain areas, such as 
ventilator-dependent patients. Some case types (MS-LTC-DRGs) may be 
treated, to a large extent, in hospitals that have, from a perspective 
of charges, relatively high (or low) charges. This nonrandom 
distribution of cases with relatively high (or low) charges in specific 
MS-LTC-DRGs has the potential to inappropriately distort the measure of 
average charges. To account for the fact that cases may not be randomly 
distributed across LTCHs, consistent with the methodology we have used 
since the implementation of the LTCH PPS, in this FY 2022 IPPS/LTCH PPS 
final rule, as we proposed in the FY 2022 IPPS/LTCH PPS proposed rule 
(86 FR 25541), we continued to use a hospital-specific relative value 
(HSRV) methodology to calculate the MS-LTC-DRG relative weights for FY 
2022. We believe that this method removes this hospital-specific source 
of bias in measuring LTCH average charges (67 FR 55985). Specifically, 
under this methodology, we reduced the impact of the variation in 
charges across providers on any particular MS-LTC-DRG relative weight 
by converting each LTCH's charge for an applicable LTCH case to a 
relative value based on that LTCH's average charge for such cases.
    Under the HSRV methodology, we standardize charges for each LTCH by 
converting its charges for each applicable LTCH case to hospital-
specific relative charge values and then adjusting those values for the 
LTCH's case-mix. The adjustment for case-mix is needed to rescale the 
hospital-specific relative charge values (which, by definition, average 
1.0 for each LTCH). The average relative weight for an LTCH is its 
case-mix; therefore, it is reasonable to scale each LTCH's average 
relative charge value by its case-mix. In this way, each LTCH's 
relative charge value is adjusted by its case-mix to an average that 
reflects the complexity of the applicable LTCH cases it treats relative 
to the complexity of the applicable LTCH cases treated by all other 
LTCHs (the average LTCH PPS case-mix of all applicable LTCH cases 
across all LTCHs).
    In accordance with our established methodology, for FY 2022, as we 
proposed, we continued to standardize charges for each applicable LTCH 
case by first dividing the adjusted charge for the case (adjusted for 
SSOs under Sec.  412.529 as described in section VII.B.3.g. (Step 3) of 
the preamble of this final rule) by the average adjusted charge for all 
applicable LTCH cases at the LTCH in which the case was treated. SSO 
cases are cases with a length of stay that is less than or equal to 
five-sixths the average length of stay of the MS-LTC-DRG (Sec. Sec.  
412.529 and 412.503). The average adjusted charge reflects the average 
intensity of the health care services delivered by a particular LTCH 
and the average cost level of that LTCH. The resulting ratio was 
multiplied by that LTCH's case-mix index to determine the standardized 
charge for the case.
    Multiplying the resulting ratio by the LTCH's case-mix index 
accounts for the fact that the same relative charges are given greater 
weight at an LTCH with higher average costs than they would at an LTCH 
with low average costs, which is needed to adjust each LTCH's relative 
charge value to reflect its case-mix relative to the average case-mix 
for all LTCHs. By standardizing charges in this manner, we count 
charges for a Medicare patient at an LTCH with high average charges as 
less resource intensive than they would be at an LTCH with low average 
charges. For example, a $10,000 charge for a case at an LTCH with an 
average adjusted charge of $17,500 reflects a higher level of relative 
resource use than a $10,000 charge for a case at an LTCH with the same 
case-mix, but an average adjusted charge of $35,000. We believe that 
the adjusted charge of an individual case more accurately reflects 
actual resource use for an individual LTCH because the variation in 
charges due to systematic differences in the markup of charges among 
LTCHs is taken into account.
e. Treatment of Severity Levels in Developing the MS-LTC-DRG Relative 
Weights
    For purposes of determining the MS-LTC-DRG relative weights, under 
our historical methodology, there are three different categories of MS-
DRGs based on volume of cases within specific MS-LTC-DRGs: (1) MS-LTC-
DRGs with at least 25 applicable LTCH cases in the data used to 
calculate the relative weight, which are each assigned a unique 
relative weight; (2) low-volume MS-LTC-DRGs (that is, MS-LTC-DRGs that 
contain between 1 and 24 applicable LTCH cases that are grouped into 
quintiles (as described later in this section of this final rule) and 
assigned the relative weight of the quintile); and (3) no-volume MS-
LTC-DRGs that are cross-walked to other MS-LTC-DRGs based on the 
clinical similarities and assigned the relative weight of the cross-
walked MS-LTC-DRG (as described in greater detail in this final rule). 
For FY 2022, as we proposed in the FY 2022 IPPS/LTCH PPS proposed rule 
(86 FR 25542), we are continuing to use applicable LTCH cases to 
establish the same volume-based categories to calculate the FY 2022 MS-
LTC-DRG relative weights.
    In determining the FY 2022 MS-LTC-DRG relative weights, when 
necessary, as is our longstanding practice, as we proposed, we made 
adjustments to account for nonmonotonicity, as discussed in greater 
detail in Step 6 of section VII.B.3.g. of the preamble of this final 
rule. We refer readers to the discussion in the FY 2010 IPPS/RY 2010 
LTCH PPS final rule for our rationale for including an adjustment for 
nonmonotonicity (74 FR 43953 through 43954).
f. Low-Volume MS-LTC-DRGs
    In order to account for MS-LTC-DRGs with low-volume (that is, with 
fewer than 25 applicable LTCH cases), consistent with our existing 
methodology, as we proposed in the FY 2022 IPPS/LTCH PPS proposed rule 
(86 FR 25542), we are continuing to employ the quintile methodology for 
low-volume MS-LTC-DRGs, such that we grouped the ``low-volume MS-LTC-
DRGs'' (that is, MS-LTC-DRGs that contain between 1 and 24 applicable 
LTCH cases into one of five categories (quintiles) based on average 
charges (67 FR 55984 through 55995; 72 FR 47283 through 47288; and 81 
FR 25148).) In cases where the initial assignment of a low-volume MS-
LTC-DRG to a quintile results in nonmonotonicity within a base-DRG, as 
we proposed, we made adjustments to the resulting low-volume MS-LTC-
DRGs to preserve monotonicity, as discussed in detail in section 
VII.B.3.g. (Step 6) of the preamble of this final rule.
    In this final rule, based on the best available data (that is, the 
March 2020 update of the FY 2019 MedPAR files), we identified 251 MS-
LTC-DRGs that contained between 1 and 24 applicable

[[Page 45336]]

LTCH cases. This list of MS-LTC-DRGs was then divided into 1 of the 5 
low-volume quintiles, each containing at least 50 MS-LTC-DRGs (251/5 = 
50 with a remainder of 1). We assigned the low-volume MS-LTC-DRGs to 
specific low-volume quintiles by sorting the low-volume MS-LTC-DRGs in 
ascending order by average charge in accordance with our established 
methodology. Based on the data available for this final rule, the 
number of MS-LTC-DRGs with less than 25 applicable LTCH cases was not 
evenly divisible by 5 and, therefore, as we proposed, we employed our 
historical methodology for determining which of the low-volume 
quintiles would contain the additional low-volume MS-LTC-DRG. 
Specifically for this final rule, because the average charge of the 
51st low-volume MS-LTC-DRG in the sorted list was closer to the average 
charge of the 50th low-volume MS-LTC-DRG (assigned to Quintile 1) than 
to the average charge of the 52nd low-volume MS-LTC-DRG (assigned to 
Quintile 2), we assigned it to Quintile 1 (such that Quintile 1 
contains 51 low-volume MS-LTC-DRGs before any adjustments for 
nonmonotonicity, as discussed in this final rule). This resulted in 4 
of the 5 low-volume quintiles containing 50 MS-LTC-DRGs (Quintiles 2, 
3, 4, and 5) and 1 of the low-volume quintiles containing 51 MS-LTC-
DRGs (Quintile 1). As discussed earlier, for this final rule, we are 
providing the list of the composition of the low-volume quintiles for 
low-volume MS-LTC-DRGs for FY 2022 in a supplemental data file for 
public use posted via the internet on the CMS website for this final 
rule at: http://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/AcuteInpatientPPS/index.html in order to streamline the information 
made available to the public that is used in the annual development of 
Table 11.
    In order to determine the FY 2022 relative weights for the low-
volume MS-LTC-DRGs, consistent with our historical practice, as we 
proposed, we used the five low-volume quintiles described previously. 
We determined a relative weight and (geometric) average length of stay 
for each of the five low-volume quintiles using the methodology 
described in section VII.B.3.g. of the preamble of this final rule. We 
assigned the same relative weight and average length of stay to each of 
the low-volume MS-LTC-DRGs that make up an individual low-volume 
quintile. We note that, as this system is dynamic, it is possible that 
the number and specific type of MS-LTC-DRGs with a low-volume of 
applicable LTCH cases will vary in the future. Furthermore, we note 
that we continue to monitor the volume (that is, the number of 
applicable LTCH cases) in the low-volume quintiles to ensure that our 
quintile assignments used in determining the MS-LTC-DRG relative 
weights result in appropriate payment for LTCH cases grouped to low-
volume MS-LTC-DRGs and do not result in an unintended financial 
incentive for LTCHs to inappropriately admit these types of cases.
g. Steps for Determining the FY 2022 MS-LTC-DRG Relative Weights
    In this final rule, as we proposed in the FY 2022 IPPS/LTCH PPS 
proposed rule (86 FR 25542), we are continuing to use our current 
methodology to determine the FY 2022 MS-LTC-DRG relative weights.
    In summary, to determine the FY 2022 MS-LTC-DRG relative weights, 
as we proposed, we grouped applicable LTCH cases to the appropriate MS-
LTC-DRG, while taking into account the low-volume quintiles (as 
described previously) and cross-walked no-volume MS-LTC-DRGs (as 
described later in this section). After establishing the appropriate 
MS-LTC-DRG (or low-volume quintile), as we proposed, we calculated the 
FY 2022 relative weights by first removing cases with a length of stay 
of 7 days or less and statistical outliers (Steps 1 and 2). Next, as we 
proposed, we adjusted the number of applicable LTCH cases in each MS-
LTC-DRG (or low-volume quintile) for the effect of SSO cases (Step 3). 
After removing applicable LTCH cases with a length of stay of 7 days or 
less (Step 1) and statistical outliers (Step 2), which are the SSO-
adjusted applicable LTCH cases and corresponding charges (Step 3), as 
we proposed, we calculated ``relative adjusted weights'' for each MS-
LTC-DRG (or low-volume quintile) using the HSRV method.
    Step 1--Remove cases with a length of stay of 7 days or less.
    The first step in our calculation of the FY 2022 MS-LTC-DRG 
relative weights is to remove cases with a length of stay of 7 days or 
less. The MS-LTC-DRG relative weights reflect the average of resources 
used on representative cases of a specific type. Generally, cases with 
a length of stay of 7 days or less do not belong in an LTCH because 
these stays do not fully receive or benefit from treatment that is 
typical in an LTCH stay, and full resources are often not used in the 
earlier stages of admission to an LTCH. If we were to include stays of 
7 days or less in the computation of the FY 2022 MS-LTC-DRG relative 
weights, the value of many relative weights would decrease and, 
therefore, payments would decrease to a level that may no longer be 
appropriate. We do not believe that it would be appropriate to 
compromise the integrity of the payment determination for those LTCH 
cases that actually benefit from and receive a full course of treatment 
at an LTCH by including data from these very short stays. Therefore, 
consistent with our existing relative weight methodology, in 
determining the FY 2022 MS-LTC-DRG relative weights, as we proposed, we 
removed LTCH cases with a length of stay of 7 days or less from 
applicable LTCH cases. (For additional information on what is removed 
in this step of the relative weight methodology, we refer readers to 67 
FR 55989 and 74 FR 43959.)
    Step 2--Remove statistical outliers.
    The next step in our calculation of the FY 2022 MS-LTC-DRG relative 
weights is to remove statistical outlier cases from the LTCH cases with 
a length of stay of at least 8 days. Consistent with our existing 
relative weight methodology, as we proposed, we continued to define 
statistical outliers as cases that are outside of 3.0 standard 
deviations from the mean of the log distribution of both charges per 
case and the charges per day for each MS-LTC-DRG. These statistical 
outliers are removed prior to calculating the relative weights because 
we believe that they may represent aberrations in the data that distort 
the measure of average resource use. Including those LTCH cases in the 
calculation of the relative weights could result in an inaccurate 
relative weight that does not truly reflect relative resource use among 
those MS-LTC-DRGs. (For additional information on what is removed in 
this step of the relative weight methodology, we refer readers to 67 FR 
55989 and 74 FR 43959.) After removing cases with a length of stay of 7 
days or less and statistical outliers, we were left with applicable 
LTCH cases that have a length of stay greater than or equal to 8 days. 
In this final rule, we refer to these cases as ``trimmed applicable 
LTCH cases.''
    Step 3--Adjust charges for the effects of SSOs.
    As the next step in the calculation of the FY 2022 MS-LTC-DRG 
relative weights, consistent with our historical approach, as we 
proposed, we adjusted each LTCH's charges per discharge for those 
remaining cases (that is, trimmed applicable LTCH cases) for the 
effects of SSOs (as defined in Sec.  412.529(a) in conjunction with 
Sec.  412.503). Specifically, as we proposed, we made this adjustment 
by counting an SSO case as a fraction of a discharge based on the ratio 
of the length of stay of the

[[Page 45337]]

case to the average length of stay of all cases grouped to the MS-LTC-
DRG. This has the effect of proportionately reducing the impact of the 
lower charges for the SSO cases in calculating the average charge for 
the MS-LTC-DRG. This process produces the same result as if the actual 
charges per discharge of an SSO case were adjusted to what they would 
have been had the patient's length of stay been equal to the average 
length of stay of the MS-LTC-DRG.
    Counting SSO cases as full LTCH cases with no adjustment in 
determining the FY 2022 MS-LTC-DRG relative weights would lower the FY 
2022 MS-LTC-DRG relative weight for affected MS-LTC-DRGs because the 
relatively lower charges of the SSO cases would bring down the average 
charge for all cases within a MS-LTC-DRG. This would result in an 
``underpayment'' for non-SSO cases and an ``overpayment'' for SSO 
cases. Therefore, as we proposed, we continued to adjust for SSO cases 
under Sec.  412.529 in this manner because it would result in more 
appropriate payments for all LTCH PPS standard Federal payment rate 
cases. (For additional information on this step of the relative weight 
methodology, we refer readers to 67 FR 55989 and 74 FR 43959.)
    Step 4--Calculate the FY 2022 MS-LTC-DRG relative weights on an 
iterative basis.
    Consistent with our historical relative weight methodology, as we 
proposed, we calculated the FY 2022 MS-LTC-DRG relative weights using 
the HSRV methodology, which is an iterative process. First, for each 
SSO-adjusted trimmed applicable LTCH case, we calculated a hospital-
specific relative charge value by dividing the charge per discharge 
after adjusting for SSOs of the LTCH case (from Step 3) by the average 
charge per SSO-adjusted discharge for the LTCH in which the case 
occurred. The resulting ratio is then multiplied by the LTCH's case-mix 
index to produce an adjusted hospital-specific relative charge value 
for the case. We used an initial case-mix index value of 1.0 for each 
LTCH.
    For each MS-LTC-DRG, we calculated the FY 2022 relative weight by 
dividing the SSO-adjusted average of the hospital-specific relative 
charge values for applicable LTCH cases for the MS-LTC-DRG (that is, 
the sum of the hospital-specific relative charge value, as previously 
stated, divided by the sum of equivalent cases from Step 3 for each MS-
LTC-DRG) by the overall SSO-adjusted average hospital-specific relative 
charge value across all applicable LTCH cases for all LTCHs (that is, 
the sum of the hospital-specific relative charge value, as previously 
stated, divided by the sum of equivalent applicable LTCH cases from 
Step 3 for each MS-LTC-DRG). Using these recalculated MS-LTC-DRG 
relative weights, each LTCH's average relative weight for all of its 
SSO-adjusted trimmed applicable LTCH cases (that is, its case-mix) was 
calculated by dividing the sum of all the LTCH's MS-LTC-DRG relative 
weights by its total number of SSO-adjusted trimmed applicable LTCH 
cases. The LTCHs' hospital-specific relative charge values (from 
previous) are then multiplied by the hospital-specific case-mix 
indexes. The hospital-specific case-mix adjusted relative charge values 
are then used to calculate a new set of MS-LTC-DRG relative weights 
across all LTCHs. This iterative process continued until there was 
convergence between the relative weights produced at adjacent steps, 
for example, when the maximum difference was less than 0.0001.
    Step 5--Determine a FY 2022 relative weight for MS-LTC-DRGs with no 
applicable LTCH cases.
    Using the trimmed applicable LTCH cases, consistent with our 
historical methodology, we identified the MS-LTC-DRGs for which there 
were no claims in the March 2020 update of the FY 2019 MedPAR file and, 
therefore, for which no charge data was available for these MS-LTC-
DRGs. Because patients with a number of the diagnoses under these MS-
LTC-DRGs may be treated at LTCHs, consistent with our historical 
methodology, we generally assign a relative weight to each of the no-
volume MS-LTC-DRGs based on clinical similarity and relative costliness 
(with the exception of ``transplant'' MS-LTC-DRGs, ``error'' MS-LTC-
DRGs, and MS-LTC-DRGs that indicate a principal diagnosis related to a 
psychiatric diagnosis or rehabilitation (referred to as the 
``psychiatric or rehabilitation'' MS-LTC-DRGs), as discussed later in 
this section of this final rule). (For additional information on this 
step of the relative weight methodology, we refer readers to 67 FR 
55991 and 74 FR 43959 through 43960.)
    Consistent with our existing methodology, as we proposed, we cross-
walked each no-volume MS-LTC-DRG to another MS-LTC-DRG for which we 
calculated a relative weight (determined in accordance with the 
methodology as previously described). Then, the ``no-volume'' MS-LTC-
DRG is assigned the same relative weight (and average length of stay) 
of the MS-LTC-DRG to which it was cross-walked (as described in greater 
detail in this section of this final rule).
    Of the 767 MS-LTC-DRGs for FY 2022, we identified 375 MS-LTC-DRGs 
for which there were no trimmed applicable LTCH cases. This number 
includes the 11 ``transplant'' MS-LTC-DRGs, the 2 ``error'' MS-LTC-
DRGs, and the 15 ``psychiatric or rehabilitation'' MS-LTC-DRGs, which 
are discussed in this section of this rule, such that we identified 347 
MS-LTC-DRGs that for which, as we proposed, we assigned a relative 
weight using our existing ``no-volume'' MS-LTC-DRG methodology (that 
is, 375-11-2-15 = 347). As we proposed, we assigned relative weights to 
each of the 347 no-volume MS-LTC-DRGs based on clinical similarity and 
relative costliness to 1 of the remaining 392 (767-375 = 392) MS-LTC-
DRGs for which we calculated relative weights based on the trimmed 
applicable LTCH cases in the FY 2019 MedPAR file data using the steps 
described previously. (For the remainder of this discussion, we refer 
to the ``cross-walked'' MS-LTC-DRGs as one of the 392 MS-LTC-DRGs to 
which we cross-walked each of the 347 ``no-volume'' MS-LTC-DRGs.) Then, 
as we generally proposed, we assigned the 347 no-volume MS-LTC-DRGs the 
relative weight of the cross-walked MS-LTC-DRG. (As explained in Step 
6, when necessary, we made adjustments to account for nonmonotonicity.)
    We cross-walked the no-volume MS-LTC-DRG to a MS-LTC-DRG for which 
we calculated relative weights based on the March 2020 update of the FY 
2019 MedPAR file, and to which it is similar clinically in intensity of 
use of resources and relative costliness as determined by criteria such 
as care provided during the period of time surrounding surgery, 
surgical approach (if applicable), length of time of surgical 
procedure, postoperative care, and length of stay. (For more details on 
our process for evaluating relative costliness, we refer readers to the 
FY 2010 IPPS/RY 2010 LTCH PPS final rule (73 FR 48543).) We believe in 
the rare event that there would be a few LTCH cases grouped to one of 
the no-volume MS-LTC-DRGs in FY 2022, the relative weights assigned 
based on the cross-walked MS-LTC-DRGs would result in an appropriate 
LTCH PPS payment because the crosswalks, which are based on clinical 
similarity and relative costliness, would be expected to generally 
require equivalent relative resource use.
    Then we assigned the relative weight of the cross-walked MS-LTC-DRG 
as the relative weight for the no-volume MS-LTC-DRG such that both of 
these MS-LTC-DRGs (that is, the no-volume

[[Page 45338]]

MS-LTC-DRG and the cross-walked MS-LTC-DRG) have the same relative 
weight (and average length of stay) for FY 2022. We note that, if the 
cross-walked MS-LTC-DRG had 25 applicable LTCH cases or more, its 
relative weight (calculated using the methodology as previously 
described in Steps 1 through 4) is assigned to the no-volume MS-LTC-DRG 
as well. Similarly, if the MS-LTC-DRG to which the no-volume MS-LTC-DRG 
was cross-walked had 24 or less cases and, therefore, was designated to 
1 of the low-volume quintiles for purposes of determining the relative 
weights, we assigned the relative weight of the applicable low-volume 
quintile to the no-volume MS-LTC-DRG such that both of these MS-LTC-
DRGs (that is, the no-volume MS-LTC-DRG and the cross-walked MS-LTC-
DRG) have the same relative weight for FY 2022. (As we noted 
previously, in the infrequent case where nonmonotonicity involving a 
no-volume MS-LTC-DRG resulted, additional adjustments as described in 
Step 6 are required in order to maintain monotonically increasing 
relative weights.)
    As discussed earlier, for this final rule, we are providing the 
list of the no-volume MS-LTC-DRGs and the MS-LTC-DRGs to which each was 
cross-walked (that is, the cross-walked MS-LTC-DRGs) for FY 2022 in a 
supplemental data file for public use posted via the internet on the 
CMS website for this final rule at: http://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/AcuteInpatientPPS/index.html in order 
to streamline the information made available to the public that is used 
in the annual development of Table 11.
    To illustrate this methodology for determining the relative weights 
for the FY 2022 MS-LTC-DRGs with no applicable LTCH cases, we are 
providing the following example, which refers to the no-volume MS-LTC-
DRGs crosswalk information for FY 2022 (which, as previously stated, we 
are providing in a supplemental data file posted via the internet on 
the CMS website for this final rule).
    Example: There were no trimmed applicable LTCH cases in the FY 2019 
MedPAR file that we are using for this final rule for MS-LTC-DRG 061 
(Ischemic stroke, precerebral occlusion or transient ischemia with 
thrombolytic agent with MCC). We determined that MS-LTC-DRG 070 
(Nonspecific cerebrovascular disorders with MCC) is similar clinically 
and based on resource use to MS-LTC-DRG 061. Therefore, we assigned the 
same relative weight (and average length of stay) of MS-LTC-DRG 70 of 
0.8732 for FY 2022 to MS-LTC-DRG 061 (we refer readers to Table 11, 
which is listed in section VI. of the Addendum to this final rule and 
is available via the internet on the CMS website).
    Again, we note that, as this system is dynamic, it is entirely 
possible that the number of MS-LTC-DRGs with no volume will vary in the 
future. Consistent with our historical practice, as we proposed, we 
used the best available claims data to identify the trimmed applicable 
LTCH cases from which we determined the relative weights in the final 
rule.
    For FY 2022, consistent with our historical relative weight 
methodology, we proposed to establish a relative weight of 0.0000 for 
the following transplant MS-LTC-DRGs: Heart Transplant or Implant of 
Heart Assist System with MCC (MS-LTC-DRG 001); Heart Transplant or 
Implant of Heart Assist System without MCC (MS-LTC-DRG 002); Liver 
Transplant with MCC or Intestinal Transplant (MS-LTC-DRG 005); Liver 
Transplant without MCC (MS-LTC-DRG 006); Lung Transplant (MS-LTC-DRG 
007); Simultaneous Pancreas/Kidney Transplant (MS-LTC-DRG 008); 
Simultaneous Pancreas/Kidney Transplant with Hemodialysis (MS-LTC-DRG 
019); Pancreas Transplant (MS-LTC-DRG 010); Kidney Transplant (MS-LTC-
DRG 652); Kidney Transplant with Hemodialysis with MCC (MS-LTC-DRG 
650), and Kidney Transplant with Hemodialysis without MCC (MS LTC DRG 
651). This is because Medicare only covers these procedures if they are 
performed at a hospital that has been certified for the specific 
procedures by Medicare and presently no LTCH has been so certified. At 
the present time, we include these 11 transplant MS-LTC-DRGs in the 
GROUPER program for administrative purposes only. Because we use the 
same GROUPER program for LTCHs as is used under the IPPS, removing 
these MS-LTC-DRGs would be administratively burdensome. (For additional 
information regarding our treatment of transplant MS-LTC-DRGs, we refer 
readers to the RY 2010 LTCH PPS final rule (74 FR 43964).) In addition, 
consistent with our historical policy, as we proposed, we established a 
relative weight of 0.0000 for the 2 ``error'' MS-LTC-DRGs (that is, MS-
LTC-DRG 998 (Principal Diagnosis Invalid as Discharge Diagnosis) and 
MS-LTC-DRG 999 (Ungroupable)) because applicable LTCH cases grouped to 
these MS-LTC-DRGs cannot be properly assigned to an MS-LTC-DRG 
according to the grouping logic.
    Additionally, as we proposed, we established a relative weight of 
0.0000 for the following ``psychiatric or rehabilitation'' MS-LTC-DRGs: 
MS-LTC-DRG 876 (O.R. Procedure with Principal Diagnoses of Mental 
Illness); MS-LTC-DRG 880 (Acute Adjustment Reaction & Psychosocial 
Dysfunction); MS-LTC-DRG 881 (Depressive Neuroses); MS-LTC-DRG 882 
(Neuroses Except Depressive); MS-LTC-DRG 883 (Disorders of Personality 
& Impulse Control); MS-LTC-DRG 884 (Organic Disturbances & Mental 
Retardation); MS-LTC-DRG 885 (Psychoses); MS-LTC-DRG 886 (Behavioral & 
Developmental Disorders); MS-LTC-DRG 887 (Other Mental Disorder 
Diagnoses); MS-LTC-DRG 894 (Alcohol/Drug Abuse or Dependence, Left 
Ama); MS-LTC-DRG 895 (Alcohol/Drug Abuse or Dependence, with 
Rehabilitation Therapy); MS-LTC-DRG 896 (Alcohol/Drug Abuse or 
Dependence, without Rehabilitation Therapy with MCC); MS-LTC-DRG 897 
(Alcohol/Drug Abuse or Dependence, without Rehabilitation Therapy 
without MCC); MS-LTC-DRG 945 (Rehabilitation with CC/MCC); and MS-LTC-
DRG 946 (Rehabilitation without CC/MCC). As we proposed, we established 
a relative weight 0.0000 for these 15 ``psychiatric or rehabilitation'' 
MS LTC DRGs because the blended payment rate and temporary exceptions 
to the site neutral payment rate will not be applicable for any LTCH 
discharges occurring in FY 2022, and as such payment under the LTCH PPS 
will be no longer be made in part based on the LTCH PPS standard 
Federal payment rate for any discharges assigned to those MS-DRGs.
    Step 6--Adjust the FY 2022 MS-LTC-DRG relative weights to account 
for nonmonotonically increasing relative weights.
    The MS-DRGs contain base DRGs that have been subdivided into one, 
two, or three severity of illness levels. Where there are three 
severity levels, the most severe level has at least one secondary 
diagnosis code that is referred to as an MCC (that is, major 
complication or comorbidity). The next lower severity level contains 
cases with at least one secondary diagnosis code that is a CC (that is, 
complication or comorbidity). Those cases without an MCC or a CC are 
referred to as ``without CC/MCC.'' When data do not support the 
creation of three severity levels, the base MS-DRG is subdivided into 
either two levels or the base MS-DRG is not subdivided. The two-level 
subdivisions may consist of the MS-DRG with CC/MCC and the MS-DRG 
without CC/MCC. Alternatively, the other type of two-

[[Page 45339]]

level subdivision may consist of the MS-DRG with MCC and the MS-DRG 
without MCC.
    In those base MS-LTC-DRGs that are split into either two or three 
severity levels, cases classified into the ``without CC/MCC'' MS-LTC-
DRG are expected to have a lower resource use (and lower costs) than 
the ``with CC/MCC'' MS-LTC-DRG (in the case of a two-level split) or 
both the ``with CC'' and the ``with MCC'' MS-LTC-DRGs (in the case of a 
three-level split). That is, theoretically, cases that are more severe 
typically require greater expenditure of medical care resources and 
would result in higher average charges. Therefore, in the three 
severity levels, relative weights should increase by severity, from 
lowest to highest. If the relative weights decrease as severity 
increases (that is, if within a base MS-LTC-DRG, an MS-LTC-DRG with CC 
has a higher relative weight than one with MCC, or the MS-LTC-DRG 
``without CC/MCC'' has a higher relative weight than either of the 
others), they are nonmonotonic. We continue to believe that utilizing 
nonmonotonic relative weights to adjust Medicare payments would result 
in inappropriate payments because the payment for the cases in the 
higher severity level in a base MS-LTC-DRG (which are generally 
expected to have higher resource use and costs) would be lower than the 
payment for cases in a lower severity level within the same base MS-
LTC-DRG (which are generally expected to have lower resource use and 
costs). Therefore, in determining the FY 2022 MS-LTC-DRG relative 
weights, consistent with our historical methodology, as we proposed, we 
continued to combine MS-LTC-DRG severity levels within a base MS-LTC-
DRG for the purpose of computing a relative weight when necessary to 
ensure that monotonicity is maintained. For a comprehensive description 
of our existing methodology to adjust for nonmonotonicity, we refer 
readers to the FY 2010 IPPS/RY 2010 LTCH PPS final rule (74 FR 43964 
through 43966). Any adjustments for nonmonotonicity that were made in 
determining the FY 2022 MS-LTC-DRG relative weights in this final rule 
by applying this methodology are denoted in Table 11, which is listed 
in section VI. of the Addendum to this final rule and is available via 
the internet on the CMS website.
    Step 7--Calculate the FY 2022 MS-LTC-DRG reclassification and 
recalibration budget neutrality factor.
    In accordance with the regulations at Sec.  412.517(b) (in 
conjunction with Sec.  412.503), the annual update to the MS-LTC-DRG 
classifications and relative weights is done in a budget neutral manner 
such that estimated aggregate LTCH PPS payments would be unaffected, 
that is, would be neither greater than nor less than the estimated 
aggregate LTCH PPS payments that would have been made without the MS-
LTC-DRG classification and relative weight changes. (For a detailed 
discussion on the establishment of the budget neutrality requirement 
for the annual update of the MS-LTC-DRG classifications and relative 
weights, we refer readers to the RY 2008 LTCH PPS final rule (72 FR 
26881 and 26882).)
    The MS-LTC-DRG classifications and relative weights are updated 
annually based on the best available LTCH claims data to reflect 
changes in relative LTCH resource use (Sec.  412.517(a) in conjunction 
with Sec.  412.503). To achieve the budget neutrality requirement at 
Sec.  412.517(b), under our established methodology, for each annual 
update, the MS-LTC-DRG relative weights are uniformly adjusted to 
ensure that estimated aggregate payments under the LTCH PPS would not 
be affected (that is, decreased or increased). Consistent with that 
provision, as we proposed, we updated the MS-LTC-DRG classifications 
and relative weights for FY 2022 based on the best available LTCH data 
for applicable LTCH cases, and continued to apply a budget neutrality 
adjustment in determining the FY 2022 MS-LTC-DRG relative weights.
    In this final rule, to ensure budget neutrality in the update to 
the MS-LTC-DRG classifications and relative weights under Sec.  
412.517(b), as we proposed, we continued to use our established two-
step budget neutrality methodology.
    To calculate the normalization factor for FY 2022, as we proposed 
in the FY 2022 IPPS/LTCH PPS proposed rule (86 FR 25546), we grouped 
applicable LTCH cases using the FY 2022 Version 39 GROUPER, and the 
recalibrated FY 2022 MS-LTC-DRG relative weights to calculate the 
average case-mix index (CMI); we grouped the same applicable LTCH cases 
using the FY 2021 GROUPER Version 38 and MS-LTC-DRG relative weights 
and calculated the average CMI; and computed the ratio by dividing the 
average CMI for FY 2021 by the average CMI for FY 2022. That ratio is 
the normalization factor. Because the calculation of the normalization 
factor involves the relative weights for the MS-LTC-DRGs that contained 
applicable LTCH cases to calculate the average CMIs, any low-volume MS-
LTC-DRGs are included in the calculation (and the MS-LTC-DRGs with no 
applicable LTCH cases are not included in the calculation).
    To calculate the budget neutrality adjustment factor, we simulated 
estimated total FY 2022 LTCH PPS standard Federal payment rate payments 
for applicable LTCH cases using the FY 2022 normalized relative weights 
and GROUPER Version 39; simulated estimated total FY 2022 LTCH PPS 
standard Federal payment rate payments for applicable LTCH cases using 
the FY 2021 MS-LTC-DRG relative weights and the FY 2021 GROUPER Version 
38; and calculated the ratio of these estimated total payments by 
dividing the simulated estimated total LTCH PPS standard Federal 
payment rate payments using the FY 2021 MS-LTC-DRG relative weights and 
the GROUPER Version 38 by the simulated estimated total LTCH PPS 
standard Federal payment rate payments using the FY 2022 MS-LTC-DRG 
relative weights and the GROUPER Version 39. The resulting ratio is the 
budget neutrality adjustment factor. The calculation of the budget 
neutrality factor involves the relative weights for the LTCH cases used 
in the payment simulation, which includes any cases grouped to low-
volume MS-LTC-DRGs, and generally does not include payments for cases 
grouped to a MS-LTC-DRG with no applicable LTCH cases. Occasionally, a 
few LTCH cases (that is, those with a covered length of stay of 7 days 
or less), which are removed from the relative weight calculation in 
step 2 that are grouped to a MS-LTC-DRG with no applicable LTCH cases 
are included in the payment simulations used to calculate the budget 
neutrality factor. However, the number and payment amount of such cases 
have a negligible impact on the budget neutrality factor calculation.
    In this final rule, to ensure budget neutrality in the update to 
the MS-LTC-DRG classifications and relative weights under Sec.  
412.517(b), as we proposed, we continued to use our established two-
step budget neutrality methodology. Therefore, in this final rule, in 
the first step of our MS-LTC-DRG budget neutrality methodology, for FY 
2022, as we proposed, we calculated and applied a normalization factor 
to the recalibrated relative weights (the result of Steps 1 through 6 
discussed previously) to ensure that estimated payments are not 
affected by changes in the composition of case types or the changes to 
the classification system. That is, the normalization adjustment is 
intended to ensure that the recalibration of the MS-LTC-DRG relative 
weights (that is, the process itself) neither increases nor decreases 
the average case-mix index.

[[Page 45340]]

    To calculate the normalization factor for FY 2022 (the first step 
of our budget neutrality methodology), we used the following three 
steps: (1.a.) Use the applicable LTCH cases from the best available 
data (that is, LTCH discharges from the FY 2019 MedPAR file) and group 
them using the FY 2022 GROUPER (that is, Version 39 for FY 2022) and 
the recalibrated FY 2022 MS-LTC-DRG relative weights (determined in 
Steps 1 through 6 discussed previously) to calculate the average case-
mix index; (1.b.) group the same applicable LTCH cases (as are used in 
Step 1.a.) using the FY 2021 GROUPER (Version 38) and FY 2021 MS-LTC-
DRG relative weights and calculate the average case-mix index; and 
(1.c.) compute the ratio of these average case-mix indexes by dividing 
the average CMI for FY 2021 (determined in Step 1.b.) by the average 
case-mix index for FY 2022 (determined in Step 1.a.). As a result, in 
determining the MS-LTC-DRG relative weights for FY 2022, each 
recalibrated MS-LTC-DRG relative weight is multiplied by the 
normalization factor of 1.25815 (determined in Step 1.c.) in the first 
step of the budget neutrality methodology, which produced ``normalized 
relative weights.''
    In the second step of our MS-LTC-DRG budget neutrality methodology, 
we calculated a second budget neutrality factor consisting of the ratio 
of estimated aggregate FY 2022 LTCH PPS standard Federal payment rate 
payments for applicable LTCH cases (the sum of all calculations under 
Step 1.b. stated previously) before reclassification and recalibration 
to estimated aggregate payments for FY 2022 LTCH PPS standard Federal 
payment rate payments for applicable LTCH cases after reclassification 
and recalibration (that is, the sum of all calculations under Step 1.a. 
stated previously).
    That is, for this final rule, for FY 2022, under the second step of 
the budget neutrality methodology, as we proposed, we determined the 
budget neutrality adjustment factor using the following three steps: 
(2.a.) Simulate estimated total FY 2022 LTCH PPS standard Federal 
payment rate payments for applicable LTCH cases using the normalized 
relative weights for FY 2022 and GROUPER Version 39 (as described 
previously); (2.b.) simulate estimated total FY 2022 LTCH PPS standard 
Federal payment rate payments for applicable LTCH cases using the FY 
2021 GROUPER (Version 38) and the FY 2021 MS-LTC-DRG relative weights 
in Table 11 of the FY 2021 IPPS/LTCH PPS final rule available on the 
internet, as described in section VI. of the Addendum of that final 
rule; and (2.c.) calculate the ratio of these estimated total payments 
by dividing the value determined in Step 2.b. by the value determined 
in Step 2.a. In determining the FY 2022 MS-LTC-DRG relative weights, 
each normalized relative weight is then multiplied by a budget 
neutrality factor of 1.0002384 (the value determined in Step 2.c.) in 
the second step of the budget neutrality methodology to achieve the 
budget neutrality requirement at Sec.  412.517(b).
    Accordingly, in determining the FY 2022 MS-LTC-DRG relative weights 
in this final rule, consistent with our existing methodology, as we 
proposed, we applied a normalization factor of 1.25815 and a budget 
neutrality factor of 1.0002384. Table 11, which is listed in section 
VI. of the Addendum to this final rule and is available via the 
internet on the CMS website, lists the MS-LTC-DRGs and their respective 
relative weights, geometric mean length of stay, and five-sixths of the 
geometric mean length of stay (used to identify SSO cases under Sec.  
412.529(a)) for FY 2022.

C. Changes to the LTCH PPS Payment Rates and Other Changes to the LTCH 
PPS for FY 2022

1. Overview of Development of the LTCH PPS Standard Federal Payment 
Rates
    The basic methodology for determining LTCH PPS standard Federal 
payment rates is currently set forth at 42 CFR 412.515 through 412.533 
and Sec.  412.535. In this section, we discuss the factors that we used 
to update the LTCH PPS standard Federal payment rate for FY 2022, that 
is, effective for LTCH discharges occurring on or after October 1, 2021 
through September 30, 2022. Under the dual rate LTCH PPS payment 
structure required by statute, beginning with discharges in cost 
reporting periods beginning in FY 2016, only LTCH discharges that meet 
the criteria for exclusion from the site neutral payment rate are paid 
based on the LTCH PPS standard Federal payment rate specified at 42 CFR 
412.523. (For additional details on our finalized policies related to 
the dual rate LTCH PPS payment structure required by statute, we refer 
readers to the FY 2016 IPPS/LTCH PPS final rule (80 FR 49601 through 
49623).)
    Prior to the implementation of the dual payment rate system in FY 
2016, all LTCH discharges were paid similarly to those now exempt from 
the site neutral payment rate. That legacy payment rate was called the 
standard Federal rate. For details on the development of the initial 
standard Federal rate for FY 2003, we refer readers to the August 30, 
2002 LTCH PPS final rule (67 FR 56027 through 56037). For subsequent 
updates to the standard Federal rate (FYs 2003 through 2015)/LTCH PPS 
standard Federal payment rate (FY 2016 through present) as implemented 
under 42 CFR 412.523(c)(3), we refer readers to the FY 2020 IPPS/LTCH 
PPS final rule (84 FR 42445 through 42446).
    In this FY 2022 IPPS/LTCH PPS final rule, we present our policies 
related to the annual update to the LTCH PPS standard Federal payment 
rate for FY 2022.
    The update to the LTCH PPS standard Federal payment rate for FY 
2022 is presented in section V.A. of the Addendum to this final rule. 
The components of the annual update to the LTCH PPS standard Federal 
payment rate for FY 2022 are discussed in this section, including the 
statutory reduction to the annual update for LTCHs that fail to submit 
quality reporting data for FY 2022 as required by the statute (as 
discussed in section VIII.C.2.c. of the preamble of this final rule). 
As we proposed in the FY 2022 IPPS/LTCH PPS proposed rule (86 FR 
25547), we also made an adjustment to the LTCH PPS standard Federal 
payment rate to account for the estimated effect of the changes to the 
area wage level for FY 2022 on estimated aggregate LTCH PPS payments, 
in accordance with 42 CFR 412.523(d)(4) (as discussed in section V.B. 
of the Addendum to this final rule). (We note that in the FY 2022 IPPS/
LTCH PPS proposed rule, we did not make any proposals which would 
change the FY 2022 LTCH PPS standard Federal payment rate that are 
based on the elimination of the 25-percent threshold policy because the 
permanent, one-time factor was proposed and adopted in the FY 2021 
IPPS/LTCH PPS Final Rule for FY 2021 and subsequent years (85 FR 
58907)).
2. FY 2022 LTCH PPS Standard Federal Payment Rate Annual Market Basket 
Update
a. Overview
    Historically, the Medicare program has used a market basket to 
account for input price increases in the services furnished by 
providers. The market basket used for the LTCH PPS includes both 
operating and capital related costs of LTCHs because the LTCH PPS uses 
a single payment rate for both operating and capital-related costs. We 
adopted the 2017-based LTCH market basket for

[[Page 45341]]

use under the LTCH PPS beginning in FY 2021 (85 FR 58907 through 
58909). For additional details on the historical development of the 
market basket used under the LTCH PPS, we refer readers to the FY 2013 
IPPS/LTCH PPS final rule (77 FR 53467 through 53476), and for a 
complete discussion of the LTCH market basket and a description of the 
methodologies used to determine the operating and capital-related 
portions of the 2017-based LTCH market basket, we refer readers to the 
FY 2021 IPPS/LTCH PPS final rule (85 FR 58909 through 58926).
    Section 3401(c) of the Affordable Care Act provides for certain 
adjustments to any annual update to the LTCH PPS standard Federal 
payment rate and refers to the timeframes associated with such 
adjustments as a ``rate year.'' We note that, because the annual update 
to the LTCH PPS policies, rates, and factors now occurs on October 1, 
we adopted the term ``fiscal year'' (FY) rather than ``rate year'' (RY) 
under the LTCH PPS beginning October 1, 2010, to conform with the 
standard definition of the Federal fiscal year (October 1 through 
September 30) used by other PPSs, such as the IPPS (75 FR 50396 through 
50397). Although the language of sections 3004(a), 3401(c), 10319, and 
1105(b) of the Affordable Care Act refers to years 2010 and thereafter 
under the LTCH PPS as ``rate year,'' consistent with our change in the 
terminology used under the LTCH PPS from ``rate year'' to ``fiscal 
year,'' for purposes of clarity, when discussing the annual update for 
the LTCH PPS standard Federal payment rate, including the provisions of 
the Affordable Care Act, we use ``fiscal year'' rather than ``rate 
year'' for 2011 and subsequent years.
b. Annual Update to the LTCH PPS Standard Federal Payment Rate for FY 
2022
    CMS has used an estimated market basket increase to update the LTCH 
PPS. As previously noted, we adopted the 2017-based LTCH market basket 
for use under the LTCH PPS beginning in FY 2021. The 2017-based LTCH 
market basket is primarily based on the Medicare cost report data 
submitted by LTCHs and, therefore, specifically reflects the cost 
structures of only LTCHs. (For additional details on the development of 
the 2017-based LTCH market basket, we refer readers to the FY 2021 
IPPS/LTCH PPS final rule (85 FR 58909 through 58926).)
    In the FY 2021 IPPS/LTCH final rule, we finalized the price proxies 
for the 2017-based LTCH market basket. In that final rule, we 
established the use of the Moody's AAA Corporate Bond Yield index as 
the price proxy for the For-profit Interest cost category (85 FR 
58919). Effective for December 2020, the Moody's AAA Corporate Bond 
series is no longer available for use under license to IGI, the 
nationally-recognized economic and financial forecasting firm with 
which we contract to forecast the components of the market baskets 
productivity adjustment. In the FY 2022 IPPS/LTCH PPS proposed rule, we 
proposed to use the iBoxx AAA Corporate Bond Yield index instead of the 
Moody's AAA Corporate Bond Yield index in the 2017-based LTCH market 
basket. We stated that because the iBoxx AAA Corporate Bond Yield index 
captures the same technical concept as the current corporate bond proxy 
and tracks similarly to the current measure that is no longer 
available, we believe that using the iBoxx AAA Corporate Bond Yield 
index is technically appropriate to use in the 2017-based LTCH market 
basket (86 FR 25558). We did not receive any comments on the proposed 
change to the price proxy for the AAA Corporate Bond Yield index for 
the for-profit cost category. Therefore, we are finalizing the use of 
the iBoxx AAA Corporate Bond Yield index for use in the 2017-based LTCH 
market basket as proposed.
    We continue to believe that the 2017-based LTCH market basket 
appropriately reflects the cost structure of LTCHs for the reasons 
discussed when we adopted its use in the FY 2021 IPPS/LTCH PPS final 
rule. Therefore, in this final rule, as we proposed in the FY 2022 
IPPS/LTCH PPS proposed rule (86 FR 25548), we used the 2017-based LTCH 
market basket to update the LTCH PPS standard Federal payment rate for 
FY 2022.
    Section 1886(m)(3)(A) of the Act provides that, beginning in FY 
2010, any annual update to the LTCH PPS standard Federal payment rate 
is reduced by the adjustments specified in clauses (i) and (ii) of 
subparagraph (A), as applicable. Clause (i) of section 1886(m)(3)(A) of 
the Act provides for a reduction, for FY 2012 and each subsequent rate 
year, by the productivity adjustment described in section 
1886(b)(3)(B)(xi)(II) of the Act (that is, ``the productivity 
adjustment''). We note that effective with FY 2022 and forward, CMS is 
changing the name of this adjustment to refer to it as the productivity 
adjustment rather than the MFP adjustment. We note that this is not a 
change in policy as the methodology for deriving the adjustment relies 
on the same underlying data and methodology. This change in terminology 
results in a title more consistent with the statutory language 
described in section 1886(b)(3)(B)(xi)(II) of the Act. Clause (ii) of 
section 1886(m)(3)(A) of the Act provided for a reduction, for each of 
FYs 2010 through 2019, by the ``other adjustment'' described in section 
1886(m)(4)(F) of the Act; therefore, it is not applicable for FY 2022.
    Section 1886(m)(3)(B) of the Act provides that the application of 
paragraph (3) of section 1886(m) of the Act may result in the annual 
update being less than zero for a rate year, and may result in payment 
rates for a rate year being less than such payment rates for the 
preceding rate year.
c. Adjustment to the LTCH PPS Standard Federal Payment Rate Under the 
Long-Term Care Hospital Quality Reporting Program (LTCH QRP)
    In accordance with section 1886(m)(5) of the Act, the Secretary 
established the Long-Term Care Hospital Quality Reporting Program (LTCH 
QRP). The reduction in the annual update to the LTCH PPS standard 
Federal payment rate for failure to report quality data under the LTCH 
QRP for FY 2014 and subsequent fiscal years is codified under 42 CFR 
412.523(c)(4). The LTCH QRP, as required for FY 2014 and subsequent 
fiscal years by section 1886(m)(5)(A)(i) of the Act, applies a 2.0 
percentage point reduction to any update under 42 CFR 412.523(c)(3) for 
an LTCH that does not submit quality reporting data to the Secretary in 
accordance with section 1886(m)(5)(C) of the Act with respect to such a 
year (that is, in the form and manner and at the time specified by the 
Secretary under the LTCH QRP) (42 CFR 412.523(c)(4)(i)). Section 
1886(m)(5)(A)(ii) of the Act provides that the application of the 2.0 
percentage points reduction may result in an annual update that is less 
than 0.0 for a year, and may result in LTCH PPS payment rates for a 
year being less than such LTCH PPS payment rates for the preceding 
year. Furthermore, section 1886(m)(5)(B) of the Act specifies that the 
2.0 percentage points reduction is applied in a noncumulative manner, 
such that any reduction made under section 1886(m)(5)(A) of the Act 
shall apply only with respect to the year involved, and shall not be 
taken into account in computing the LTCH PPS payment amount for a 
subsequent year. These requirements are codified in the regulations at 
42 CFR 412.523(c)(4). (For additional information on the history of the 
LTCH QRP, including the statutory authority and the selected measures, 
we refer readers to section VIII.C. of the preamble of this final 
rule.)

[[Page 45342]]

d. Annual Market Basket Update Under the LTCH PPS for FY 2022
    Consistent with our historical practice, we estimate the market 
basket increase and the productivity adjustment based on IGI's forecast 
using the most recent available data. Based on IGI's fourth quarter 
2020 forecast, the proposed FY 2022 full market basket estimate for the 
LTCH PPS using the 2017-based LTCH market basket was 2.4 percent. The 
proposed productivity adjustment for FY 2022 based on IGI's fourth 
quarter 2020 forecast was 0.2 percent.
    For FY 2022, section 1886(m)(3)(A)(i) of the Act requires that any 
annual update to the LTCH PPS standard Federal payment rate be reduced 
by the productivity adjustment, described in section 
1886(b)(3)(B)(xi)(II) of the Act. Consistent with the statute, we 
proposed in the FY 2022 IPPS/LTCH PPS proposed rule (86 FR 25548), to 
reduce the full estimated FY 2022 market basket increase by the FY 2022 
productivity adjustment. To determine the proposed market basket 
increase for LTCHs for FY 2022, as reduced by the proposed productivity 
adjustment, consistent with our established methodology, we subtracted 
the proposed FY 2022 productivity adjustment from the estimated FY 2022 
market basket increase. (For additional details on our established 
methodology for adjusting the market basket increase by the 
productivity adjustment, we refer readers to the FY 2012 IPPS/LTCH PPS 
final rule (76 FR 51771).)
    For FY 2022, section 1886(m)(5) of the Act requires that, for LTCHs 
that do not submit quality reporting data as required under the LTCH 
QRP, any annual update to an LTCH PPS standard Federal payment rate, 
after application of the adjustments required by section 1886(m)(3) of 
the Act, shall be further reduced by 2.0 percentage points. Therefore, 
for LTCHs that fail to submit quality reporting data under the LTCH 
QRP, the proposed 2.4 percent update to the LTCH PPS standard Federal 
payment rate for FY 2022 would be reduced by the 0.2 percentage point 
productivity adjustment as required under section 1886(m)(3)(A)(i) of 
the Act and the additional 2.0 percentage points reduction required by 
section 1886(m)(5) of the Act.
    In the FY 2022 IPPS/LTCH PPS proposed rule, in accordance with the 
statute, we proposed to reduce the proposed FY 2022 full market basket 
estimate of 2.4 percent (based on IGI's fourth quarter 2020 forecast of 
the 2017-based LTCH market basket) by the proposed FY 2022 productivity 
adjustment of 0.2 percentage point (based on IGI's fourth quarter 2020 
forecast). Therefore, under the authority of section 123 of the BBRA as 
amended by section 307(b) of the BIPA, consistent with 42 CFR 
412.523(c)(3)(xvii), we proposed to establish an annual market basket 
update to the LTCH PPS standard Federal payment rate for FY 2022 of 2.2 
percent (that is, the most recent estimate of the LTCH PPS market 
basket increase of 2.4 percent less the productivity adjustment of 0.2 
percentage point). For LTCHs that fail to submit quality reporting data 
under the LTCH QRP, under 42 CFR 412.523(c)(3)(xvii) in conjunction 
with 42 CFR 412.523(c)(4), we proposed to further reduce the annual 
update to the LTCH PPS standard Federal payment rate by 2.0 percentage 
points, in accordance with section 1886(m)(5) of the Act. Accordingly, 
we proposed to establish an annual update to the LTCH PPS standard 
Federal payment rate of 0.2 percent (that is, 2.2 percent minus 2.0 
percentage points) for FY 2022 for LTCHs that fail to submit quality 
reporting data as required under the LTCH QRP. Consistent with our 
historical practice, we proposed in the FY 2022 IPPS/LTCH PPS proposed 
rule (86 FR 25549), to use a more recent estimate of the market basket 
and the productivity adjustment, if appropriate, in the final rule to 
establish an annual update to the LTCH PPS standard Federal payment 
rate for FY 2022. (We note that, consistent with historical practice, 
we also proposed to adjust the FY 2022 LTCH PPS standard Federal 
payment rate by an area wage level budget neutrality factor in 
accordance with 42 CFR 412.523(d)(4) (as discussed in section V.B.5. of 
the Addendum to the proposed rule).
    We did not receive any comments on the proposed LTCH market basket 
update or the productivity adjustment. Therefore, we are finalizing the 
LTCH payment update using the most recent forecast of the market basket 
and productivity adjustment. As such, based on IGI's second quarter 
2021 forecast, the FY 2022 full market basket estimate for the LTCH PPS 
using the 2017-based LTCH market basket is 2.6 percent. The current 
estimate of the productivity adjustment for FY 2022 based on IGI's 
second quarter 2021 forecast is 0.7 percent. Therefore, under the 
authority of section 123 of the BBRA as amended by section 307(b) of 
the BIPA, consistent with 42 CFR 412.523(c)(3)(xvii), we are 
establishing an annual market basket update to the LTCH PPS standard 
Federal payment rate for FY 2022 of 1.9 percent (that is, the most 
recent estimate of the LTCH PPS market basket increase of 2.6 percent 
less the productivity adjustment of 0.7 percentage point).
    For LTCHs that fail to submit quality reporting data under the LTCH 
QRP, under 42 CFR 412.523(c)(3)(xvii) in conjunction with 42 CFR 
412.523(c)(4), as we proposed, we further reduced the annual update to 
the LTCH PPS standard Federal payment rate by 2.0 percentage points, in 
accordance with section 1886(m)(5) of the Act. Accordingly, we are 
establishing an annual update to the LTCH PPS standard Federal payment 
rate of -0.1 percent (that is, 1.9 percent minus 2.0 percentage points) 
for FY 2022 for LTCHs that fail to submit quality reporting data as 
required under the LTCH QRP.

IX. Quality Data Reporting Requirements for Specific Providers and 
Suppliers

    In section IX. of the preamble of the FY 2022 IPPS/LTCH PPS 
proposed rule (86 FR 25549 through 25628), we sought public comment on 
two focus areas, and also proposed changes to the Medicare quality 
reporting systems:
     In section IX.A., advancing to digital quality measurement 
and the use of Fast Healthcare Interoperability Resources (FHIR) in 
hospital quality programs;
     In section IX.B., closing the health equity gap in CMS 
hospital quality programs;
     In section IX.C., the Hospital IQR Program;
     In section IX.D., the PCHQR Program; and
     In section IX.E., the LTCH QRP.
    In addition, in section IX.F. of the preamble of that proposed rule 
(86 FR 25628 through 25654), we proposed changes to the Medicare 
Promoting Interoperability Program (previously known as the Medicare 
and Medicaid EHR Incentive Programs) for eligible hospitals and 
critical access hospitals (CAHs).

A. Advancing to Digital Quality Measurement and the Use of Fast 
Healthcare Interoperability Resources (FHIR) in Hospital Quality 
Programs--Request for Information

    We aim to move fully to digital quality measurement in CMS quality 
reporting and value-based purchasing programs by 2025. As part of this 
modernization of our quality measurement enterprise, we issued a 
request for information (RFI). The purpose of this RFI was to gather 
broad public input solely for planning purposes for our transition to 
digital quality measurement. Any updates to

[[Page 45343]]

specific program requirements related to providing data for quality 
measurement and reporting provisions will be addressed through future 
rulemaking, as necessary. The RFI contained five parts:
     Background. This part provides information on our quality 
measurement programs and our goal to move fully to digital quality 
measurement by 2025. This part also provides a summary of recent HHS 
policy developments that are advancing interoperability and could 
support our move towards full digital quality measurement.
     Definition of Digital Quality Measures (dQMs). This part 
provides a potential definition for dQMs. Specific requests for input 
are included in the section.
     Use of Fast Healthcare Interoperability Resources 
(FHIR[supreg]) for current electronic clinical quality measures 
(eCQMs). This part provides information on current activities underway 
to align CMS eCQMs with the FHIR standard and support quality 
measurement via application programming interfaces (APIs), and 
contrasts this approach to current eCQM standards and practice.
     Changes Under Consideration to Advance Digital Quality 
Measurement: Actions in Four Areas to Transition to Digital Quality 
Measures by 2025. This part introduces four possible steps that would 
enable transformation of CMS' quality measurement enterprise to be 
fully digital by 2025. Specific requests for input are included in the 
section.
     Solicitation of Comments. This part lists all requests for 
input included in the sections of this RFI.
1. Background
    As required by law, we implement quality measurement and value-
based purchasing programs across a broad range of inpatient acute care, 
outpatient, and post-acute care (PAC) settings consistent with our 
mission to improve the quality of health care for Americans through 
measurement, transparency, and increasingly, value-based purchasing. 
These quality programs are foundational for incentivizing value-based 
care, contributing to improvements in health care, enhancing patient 
outcomes, and informing consumer choice. In October 2017, we launched 
the Meaningful Measures Framework. This framework for quality 
measurement captures our vision to better address health care quality 
priorities and gaps, including emphasizing digital quality measurement, 
reducing measurement burden, and promoting patient perspectives, while 
also focusing on modernization and innovation. The scope of the 
Meaningful Measures Framework evolves as the health care environment 
continues to change.\804\ Consistent with the Meaningful Measures 
Framework, we aim to move fully to digital quality measurement by 2025. 
We acknowledge providers within the various care and practice settings 
covered by our quality programs may be at different stages of 
readiness, and therefore, the timeline for achieving full digital 
quality measurement across our quality reporting programs may vary.
    We also continue to evolve the Medicare Promoting Interoperability 
Program's focus on the use of certified electronic health record (EHR) 
technology, from an initial focus on electronic data capture to 
enhancing information exchange and expanding quality measurement (83 FR 
41634). However, reporting data for quality measurement via EHRs 
remains burdensome, and our current approach to quality measurement 
does not readily incorporate emerging data sources such as patient-
reported outcomes (PRO) and patient-generated health data (PGHD).\805\ 
There is a need to streamline our approach to data collection, 
calculation, and reporting to fully leverage clinical and patient-
centered information for measurement, improvement, and learning.
    Additionally, advancements in technical standards and associated 
regulatory initiatives to improve interoperability of healthcare data 
are creating an opportunity to significantly improve our quality 
measurement systems. In May 2020, we finalized interoperability 
requirements in the CMS Interoperability and Patient Access final rule 
(85 FR 25510) to support beneficiary access to data held by certain 
payers. At the same time, the Office of the National Coordinator for 
Health Information Technology (ONC) finalized policies in the ONC 21st 
Century Cures Act final rule (85 FR 25642) to advance the 
interoperability of health information technology (IT) as defined in 
section 4003 of the Cures Act, including the ``complete access, 
exchange, and use of all electronically accessible health 
information.'' Closely working with ONC, we collaboratively identified 
Health Level 7 (HL7[supreg]) FHIR Release 4.0.1 as the standard to 
support Application Programming Interface (API) policies in both rules. 
ONC, on behalf of HHS, adopted the HL7 FHIR Release 4.0.1 for APIs and 
related implementation specifications at 45 CFR 170.215. We believe the 
FHIR standard has the potential to be a more efficient and modular 
standard to enable APIs. We also believe this standard enables 
collaboration and information sharing, which is essential for 
delivering high-quality care and better outcomes at a lower cost. By 
aligning technology requirements for payers, health care providers, and 
health IT developers HHS can advance an interoperable health IT 
infrastructure that ensures providers and patients have access to 
health data when and where it is needed.
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    \804\ Meaningful Measures 2.0: Moving from Measure Reduction to 
Modernization. Available at: https://www.cms.gov/meaningful-measures-20-moving-measure-reduction-modernization.
    \805\ What are patient generated health data: https://www.healthit.gov/topic/otherhot-topics/what-are-patient-generated-health-data.
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    In the ONC 21st Century Cures Act final rule, ONC adopted a 
``Standardized API for Patient and Population Services'' certification 
criterion for health IT that requires the use of FHIR Release 4 and 
several implementation specifications. Health IT certified to this 
criterion will offer single patient and multiple patient services that 
can be accessed by third party applications (85 FR 25742).\806\ The ONC 
21st Century Cures Act final rule also requires health IT developers to 
update their certified health IT to support the United States Core Data 
for Interoperability (USCDI) standard.\807\ The scope of patient data 
identified in the USCDI and the data standards that support this data 
set are expected to evolve over time, starting with data specified in 
Version 1 of the USCDI. In November 2020, ONC issued an interim final 
rule with comment period extending the date when health IT developers 
must make technology meeting updated certification criteria available 
under the ONC Health IT Certification Program until December 31, 2022 
(85 FR 70064).\808\
---------------------------------------------------------------------------

    \806\ Application Programming Interfaces (API) Resource Guide, 
Version 1.0. Available at: https://www.healthit.gov/sites/default/files/page/2020-11/API-Resource-Guide_v1_0.pdf.
    \807\ https://www.healthit.gov/isa/united-states-core-data-interoperability-uscdi.
    \808\ Information Blocking and the ONC Health IT Certification 
Program: Extension of Compliance Dates and Timeframes in Response to 
the Covid-19 Public Health Emergency. Available at: https://www.govinfo.gov/content/pkg/FR-2020-11-04/pdf/2020-24376.pdf.
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    The CMS Interoperability and Patient Access final rule (85 FR 
25510) and program policies build on the ONC 21st Century Cures Act 
final rule (85 FR 25642). The CMS Interoperability and Patient Access 
final rule and policies require certain payers (for example, Medicare 
Advantage organizations, Medicaid and CHIP Fee-for-Service programs, 
Medicaid managed care plans, CHIP managed care entities, and issuers of 
certain Qualified Health Plan

[[Page 45344]]

[QHP] on the Federally-facilitated Exchanges [FFEs]) to implement and 
maintain a standards-based Patient Access API using HL7 FHIR Release 
4.0.1 to make available certain data to their enrollees and 
beneficiaries (called ``patients'' in the CMS interoperability rule). 
These certain data include data concerning claims and encounters, with 
the intent to ensure access to their own health care information 
through third-party software applications. The rule also established 
new Conditions of Participation for Medicare and Medicaid participating 
hospitals and critical access hospitals (CAHs), requiring them to send 
electronic notifications to another healthcare facility or community 
provider or practitioner when a patient is admitted, discharged, or 
transferred (85 FR 25603). In the CY 2021 Physician Fee Schedule (PFS) 
final rule (85 FR 84472), we finalized a policy to align the certified 
EHR technology required for use in the Promoting Interoperability 
Programs and the MIPS Promoting Interoperability performance category 
with the updates to health IT certification criteria finalized in the 
ONC 21st Century Cures Act final rule. Under this policy, MIPS eligible 
clinicians, and eligible hospitals and CAHs participating in the 
Promoting Interoperability Programs, must use technology meeting the 
updated certification criteria for performance and reporting periods 
beginning in 2023 (85 FR 84825).
    The use of APIs can also reduce long-standing barriers to quality 
measurement. Currently, health IT developers are required to implement 
individual measure specifications within their health IT products. The 
health IT developer must also accommodate how that product connects 
with the unique variety of systems within a specific care setting.\809\ 
This may be further complicated by systems that integrate a wide range 
of data schemas. This process is burdensome and costly, and it is 
difficult to reliably obtain high quality data across systems. As 
health IT developers map their health IT data to the FHIR standard and 
related implementation specifications, APIs can enable these structured 
data to be easily accessible for quality measurement or other use 
cases, such as care coordination, clinical decision support, and 
supporting patient access.
---------------------------------------------------------------------------

    \809\ The Office of the National Coordinator for Health 
Information Technology, Strategy on Reducing Regulatory and 
Administrative Burden Relating to the Use of Health IT and EHRs, 
Final Report (Feb. 2020). Available at: https://www.healthit.gov/sites/default/files/page/2020-02/BurdenReport_0.pdf.
---------------------------------------------------------------------------

    We believe the emerging data standardization and interoperability 
enabled by APIs will support the transition to full digital quality 
measurement by 2025, and are committed to exploring and seeking input 
on potential solutions for the transition to digital quality 
measurement as described in this RFI.
2. Definition of Digital Quality Measures
    In the proposed rule, we sought to refine the definition of digital 
quality measures (dQMs) to further operationalize our objective of 
fully transitioning to dQMs by 2025. We previously noted dQMs use 
``sources of health information that are captured and can be 
transmitted electronically and via interoperable systems'' (85 FR 
84845). In this RFI, we sought input on future elaboration that would 
define a dQM as a software that processes digital data to produce a 
measure score or measure scores. Data sources for dQMs may include 
administrative systems, electronically submitted clinical assessment 
data, case management systems, EHRs, instruments (for example, medical 
devices and wearable devices), patient portals or applications (for 
example, for collection of patient-generated health data), health 
information exchanges (HIEs) or registries, and other sources. We also 
noted that dQMs are intended to improve the patient experience 
including quality of care, improve the health of populations, and/or 
reduce costs.
    We discuss one potential approach to developing dQM software in 
section IX.A.4.b. of the preamble of this final rule. In this section, 
we sought comment on the potential definition of dQMs in this RFI.
    We also sought feedback on how leveraging advances in technology 
(for example, FHIR APIs) to access and electronically transmit 
interoperable data for dQMs could reinforce other activities to support 
quality measurement and improvement (for example, the aggregation of 
data across multiple data sources, rapid-cycle feedback, and alignment 
of programmatic requirements).
    The transition to dQMs relies on advances in data standardization 
and interoperability. As providers and payers work to implement the 
required advances in interoperability over the next several years, we 
will continue to support reporting of eCQMs through CMS quality 
reporting programs and through the Promoting Interoperability 
programs.\810\ These fully digital measures continue to be important 
drivers of interoperability advancement and learning. As discussed in 
the next section, CMS is currently re-specifying and testing these 
measures to use FHIR rather than the currently adopted Quality Data 
Model (QDM) in anticipation of the wider use of FHIR standards. CMS 
intends to apply significant components of the output of this work, 
such as the re-specified measure logic and the learning done through 
measure testing with FHIR APIs, to define and build future dQMs that 
take advantage of the expansion of standardized, interoperable data.
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    \810\ eCQI Resource Center, https://ecqi.healthit.gov/.
---------------------------------------------------------------------------

3. Use of FHIR for Current eCQMs
    Since we adopted eCQMs in our hospital and clinician quality 
programs, we have heard from stakeholders about the technological 
challenges, burden, and related costs of reporting eCQM data. The CMS 
eCQM Strategy Project engaged with stakeholders through site visits and 
listening sessions with health systems and provider organizations to 
learn about their experiences. This stakeholder feedback identified 
recommendations to improve processes related to alignment; development; 
implementation and reporting; certification; and communication, 
education, and outreach. Over the past two years, we have focused on 
opportunities to streamline and modernize quality data collection and 
reporting processes, such as exploring FHIR[supreg] (http://hl7.org/fhir) as a framework for measure structure and data submission for 
quality reporting programs, specifically for eCQMs. FHIR is a free and 
open source standards framework (in both commercial and government 
settings) created by Health Level Seven International (HL7[supreg]) 
that establishes a common language and process for all health 
information technology. FHIR allows systems to communicate and 
information to be shared seamlessly, with a lower burden for hospitals, 
providers, clinicians, vendors, and quality measurement stakeholders. 
Specifically, for quality reporting, FHIR enables representing the data 
in eCQMs as well as provides a structure for eCQMs and reporting, using 
FHIR as the standard for all. Whereas today, multiple standards being 
used to report eCQMs is challenging and burdensome.
    We are working to convert current eCQMs to the FHIR standard. We 
are currently testing the exchange of data elements represented in FHIR 
to CMS

[[Page 45345]]

through ongoing HL7 Connectathons and integrated system testing by 
using and refining implementation guides. Submitting data through FHIR 
APIs has the potential to improve data exchange by providing consistent 
security, performance, scalability, and structure to all users. In 
addition, development of FHIR APIs could decrease provider burden by 
automating more of the measure data collection process. We continue to 
explore and expand potential applications of the FHIR standard and 
testing with eCQM use cases, and we are considering a transition to 
FHIR-based quality reporting with the use of the FHIR standard for 
eCQMs in quality and value-based reporting programs. As we move to an 
all-dQM format for quality programs, we are depending on testing 
results and community readiness to improve interoperability, reduce 
burden, and facilitate better patient care. We will continue to 
consider how to leverage the interoperability advantages offered by the 
FHIR standards and API-based data submission, including digital quality 
measurement.
4. Changes Under Consideration To Advance Digital Quality Measurement: 
Potential Actions in Four Areas to Transition to Digital Quality 
Measures by 2025
    Building on the advances in interoperability and learning from 
testing of FHIR-converted eCQMs, we aim to move fully to dQMs, 
originating from sources of health information that are captured and 
can be transmitted electronically via interoperable systems, by 2025.
    To enable this transformation, we are considering further 
modernization of the quality measurement enterprise in four major ways: 
(1) Leverage and advance standards for digital data and obtain all EHR 
data required for quality measures via provider FHIR-based APIs; (2) 
redesign our quality measures to be self-contained tools; (3) better 
support data aggregation; and (4) work to align measure requirements 
across our reporting programs, other Federal programs and agencies, and 
the private sector where appropriate.
    These changes would enable us to collect and utilize more timely, 
actionable, and standardized data from diverse sources and care 
settings to improve the scope and quality of data used in quality 
reporting and payment programs, reduce quality reporting burden, and 
make results available to stakeholders in a rapid-cycle fashion. Data 
collection and reporting efforts would become more efficient, supported 
by advances in interoperability and data standardization. Aggregation 
of data from multiple sources would allow assessments of costs and 
outcomes to be measured across multiple care settings for an individual 
patient or clinical conditions. We believe that aggregating data for 
measurement can incorporate a more holistic assessment of an 
individual's health and health care and produce the rich set of data 
needed to enable patients and caregivers to make informed decisions by 
combining data from multiple sources (for example, patient reported 
data, EHR data, and claims data) for measurement.
    Perhaps most importantly, these steps would help us deliver on the 
full promise of quality measurement and drive us toward a learning 
health system that transforms healthcare quality, safety, and 
coordination and effectively measures and achieves value-based care. 
The shift from a static to a learning health system hinges on the 
interoperability of healthcare data, and the use of standardized data. 
dQMs would leverage this interoperability to deliver on the promise of 
a learning health system wherein standards-based data sharing and 
analysis, rapid-cycle feedback, and quality measurement and incentives 
are aligned for continuous improvement in patient-centered care. 
Similarly, standardized, interoperable data used for measurement can 
also be used for other use cases, such as clinical decision support, 
care coordination and care decision support, which impacts health care 
and care quality.
    We requested comments on four potential future actions that would 
enable transformation to a fully digital quality measurement enterprise 
by 2025.
a. Leveraging and Advancing Standards for Digital Data and Obtaining 
all EHR Data Required for Quality Measures via Provider FHIR-Based APIs
    We are considering targeting the data required for our quality 
measures that utilize EHR data to be data retrieved via FHIR-based APIs 
based on standardized, interoperable data. Utilizing standardized data 
for EHR-based measurement (based on FHIR and associated implementation 
guides) and aligning where possible with interoperability requirements 
can eliminate the data collection burden providers currently experience 
with required chart-abstracted quality measures and reduce the burden 
of reporting digital quality measure results. We can fully leverage 
this advance to adapt eCQMs and expand to other dQMs through the 
adoption of interoperable standards across other digital data sources. 
We are considering methods and approaches to leverage the 
interoperability data requirements for APIs in certified health IT set 
by the ONC 21st Century Cures Act final rule to support modernization 
of CMS quality measure reporting. As discussed previously, these 
requirements will be included in certified technology in future years 
(85 FR 84825) including availability of data included in the USCDI via 
standards-based APIs, and CMS will require clinicians and hospitals 
participating in MIPS and the Promoting Interoperability Programs, 
respectively, to transition to use of certified technology updated 
consistent with the 2015 Cures Edition Update (85 FR 84825).
    Digital data used for measurement could also expand beyond data 
captured in traditional clinical settings, administrative claims data, 
and EHRs. Many important data sources are not currently captured 
digitally, such as survey and PGHD. We intend to work to innovate and 
broaden the digital data used across the quality measurement enterprise 
beyond the clinical EHR and administrative claims. Agreed upon 
standards for these data, and associated implementation guides will be 
important for interoperability and quality measurement. We will 
consider developing clear guidelines and requirements for these digital 
data that align with interoperability requirements, for example, 
requirements for expressing data in standards, exposing data via 
standards-based APIs, and incentivizing technologies that innovate data 
capture and interoperability.
    High quality data are also essential for reliable and valid 
measurement. Hence, in implementing the shift to collect all clinical 
EHR data via FHIR-based APIs, we would support efforts to strengthen 
and test the quality of the data obtained through FHIR-based APIs for 
quality measurement. We currently conduct audits of electronic data 
submitted to the Hospital IQR Program with functions including checks 
for data completeness and data accuracy, confirmation of proper data 
formatting, alignment with standards, and appropriate data cleaning (82 
FR 38398 through 38402). These functions would continue and be applied 
to dQMs and further expanded to automate the manual validation of the 
data compared to the original data source (for example, the medical 
record) where possible. Analytic advancements such as natural language 
processing, big data analytics, and artificial intelligence, can 
support this evolution. These techniques can be applied to validating 
observed patterns in data and inferences or conclusions

[[Page 45346]]

drawn from associations, as data are received, to ensure high quality 
data are used for measurement.
    We sought feedback on the goal of aligning data needed for quality 
measurement with interoperability requirements and the strengths and 
limitations of this approach. We also sought feedback on the importance 
of and approaches to supporting inclusion of PGHD and other currently 
non-standardized data. We also welcomed comment on approaches for 
testing data quality and validity.
b. Redesigning Quality Measures To Be Self-Contained Tools
    We are considering approaches for including quality measures that 
take advantage of standardized data and interoperability requirements 
that have expanded flexibility and functionality compared to CMS' 
current eCQMs. We are considering defining and developing dQM software 
as end-to-end measure calculation solutions that retrieve data from 
primarily FHIR-based resources maintained by providers, payers, CMS, 
and others; calculate measure score(s), and produce reports. In 
general, we believe to optimize the use of standardized and 
interoperable data, the software solution for dQMs should do the 
following:
     Have the flexibility to support calculation of single or 
multiple quality measure(s).
     Perform three functions--
    ++ Obtain data via automated queries from a broad set of digital 
data sources (initially from EHRs, and in the future from claims, PRO, 
and PGHD);
    ++ Calculate the measure score according to measure logic; and
    ++ Generate measure score report(s).
     Be compatible with any data source systems that implement 
standard interoperability requirements.
     Exist separately from digital data source(s) and respect 
the limitations of the functionality of those data sources.
     Be tested and updated independently of the data source 
systems.
     Operate in accordance with health information protection 
requirements under applicable laws and comply with governance functions 
for health information exchange.
     Have the flexibility to be deployed by individual health 
systems, health IT vendors, data aggregators, and health plans; and/or 
run by CMS depending on the program and measure needs and 
specifications.
     Be designed to enable easy installation for supplemental 
uses by medical professionals and other non-technical end-users, such 
as local calculation of quality measure scores or quality improvement.
     Have the flexibility to employ current and evolving 
advanced analytic approaches such as natural language processing.
     Be designed to support pro-competitive practices for 
development, maintenance, and implementation as well as diffusion of 
quality measurement and related quality improvement and clinical tools 
through, for example, the use of open-source core architecture.
    We sought comment on these suggested functionalities and other 
additional functionalities that quality measure tools should ideally 
have particularly in the context of the possible expanding availability 
of standardized and interoperable data (for example, standardized EHR 
data available via FHIR-based APIs).
    We were also interested whether and how this more open, agile 
strategy may facilitate broader engagement in quality measure 
development, the use of tools developed for measurement for local 
quality improvement, and/or the application of quality tools for 
related purposes such as public health or research.
c. Building a Pathway to Data Aggregation in Support of Quality 
Measurement
    Using multiple sources of collected data to inform measurement 
would reduce data fragmentation (or, different pieces of data regarding 
a single patient stored in many different places). Additionally, we are 
considering expanding and establishing policies and processes for data 
aggregation and measure calculation by third-party aggregators that 
include, but are not limited to, HIEs and clinical registries. 
Qualified Clinical Data Registries and Qualified Registries that report 
quality measures for eligible clinicians in the Merit-based Incentive 
Payment System (MIPS) program are potential examples \811\ at 42 CFR 
414.1440(b)(2)(iv) and (v) and 414.1440(c)(2)(iii) and (iv) and can 
also support measure reporting. We are considering establishing similar 
policies for third-party aggregators to maintain the integrity of our 
measure reporting process and to encourage market innovation.
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    \811\ Calendar Year (CY) 2021 Physician Fee Schedule Final Rule: 
Finalized (New and Updated) Qualified Clinical Data Registry (QCDR) 
and Qualified Registry Policies, https://qpp-cm-prod-content.s3.amazonaws.com/uploads/1362/QCDR%20and%20QR%20Updates%202021%20Final%20Rule%20Fact%20Sheet.pdf.
---------------------------------------------------------------------------

    We sought feedback on aggregation of data from multiple sources to 
inform measurement and potential policy considerations. We also sought 
feedback on the role data aggregators can and should play in CMS 
quality measure reporting in collaboration with providers, and how we 
can best facilitate and enable aggregation.
d. Potential Future Alignment of Measures Across Reporting Programs, 
Federal and State Agencies, and the Private Sector
    We are committed to using policy levers and working with 
stakeholders to solve the issue of interoperable data exchange and to 
transition to full digital quality measurement. We are considering the 
future potential development and multi-staged implementation of a 
common portfolio of dQMs across our regulated programs, agencies, and 
private payers. This common portfolio would require alignment of: (1) 
Measure concepts and specifications including narrative statements, 
measure logic, and value sets; and (2) the individual data elements 
used to build these measure specifications and calculate the measure 
logic. Further, the required data elements would be limited to 
standardized, interoperable data elements to the fullest extent 
possible; hence, part of the alignment strategy will be the 
consideration and advancement of data standards and implementation 
guides for key data elements. We would coordinate closely with quality 
measure developers, Federal and State agencies, and private payers to 
develop and to maintain a cohesive dQM portfolio that meets our 
programmatic requirements and that fully aligns across Federal and 
State agencies and payers to the extent possible.
    We intend for this coordination to be ongoing and allow for 
continuous refinement to ensure quality measures remain aligned with 
evolving healthcare practices and priorities (for example, PROs, 
disparities, and care coordination), and track with the transformation 
of data collection, alignment with health IT module updates including 
capabilities and standards adopted by ONC (for example, standards to 
enable APIs). This coordination would build on the principles outlined 
in HHS' National Health Quality Roadmap.\812\ It would focus on the 
quality domains of safety,

[[Page 45347]]

timeliness, efficiency, effectiveness, equitability, and patient-
centeredness. It would leverage several existing Federal and public-
private efforts including our Meaningful Measures 2.0 Framework; the 
Federal Electronic Health Record Modernization (Department of Defense 
and Veterans Affairs [DoD/VA]); the Agency for Healthcare Research and 
Quality's Clinical Decision Support Initiative; the Centers for Disease 
Control and Prevention's Adapting Clinical Guidelines for the Digital 
Age initiative; Core Quality Measure Collaborative, which convenes 
stakeholders from America's Health Insurance Plans (AHIP), CMS, 
National Quality Forum (NQF), provider organizations, private payers, 
and consumers and develops consensus on quality measures for provider 
specialties; and the NQF-convened Measure Applications Partnership 
(MAP), which recommends measures for use in public payment and 
reporting programs. We would coordinate with HL7's ongoing work to 
advance FHIR resources in critical areas to support patient care and 
measurement such as social determinants of health. Through this 
coordination, we would identify which existing measures could be used 
or evolved to be used as dQMs, in recognition of current healthcare 
practice and priorities.
---------------------------------------------------------------------------

    \812\ Department of Health and Human Services, National Health 
Quality Roadmap (May 2020). Available at: https://www.hhs.gov/sites/default/files/national-health-quality-roadmap.pdf.
---------------------------------------------------------------------------

    This multi-stakeholder, joint Federal, State, and industry effort, 
made possible and enabled by the pending advances towards true 
interoperability, would yield a significantly improved quality 
measurement enterprise. The success of the dQM portfolio would be 
enhanced by the degree to which the measures achieve our programmatic 
requirements for measures as well as the requirements of other agencies 
and payers.
    We sought feedback on initial priority areas for the dQM portfolio 
given evolving interoperability requirements (for example, measurement 
areas, measure requirements, tools, and data standards). We also sought 
to identify opportunities to collaborate with other Federal agencies, 
states, and the private sector to adopt standards and technology-driven 
solutions to address our quality measurement priorities across sectors.
5. Solicitation of Comments
    We sought input on the future development of the following:
     Definition of Digital Quality Measures. We sought feedback 
on the following as described in section IX.A.2. of the preamble of 
this final rule:
    ++ Do you have feedback on the dQM definition?
    ++ Does this approach to defining and deploying dQMs to interface 
with FHIR-based APIs seem promising? We also welcomed more specific 
comments on the attributes or functions to support such an approach of 
deploying dQMs.
     Use of FHIR for Current eCQMs. We sought feedback on the 
following as described in section IX.A.3. of the preamble of this final 
rule:
    ++ Do you agree that a transition to FHIR-based quality reporting 
can reduce burden on health IT vendors and providers?
    ++ Would access to near real-time quality measure scores benefit 
your practice?
    ++ What parts of the current CMS QRDA IGs cause the most burden?
    ++ What could we include in a CMS FHIR Reporting IG to reduce 
burden on providers and vendors?
     Changes Under Consideration to Advance Digital Quality 
Measurement: Actions in Four Areas to Transition to Digital Quality 
Measures by 2025.
    ++ We sought feedback on the following as described in section 
IX.A.4.a. of the preamble of this final rule:

--Do you agree with the goal of aligning data needed for quality 
measurement with interoperability requirements? What are the strengths 
and limitations of this approach? Are there specific FHIR 
Implementation Guides suggested for consideration?
--How important is a data standardization approach that also supports 
inclusion of PGHD and other currently non-standardized data?
--What are possible approaches for testing data quality and validity?

    ++ We sought feedback on the following as described in section 
IX.A.4.b. of the preamble of this final rule:

--What functionalities, described in Section (4)(b) or others, should 
quality measure tools ideally have in the context of the pending 
availability of standardized and interoperable data (for example, 
standardized EHR data available via FHIR-based APIs)?
--How would this more open, agile strategy for end-to-end measure 
calculation facilitate broader engagement in quality measure 
development, the use of tools developed for measurement for local 
quality improvement, and/or the application of quality tools for 
related purposes such as public health or research?
    ++ We sought feedback on the following as described in section 
IX.A.4.c. of the preamble of this final rule:

--Do you have feedback on policy considerations for aggregation of data 
from multiple sources being used to inform measurement?
--Do you have feedback on the role data aggregators can and should play 
in CMS quality measure reporting in collaboration with providers? How 
can CMS best facilitate and enable aggregation?

    ++ We sought feedback on the following as described in section 
IX.A.4.d. of the preamble of this final rule:

--What are initial priority areas for the dQM portfolio given evolving 
interoperability requirements (for example, measurement areas, measure 
requirements, tools)?
--We also sought to identify opportunities to collaborate with other 
Federal agencies, states, and the private sector to adopt standards and 
technology-driven solutions to address our quality measurement 
priorities and across sectors.

    We recommended commenters consider provisions in the CMS 
Interoperability and Patient Access final rule (85 FR 25510), CMS CY 
2021 PFS final rule (85 FR 84472), and the ONC 21st Century Cures Act 
final rule (85 FR 25642).
    We plan to continue working with other agencies and stakeholders to 
coordinate and to inform any potential transition to dQMs by 2025. 
While we will not be responding to specific comments submitted in 
response to this RFI in this FY 2022 IPPS/LTCH PPS final rule, we will 
actively consider all input as we develop future regulatory proposals 
or future subregulatory policy guidance. Any updates to specific 
program requirements related to quality measurement and reporting 
provisions would be addressed through separate and future notice-and-
comment rulemaking, as necessary.
    We received comments on these topics.
    Comment: There was widespread support among commenters for digital 
quality measurement. Several commenters supported CMS' transition to 
digital quality measurement. Several commenters noted that implementing 
FHIR would simplify the measure reporting process and produce more 
timely and actionable information. They also expressed support for 
transitioning to dQMs to reduce reliance on manual processes. Some 
comments welcomed the use of FHIR in light of the COVID-19 PHE and 
highlighted the need for harmonized data to quickly share important 
information.

[[Page 45348]]

    However, most commenters questioned the feasibility of the proposed 
2025 implementation timeline. Some commenters noted the timeline is 
ambitious. Some commenters provided feedback on what CMS could provide 
as it transitions to digital quality measurement. Commenters also 
stated that this process would be resource intensive for providers and 
healthcare systems. Commenters highlighted that measures have not been 
selected and recommended that measure specifications should be made 
available in a timely manner to reduce provider and hospital 
administrative burden. Within this context, they recommended that 
measures be vetted by stakeholders, field tested, and validated, and 
some commenters also suggested endorsement by the National Quality 
Forum (NQF). In addition, several commenters requested specialty-
specific implementation guides.
    Several commenters were concerned by the lack of accepted standards 
for social determinants of health (SDOH) data and potential data 
quality issues when mapping data from multiple sources. Other 
commenters expressed concern that dQMs could become a measure of vendor 
capabilities rather than quality of care.
    Some commenters did not support implementing FHIR. Some commenters 
expressed concern regarding the maturity of the FHIR standard for 
quality measurement reporting, versioning, and industry readiness to 
implement FHIR. They recommended that CMS support existing efforts of 
healthcare providers and health IT vendors to develop and implement 
interoperability, many of which are based on non-FHIR standards.
    Response: We appreciate all of the comments on and interest in this 
topic. We believe that this input is very valuable in the continuing 
development of our transition to digital quality measurement in CMS 
quality reporting and value-based purchasing programs by 2025. We will 
continue to take all comments into account as we develop future 
regulatory proposals or other guidance for our digital quality 
measurement efforts.
    In the FY 2022 IPPS/LTCH PPS proposed rule (86 FR 25550), we 
clarified a potential future definition of dQMs as a software that 
processes digital data to produce a measure score or measure scores.
    Comment: Several commenters appreciated CMS' clarifications of the 
dQM definition. Some commenters supported the potential definition of 
dQMs and appreciated that CMS is thinking broadly. A commenter lauded 
the potential definition, noting the payoff would be richer data and 
measures that could facilitate use of artificial intelligence and real-
time reporting.
    Other commenters stated that the potential definition is too broad 
to be meaningful and that it lacks clarity. Within this context, some 
commenters requested a more formal definition of dQMs and of terms used 
by CMS, such as patient portals or health information exchanges or 
registries. They also asked for examples to illustrate how dQMs could 
be used for quality improvement. Some commenters suggested refinements 
to the potential definition. A couple of commenters noted that dQMs 
should be viewed as a framework and that the word ``software'' in the 
potential definition is confusing as it does not align with the current 
structure of a quality measure.
    Response: We appreciate all of the comments on and interest in this 
topic. We believe that this input is very valuable in the continuing 
development of our transition to digital quality measurement in CMS 
quality reporting and value-based purchasing programs by 2025. We will 
continue to take all comments into account as we develop future 
regulatory proposals or other guidance for our digital quality 
measurement efforts.
    As noted above, we requested input on the use of FHIR for eCQMs and 
actions in four areas to transition to dQMs by 2025 including:
    (1) Leveraging and advancing standards for digital data and 
obtaining all EHR data required for quality measures via provider FHIR-
based APIs.
    (2) Redesigning quality measures to be self-contained tools.
    (3) Building a pathway to data aggregation in support of quality 
measurement.
    (4) Potential future alignment of measures across reporting 
programs, Federal and state agencies, and the private sector.
    Comment: Several commenters supported CMS' efforts to use data from 
different sources. The commenters noted capturing data through 
traditional and emerging sources, including patient-generated health 
data, could provide a comprehensive picture of patient outcomes, 
quality, and value. Further, some commenters noted the ability of dQMs 
to use multiple data sources could reduce administrative burden. 
However, others pointed out that the list includes several data 
sources, such as patient wearables, that have not been adequately 
vetted and tested.
    Several commenters noted the importance of data quality. Some 
commenters raised concerns that the accuracy and reliability of dQMs 
could be compromised by poor data quality. They recommended CMS 
consider the development of source system verification and/or 
certification criteria.
    Others noted the importance of reliable and accurate patient 
matching to ensure interoperability. They recommended using a universal 
patient identifier to allow for the matching of patient records when 
derived from different sources.
    Several commenters stated that using a multitude of data sources 
will increase the burden and costs associated with measure development 
and testing. Some commenters raised a concern that not all data are 
captured in such a way that it can be pulled via FHIR API. For example, 
radiology or lab reports are scanned into the EHR system.
    Most commenters expressed general support for FHIR-based APIs for 
quality measurement and agreed the approach will eventually reduce 
complexity and ease reporting burden over time. Some commenters 
suggested specific FHIR Implementation Guides for use, or modifying or 
expanding existing ones.
    However, several commenters expressed concerns about the use of 
FHIR-based APIs such as the infrastructure and financial readiness, 
providers' unfamiliarity with FHIR, and governance of collecting raw 
digital data, and data stewardship. Some commenters were concerned the 
transition period will place increased burden on health systems and 
providers. In addition, they noted that some health systems or 
practices may not have the infrastructure in place or the financial 
capability to develop, test, and implement dQMs. A commenter pointed 
out that pediatricians are limited by EHR functionality that focuses on 
adults. These commenters expressed support for a timeline that accounts 
for various stages of readiness across health sectors and specialties.
    Some commenters agreed with redesigning quality measures as self-
contained tools and agreed with their functionalities necessary to 
achieve digital quality measurement. They noted it would be beneficial 
to those with less technical support. Other commenters requested 
clarification on the tools and plans for validating digital measures.
    Several commenters commented on current limitations for aggregation 
such as reliable patient-matching, opportunities for data aggregation 
by third-parties, and steps CMS could take to enable aggregation, such 
as mandating standards or playing the role

[[Page 45349]]

of an aggregator. Some commenters stated that CMS should leverage 
existing infrastructure, such as HIEs, to support quality measurement 
and reporting, and real-time information sharing, while other 
commenters supported CMS serving as a data aggregator to ensure 
consistency and accuracy in quality measure reporting.
    Commenters expressed support for alignment of measurement areas, 
specifications, data elements used to build the specifications, and 
tools across reporting programs. Commenters applauded CMS working with 
stakeholders on aligning data needed for quality measurement with 
interoperability requirements, and some commenters requested 
clarification about the role of stakeholders in the process. Commenters 
also noted alignment could leverage data routinely captured during and 
across the continuum of clinical care, simplify quality reporting, 
reduce challenges associated with managing various standards and 
formats, support other use cases such as clinical decision support, and 
ultimately help achieve health equity.
    Several commenters supported the development of a common dQM 
portfolio. Some commenters suggested CMS use a common dQM portfolio as 
the framework of the ongoing transition to digital quality measurement, 
such as aligning data standards with priority areas in the portfolio. 
Some commenters encouraged CMS to identify which existing measures 
could be used as dQMs while concurrently identifying future priority 
areas. Another commenter noted CMS should implement dQMs that provide 
clinically meaningful data within one setting even if the dQMs are not 
ready to be used in other programs. This could encourage dQM 
implementation and could help enable implementation in other settings. 
On the other hand, a commenter suggested CMS align with HHS strategic 
priorities rather than a common dQM portfolio.
    Many commenters encouraged CMS to work with the ONC on data and 
interoperability standards, and relevant certification criteria for EHR 
technology. Commenters indicated that data elements should be 
consistent with the United States Core Data for Interoperability 
(USCDI) wherever possible, with a commenter noting that this is 
``critical''.
    Some commenters noted additional areas of focus or alignment 
opportunities for CMS. For example, some commenters noted the 
importance of standardizing SDOH reporting requirements or high-cost 
conditions. Others encouraged CMS to develop an immunization registry, 
noting both the importance of immunizations and the profound 
disparities in immunization rates across racial and ethnic groups as 
recognized through the COVID-19 pandemic.
    Several commenters supported a phased approach to dQM 
implementation. Several commenters requested CMS allow adequate time 
for implementation, testing, and validation to ensure successful 
transition to dQMs. Some commenters suggested CMS focus first on 
aligning data standards, then tools and measure requirements. Some 
commenters also urged CMS to consider pilot opportunities, program 
incentives, or flexibilities in reporting. A commenter requested that 
CMS consider alignment with the Interoperability and Patient Access 
final rule. Another commenter urged CMS to consider the impact of 
alignment on underserved communities and patients.
    Response: We appreciate all of the comments on and interest in this 
topic. We believe that this input is very valuable in the continuing 
development of our transition to digital quality measurement in CMS 
quality reporting and value-based purchasing programs by 2025. We will 
continue to take all comments into account as we develop future 
regulatory proposals or other guidance for our digital quality 
measurement efforts.

B. Closing the Health Equity Gap in CMS Hospital Quality Programs--
Request for Information

    Persistent inequities in health care outcomes exist in the United 
States, including among Medicare patients. In recognition of persistent 
health disparities and the importance of closing the health equity gap, 
we request information on revising several related CMS programs to make 
reporting of health disparities based on social risk factors and race 
and ethnicity more comprehensive and actionable for hospitals, 
providers, and patients. The following is part of an ongoing effort 
across CMS to evaluate appropriate initiatives to reduce health 
disparities. Feedback will be used to inform the creation of a future, 
comprehensive, RFI focused on closing the health equity gap in CMS 
programs and policies.
    This RFI contains four parts:
     Background. This section provides information describing 
our commitment to health equity, and existing initiatives with an 
emphasis on reducing health disparities.
     Current CMS Disparity Methods. This section 
describes the methods, measures, and indicators of social risk 
currently used with the CMS Disparity Methods.
     Future potential stratification of quality 
measure results by race and ethnicity. This section describes three 
potential future expansions of the CMS Disparity Methods, including (a) 
Future Potential Stratification of Quality Measure Results by Race and 
Ethnicity, (b) Improving Demographic Data Collection, and (c) Potential 
Creation of a Hospital Equity Score to Synthesize Results Across 
Multiple Social Risk Factors.
     Solicitation of public comment. This section 
specifies 10 requests for feedback on the topics listed previously. We 
received feedback on these topics and provide a summary of and response 
to some of the comments below. We also note our intention for an 
additional RFI or rulemaking on this topic in the future.
1. Background
    Significant and persistent inequities in health care outcomes exist 
in the United States. Belonging to a racial or ethnic minority group; 
living with a disability; being a member of the lesbian, gay, bisexual, 
transgender, and queer (LGBTQ+) community; living in a rural area; or 
being near or below the poverty level, is often associated with worse 
health outcomes. 813 814 815 
816 817 818 819 
820 Such disparities in health outcomes are the result of 
number of factors, but importantly for CMS programs, although not the 
sole determinant, poor access and provision of lower quality health 
care contribute

[[Page 45350]]

to health disparities. For instance, numerous studies have shown that 
among Medicare beneficiaries, racial and ethnic minority individuals 
often receive lower quality of care, report lower experiences of care, 
and experience more frequent hospital readmissions and procedural 
complications.821 822 823 
824 825 826 Readmission rates for 
common conditions in the Hospital Readmissions Reduction Program are 
higher for Black Medicare beneficiaries and higher for Hispanic 
Medicare beneficiaries with Congestive Heart Failure and Acute 
Myocardial Infarction.827 828 829 830 831 Studies have also 
shown that African Americans are significantly more likely than White 
Americans to die prematurely from heart disease and stroke.\832\ The 
COVID-19 pandemic has further illustrated many of these longstanding 
health inequities with higher rates of infection, hospitalization, and 
mortality among Black, Latino, and Indigenous and Native American 
persons relative to White persons.833 834 As noted by the 
Centers for Disease Control ``long-standing systemic health and social 
inequities have put many people from racial and ethnic minority groups 
at increased risk of getting sick and dying from COVID-19.'' \835\ One 
important strategy for addressing these important inequities is 
improving data collection to allow for better measurement and reporting 
on equity across our programs and policies.
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    \813\ Joynt KE, Orav E, Jha AK. Thirty-Day Readmission Rates for 
Medicare Beneficiaries by Race and Site of Care. JAMA. 2011; 
305(7):675-681.
    \814\ Lindenauer PK, Lagu T, Rothberg MB, et al. Income 
Inequality and 30 Day Outcomes After Acute Myocardial Infarction, 
Heart Failure, and Pneumonia: Retrospective Cohort Study. British 
Medical Journal. 2013; 346.
    \815\ Trivedi AN, Nsa W, Hausmann LRM, et al. Quality and Equity 
of Care in U.S. Hospitals. New England Journal of Medicine. 2014; 
371(24):2298-2308.
    \816\ Polyakova, M., et al. Racial Disparities In Excess All-
Cause Mortality During The Early COVID-19 Pandemic Varied 
Substantially Across States. Health Affairs. 2021; 40(2): 307-316.
    \817\ Rural Health Research Gateway. Rural Communities: Age, 
Income, and Health Status. Rural Health Research Recap. November 
2018. Available at: https://www.ruralhealthresearch.org/assets/2200-8536/rural-communities-age-income-health-status-recap.pdf.
    \818\ https://www.minorityhealth.hhs.gov/assets/PDF/Update_HHS_Disparities_Dept-FY2020.pdf.
    \819\ www.cdc.gov/mmwr/volumes/70/wr/mm7005a1.htm.
    \820\ Poteat TC, Reisner SL, Miller M, Wirtz AL. COVID-19 
Vulnerability of Transgender Women With and Without HIV Infection in 
the Eastern and Southern U.S. Preprint. medRxiv. 
2020;2020.07.21.20159327. Published 2020 Jul 24. doi:10.1101/
2020.07.21.20159327.
    \821\ Martino, SC, Elliott, MN, Dembosky, JW, Hambarsoomian, K, 
Burkhart, Q, Klein, DJ, Gildner, J, and Haviland, AM. Racial, 
Ethnic, and Gender Disparities in Health Care in Medicare Advantage. 
Baltimore, MD: CMS Office of Minority Health. 2020.
    \822\ Guide to Reducing Disparities in Readmissions. CMS Office 
of Minority Health. Revised August 2018. Available at: https://www.cms.gov/About-CMS/Agency-Information/OMH/Downloads/OMH_Readmissions_Guide.pdf.
    \823\ Singh JA, Lu X, Rosenthal GE, Ibrahim S, Cram P. Racial 
disparities in knee and hip total joint arthroplasty: An 18-year 
analysis of national Medicare data. Ann Rheum Dis. 2014 Dec; 
73(12):2107-15.
    \824\ Rivera-Hernandez M, Rahman M, Mor V, Trivedi AN. Racial 
Disparities in Readmission Rates among Patients Discharged to 
Skilled Nursing Facilities. J Am Geriatr Soc. 2019 Aug;67(8):1672-
1679.
    \825\ Joynt KE, Orav E, Jha AK. Thirty-Day Readmission Rates for 
Medicare Beneficiaries by Race and Site of Care. JAMA. 
2011;305(7):675-681.
    \826\ Tsai TC, Orav EJ, Joynt KE. Disparities in surgical 30-day 
readmission rates for Medicare beneficiaries by race and site of 
care. Ann Surg. Jun 2014;259(6):1086-1090.
    \827\ Rodriguez F, Joynt KE, Lopez L, Saldana F, Jha AK. 
Readmission rates for Hispanic Medicare beneficiaries with heart 
failure and acute myocardial infarction. Am Heart J. Aug 
2011;162(2):254-261 e253.
    \828\ Centers for Medicare and Medicaid Services. Medicare 
Hospital Quality Chartbook: Performance Report on Outcome Measures; 
2014. Available at: https://www.cms.gov/medicare/quality-initiatives-patient-assessment-instruments/hospitalqualityinits/downloads/medicare-hospital-quality-chartbook-2014.pdf.
    \829\ Guide to Reducing Disparities in Readmissions. CMS Office 
of Minority Health. Revised August 2018. Available at: https://www.cms.gov/About-CMS/Agency-Information/OMH/Downloads/OMH_Readmissions_Guide.pdf.
    \830\ Prieto-Centurion V, Gussin HA, Rolle AJ, Krishnan JA. 
Chronic obstructive pulmonary disease readmissions at minority-
serving institutions. Ann Am Thorac Soc. Dec 2013;10(6):680-684.
    \831\ Joynt KE, Orav E, Jha AK. Thirty-Day Readmission Rates for 
Medicare Beneficiaries by Race and Site of Care. JAMA. 
2011;305(7):675-681.
    \832\ Health and Human Services. Heart disease and African 
Americans. (March 29, 2021). https://www.minorityhealth.hhs.gov/omh/browse.aspx?lvl=4&lvlid=19.
    \833\ https://www.cms.gov/files/document/medicare-covid-19-data-snapshot-fact-sheet.pdf.
    \834\ Ochieng N, Cubanski J, Neuman T, Artiga S, and Damico A. 
Racial and Ethnic Health Inequities and Medicare. Kaiser Family 
Foundation. February 2021. Available at: https://www.kff.org/medicare/report/racial-and-ethnic-health-inequities-and-medicare/.
    \835\ https://www.cdc.gov/coronavirus/2019-ncov/community/health-equity/race-ethnicity.html.
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    We are committed to achieving equity in health care outcomes for 
our beneficiaries by supporting providers in quality improvement 
activities to reduce health inequities, enabling them to make more 
informed decisions, and promoting provider accountability for health 
care disparities.\836\ For the purposes of this rule, we are using a 
definition of equity established in Executive Order 13985, issued on 
January 25, 2021, as ``the consistent and systematic fair, just, and 
impartial treatment of all individuals, including individuals who 
belong to underserved communities that have been denied such treatment, 
such as Black, Latino, and Indigenous and Native American persons, 
Asian Americans and Pacific Islanders and other persons of color; 
members of religious minorities; lesbian, gay, bisexual, transgender, 
and queer (LGBTQ+) persons; persons with disabilities; persons who live 
in rural areas; and persons otherwise adversely affected by persistent 
poverty or inequality.'' \837\ We note that this definition was 
recently established and provides a useful, common definition for 
equity across different areas of government, although numerous other 
definitions of equity exist.
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    \836\ https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/QualityInitiativesGenInfo/Downloads/CMS-Quality-Strategy.pdf.
    \837\ https://www.federalregister.gov/documents/2021/01/25/2021-01753/advancing-racial-equity-and-support-for-underserved-communities-through-the-Federal-government.
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    Our ongoing commitment to closing the equity gap in CMS quality 
programs is demonstrated by a portfolio of programs aimed at making 
information on the quality of health care providers and services, 
including disparities, more transparent to consumers and providers. The 
CMS Equity Plan for Improving Quality in Medicare outlines a path to 
equity which aims to support Quality Improvement Network Quality 
Improvement Organizations (QIN-QIOs); Federal, State, territorial, 
local, and tribal organizations; providers; researchers; policymakers; 
beneficiaries and their families; and other stakeholders in activities 
to achieve health equity.\838\ The CMS Equity Plan for Improving 
Quality in Medicare focuses on three core priority areas which inform 
our policies and programs: (1) Increasing understanding and awareness 
of health disparities; (2) developing and disseminating solutions to 
achieve health equity; and (3) implementing sustainable actions to 
achieve health equity.\839\ The CMS Quality Strategy \840\ and 
Meaningful Measures Framework \841\ also include elimination of racial 
and ethnic disparities as central principles. Our efforts aimed at 
closing the health equity gap to date have included providing 
transparency of health disparities, supporting providers and health 
officials with evidence-informed solutions to address social 
determinants of health and achieve health equity, and reporting to 
providers on gaps in quality as follows:
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    \838\ Centers for Medicare & Medicaid Services Office of 
Minority Health. The CMS Equity Plan for Improving Quality in 
Medicare. 2015-2021. Available at: https://www.cms.gov/About-CMS/Agency-Information/OMH/OMH_Dwnld-CMS_EquityPlanforMedicare_090615.pdf.
    \839\ Centers for Medicare & Medicaid Services Office of 
Minority Health. The CMS Equity Plan for Improving Quality in 
Medicare. Available at: https://www.cms.gov/About-CMS/Agency-Information/OMH/OMH_Dwnld-CMS_EquityPlanforMedicare_090615.pdf.
    \840\ Centers for Medicare & Medicaid Services. CMS Quality 
Strategy. 2016. Available at: https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/QualityInitiativesGenInfo/Downloads/CMS-Quality-Strategy.pdf.
    \841\ https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/QualityInitiativesGenInfo/MMF/General-info-Sub-Page.
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     The CMS Mapping Medicare Disparities Tool which is an 
interactive map that identifies areas of disparities and is a starting 
point to understand and investigate geographic, racial and ethnic 
differences in health outcomes for Medicare patients.\842\
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    \842\ https://www.cms.gov/About-CMS/Agency-Information/OMH/OMH-Mapping-Medicare-Disparities.
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     The Racial, Ethnic, and Gender Disparities in Health Care 
in Medicare Advantage Stratified Report, which highlights racial and 
ethnic differences in health care experiences and clinical

[[Page 45351]]

care, compares quality of care for women and men, and looks at racial 
and ethnic differences in quality of care among women and men 
separately for Medicare Advantage plans.\843\
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    \843\ https://www.cms.gov/About-CMS/Agency-Information/OMH/research-and-data/statistics-and-data/stratified-reporting.
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     The Rural-Urban Disparities in Health Care in Medicare 
Report which details rural-urban differences in health care experiences 
and clinical care.\844\
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    \844\ Centers for Medicare & Medicaid Services. Rural-Urban 
Disparities in Health Care in Medicare. 2019. Available at: https://www.cms.gov/About-CMS/Agency-Information/OMH/Downloads/Rural-Urban-Disparities-in-Health-Care-in-Medicare-Report.pdf.
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     The Standardized Patient Assessment Data Elements for 
certain post-acute care Quality Reporting Programs, which now includes 
data reporting for race and ethnicity and preferred language, in 
addition to screening questions for social needs (84 FR 42536 through 
42588).
     The CMS Innovation Center's Accountable Health Communities 
Model which includes standardized collection of health-related social 
needs data.
     The Guide to Reducing Disparities which provides an 
overview of key issues related to disparities in readmissions and 
reviews set of activities that can help hospital leaders reduce 
readmissions in diverse populations.\845\
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    \845\ Guide to Reducing Disparities in Readmissions. CMS Office 
of Minority Health. Revised August 2018. Available at: https://www.cms.gov/About-CMS/Agency-Information/OMH/Downloads/OMH_Readmissions_Guide.pdf.
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     The CMS State Health Official Letter, Opportunities in 
Medicaid and CHIP to Address Social Determinants of Health (SDOH) 
released on January 7, 2021, which outlines opportunities under 
Medicaid and the Children's Health Insurance program (CHIP) to better 
address SDOH and to support states with designing programs, benefits, 
and services that can more effectively improve population health, 
reduce disability, and lower overall health care costs in the Medicaid 
and CHIP programs by addressing SDOH.\846\
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    \846\ CMS State Health Official Letter. Opportunities in 
Medicaid and CHIP to Address Social Determinants of Health. January 
7, 2021. Available at https://www.medicaid.gov/Federal-policy-guidance/downloads/sho21001.pdf.
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     The CMS Disparity Methods which provide hospital-level 
confidential results stratified by dual eligibility for condition-
specific readmission measures currently included in the Hospital 
Readmissions Reduction Program (see 84 FR 42496 through 42500 for a 
discussion of using stratified data in additional measures).
    These programs are informed by reports by the National Academies of 
Science, Engineering and Medicine (NASEM) \847\ and the Office of the 
Assistant Secretary for Planning and Evaluation (ASPE) \848\ which have 
examined the influence of social risk factors on several of our quality 
programs. In this RFI, we address only the eighth initiative as 
previously listed, the CMS Disparity Methods. We discuss the 
implementation of these methods to date and present considerations for 
continuing to improve and expand use of these methods to provide 
providers and ultimately consumers with actionable information on 
disparities in health care quality to support efforts at closing the 
equity gap.
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    \847\ National Academies of Sciences, Engineering, and Medicine. 
2016. Accounting for Social Risk Factors in Medicare Payment: 
Identifying Social Risk Factors. Washington, DC: The National 
Academies Press. https://doi.org/10.17226/21858.
    \848\ https://aspe.hhs.gov/pdf-report/report-congress-social-risk-factors-and-performance-under-medicares-value-based-purchasing-programs.
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2. Current CMS Disparity Methods
    We first sought public comment on potential public reporting of 
hospital quality measure data stratified by social risk factors in the 
FY 2017 IPPS/LTCH PPS proposed rule (81 FR 25199). In the FY 2018 IPPS/
LTCH PPS final rule (82 FR 38403 through 38409), we considered 
potential confidential reporting of the Hospital Inpatient Quality 
Reporting (IQR) Program Pneumonia Readmission (NQF#0506) and Pneumonia 
Mortality (NQF#0468) measures stratified by dual-eligibility status. We 
initially focused on stratification by dual eligibility which is 
consistent with recommendations from ASPE's First Report to Congress 
which was required by the Improving Medicare Post-Acute Care 
Transformation (IMPACT) Act of 2014 (Pub. L. 113-185).\849\ This report 
found that in the context of value-based purchasing (VBP) programs, 
dual eligibility, as an indicator of social risk, was among the most 
powerful predictors of poor health outcomes among those social risk 
factors that ASPE examined and tested. We also solicited feedback on 
the two potential methods for illuminating differences in outcomes 
rates among patient groups within a provider's patient population that 
would allow for a comparison of those differences, or disparities, 
across providers. A first method (the Within-Hospital disparity method) 
promotes quality improvement by calculating differences in outcome 
rates among patient groups within a hospital while accounting for their 
clinical risk factors. This method also allows for a comparison of the 
magnitude of disparity across hospitals, so hospitals can assess how 
well they are closing disparity gaps compared to other hospitals. The 
second methodological approach (the Across-Hospital method) is 
complementary and assesses hospitals' outcome rates for dual-eligible 
patients only, across hospitals, allowing for a comparison among 
hospitals on their performance caring for their patients with social 
risk factors. We also specifically solicited feedback on which social 
risk factors provide the most valuable information to stakeholders. 
Overall, comments supported the use of dual eligibility as a proxy for 
social risk, although commenters also suggested investigation of 
additional social risk factors, and we continue to consider which risk 
factors provide the most valuable information to stakeholders.
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    \849\ https://aspe.hhs.gov/pdf-report/report-congress-social-risk-factors-and-performance-under-medicares-value-based-purchasing-programs.
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    In the FY 2019 IPPS/LTCH PPS final rule (82 FR 41597 through 41601) 
we finalized plans to provide confidential hospital-specific reports 
(HSRs) containing stratified results of the Pneumonia Readmission (NQF# 
0506) and Pneumonia Mortality (NQF#0468) measures including both the 
Across-Hospital Disparity Method and the Within-Hospital Disparity 
Methods (disparity methods) stratified by full-benefit dual 
eligibility. In the FY 2019 final rule (83 FR 41554 through 41556) we 
also removed six condition/procedure-specific readmission measures, 
including the Pneumonia Readmission Measure (NQF#0506) (83 FR 41544 
through 41556) and five mortality measures, including the Pneumonia 
Mortality measures (NQF#0468) (83 FR 41556 through 41558) from the 
Hospital IQR Program. The Pneumonia Readmission measure (NQF#0506) and 
the other condition/procedure-specific readmission measures remained in 
the HRRP. We also noted in the FY 2019 final rule, that for the future, 
we were considering: (1) Expanding our efforts to provide stratified 
data in confidential HSRs for other measures; (2) including other 
social risk factors beyond dual eligible status in confidential HSRs; 
and (3) eventually, making stratified data publicly available on the 
Hospital Compare (now Care Compare) website or successor website (83 FR 
41598). In 2019 we provided hospitals with results of the Pneumonia 
Readmission measure (NQF#0506) stratified using full-benefit dual 
eligibility. We provided this

[[Page 45352]]

information in annual confidential HSRs for claims-based measures.
    In the FY 2020 IPPS/LTCH PPS final rule (84 FR 42388 through 42390) 
we invited public comment on our proposal to apply the disparity 
methods to additional outcome measures for confidential reporting to 
the five additional condition/procedure-specific readmission measures: 
(1) Hospital 30-Day, All-Cause, Risk-Standardized Readmission Rate 
(RSRR) Following Acute Myocardial Infarction (AMI) Hospitalization (NQF 
#0505) (AMI Readmission measure); (2) Hospital 30-Day, All-Cause, Risk-
Standardized Readmission Rate (RSRR) Following Coronary Artery Bypass 
Graft (CABG) Surgery (NQF #2515) (CABG Readmission measure); (3) 
Hospital 30-Day, All-Cause, Risk-Standardized Readmission Rate (RSRR) 
Following Chronic Obstructive Pulmonary Disease (COPD) Hospitalization 
(NQF #1891) (COPD Readmission measure); (4) Hospital 30-Day, All-Cause, 
Risk-Standardized Readmission Rate (RSRR) Following Heart Failure (HF) 
Hospitalization (NQF #0330) (HF Readmission measure); and (5) Hospital-
Level 30-Day, All-Cause, Risk-Standardized Readmission Rate (RSRR) 
Following Elective Primary Total Hip Arthroplasty (THA) and/or Total 
Knee Arthroplasty (TKA) (NQF #1551) (THA/TKA Readmission measure). Many 
commenters supported our proposal to continue to provide hospitals with 
confidential hospital-specific reports on the Pneumonia Readmission 
measure using the two disparity methods and to expand that effort to 
include the five additional condition/procedure-specific readmission 
measures. Commenters expressed concern with stratifying measure data 
based only on dual-eligibility status and recommended that we continue 
to consider and refine additional social risk factors for 
stratification in confidential HSRs and specifically consider 
additional factors that might affect outcomes or result in higher 
spending, including race, ethnicity, geographic area, sex, disability, 
education, and access to care. A commenter expressed concern about the 
reliability of race and ethnicity data if CMS should consider 
stratifying hospital quality data by such factors and recommended that 
CMS develop a proposal to improve the collection of race and ethnicity 
data or to promote public transparency using data that are of mixed 
quality, before reporting such data publicly. We replied that we 
focused our initial efforts on providing disparity results based on 
dual-eligible status because of strong evidence demonstrating worse 
health outcomes among dual-eligible Medicare beneficiaries, and because 
reliable information is readily available in our administrative claims. 
We also noted that we continue to explore opportunities to account for 
additional social risk factors in the future, including evaluating new 
sources of social risk factor data and how to capture such data, 
engaging with stakeholders, and examining the availability and 
feasibility of accounting for social risk factors which might influence 
quality outcome measures.
    ASPE's Second Report to Congress on Social Risk Factors and 
Performance in Medicare's Value-Based Purchasing Program,\850\ required 
by the Improving Medicare Post-Acute Care Transformation (IMPACT) Act 
of 2014, released in March 2020, recommended among other things, that 
CMS should explore ways to encourage providers to collect social risk 
information, that quality reporting programs should include health 
equity measures, and that quality and resource use measures should be 
reported separately for dually enrolled beneficiaries and other 
beneficiaries.
---------------------------------------------------------------------------

    \850\ Office of the Assistant Secretary for Planning and 
Evaluation (ASPE) (2020). Report to Congress: Social Risk Factors 
and Performance Under Medicare's Value-Based Purchasing Program 
(Second of Two Reports). Available at: https://aspe.hhs.gov/pdf-report/second-impact-report-to-congress.
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    In 2020, we provided hospitals with results of each of the six 
condition/procedure-specific readmission measures, for which reporting 
requirements were met, stratified using full-benefit dual eligibility. 
We provided this information in annual confidential HSRs for claims-
based measures. Results were made available for hospitals to download 
through the secure portal within the QualityNet website each spring. 
Results for the 2020 confidential reporting period for the CMS 
Disparity Methods showed worse outcomes for dually eligible 
beneficiaries across the majority of hospitals for all six condition-
specific measures.\851\ These results underscore the importance of 
continuing to make health care equity information more available to 
providers to promote quality improvement.
---------------------------------------------------------------------------

    \851\ https://qualitynet.cms.gov/inpatient/measures/disparity-methods/methodology.
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    For additional information on the two disparity methods, we refer 
readers to the technical report available on the Quality Net website 
(https://qualitynet.cms.gov/inpatient/measures/disparity-methods/resources#tab2), as well as the FY 2018 IPPS/LTCH PPS final rule (82 FR 
38405 through 38407).
3. Potential Expansion of the CMS Disparity Methods
    We are committed to advancing health equity by improving data 
collection to better measure and analyze disparities across programs 
and policies.\852\ As we described previously, we have been 
considering, among other things, expanding our efforts to provide 
stratified data for additional social risk factors and measures, 
optimizing the ease-of-use of the results, enhancing public 
transparency of equity results, and building towards provider 
accountability for health equity. We sought public comment on three 
potential future expansions of the CMS Disparity Methods, including: 
(1) Future potential stratification of quality measure results by race 
and ethnicity, (2) improving demographic data collection; and (3) the 
potential creation of a Hospital Equity Score to synthesize results 
across multiple social risk factors.
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    \852\ Centers for Medicare Services. CMS Quality Strategy. 2016. 
Available at: https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/QualityInitiativesGenInfo/Downloads/CMS-Quality-Strategy.pdf.
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a. Future Potential Stratification of Quality Measure Results by Race 
and Ethnicity
    The Administration's Executive Order on Advancing Racial Equity and 
Support for Underserved Communities Through the Federal Government 
directs agencies to assess potential barriers that underserved 
communities and individuals may face to enrollment in and access to 
benefits and services in Federal Programs. As summarized previously, 
studies have shown that among Medicare beneficiaries, racial and ethnic 
minority persons often experience worse health outcomes, including more 
frequent hospital readmissions and procedural complications. We are 
considering expanding the disparity methods to include stratification 
of the condition/procedure-specific readmission measures by race and 
ethnicity. The 1997 Office of Management and Budget (OMB) Revisions to 
the Standards for the Collection of Federal Data on Race and Ethnicity, 
outlines the racial and ethnic categories which may potentially be used 
for reporting the disparity methods, which we note are intended to be 
considered as social and cultural, and not biological or genetic.\853\ 
The

[[Page 45353]]

1997 OMB Standard lists five minimum categories of race: (1) American 
Indian or Alaska Native; (2) Asian; (3) Black or African American; (4) 
Native Hawaiian or Other Pacific Islander; (5) and White. In the OMB 
standards, Hispanic or Latino is the only ethnicity category included, 
and since race and ethnicity are two separate and distinct concepts, 
persons who report themselves as Hispanic or Latino can be of any 
race.\854\ Another example, the ``Race & Ethnicity--CDC'' code system 
in PHIN Vocabulary Access and Distribution System (VADS) \855\ permits 
a more granular structured recording of a patient's race and ethnicity 
with its inclusion of over 900 concepts for race and ethnicity. The 
recording and exchange of patient race and ethnicity at such a granular 
level can facilitate the accurate identification and analysis of health 
disparities based on race and ethnicity. Further, the ``Race & 
Ethnicity--CDC'' code system has a hierarchy that rolls up to the OMB 
minimum categories for race and ethnicity and, thus, supports 
aggregation and reporting using the OMB standard. ONC includes both the 
CDC and OMB standards in its criterion for certified health IT 
products.\856\ For race and ethnicity, a certified health IT product 
must be able to express both detailed races and ethnicities using any 
of the 900 plus concepts in the ``Race & Ethnicity--CDC'' code system 
in the Public Health Information Network (PHIN) Vocabulary Access and 
Distribution Systems (VADS), as well as aggregate each one of a 
patient's races and ethnicities to the categories in the OMB standard 
for race and ethnicity. This approach can reduce burden on providers 
recording demographics using certified products.
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    \853\ Revisions to the standards for the classification of 
Federal data on race and ethnicity. 62 FR 58782-58790.
    \854\ https://www.census.gov/topics/population/hispanic-origin/about.html.
    \855\ https://phinvads.cdc.gov/vads/ViewValueSet.action?id=67D34BBC-617F-DD11-B38D-00188B398520.
    \856\ See https://www.healthit.gov/isa/representing-patient-race-and-ethnicity. For more information about the certification 
criterion for ``Demographics'' in the ONC Health IT Certification 
program, see https://www.healthit.gov/test-method/demographics.
---------------------------------------------------------------------------

    Self-reported race and ethnicity data are the gold standard for 
classifying an individual according to race or ethnicity. However, CMS 
currently does not consistently collect self-reported race and 
ethnicity for the Medicare program, but instead gets the data from the 
Social Security Administration (SSA) and the data accuracy and 
comprehensiveness have proven challenging despite capabilities in the 
marketplace via certified health IT products. Historical inaccuracies 
in Federal data systems and limited collection classifications have 
also contributed to the limited quality of race and ethnicity 
information in our administrative data systems.\857\ In recent decades, 
to address these data quality issues, we have undertaken numerous 
initiatives, including updating data taxonomies and conducting direct 
mailings to some beneficiaries to enable more comprehensive racial and 
ethnic identification.858 859 Despite those efforts, studies 
reveal varying data accuracy in identification of racial and ethnic 
groups in Medicare administrative data, with higher sensitivity for 
correctly identifying White and Black individuals, and lower 
sensitivity for correctly identifying individuals of Hispanic ethnicity 
or of Asian/Pacific Islander (API) and American Indian/Alaskan Native 
race.\860\ Incorrectly classified race or ethnicity may result in 
overestimation or underestimation in the quality of care received by 
certain groups of beneficiaries.
---------------------------------------------------------------------------

    \857\ Zaslavasky AM, Ayanian JZ, Zaborski LB. The validity of 
racial and ethnic codes in enrollment data for Medicare 
beneficiaries. Health Services Research, 2012 Jun (47) (3 Pt 2): 
1300-21.
    \858\ Filice CE, Joynt KE. Examining Race and Ethnicity 
Information in Medicare Administrative Data. Med Care. 2017; 
55(12):e170-e176. doi:10.1097/MLR.0000000000000608.
    \859\ Eicheldinger, C., & Bonito, A. (2008). More accurate 
racial and ethnic codes for Medicare administrative data. Health 
Care Financing Review, 29(3), 27-42.
    \860\ Zaslavsky AM, Ayanian JZ, Zaborski LB. The validity of 
race and ethnicity in enrollment data for Medicare beneficiaries. 
Health Serv Res. 2012 Jun;47(3 Pt 2):1300-21.
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    We continue to work with Federal and private partners to better 
collect and leverage data on social risk to improve our understanding 
of how these factors can be better measured in order to close the 
health equity gap. Among other things, we have developed an Inventory 
of Resources for Standardized Demographic and Language Data Collection 
\861\ and supported collection of specialized International 
Classification of Disease, 10th Edition, Clinical Modification (ICD-10-
CM) codes for describing the socioeconomic, cultural, and environmental 
determinants of health, and sponsored several initiatives to 
statistically estimate race and ethnicity information when it is 
absent.\862\ The Office of the National Coordinator for Health 
Information Technology (ONC) included social, psychological, and 
behavioral standards in the 2015 Edition health information technology 
certification criteria (2015 Edition), providing interoperability 
standards (LOINC [Logical Observation Identifiers Names and Codes] and 
SNOMED CT [Systematized Nomenclature of Medicine--Clinical Terms]) for 
financial strain, education, social connection and isolation, and 
others. Additional stakeholder efforts underway to expand capabilities 
to capture additional social determinants of health data elements 
include the Gravity Project to identify and harmonize social risk 
factor data for interoperable electronic health information exchange 
for EHR fields, as well as proposals to expand the ICD-10 
(International Classification of Diseases, Tenth Revision) Z-codes, the 
alphanumeric codes used worldwide to represent diagnoses.\863\
---------------------------------------------------------------------------

    \861\ Centers for Medicare & Medicaid Services. Building an 
Organizational Response to Health Disparities Inventory of Resources 
for Standardized Demographic and Language Data Collection. 2020. 
Available at: https://www.cms.gov/About-CMS/Agency-Information/OMH/Downloads/Data-Collection-Resources.pdf.
    \862\ https://pubmed.ncbi.nlm.nih.gov/18567241/,https://pubmed.ncbi.nlm.nih.gov/30506674/, Eicheldinger C, Bonito A. More 
accurate racial and ethnic codes for Medicare administrative data. 
Health Care Financ Rev. 2008; 29(3):27-42. Haas A, Elliott MN, 
Dembosky JW, et al. Imputation of race/ethnicity to enable 
measurement of HEDIS performance by race/ethnicity. Health Serv Res. 
2019; 54(1):13-23. doi:10.1111/1475-6773.13099.
    \863\ https://aspe.hhs.gov/pdf-report/second-impact-report-to-congress.
---------------------------------------------------------------------------

    While development of sustainable and consistent programs to collect 
data on social determinants of health can be considerable undertakings, 
we recognize that another method to identify better race and ethnicity 
data is needed in the short term to address the need for reporting on 
health equity. In working with our contractors, two algorithms have 
been developed to indirectly estimate the race and ethnicity of 
Medicare beneficiaries (as described further in the next section). We 
believe that using indirect estimation can help to overcome the current 
limitations of demographic information and enable timelier reporting of 
equity results until longer term collaborations to improve demographic 
data quality across the health care sector materialize. The use of 
indirect estimated race and ethnicity for conducting stratified 
reporting does not place any additional collection or reporting burdens 
on hospitals as these data are derived using existing administrative 
and census-linked data.
    Indirect estimation relies on a statistical imputation method for 
inferring a missing variable or improving an imperfect administrative 
variable using a related set of information that is more readily 
available.\864\ Indirectly estimated data

[[Page 45354]]

are most commonly used at the population level (such as the hospital or 
health plan-level) where aggregated results form a more accurate 
description of the population than existing, imperfect data sets. These 
methods often estimate race and ethnicity using a combination of other 
data sources which are predictive of self-identified race and 
ethnicity, such as language preference, information about race and 
ethnicity in our administrative records, first and last names matched 
to validated lists of names correlated to specific national origin 
groups, and the racial and ethnic composition of the surrounding 
neighborhood. Indirect estimation has been used in other settings to 
support population-based equity measurement when self-identified data 
are not available.\865\
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    \864\ Institute of Medicine. 2009. Race, Ethnicity, and Language 
Data: Standardization for Health Care Quality Improvement. 
Washington, DC: The National Academies Press. Available at: https://www.ahrq.gov/sites/default/files/publications/files/iomracereport.pdf.
    \865\ Institute of Medicine. 2009. Race, Ethnicity, and Language 
Data: Standardization for Health Care Quality Improvement. 
Washington, DC: The National Academies Press. Available at: https://www.ahrq.gov/sites/default/files/publications/files/iomracereport.pdf.
---------------------------------------------------------------------------

    As described earlier, we previously supported the development of 
two such methods of indirect estimation of race and ethnicity among 
Medicare beneficiaries. One indirect estimation approach developed by 
our contractor uses Medicare administrative data, first name and 
surname matching, derived from the U.S. Census and other sources, with 
beneficiary language preference, State of residence, and the source of 
the race and ethnicity code in Medicare administrative data to 
reclassify some beneficiaries as Hispanic or Asian/Pacific Islander 
(API).\866\ In recent years, we have also worked with another 
contractor to develop a new approach, the Medicare Bayesian Improved 
Surname Geocoding (MBISG), which combines Medicare administrative data, 
first and surname matching, geocoded residential address linked to the 
2010 U.S. Census, and uses both Bayesian updating and multinomial 
logistic regression to estimate the probability of belonging to each of 
six racial/ethnic groups.\867\
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    \866\ Bonito AJ, Bann C, Eicheldinger C, Carpenter L. Creation 
of New Race-Ethnicity Codes and Socioeconomic Status (SES) 
Indicators for Medicare Beneficiaries. Final Report, Sub-Task 2. 
(Prepared by RTI International for the Centers for Medicare and 
Medicaid Services through an interagency agreement with the Agency 
for Healthcare Research and Policy, under Contract No. 500-00-0024, 
Task No. 21) AHRQ Publication No. 08-0029-EF. Rockville, MD, Agency 
for Healthcare Research and Quality. January 2008. Available at: 
https://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.233.6403&rep=rep1&type=pdf.
    \867\ Haas, A., Elliott, M. et al (2018). Imputation of race/
ethnicity to enable measurement of HEDIS performance by race/
ethnicity. Health Services Research, 54:13-23 and Bonito AJ, Bann C, 
Eicheldinger C, Carpenter L. Creation of New Race-Ethnicity Codes 
and Socioeconomic Status (SES) Indicators for Medicare 
Beneficiaries. Final Report, Sub-Task 2. (Prepared by RTI 
International for the Centers for Medicare and Medicaid Services 
through an interagency agreement with the Agency for Healthcare 
Research and Policy, under Contract No. 500-00-0024, Task No. 21) 
AHRQ Publication No. 08-0029-EF. Rockville, MD, Agency for 
Healthcare Research and Quality. January 2008. Available at: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6338295/pdf/HESR-54-13.pdf.
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    The MBISG model is currently used to conduct the national, 
contract-level, stratified reporting of Medicare Part C & D performance 
data for Medicare Advantage Plans by race and ethnicity.\868\ 
Validation testing reveals concordances of 0.88 through 0.95 between 
indirectly estimated and self report among individuals who identify as 
White, Black, Hispanic, and API for MBISG version 2.0 and concordances 
with self-reported race and ethnicity of 0.96 through 0.99 for these 
API, Black, Hispanic, and White beneficiaries for MBISG version 
2.1.869 870 871 The algorithms under consideration are 
considerably less accurate for individuals who self-identify as 
American Indian/Alaskan Native or multiracial. \872\ Indirect 
estimation can be a statistically reliable approach for calculating 
population-level equity results for groups of individuals (such as the 
hospital-level) and is not intended, nor being considered, as an 
approach for inferring the race and ethnicity of an individual.
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    \868\ The Office of Minority Health (2020). Racial, Ethnic, and 
Gender Disparities in Health Care in Medicare Advantage, The Centers 
for Medicare and Medicaid Services, (pg vii). https://www.cms.gov/About-CMS/Agency-Information/OMH/research-and-data/statistics-and-data/stratified-reporting.
    \869\ The Office of Minority Health (2020). Racial, Ethnic, and 
Gender Disparities in Health Care in Medicare Advantage, The Centers 
for Medicare and Medicaid Services, (pg vii). https://www.cms.gov/About-CMS/Agency-Information/OMH/research-and-data/statistics-and-data/stratified-reporting.
    \870\ MBISG 2.1 validation results performed under contract #GS-
10F-0012Y/HHSM-500-2016-00097G. Pending public release of the 2021 
Part C and D Performance Data Stratified by Race, Ethnicity, and 
Gender Report, available at: https://www.cms.gov/About-CMS/Agency-Information/OMH/research-and-data/statistics-and-data/stratified-reporting.
    \871\ We note to readers that in this final rule we clarify this 
sentence to read as follows: Validation testing reveals concordances 
with self-reported race and ethnicity of 0.96 through 0.99 for API, 
Black, Hispanic, and White beneficiaries for MBISG version 2.1.59.
    \872\ Haas, A, Elliott, MN, Dembosky, JW, et al. Imputation of 
race/ethnicity to enable measurement of HEDIS performance by race/
ethnicity. Health Serv Res. 2019; 54: 13-23. https://doi.org/10.1111/1475-6773.13099.
---------------------------------------------------------------------------

    However, despite the high degree of statistical accuracy of the 
indirect estimation algorithms under consideration, there remains the 
small risk of unintentionally introducing measurement bias. For 
example, if the indirect estimation is not as accurate in correctly 
estimating race and ethnicity in certain geographies or populations it 
could lead to some bias in the method results. Such bias might result 
in slight overestimation or underestimation of the quality of care 
received by a given group. We believe this amount of bias is 
considerably less than would be expected if stratified reporting were 
conducted using the race and ethnicity currently contained in our 
administrative data. Indirect estimation of race and ethnicity is 
envisioned as an intermediate step, filling the pressing need for more 
accurate demographic information for the purposes of exploring 
inequities in service delivery, while allowing newer approaches, as 
described in the next section, for improving demographic data 
collection to progress. We were interested in learning more about, and 
solicited comments about, the potential benefits and challenges 
associated with measuring hospital equity using an imputation algorithm 
to enhance existing administrative data quality for race and ethnicity 
until self-reported information is sufficiently available.
b. Improving Demographic Data Collection
    Stratified hospital-level reporting using indirectly estimated race 
and ethnicity would represent an important advance in our ability to 
provide accurate equity reports to hospitals. However, self-reported 
race and ethnicity data are the gold standard for classifying an 
individual according to race or ethnicity. The CMS Quality Strategy 
outlines our commitment to strengthening infrastructure and data 
systems by ensuring that standardized demographic information is 
collected to identify disparities in health care delivery 
outcomes.\873\ Collection and sharing of a standardized set of social, 
psychological, and behavioral data by hospitals, including race and 
ethnicity, using electronic data definitions which permit nationwide, 
interoperable health information exchange, can significantly enhance 
the accuracy and robustness of our equity reporting.\874\ This could

[[Page 45355]]

potentially include expansion of stratified reporting to additional 
social factors, such as language preference and disability status, 
where accuracy of administrative data is currently limited. We are 
mindful that additional resources, including data collection and staff 
training may be necessary to ensure that conditions are created whereby 
all patients are comfortable answering all demographic questions, and 
that individual preferences for non-response are maintained.
---------------------------------------------------------------------------

    \873\ Centers for Medicare & Medicaid Services. CMS Quality 
Strategy. 2016. Available at: https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/QualityInitiativesGenInfo/Downloads/CMS-Quality-Strategy.pdf.
    \874\ The Office of the National Coordinator for Health 
Information Technology. United State Core Data for Interoperability 
Draft Version 2. 2021. Available at: https://www.healthit.gov/isa/sites/isa/files/2021-01/Draft-USCDI-Version-2-January-2021-Final.pdf.
---------------------------------------------------------------------------

    We note that eligible hospitals and CAHs participating in the 
Medicare Promoting Interoperability Program must use certified EHR 
technology (CEHRT) that has been certified to the 2015 Edition of 
health IT certification criteria. As noted previously, the 
certification criterion for Demographics under the 2015 Edition (at 45 
CFR 170.315(a)(5)) supports collection of data using both the OMB 
standards for collecting data on race and ethnicity as well as the more 
granular ``Race & Ethnicity--CDC'' standard. In the 2020 ONC 21st 
Century Cures Act final rule, ONC also adopted a new framework for the 
core data set which certified health IT products must exchange, called 
the United States Core Data for Interoperability (USCDI) (85 FR 25669). 
The USCDI incorporates the demographic data and associated code sets 
finalized for the 2015 Edition certification criteria.
    As noted previously, ONC also finalized a certification criterion 
in the 2015 Edition which supports a certified health IT product's 
ability to collect social, psychological, and behavioral data (at 45 
CFR 170.315(a)(15)). However, this functionality is not included as 
part of the certified EHR technology required by the Promoting 
Interoperability program. While the technical functionality exists to 
achieve the gold standard of data collection, we understand challenges 
and barriers exist in using the technologies with these capabilities.
    We were interested in learning about, and solicited comments on, 
current data collection practices by hospitals to capture demographic 
data elements (such as race, ethnicity, sex, sexual orientation, and 
gender identity (SOGI), language preference, tribal membership, and 
disability status). Further, we sought comment on potential challenges 
facing hospital collection, at the time of admission, of a minimum set 
of demographic data elements in alignment with national data collection 
standards (such as the standards finalized by the Affordable Care Act 
\875\) and standards for interoperable exchange (such as the United 
States Core Data for Interoperability incorporated into certified 
health IT products as part of the 2015 Edition of health IT 
certification criteria \876\). Advancing data interoperability through 
collection of a minimum set of demographic data collection, and 
incorporation of this demographic information into quality measure 
specifications, has the potential for improving the robustness of the 
disparity method results, potentially permitting reporting using more 
accurate, self-reported information, such as race and ethnicity, and 
expanding reporting to additional dimensions of equity, including 
stratified reporting by disability status.
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    \875\ https://minorityhealth.hhs.gov/assets/pdf/checked/1/Fact_Sheet_Section_4302.pdf.
    \876\ https://www.healthit.gov/isa/united-states-core-data-interoperability-uscdi.
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c. Potential Creation of a Hospital Equity Score To Synthesize Results 
Across Multiple Social Risk Factors
    As we previously described, we are considering expanding the 
disparity methods to include two social risk factors (dual eligibility 
which is currently reported and race/ethnicity, which is considered 
here in this RFI). This approach would improve the comprehensiveness of 
health equity information provided to hospitals. Aggregated results 
from multiple measures and multiple social factors, using output from 
the disparity methods, in the format of a summary score, can improve 
the usefulness of the equity results. In working with our contractors, 
we recently developed an equity summary score for Medicare Advantage 
contracts/plans, the Health Equity Summary Score (HESS), with 
application to stratified reporting using two social risk factors: Dual 
eligibility and race and ethnicity, as described in Incentivizing 
Excellent Care to At-Risk Groups with a Health Equity Summary 
Score.\877\
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    \877\ Agniel D, Martino SC, Burkhart Q, et al. Incentivizing 
Excellent Care to At-Risk Groups with a Health Equity Summary Score. 
J Gen Intern Med. Published online November 11, 2019. doi:10.1007/
s11606-019-05473-x.
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    The HESS calculates standardized and combined performance scores 
synthesized across the two social risk factors. The HESS also combines 
results of the within-plan method (similar to the Within-Hospital 
method) and across-plan method (similar to the Across-Hospital method) 
across multiple performance measures.\878\
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    \878\ Agniel D, Martino SC, Burkhart Q, et al. Incentivizing 
Excellent Care to At-Risk Groups with a Health Equity Summary Score. 
J Gen Intern Med. Published online November 11, 2019. doi:10.1007/
s11606-019-05473-x.
---------------------------------------------------------------------------

    We are considering creating a Hospital Equity Score, not yet 
developed, which would be modeled off the HESS, but adapted to the 
context of risk-adjusted hospital outcome measures and potentially 
other hospital quality measures used in CMS programs. We envision that 
the Hospital Equity Score would synthesize results for a range of 
measures and use multiple social risk factors which have been reported 
to hospitals as part of the CMS Disparity Methods. We believe that 
creation of the Hospital Equity Score has the potential to supplement 
the overall measure data already reporting on the Care Compare or 
successor website, by providing easy to interpret information regarding 
disparities measured within individual hospitals and across hospitals 
nationally. A summary score would be useful to decrease burden by 
minimizing the number of measure results provided and providing an 
overall indicator of equity.
    The Hospital Equity Score under consideration would potentially--
     Summarize hospital performance across multiple social risk 
factors (initially dual eligibility and race and ethnicity, as 
described previously); and
     Summarize hospital performance across the two disparity 
methods (that is, the Within-Hospital Disparity Method and the Across-
Hospital Disparity Method) and potentially multiple measures.
    Prior to any potential future public reporting, if we determine 
that a Hospital Equity Score can be feasibly and accurately calculated, 
we intend to initially provide results of the Hospital Equity Score in 
confidential HSRs which hospitals will be able download. Any potential 
future proposal to display the Hospital Equity Score on the Care 
Compare or successor website would be made through future rulemaking.
4. Solicitation of Public Comment
    We sought comment on the possibility of expanding our current 
disparities methods to include reporting by race and ethnicity using 
indirect estimation. We also sought comment on the possibility of 
hospital collection of standardized demographic information for the 
purposes of potentially incorporating into measure specifications to 
permit more robust equity measurement. Additionally, we sought comment 
on the design of a

[[Page 45356]]

Hospital Equity Score for calculating results across multiple social 
risk factors and measures, including race/ethnicity and dual 
eligibility. Any data pertaining to these areas that are recommended 
for collection for measure reporting for a CMS program and any 
potential public disclosure on Care Compare or successor website would 
be addressed through separate and future notice- and-comment 
rulemaking. We plan to continue working with ASPE, hospitals, the 
public, and other key stakeholders on this important issue to identify 
policy solutions that achieve the goals of attaining health equity for 
all patients and minimizing unintended consequences. We received 
feedback on these topics and provide a summary of and response to some 
of the comments below. We also note our intention for additional RFI or 
rulemaking on this topic in the future.
    Specifically, we invited public comment on the following:
 Future Potential Stratification of Quality Measure Results by 
Race and Ethnicity
    ++ The potential future application of an algorithm to indirectly 
estimate race and ethnicity to permit stratification of measures (in 
addition to dual-eligibility) for hospital--level disparity reporting, 
until more accurate forms of self-identified demographic information 
are available.
    ++ Appropriate privacy safeguards with respect to data produced 
from the indirect estimation of race and ethnicity to ensure that such 
data is properly identified if/when it is shared with providers.
    ++ Ways to address the challenges of defining and collecting 
accurate and standardized self-identified demographic information, 
including information on race and ethnicity, disability, and language 
preference for the purposes of reporting, measure stratification, and 
other data collection efforts relating to quality.
    ++ Recommendations for other types of feasibly collected data 
elements for measuring disadvantage and discrimination, for the 
purposes of quality reporting and measure stratification, in addition 
to, or in combination with, race and ethnicity.
    ++ Recommendations for other types of quality measures or 
measurement domains, in addition to readmission measures, to prioritize 
for stratified reporting by dual eligibility, race and ethnicity, and 
disability.
    ++ Examples of approaches, methods, research, and/or considerations 
for use of data-driven technologies that do not facilitate exacerbation 
of health inequities, recognizing that biases may occur in algorithms 
or be encoded in datasets.
 Improving Demographic Data Collection
    ++ Experiences of users of certified health IT regarding local 
adoption of practices for collection of demographic elements, the 
perceived value of using these data for improving decision-making and 
care delivery, and the potential challenges and benefits of collecting 
and using more granular, structured demographic information, such as 
the ``Race & Ethnicity--CDC'' code system.
    ++ The possible collection of a minimum set of demographic data 
elements (such as race, ethnicity, sex, sexual orientation and gender 
identity (SOGI), primary language, tribal membership, and disability 
status), by hospitals at the time of admission, using electronic data 
definitions which permit nationwide, interoperable health information 
exchange, for the purposes of incorporating into measure specifications 
and other data collection efforts relating to quality.
 Potential Creation of a Hospital Equity Score To Synthesize 
Results Across Multiple Social Risk Factors
    ++ The possible creation and confidential reporting of a Hospital 
Equity Score to synthesize results across multiple social risk factors, 
proxies for social risk, and disparity measures.
    ++ Interventions hospitals could institute to improve a low 
Hospital Equity Score and how improved demographic data could assist 
with these efforts.
    We received comments on these topics.
    Comment: Many commenters supported the collection of data that 
would permit stratification of quality measures by race, ethnicity, and 
dual eligibility status. Some commenters recommended that CMS continue 
to explore ways to stratify quality measures, such as including more 
subcategories for race and ethnicity or collecting data on additional 
demographic categories like language and disability. A commenter noted 
that CMS could provide confidential feedback reports regarding quality 
measures stratified using such data. Several commenters noted that such 
stratified reporting could lead to more targeted interventions. A 
commenter was concerned about reporting stratified measures, noting 
that some categories for race and ethnicity may have small sample 
sizes. Another commenter was concerned that expanding stratified 
reporting may increase burden on providers and negatively impact the 
patient experience.
    Response: We thank the commenters for their feedback. We agree that 
stratified hospital-level reporting by dual eligibility status, 
indirectly estimated race and ethnicity, and other demographic and 
social factors has potential to support quality improvement activities 
to improve quality of care and reduce disparities in hospital outcomes. 
We intend to provide future confidential feedback reports to providers 
on quality measure performance across our quality programs, broken out 
by race and ethnicity. We will consider the feasibility of measures for 
stratification and specific programs for confidential reporting, as 
well as the timeframes for confidential reporting and a potential 
transition to public reporting on an individual basis in collaboration 
with our stakeholders.
    Comment: Commenters also noted the need to create standards for 
data collection, as these standards could impact stratification. A 
commenter noted that the demand on provider staff resources should be 
considered as CMS develops standards and methodologies for collecting 
demographic data. Methodologies for stratification could include ways 
to compare similar facilities characterized by payer mix, patient mix, 
and levels of funding and resources. A commenter noted that lack of 
standardization in data collection could impact documentation of mixed-
race individuals specifically.
    Response: We appreciate the feedback provided by the commenters 
regarding approaches for incorporating additional demographic 
characteristics into analyses that address and advance health equity. 
When considering future policy development, CMS intends that conduct 
any future collection of demographic and social risk factor data would 
be conducted in a manner that minimizes provider reporting burden. We 
will take commenters' feedback into consideration in future policy 
development.
    Comment: Several commenters supported the indirect estimation of 
race and ethnicity but noted some caveats. For example, commenters 
recommended that methods for indirect estimation should be validated 
and vetted by recognized authorities such as the National Quality 
Forum. A commenter noted that indirect estimation of race and ethnicity 
could help overcome limitations regarding demographic information 
available in existing data sources. Several commenters preferred using 
self-

[[Page 45357]]

reported data to identify race and ethnicity, rather than indirect 
methods, noting that self-reported data is the preferred ``gold-
standard'' for information on these demographic characteristics. A 
commenter suggested that indirect estimation should be used to assist 
hospitals in assessing race and ethnicity data completeness, rather 
than using outcome performance. A few commenters opposed indirect 
estimation because it may introduce bias in data or discourage 
hospitals from improving their data collection efforts. These 
commenters recommended CMS focus on supporting efforts to improve data 
collection instead of indirect estimation. For example, a commenter 
recommended training providers to get better self-reported data from 
individuals. A commenter provided feedback about the methodology for 
indirect estimation and noted that using first and last names matched 
to specific national origin groups, and using the racial and ethnic 
composition of the neighborhood surrounding a particular facility is 
not recommended because it too closely resembles a long standing 
`racial profiling' stigma.
    Response: We are sensitive to the concerns raised by stakeholders 
about indirect estimation. As we summarized in the FY 2022 IPPS/LTCH 
PPS proposed rule, the Medicare program has historically not collected 
information directly from beneficiaries on race and ethnicity, instead 
relying on data collected by the Social Security Administration, which 
is limited in several ways. A number of barriers contribute to this 
information being insufficiently accurate to examine hospital-level 
disparities (86 FR 25558 through 25561). For example, prior to 1980, 
only three categories (White, Black, and Other) were available for 
individuals to self-report race, and respondents were not able to 
indicate Asian, American Indian/Alaska Native, Hispanic, or Pacific 
Islander identities. As a result of these constrained response options, 
many current beneficiaries may not have had the opportunity to 
accurately self-report their race and ethnicity. Although we have 
undertaken significant efforts to update incorrect race and ethnicity 
information many inaccuracies remain, limiting our ability to 
accurately measure disparities. In addition, there is a significant 
portion of beneficiaries for which race and ethnicity has not been 
collected and is unknown.
    As summarized in the FY 2022 IPPS/LTCH PPS proposed rule, in recent 
years we have sponsored the development of two indirect estimation 
algorithms, both intended to correct and improve administrative 
information on race and ethnicity (86 FR 25558 through 25561). Indirect 
estimation methods such as these can generally be used in two different 
ways (a) to estimate race and ethnicity in the absence of self-reported 
data or to (b) improve administrative data in which beneficiaries 
provided a self-report of race and ethnicity but were not permitted a 
full set of response options (post-1980).\879\ While there is evidence 
supporting the validity of both approaches, the method described in (b) 
has proven to be particularly accurate, where indirect estimation 
allows better estimation of the responses people would give when 
permitted a full set of response options, based on the administrative 
variables. The option we are considering, as described situation (b) 
uses an algorithm to augment existing data to allow a constrained 
administrative self-reported variable to better match what Medicare 
beneficiaries themselves may have chosen when given a comprehensive set 
of response options on race and ethnicity.
---------------------------------------------------------------------------

    \879\ Office of Management and Budget, DIRECTIVE NO. 15, Race 
and Ethnic Standards for Federal Statistics and Administrative 
Reporting, available at: https://wonder.cdc.gov/wonder/help/populations/bridged-race/directive15.html.
---------------------------------------------------------------------------

    One of the algorithms under consideration, the Medicare Bayesian 
Improved Surname Geocoding Version 2.1 (MBISG) uses the original 
beneficiary self-report, but uses additional information supplied by 
Medicare beneficiaries and information about neighborhood composition, 
to provide a better estimation of what Medicare beneficiaries would 
self-report when given a full set of response options for race and 
ethnicity. With respect to Asian and Pacific Islander, Black, Hispanic 
and White Medicare beneficiaries, the improved version of the 
administrative variable has 96-99 percent concordance with what 
Medicare beneficiaries themselves report when allowed a full set of 
response options, matching better than the original self-reported 
variable in which most Medicare beneficiaries were not allowed to 
indicate Asian, American Indian/Alaska Native, Hispanic, or Pacific 
Islander identities.\880\ The MBISG also offers distinct advantages 
because it generates probabilities of identification in each racial and 
ethnic group for each beneficiary, as opposed to an assignment to a 
single group, allowing for more robust disparity estimates that reflect 
individuals who identify with more than one racial or ethnic group.
---------------------------------------------------------------------------

    \880\ MBISG 2.1 validation results performed under contract #GS-
10F-0012Y/HHSM-500-2016-00097G. Pending public release of the 2021 
Part C and D Performance Data Stratified by Race, Ethnicity, and 
Gender Report, available at: https://www.cms.gov/About-CMS/Agency-Information/OMH/research-and-data/statistics-and-data/stratified-reporting.
---------------------------------------------------------------------------

    The MBISG incorporates multiple sources of information to develop 
probabilities for beneficiary identification with particular racial and 
ethnic groups. In addition to surname matching, where accuracy may vary 
within certain national origin groups, the model also considers 
information on race and ethnicity which that person reported to the 
SSA, the person's first name, the composition of the census block group 
where they live, and other demographic information that Medicare 
beneficiary shared. Through such a holistic approach, the MBISG can 
make accurate comparisons between groups of Medicare beneficiaries 
regarding the quality of care received, including groups where surname 
matching alone may be less accurate, for example, people of certain 
national origin groups and people who changed their surnames upon 
marriage. The MBISG is also designed to consider those who identify as 
multiracial and allows measurement in Census categories that 
distinguish those who chose a single racial identity or more than one, 
as well as considering endorsement of Hispanic ethnicity. Notably, we 
do not believe the MBISG is well suited to make inferences about single 
individuals, only inferences about aggregated groups; while individuals 
may be misclassified based on names or residence, validation studies 
indicate that in aggregate these errors do not bias the results in 
either direction.
    We agree that self-reported demographic information is the gold 
standard and are committed to continuing to efforts to enhance data 
collection, standardization, and interoperability, as summarized in the 
FY 2022 IPPS/LTCH PPS proposed rule, although we recognize that these 
efforts often take time to materialize (86 FR 25554 through 25561). We 
believe that use of statistical imputation models, such as the MBISG, 
will permit us to provide more accurate, less biased information on 
disparities in hospital outcomes until higher quality data are 
available. As noted in IX.B.3 we intend to provide information to 
providers on quality measure performance across our quality programs in 
the future, broken out by race and ethnicity in confidential feedback 
reports. We will consider the timeframe for confidential and public 
reporting, measures to include in reporting, methodological 
feasibility, and specific programs, on an individual

[[Page 45358]]

basis in collaboration with our stakeholders.
    Comment: Many commenters supported the collection of additional 
social and demographic data, including the development of a minimum 
dataset. A commenter noted using the ONC United States Core Data for 
Interoperability as a minimum dataset would be one method of ensuring 
standardization and accuracy in reported data. Commenters agreed that a 
standardized approach for data collection is necessary to have complete 
and consistent data and would lead to more accurate stratification of 
quality measures. Some commenters recommended that data collection 
approaches should align with requirements for other state or Federal 
agencies and programs. For example, a commenter suggested working with 
the OMB to refine and update the Federal requirements for social 
determinants of health and sexual orientation and gender identity data 
collection. A commenter suggested that a standardized data collection 
system was necessary to create a health equity score and explore 
disparities. Some commenters suggested that standards should include 
precautions for privacy and security to protect data. A few commenters 
suggested using incentives to improve data collection efforts, 
including financial incentives.
    Response: We appreciate all of the comments and interest regarding 
the collection and standardization of social/demographic data. We will 
take commenters' feedback into consideration in future policy 
development.
    Comment: Commenters recommended a variety of additional social and 
demographic data that they believe should be collected. Examples of 
additional information that could be collected from individuals include 
gender expression, LGBTQ+ status, disability status, language including 
English proficiency, zip code, housing security, food security, 
transportation needs, safety, veteran status, health literacy, 
functional, and cognitive status along with a person's activities of 
daily living and independent activities of daily living, ability to 
communicate, insurance coverage, access to technology, forms of 
economic or financial insecurity, availability of caregiver support, 
tribal membership, body mass index (BMI), smoking status, back pain, 
pain in extremities, and health risk status based on existing indexes 
of risk (such as the Charlson Comorbidity Index). A commenter 
recommended evaluating all inpatient and outpatient codes for 
depression mental health status, chronic narcotic or pre-operative 
narcotic use. A commenter cautioned that asking patients about 
immigration status may discourage patients from obtaining care. Another 
commenter suggested considering a structural measure of disparities 
such as how the physical and technological infrastructure available in 
communities supports delivery of care.
    Response: We appreciate the feedback provided by the commenters 
regarding approaches for incorporating other demographic 
characteristics into analyses that address and advance health equity. 
We will take commenters' feedback into consideration in future policy 
development.
    Comment: Many commenters expressed concern that additional data 
collection efforts may place an undue burden on providers and 
administrators, and would impose an additional financial burden. Some 
commenters opposed creating a ``mandate'' for additional data 
collection. Commenters recommended providing additional resources to 
support data collection, data analysis, and quality improvement 
activities, such as, provider and staff training and education, and 
education for the public. Certain commenters suggested alternatives to 
reduce provider burden. For example, some commenters discussed using 
existing data sources (for example, the HIPAA transaction dataset for 
social risk factor fields) to build a health equity framework. Another 
commenter suggested delaying the collection of additional social and 
demographic information until 2024 since hospitals are trying to comply 
with other CMS reporting and interoperability requirements. Other 
commenters suggested making targeted changes to Medicare programs to 
reduce the perceived burden.
    Response: We appreciate the feedback provided by the commenters. We 
are sensitive to the potential for increased administrative burden 
associated with improved data collection practices. We will take 
commenters' feedback into consideration in future policy development.
    Comment: Several commenters recommended engaging with stakeholders 
to improve data collection efforts and develop standards for data 
collection. Commenters suggested working with both patients and 
providers to refine the data collection process, develop clear and 
clinically meaningful reasons and rationales regarding why it is 
important to collect these data elements, and demonstrate how these 
elements support a patient-centered healthcare delivery approach. A 
commenter suggested creating a public-private partnership to improve 
data collection and take action based on disparity data. Commenters had 
several suggestions for improving the data collection process; for 
example, several commenters noted that questions for collection of 
additional demographic information should be consistent with the 2020 
Census. Another commenter suggested including demographic elements from 
the HL7 Gravity Project.
    Response: We appreciate the feedback provided by the commenters 
regarding ways to engage with stakeholders to improve demographic and 
social risk factor data collection. We will take commenters' feedback 
into consideration in future policy development.
    Comment: A commenter noted that upgrades to EHRs and related 
billing systems would be needed to standardize data collection 
processes. Several commenters discussed using electronic medical 
records to collect demographic information but expressed concerns about 
data standardization. A commenter suggested that CMS consider using a 
patient API tool as a means of collecting self-reported patient data. A 
commenter recommended including additional ICD-10 codes on claims and 
coordinating with the National Uniform Billing Committee (NUBC) on the 
utilization of the existing `patient reason for visit' fields that are 
currently available on institutional claims in order to collect 
additional social and demographic information. Several commenters 
suggested using HIEs to enhance and close the gaps in demographic data 
in the electronic health record because they can serve as a central hub 
for information sharing and confirm uniform requirements for data 
fields.
    Response: We appreciate the feedback and suggestions provided by 
the commenters regarding ways to improve demographic and social risk 
factor data collection. We will take commenters' feedback into 
consideration in future policy development.
    Comment: Several commenters noted that providers would need to 
train their staff to ensure accurate data collection, including on the 
definitions of data elements and the language used to describe data 
categories. Commenters noted that data collection processes would need 
to be culturally sensitive. A commenter suggested that improvement in 
self-reporting would require providers to build trust through 
education, transparency, accountability, and the incorporation of 
health equity into health outcome measures. Another commenter described 
how patient

[[Page 45359]]

hesitation or other barriers could impact the data collection process, 
for example based on the fact that this data collection is voluntary 
for patients and not always completed. A commenter recommended that 
data collection efforts should accommodate various literacy levels and 
the linguistic needs of patient populations. A few commenters discussed 
the timing of the collection of data and recommended including data 
collection processes at the front end of the health care visit, such as 
at the time of hospital admission, as well as at the time of Medicare 
enrollment. A commenter questioned whether point-of-admission would be 
the most efficient patient-focused way of collecting this information 
and recommended using a patient portal instead, where patients may 
provide or update their information at any time.
    Response: We appreciate the feedback provided by the commenters 
regarding ways to engage with stakeholders to improve data collection 
on demographic and social risk factors, and ways to improve data 
collection through culturally sensitive methods. We will take 
commenters' feedback into consideration in future policy development.
    Comment: Several commenters recommended additional measures, either 
new or existing, that they believe should be considered for stratified 
reporting, such as measurement of care coordination and partnership 
with ambulatory and community organizations. Commenters suggested that 
selected measures should be clinically relevant and patient-centric. A 
commenter suggested considering measures that group clinical and social 
risk together to better identify high risk patients, facilitate care 
management, and allow for management of a greater number of risk 
factors. Commenters recommended that measures should not be adopted and 
publicly reported until they are validated, standardized data is 
available across all provider settings, and the potential for 
improvement by using these measures is demonstrated. Commenters agreed, 
however, that these results could be useful for internal purposes as 
indicators of potential disparity at facilities. A commenter suggested 
that people should be grouped into similar clinical risk groups when 
identifying equity in care delivery.
    Response: We appreciate the feedback provided by the commenters 
regarding approaches for incorporating additional social and 
demographic factors into analyses that address and advance health 
equity, and about the use of these results. We also note for 
stakeholders that The Office of the National Coordinator (ONC) for 
Health Information Technology recently issued ONC Standards Bulletin 
2021-2 (SB21-2) which describes the specific capabilities health IT 
certified through the ONC Health IT Certification Program must have 
with respect to capturing and exchanging granular patient race and 
ethnicity data.\881\ We will take commenters' feedback into 
consideration in future policy development.
---------------------------------------------------------------------------

    \881\ The Office of the National Coordinator for Health 
Information Technology, ONC Health IT Standards Bulletin May 2021, 
Issue 2021-2, available at: https://www.healthit.gov/sites/default/files/page/2021-5/Standards_Bulletin_2021-2.pdf.
---------------------------------------------------------------------------

    Comment: Commenters suggested several strategies to create, 
validate, and test measures including consulting the National Quality 
Forum and working with other stakeholder groups. A commenter suggested 
modifying patient satisfaction surveys to collect additional 
information about patients' lived experiences. Another commenter 
encouraged the development of measures that create transparent, 
available, and meaningful data sets, including patient survival, 
function, and experience of care.
    Response: We appreciate the feedback provided by the commenters 
regarding strategies to create, validate, and test additional measures 
of equity. We will continue to take these suggestions into account in 
future policy development.
    Comment: Many commenters suggested CMS consider a variety of 
measures that could be included for stratification. Some measures 
addressed aspects of the care process such as coordination, access to 
health care, care transitions, readmission, or patient experience of 
care. A commenter suggested that measures relating to the care process 
could be stratified by payer type. Some of these measures were specific 
to the setting, such as long-term care hospitals or the emergency 
department. Other measures were disease or condition specific such 
cardiovascular disease, diabetes, cancer, surgery, and opioid and drug 
abuse. A few commenters suggested stratifying disease-specific 
mortality measures and measures related to infection control and 
prevention. Some commenters suggested including measures to assess the 
value of care by examining the Medicare spending per beneficiary. A 
commenter suggested exploring measures to assess the potential impact 
of the built environment or neighborhood.
    Response: We appreciate the feedback provided by the commenters 
regarding additional measures that could be considered for future 
stratification. We will take commenters' feedback into consideration in 
future policy development.
    Comment: Commenters had diverse views regarding the creation of a 
Hospital Equity Score. Some commenters supported the creation of such a 
score, while others opposed it. Commenters had several recommendations 
for steps CMS could take in creating a Hospital Equity Score including 
consulting with experts and issuing an additional RFI specifically 
focused on the creation of a Hospital Equity Score, to address the 
necessary conceptual and technical components. Some commenters 
encouraged CMS to create a stakeholder group to discuss the development 
of such a score.
    Response: We appreciate the feedback provided by the commenters 
regarding approaches for creating a succinct summary score for 
measuring health equity in the hospital setting. We will take 
commenters' feedback into consideration in future policy development.
    Comment: Several commenters opposed the creation of a Hospital 
Equity Score. Reasons commenters cited included a potential lack of 
accuracy, and low confidence that a summary score would provide 
information that could further improvement or empower patients. A 
commenter suggested that combined scores may be easily misinterpreted, 
and it would be more helpful to provide the scores for individual data 
elements that make up the summary score. A commenter noted that a score 
could negatively affect community perception of healthcare. A few 
commenters requested additional information about how the Hospital 
Equity Score would be used, the types of components that would be 
included in the score, and if the score would be tied to a program 
incentive.
    Response: We appreciate the feedback provided by the commenters 
regarding approaches for creating a succinct summary score for 
measuring health equity in the hospital setting. We will take 
commenters' feedback into consideration in future policy development.
    Comment: Several commenters suggested that scores would need to be 
based on complete and accurate data collected from a standardized data 
collection process. A commenter recommended delaying implementation of 
a score until data are accurate, or including a ramp up period before 
any public reporting of these scores or before penalties are imposed. 
Commenters described technical and

[[Page 45360]]

methodological challenges for calculating equity scores, such as 
imputing missing information without biasing the score, accounting for 
small sample sizes, and comparing scores with and across hospitals. A 
commenter was concerned that the score would require a complex 
aggregation methodology. Another suggested identifying reliable and 
valid methods of analyzing data. Commenters suggested that additional 
datapoints may be necessary to better approximate health equity. A 
commenter recommended considering Human Rights Campaign Equality Health 
Index. Another suggested that the score could be based on 
subpopulations within a hospital's population where services are 
provided.
    Response: We appreciate the feedback provided by the commenters 
regarding approaches for creating a succinct summary score for 
measuring health equity in the hospital setting. We will take 
commenters' feedback into consideration in future policy development.
    Comment: Some commenters were concerned about providers being held 
accountable for factors outside of their control. Some commenters 
suggested minimizing penalties to hospitals who provide care for 
vulnerable populations. Other commenters suggested calibrating or 
adjusting the score for social determinants of health or using risk 
adjustment when comparing scores.
    Response: We appreciate the feedback provided by the commenters 
regarding approaches for creating a succinct summary score for 
measuring health equity in the hospital setting. We will take 
commenters' feedback into consideration in future policy development.
    Comment: Some commenters noted that strategies to improve low 
scores or minimize data quality issues related to reporting scores are 
needed. For example, a commenter suggested providing correction action 
plans to improve low scores. Some commenters discouraged providing 
incentives based on the score or tying the score to reimbursement, 
while others suggested including incentive to encourage hospitals to 
participate.
    Response: We appreciate the feedback provided by the commenters 
regarding approaches for creating a succinct summary score for 
measuring health equity in the hospital setting. We will take 
commenters' feedback into consideration in future policy development.
    Comment: Many commenters expressed overall support of CMS' goals to 
advance health equity. Some commenters expressed a belief in the need 
to further extend and clarify the definition of equity provided in the 
FY 2022 IPPS/LTCH PPS proposed rule (86 FR 25555). Commenters also 
noted that where possible equity initiatives should utilize existing 
systems and aim for standardization of data collection across agencies 
and programs, produce actionable and rigorous data, and work to avoid 
increasing the administrative or financial burden on providers. Some of 
the existing efforts, systems, and organizations that commenters 
identified as potentially being useful for future efforts include ICD-
10-CM codes for social risk factors, the HL7 Gravity Project, and 
Patient ID Now Coalition. Some commenters recommended aligning aspects 
of Medicare and Medicaid programs to promote health equity efforts 
across patient populations. Several commenters expressed a desire for 
more clarity surrounding the definitions of health equity terms such as 
``social risk factors'' to reduce ambiguity of measure construction. 
Multiple commenters asked CMS to consider the limitations on using 
claims data for health equity with regards to cancer patients. A 
commenter noted that claims data cannot capture the full scope of 
relevant clinical risk, including cancer stage, genetic and genomic 
data, prior treatments, disease-specific risk scoring, or other key 
data essential for the high-complexity decision-making required to 
deliver excellent and transformative cancer care. Some commenters 
expressed a desire to publicize health equity data in order to showcase 
efforts to address inequities in the healthcare space to the broader 
community, while others suggested that health equity data should be 
reported confidentially until providers understand and are able to 
effectively use these measures. Finally, multiple commenters 
recommended that CMS focus on interventions for health equity that 
would yield immediate benefits for patients.
    Response: We appreciate the feedback provided by the commenters 
regarding measuring health equity in our hospital quality measurement 
programs. We will take commenters' feedback into consideration in 
future policy development.

C. Hospital Inpatient Quality Reporting (IQR) Program

1. Background and History of the Hospital IQR Program
    The Hospital IQR Program strives to put patients first by ensuring 
they are empowered to make decisions about their own healthcare along 
with their clinicians by using information from data-driven insights 
that are increasingly aligned with meaningful quality measures. We 
support technology that reduces burden and allows clinicians to focus 
on providing high quality healthcare for their patients. We also 
support innovative approaches to improve quality, accessibility, and 
affordability of care, while paying particular attention to improving 
clinicians' and beneficiaries' experiences when interacting with CMS 
programs. In combination with other efforts across the U.S. Department 
of Health and Human Services (HHS), we believe the Hospital IQR Program 
incentivizes hospitals to improve healthcare quality and value, while 
giving patients the tools and information needed to make the best 
decisions for themselves.
    We seek to promote higher quality and more efficient healthcare for 
Medicare beneficiaries. The adoption of widely agreed upon quality and 
cost measures supports this effort. We work with relevant stakeholders 
to define measures in almost every care setting and currently measure 
some aspect of care for almost all Medicare beneficiaries. These 
measures assess clinical processes, patient safety and adverse events, 
patient experiences with care, care coordination, and clinical 
outcomes, as well as cost of care. We have implemented quality measure 
reporting programs for multiple settings of care. To measure the 
quality of hospital inpatient services, we implemented the Hospital IQR 
Program, previously referred to as the Reporting Hospital Quality Data 
for Annual Payment Update (RHQDAPU) Program. We refer readers to the 
following final rules for detailed discussions of the history of the 
Hospital IQR Program, including statutory history, and for the measures 
we have previously adopted for the Hospital IQR Program measure set:
     The FY 2010 IPPS/LTCH PPS final rule (74 FR 43860 through 
43861);
     The FY 2011 IPPS/LTCH PPS final rule (75 FR 50180 through 
50181);
     The FY 2012 IPPS/LTCH PPS final rule (76 FR 51605 through 
61653);
     The FY 2013 IPPS/LTCH PPS final rule (77 FR 53503 through 
53555);
     The FY 2014 IPPS/LTCH PPS final rule (78 FR 50775 through 
50837);
     The FY 2015 IPPS/LTCH PPS final rule (79 FR 50217 through 
50249);
     The FY 2016 IPPS/LTCH PPS final rule (80 FR 49660 through 
49692);
     The FY 2017 IPPS/LTCH PPS final rule (81 FR 57148 through 
57150);

[[Page 45361]]

     The FY 2018 IPPS/LTCH PPS final rule (82 FR 38326 through 
38328 and 82 FR 38348);
     The FY 2019 IPPS/LTCH PPS final rule (83 FR 41538 through 
41609);
     The FY 2020 IPPS/LTCH PPS final rule (84 FR 42448 through 
42509); and
     The FY 2021 IPPS/LTCH PPS final rule (85 FR 58926 through 
58959).
    We also refer readers to 42 CFR 412.140 for Hospital IQR Program 
regulations.
2. Retention of Previously Adopted Hospital IQR Program Measures for 
Subsequent Payment Determinations
    We refer readers to the FY 2013 IPPS/LTCH PPS final rule (77 FR 
53512 through 53513) for our finalized measure retention policy. 
Pursuant to this policy, when we adopt measures for the Hospital IQR 
Program beginning with a particular payment determination, we 
automatically readopt these measures for all subsequent payment 
determinations unless a different or more limited time period is 
finalized in the measure proposals. Measures are retained unless we 
propose to remove, suspend, or replace the measures. We did not propose 
any changes to these policies in the proposed rule.
3. Removal Factors for Hospital IQR Program Measures
    We refer readers to the FY 2019 IPPS/LTCH PPS final rule (83 FR 
41540 through 41544) for a summary of the Hospital IQR Program's 
removal factors. We did not propose any changes to these policies in 
the proposed rule.
4. Considerations in Expanding and Updating Quality Measures
    We refer readers to the FY 2013 IPPS/LTCH PPS final rule (77 FR 
53510 through 53512) for a discussion of the previous considerations we 
have used to expand and update quality measures under the Hospital IQR 
Program. We also refer readers to the FY 2019 IPPS/LTCH PPS final rule 
(83 FR 41147 through 41148), in which we describe the Meaningful 
Measures Framework, our objectives under this Framework for quality 
measurement, and the quality topics that we have identified as high-
impact measurement areas that are relevant and meaningful to both 
patients and providers. We did not propose any changes to these 
policies in the proposed rule. We also note that the Hospital IQR 
Program must first adopt measures and publicly report them on the Care 
Compare and/or its successor website for at least one year before the 
Hospital VBP Program is able to adopt them. We view the value-based 
purchasing programs, including the Hospital VBP Program, as the next 
step in promoting higher quality care for Medicare beneficiaries by 
transforming Medicare from a passive payer of claims into an active 
purchaser of quality healthcare for its beneficiaries.
5. New Measures for the Hospital IQR Program Measure Set
    In the FY 2022 IPPS/LTCH PPS proposed rule (86 FR 25562 through 
25579), we proposed to adopt five new measures: (1) Maternal Morbidity 
structural measure, beginning with a shortened reporting period from 
October 1, 2021 through December 31, 2021, affecting the CY 2021 
reporting period/FY 2023 payment determination; (2) Hybrid Hospital-
Wide All-Cause Risk Standardized Mortality (Hybrid HWM) measure 
beginning with a voluntary submission period which will run from July 
1, 2022 through June 30, 2023, followed by mandatory reporting 
beginning with the reporting period which runs July 1, 2023 through 
June 30, 2024, affecting the FY 2026 payment determination; (3) COVID-
19-Vaccination Coverage among Healthcare Personnel (HCP) measure 
beginning with a shortened reporting period from October 1, 2021 
through December 31, 2021, affecting the CY 2021 reporting period/FY 
2023 payment determination; (4) Hospital Harm--Severe Hypoglycemia eCQM 
beginning with the CY 2023 reporting period/FY 2025 payment 
determination; and (5) Hospital Harm--Severe Hyperglycemia eCQM 
beginning with the CY 2023 reporting period/FY 2025 payment 
determination. We are finalizing the adoption of these measures, and we 
discuss these measures in the following sections in more detail.
a. Adoption of the Maternal Morbidity Structural Measure Beginning With 
a Shortened Reporting Period From October 1, 2021 Through December 31, 
2021, Affecting the FY 2023 Payment Determination, Followed by Annual 
Reporting Periods for Subsequent Years
(1) Background
    Despite the highest rate of spending on maternity care, the U.S. 
ranks worse than most other developed nations in preventing pregnancy-
related deaths.\882\ The Maternal Mortality Rate in the U.S. increased 
from 17 deaths per 100,000 live births in 1990 to 26 deaths per 100,000 
live births in 2015.\883\ Similar to maternal mortality, maternal 
morbidity is highly preventable.\884\ Without proper treatment, 
maternal morbidities can lead to mortality.\885\ Researchers have found 
that the presence of select maternal morbidities such as chronic 
hypertension and preeclampsia were strongly associated with increased 
odds of mortality at the time of delivery.\886\ Timely and appropriate 
treatment of maternal morbidities is imperative to prevent 
complications that can lead to maternal mortality.\887\
---------------------------------------------------------------------------

    \882\ Maternal Health in the United States. Maternal Health Task 
Force at the Harvard Chan School. Available at: https://www.mhtf.org/topics/maternal-health-in-the-united-states/.
    \883\ Maternal Health in the United States. Maternal Health Task 
Force at the Harvard Chan School. Available at: https://www.mhtf.org/topics/maternal-health-in-the-united-states/.
    \884\ Kilpatrick, S.K., Ecker, J.L. (2016). Severe Maternal 
Morbidity: Screening and Review. American Journal of Obstetrics and 
Gynecology, 215(3):B17.
    \885\ Kilpatrick, S.K., Ecker, J.L. (2016). Severe Maternal 
Morbidity: Screening and Review. American Journal of Obstetrics and 
Gynecology, 215(3):B17-B22.
    \886\ Campbell, K.H.,Savitz, D.,Werner, E.F., Pettker, C.M., 
Goffman, D., Chazotte, C., Lipkind, H.S. (2013). Maternal Morbidity 
and Risk of Death at Delivery Hospitalization. Obstetrics and 
Gynecology, 122(3): 627-633. https://journals.lww.com/greenjournal/fulltext/2013/09000/Maternal_Morbidity_and_Risk_of_Death_at_Delivery.20.aspx.
    \887\ Kilpatrick, S.K., Ecker, J.L. (2016). Severe Maternal 
Morbidity: Screening and Review. American Journal of Obstetrics and 
Gynecology, 215(3): B17.
---------------------------------------------------------------------------

    One of the main factors contributing to the increase in maternal 
morbidity and mortality is inconsistent obstetric practice.\888\ 
Hospitals in the U.S. lack standardized protocols to address obstetric 
emergencies and complications that arise during pregnancy and 
childbirth.\889\ A standardized approach to address these concerns is 
necessary to effectively manage obstetric emergencies and 
complications.\890\ Thus, assessing hospital engagement in implementing 
standardized protocols is essential to efficiently manage maternal 
morbidity nationally. Addressing this maternal health crisis and 
improving maternal health is a priority and a quality improvement goal 
for CMS.
---------------------------------------------------------------------------

    \888\ World Health Organization (WHO), Bulletin of the WHO. 
Maternal Mortality and Morbidity in the United States. Available at: 
https://www.who.int/bulletin/volumes/93/3/14-148627/en/.
    \889\ World Health Organization (WHO), Bulletin of the WHO. 
Maternal Mortality and Morbidity in the United States. Available at: 
https://www.who.int/bulletin/volumes/93/3/14-148627/en/.
    \890\ World Health Organization (WHO), Bulletin of the WHO. 
Maternal Mortality and Morbidity in the United States. Available at: 
https://www.who.int/bulletin/volumes/93/3/14-148627/en/.
---------------------------------------------------------------------------

    Therefore, in the FY 2022 IPPS/LTCH PPS proposed rule (86 FR 25562 
through 25565), we proposed to adopt the Maternal Morbidity structural 
measure, beginning with a shortened reporting period running from 
October

[[Page 45362]]

1, 2021 through December 31, 2021, affecting the FY 2023 payment 
determination, to help address this maternal health crisis. After 
which, the reporting period will be 12 months beginning with the FY 
2024 payment determination (reporting period January 1, 2022 through 
December 31, 2022) and for subsequent years. We developed this 
structural measure to determine hospital participation in a State or 
national Perinatal Quality Improvement (QI) Collaborative initiative 
and implementation of patient safety practices or bundles within that 
QI initiative. We define a State or national Perinatal Quality 
Improvement Collaborative as a Statewide or a multi-State network 
working to improve women's health and maternal health outcomes by 
addressing the quality and safety of maternity care. These 
collaboratives employ clinical practices and processes to address gaps 
in care, as well as collect and review performance data. These 
collaboratives also include implementation of evidence-based maternity 
safety bundles and/or patient safety practices to improve patient 
outcomes and reduce maternal mortality and severe maternal morbidity. 
Hospital participation in quality improvement collaboratives has been 
shown to be effective in appropriately managing maternal morbidity 
conditions that may lead to mortality or other adverse 
consequences.\891\ This measure will: (1) Determine the number of 
hospitals currently participating in a structured State or national 
Perinatal QI Collaborative; and (2) determine whether hospitals are 
implementing the safety practices or bundles included as part of these 
QI initiatives.
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    \891\ Main, E.K., Cape, V., Abreo, A., Vasher, J., Woods, A., 
Carpenter, A., Gould, J.B. (2017). Reduction of Severe Maternal 
Morbidity from Hemorrhage Using a State Perinatal Quality 
Collaborative. American Journal of Obstetrics and Gynecology, 
216(3): 298.e1. Available at: https://www.ncbi.nlm.nih.gov/pubmed/28153661.
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    State level QI programs have been shown to be effective in 
decreasing maternal morbidity.\892\ One controlled trial conducted at 
147 California hospitals utilizing a QI toolkit, which was a patient 
safety bundle for obstetrical hemorrhage, found that hospitals that had 
implemented the QI toolkit showed a 20.8 percent decrease in 
obstetrical hemorrhage versus a 1.2 percent reduction at non-
participating hospitals.\893\ We believe the Maternal Morbidity measure 
will help us better understand the current efforts of hospitals to 
improve nationwide inpatient maternal morbidity.
---------------------------------------------------------------------------

    \892\ Main, E.K., Cape, V., Abreo, A., Vasher, J., Woods, A., 
Carpenter, A., Gould, J.B. (2017). Reduction of Severe Maternal 
Morbidity from Hemorrhage Using a State Perinatal Quality 
Collaborative. American Journal of Obstetrics and Gynecology, 
216(3): 298.e4. Available at: https://www.ncbi.nlm.nih.gov/pubmed/28153661.
    \893\ Main, E.K., Cape, V., Abreo, A., Vasher, J., Woods, A., 
Carpenter, A., Gould, J.B. (2017). Reduction of Severe Maternal 
Morbidity from Hemorrhage Using a State Perinatal Quality 
Collaborative. American Journal of Obstetrics and Gynecology, 
216(3): 298.e4. Available at: https://www.ncbi.nlm.nih.gov/pubmed/28153661.
---------------------------------------------------------------------------

    The existing literature on maternal morbidity also documents how 
patient safety practices and bundles utilized in Statewide and national 
Perinatal Quality Collaborative programs can improve maternal 
outcomes.\894\ The implementation of triggers, bundles, protocols, and 
checklists have been shown to improve the quality and safety of 
obstetric care delivery.\895\ Triggers are used to identify an event 
that mandates further action by a healthcare professional, which then 
facilitates timely intervention and patient safety.\896\ Examples of 
triggers include hypertension greater than 180/110 and fever 
(temperature over 38.5 [deg]C).\897\ Bundles are a collection of 
interventions such as checklists, protocols, and educational materials 
that target a specific morbidity such as hypertension or 
hemorrhage.\898\ Protocols are precise plans of action for specific 
clinical scenarios and serve to augment memory and limit human error in 
demanding environments such as labor and delivery units.\899\ These 
evidence-based tools also facilitate improvements in timely diagnosis 
and treatment that serve to prevent morbidity.\900\ This measure will 
allow us to assess hospital participation in QI collaborative programs 
in the inpatient setting and the implementation of safety practices or 
bundles.
---------------------------------------------------------------------------

    \894\ Arora, K.S., Shields, L.E., Grobman, W.A., D'Alto, M.E. 
(2016). Triggers, Bundles, Protocols, and Checklists--What Every 
Maternal Care Provider Needs to Know. American Journal of Obstetrics 
and Gynecology, 214(4): 444-451.
    \895\ Arora, K.S., Shields, L.E., Grobman, W.A., D'Alto, M.E. 
(2016). Triggers, Bundles, Protocols, and Checklists--What Every 
Maternal Care Provider Needs to Know. American Journal of Obstetrics 
and Gynecology, 214(4): 449-450.
    \896\ Arora, K.S., Shields, L.E., Grobman, W.A., D'Alto, M.E. 
(2016). Triggers, Bundles, Protocols, and Checklists--What Every 
Maternal Care Provider Needs to Know. American Journal of Obstetrics 
and Gynecology, 214(4): 444-451.
    \897\ Forster, Alan J. MD, FRCPC; Fung, Irene; Caughey, Sharon 
MD, FRCPC; Oppenheimer, Lawrence MD, FRCPC; Beach, Cathy; Shojania, 
Kaveh G. MD; van Walraven, Carl MD, FRCPC, MSc. 2006. Adverse Events 
Detected by Clinical Surveillance on an Obstetric Service. 
Obstetrics and Gynecology, 108(5): 1073-1083.
    \898\ Arora, K.S., Shields, L.E., Grobman, W.A., D'Alto, M.E. 
(2016). Triggers, Bundles, Protocols, and Checklists--What Every 
Maternal Care Provider Needs to Know. American Journal of Obstetrics 
and Gynecology, 214(4): 444-451.
    \899\ Arora, K.S., Shields, L.E., Grobman, W.A., D'Alto, M.E. 
(2016). Triggers, Bundles, Protocols, and Checklists--What Every 
Maternal Care Provider Needs to Know. American Journal of Obstetrics 
and Gynecology, 214(4): 444-451.
    \900\ Arora, K.S., Shields, L.E., Grobman, W.A., D'Alto, M.E. 
(2016). Triggers, Bundles, Protocols, and Checklists--What Every 
Maternal Care Provider Needs to Know. American Journal of Obstetrics 
and Gynecology, 214(4): 444-451.
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    At this time, CMS quality reporting programs do not include quality 
measures that specifically address maternal morbidity. The current 
Hospital IQR Program measure set includes the PC-01 measure for 
Elective Deliveries (77 FR 53530), and the Merit-Based Incentive 
Payment System (MIPS) in the Quality Payment Program includes measures 
for Elective Delivery or Early Induction and Post-Partum Follow-up and 
Care Coordination (81 FR 77625). While these measures contribute to 
improving maternal health, they do not specifically address maternal 
morbidity. Therefore, we believe it is important to adopt this measure 
into the Hospital IQR Program.
    Under CMS' Meaningful Measures Framework, the Maternal Morbidity 
measure addresses the quality priority of ``Make Care Safer by Reducing 
Harm Caused in the Delivery of Care'' through the Meaningful Measures 
Area of ``Preventable Healthcare Harm.'' \901\ Because many of the 
factors contributing to maternal morbidity are preventable, this 
measure will be the first step toward assessing the current landscape 
of QI participation and implementation of patient safety practices or 
bundles with the objective of reducing maternal morbidity, and in turn, 
maternal mortality.
---------------------------------------------------------------------------

    \901\ The Maternal Morbidity Measure addresses the quality 
priority of ``Make Care Safer by Reducing Harm Caused in the 
Delivery of Care'' through the Meaningful Measures Area of 
``Preventable Healthcare Harm.'' More information on CMS' Meaningful 
Measures Framework is available at: https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/QualityInitiativesGenInfo/MMF/General-info-Sub-Page.
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(2) Overview of Measure
    To report on this measure, hospitals will respond to a two-part 
question: ``Does your hospital or health system participate in a 
Statewide and/or National Perinatal Quality Improvement Collaborative 
Program aimed at improving maternal outcomes during inpatient labor, 
delivery and post-partum care, and has it implemented patient safety 
practices or bundles related to maternal morbidity to address 
complications, including, but not limited to, hemorrhage, severe 
hypertension/preeclampsia or sepsis?''

[[Page 45363]]

Hospitals will then choose from the following response options: (A) 
``Yes''; (B) ``No''; or (C) ``N/A (our hospital does not provide 
inpatient labor/delivery care)'' and will submit responses once a year 
via a CMS-approved web-based tool on the QualityNet website.
    The Maternal Morbidity measure was included on the publicly 
available ``2019 Measures under Consideration Spreadsheet'' \902\ (MUC 
List), a list of measures under consideration for use in various 
Medicare programs. The Measure Applications Partnership (MAP) Hospital 
Workgroup, which the MAP Coordinating Committee oversees, reviewed the 
MUC List and the Maternal Morbidity measure (MUC2019-114) in detail on 
December 4, 2019.\903\ The MAP Hospital Workgroup reviewed the measure 
as: ``Does your hospital or health system participate in a Statewide 
and/or National Perinatal Quality Improvement Collaborative Program 
aimed at improving maternal outcomes during inpatient labor, delivery 
and post-partum care, which includes implementation of patient safety 
practices or bundles to address complications, including, but not 
limited to, hemorrhage, severe hypertension/preeclampsia or sepsis?'' 
\904\ The MAP Hospital Workgroup's preliminary recommendation was to 
not support MUC2019-114 Maternal Morbidity for rulemaking, with 
potential for mitigation.\905\
---------------------------------------------------------------------------

    \902\ 2019 Measures Under Consideration. Information available 
at: http://www.qualityforum.org/WorkArea/linkit.aspx?LinkIdentifier=id&ItemID=91406.
    \903\ National Quality Forum. Measure Applications Partnership 
(MAP) 2020 Considerations for Implementing Measures in Federal 
Programs: Hospitals. Available at: qualityforum.org/map/.
    \904\ National Quality Forum. Measure Applications Partnership 
(MAP) 2020 Considerations for Implementing Measures in Federal 
Programs: Hospitals. Available at: qualityforum.org/map/.
    \905\ National Quality Forum. Measure Applications Partnership 
(MAP) 2020 Considerations for Implementing Measures in Federal 
Programs: Hospitals. Available at: qualityforum.org/map/.
---------------------------------------------------------------------------

    The potential mitigating factors identified by the MAP Hospital 
Workgroup were to adjust the language of the question to clarify that 
the hospital is expected both to attest to participation in a quality 
improvement initiative as well as to implement patient safety practices 
or bundles to address complications and that the Maternal Morbidity 
measure go through the NQF endorsement process. The MAP Hospital 
Workgroup members suggested replacing ``which includes implementation 
of patient safety practices or bundles'' with ``and has implemented 
patient safety practices or bundles'' to clarify that the intent of the 
measure is both to identify hospitals that participate in a QI program 
and implement specific bundles known to improve outcomes.\906\ To 
address the MAP's feedback regarding the measure's usability, we made 
the aforementioned change to the measure, thereby clarifying that the 
measure will assess participation in QI initiatives and the 
implementation of patient safety practices or bundles to address 
complications (rather than assessing participation in a QI initiative 
alone).
---------------------------------------------------------------------------

    \906\ National Quality Forum. Measure Applications Partnership 
(MAP) 2020 Considerations for Implementing Measures in Federal 
Programs: Hospitals. Available at: qualityforum.org/map/.
---------------------------------------------------------------------------

    The MAP Coordinating Committee, which provides direction to the MAP 
workgroups, reconvened on January 15, 2020 and reviewed MUC2019-114 
Maternal Morbidity measure for rulemaking in detail.\907\ The MAP 
Coordinating Committee reviewed the measure as: ``Does your hospital or 
health system participate in a Statewide and/or National Perinatal 
Quality Improvement Collaborative Program aimed at improving maternal 
outcomes during inpatient labor, delivery and post-partum care, and has 
implemented patient safety practices or bundles to address 
complications, including, but not limited to, hemorrhage, severe 
hypertension/preeclampsia or sepsis?'' \908\ Upon the review of the 
measure, the MAP Coordinating Committee conditionally supported 
MUC2019-114 Maternal Morbidity for rulemaking.\909\
---------------------------------------------------------------------------

    \907\ National Quality Forum. Measure Applications Partnership 
(MAP) 2019-2020 Final Recommendations. Available at: http://www.qualityforum.org/Project_Pages/MAP_Coordinating_Committee.aspx.
    \908\ National Quality Forum. Measure Applications Partnership 
(MAP) 2019-2020 Final Recommendations. Available at: http://www.qualityforum.org/Project_Pages/MAP_Coordinating_Committee.aspx.
    \909\ National Quality Forum. Measure Applications Partnership 
(MAP) 2019-2020 Final Recommendations. Available at: http://www.qualityforum.org/Project_Pages/MAP_Coordinating_Committee.aspx.
---------------------------------------------------------------------------

    The conditions identified by the MAP Coordinating Committee 
included adjusting the language of the attestation question to clarify 
that the hospital is expected both to attest to participation in a 
quality improvement initiative as well as actually implement patient 
safety practices or bundles to address complications.\910\ In response 
to this recommendation, we adjusted the language of the attestation to 
clarify that answering ``Yes'' to the attestation reflects a yes 
response to both components of the question.
---------------------------------------------------------------------------

    \910\ National Quality Forum. Measure Applications Partnership 
(MAP) 2019-2020 Final Recommendations. Available at: http://www.qualityforum.org/Project_Pages/MAP_Coordinating_Committee.aspx.
---------------------------------------------------------------------------

    The MAP Coordinating Committee included an additional condition 
that we allow multi-hospital quality improvement collaborative 
participation, in addition to Statewide or national collaboratives, to 
account for programs sponsored by large health systems.\911\ We 
considered this, but ultimately concluded that those programs should 
not be included because they are not as well defined as State and 
national collaboratives.
---------------------------------------------------------------------------

    \911\ National Quality Forum. Measure Applications Partnership 
(MAP) 2019-2020 Final Recommendations. Available at: http://www.qualityforum.org/Project_Pages/MAP_Coordinating_Committee.aspx.
---------------------------------------------------------------------------

    The MAP Coordinating Committee also recommended adding information 
to the response options to clarify what constitutes a ``yes, no, or n/
a'' response.\912\ In response to this recommendation, we plan to 
include additional educational and clarifying detail on the QualityNet 
Secure Portal (also referred to as the Hospital Quality Reporting (HQR) 
System). Such additional educational and clarifying detail would 
explain that a hospital participating in a Statewide or national 
Perinatal Quality Improvement (QI) Collaborative, such as the 
California Maternal Quality Care Collaborative or the Alliance for 
Innovation on Maternal Health (AIM) program, that has actively 
implemented patient care safety practices and/or bundles would select 
``yes.'' A hospital that neither participates in a Statewide or 
national Perinatal QI Collaborative, such as those previously noted, 
nor has actively implemented patient safety care practices and/or 
bundles, would select ``no.'' A hospital that participates in a 
Statewide or national Perinatal QI Collaborative, but has not actively 
implemented patient care safety practices and/or bundles would select 
``no.'' Hospitals that do not provide inpatient labor and delivery care 
services would select ``n/a.''
---------------------------------------------------------------------------

    \912\ National Quality Forum. Measure Applications Partnership 
(MAP) 2019-2020 Final Recommendations. Available at: http://www.qualityforum.org/Project_Pages/MAP_Coordinating_Committee.aspx.
---------------------------------------------------------------------------

    Lastly, the MAP Coordinating Committee added a condition that the 
Maternal Morbidity measure should go through the NQF endorsement 
process

[[Page 45364]]

and receive endorsement.\913\ The MAP Coordinating Committee 
underscored that maternal morbidity is increasing at an alarming rate 
in the U.S., nearly doubling in the last decade.\914\ With no quality 
measures that address maternal morbidity, the MAP Coordinating 
Committee supported our attempts to address this healthcare crisis 
through measurement.\915\
---------------------------------------------------------------------------

    \913\ National Quality Forum. Measure Applications Partnership 
(MAP) 2019-2020 Final Recommendations. Available at: http://www.qualityforum.org/Project_Pages/MAP_Coordinating_Committee.aspx.
    \914\ National Quality Forum. Measure Applications Partnership 
(MAP) 2019-2020 Final Recommendations. Available at: http://www.qualityforum.org/Project_Pages/MAP_Coordinating_Committee.aspx.
    \915\ National Quality Forum. Measure Applications Partnership 
(MAP) 2019-2020 Final Recommendations. Available at: http://www.qualityforum.org/Project_Pages/MAP_Coordinating_Committee.aspx.
---------------------------------------------------------------------------

    Section 1886(b)(3)(B)(IX)(bb) of the Act provides an exception 
that, in the case of a specified area or medical topic determined 
appropriate by the Secretary for which a feasible and practical measure 
has not been endorsed by the entity with a contract under section 
1890(a) of the Act, the Secretary may specify a measure that is not so 
endorsed as long as due consideration is given to measures that have 
been endorsed or adopted by a consensus organization identified by the 
Secretary. We reviewed NQF-endorsed measures and were unable to 
identify any other NQF-endorsed measures that addressed maternal 
morbidity through hospital participation in State or national perinatal 
quality collaboratives and the implementation of associated bundles or 
practices. We found no other feasible and practical measures on the 
topic of maternal health, therefore we believe the exception in Section 
1886(b)(3)(B)(IX)(bb) of the Act applies.
(3) Data Submission and Reporting
    We proposed to begin with a shortened reporting period before 
transitioning to full year reporting periods to get a preliminary gauge 
of hospital participation in QI initiatives in a timely manner. 
Specifically, for the CY 2021 reporting period/FY 2023 payment 
determination, we proposed a shortened reporting period: October 1, 
2021 through December 31, 2021. Beginning with the CY 2022 reporting 
period/FY 2024 payment determination and for subsequent years, we 
proposed that the reporting period will be: January 1 through December 
31.
    We proposed to collect this data once a year via a CMS-approved 
web-based data collection tool available on the QualityNet website, 
similar to previous methods of reporting on structural measures. 
Specifications for the measure will also be posted on the CMS Measure 
Methodology page with the file name `Maternal Morbidity Structural 
Measure Specifications' at: https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/HospitalQualityInits/Measure-Methodology. We refer readers to section IX.C.9.i. of the 
preamble of this final rule for more details on our data submission and 
deadline requirements for structural measures.
    We invited public comment on this proposal.
    Comment: Several commenters supported adoption of the Maternal 
Morbidity structural measure for the Hospital IQR Program. 
Specifically, several commenters noted that a gap in quality 
improvement for the maternal setting currently exists and expressed 
appreciation for CMS' initiative to combat maternal morbidity. A 
commenter specifically expressed their appreciation of the alignment of 
the measure requirements with the Centers for Disease Control and 
Prevention (CDC) Alliance for Innovation on Maternal Health (AIM) 
bundles.
    Response: We thank the commenters for their support of the Maternal 
Morbidity structural measure and agree that improving maternal health 
is a priority and a quality improvement goal for CMS.
    Comment: Many commenters suggested updates to the proposed measure 
specifications, including: (1) Capturing specific safety practices; (2) 
collecting sociodemographic data to allow for measuring racial and 
ethnic disparities in maternal morbidity rates; (3) using electronic 
reporting instead of an attestation; and (4) revising the attestation 
question. A commenter sought clarification on whether the Maternal 
Morbidity structural measure would focus on investments in and 
resources dedicated to breastfeeding.
    Response: We thank commenters for their recommendations on changes 
to the measure specifications. While we agree that many types of 
patient safety and quality improvement initiatives are important to 
improving patient care, the standards and comprehensiveness of such 
initiatives can vary widely. We have therefore determined that this 
measure will focus on whether hospitals work with official Statewide or 
national Perinatal QI Collaboratives which meet certain standards. We 
wish to clarify that the proposed Maternal Morbidity structural measure 
does address breastfeeding. It focuses on determining hospital 
participation in a Statewide or national Perinatal QI Collaborative and 
implementation of patient safety practices or bundles within that QI 
collaborative, which includes breastfeeding. We appreciate commenters 
interest in electronic data submission. Hospitals will be required to 
submit their responses to the two-part question using a web-based tool 
via CMS' Hospital Quality Reporting (HQR) system (formerly referred to 
as the QualityNet system or QualityNet Secure Portal). We are adopting 
the measure with the stated attestation question, as proposed,\916\ 
because we believe it is critical for hospitals to both participate in 
a QI collaborative and take action to implement appropriate safety 
protocols. CMS will consider future changes to the measure during 
ongoing measure maintenance.
---------------------------------------------------------------------------

    \916\ We have added the word `it' to the Maternal Morbidity 
measure attestation question, which is a non-substantive addition 
and does not change the meaning or context.
---------------------------------------------------------------------------

    Comment: A few commenters sought clarification on participating in 
a Statewide or national Perinatal QI Collaborative, more specifically, 
which programs would count towards participation in a Statewide or 
national Perinatal QI Collaborative and recommended broadening the 
definition to include quality initiatives related to patient safety 
organizations. A commenter recommended that we include birth equity 
collaboratives to quality initiatives and others suggested that we 
include an avenue for patient and community engagement with quality 
improvement initiatives. A few commenters stated that it may be 
difficult for some facilities to attest ``Yes'' to the measure given 
that there may be volume limits on participation in quality improvement 
programs for hospitals.
    Response: We appreciate commenters' comments about Statewide or 
national Perinatal QI Collaboratives. Stakeholders seeking further 
clarification on which Statewide or national Perinatal QI 
Collaboratives will be participating can view additional education and 
clarifying program details that will be provided on the QualityNet 
website (also referred to as the Hospital Quality Reporting (HQR) 
system) at: http://www.QualityNet.cms.gov (or other successor CMS 
designated websites). With regards to broadening the types of 
initiatives included in the measure (such as those related to patient 
safety organizations, birth equity collaboratives, or community 
engagement initiatives), while we agree that many types of patient 
safety and quality improvement initiatives are

[[Page 45365]]

important to improving patient care, the standards and 
comprehensiveness of such initiatives can vary widely. We have 
therefore determined that this measure will focus on whether hospitals 
work with official Statewide or national Perinatal QI Collaboratives 
which meet certain standards. We are not aware of volume limits on 
participation in quality improvement programs for hospitals and we 
encourage stakeholders to inform us if that becomes a specific issue. 
We note that even if participation in a Statewide Perinatal QI 
Collaborative is capped, a number of national Perinatal QI 
Collaboratives are available, such that we do not anticipate hospitals 
being unable to participate due solely to volume limits. In addition, 
we highlight that the Hospital IQR Program is a pay-for-reporting 
program, and hospitals are not scored based on their performance on 
measures.
    Comment: Several commenters encouraged CMS to submit the Maternal 
Morbidity structural measure to the National Quality Forum (NQF) for 
endorsement. Commenters in favor of NQF endorsement stated that the 
Maternal Morbidity structural measure would have greater potential to 
make lasting impacts in reducing maternal morbidity if endorsed by NQF. 
A commenter expressed that they would like to see the Maternal 
Morbidity structural measure eventually evolve into a quality outcome 
measure.
    Response: We thank commenters for their recommendations. While we 
recognize the value of measures undergoing NQF endorsement review, 
given the severity of the maternal morbidity crisis and, as there are 
currently no NQF-endorsed measures that address maternal morbidity 
through hospital participation in Statewide or national Perinatal QI 
Collaboratives, we believe it is important to implement this measure as 
soon as possible. As noted above, per section 1886(b)(3)(B)(IX)(bb) of 
the Act, NQF endorsement is not a prerequisite for adoption of a 
measure into the Hospital IQR Program. In addition, we support the 
development of quality outcome measures addressing maternal morbidity 
and are considering new eCQMs in development focused on severe 
obstetrics complications.
    Comment: Many commenters had concerns regarding the measure's 
initial reporting period starting on October 1, 2021. A commenter 
recommended using the initial reporting period for informational 
purposes only and not for use in the Hospital IQR Program. Several 
commenters requested that CMS delay implementation of the Maternal 
Morbidity structural measure to allow hospitals additional time to 
research collaborative programs and prepare for accurate reporting, and 
a commenter noted that a delay would give localities time to launch 
perinatal quality collaboratives (PQC) or Alliance for Innovation on 
Maternal Health (AIM) bundles. A few commenters noted that starting 
reporting so abruptly could lead to reliability concerns in the data 
due to misreporting and could potentially lead to other unintended 
consequences. Another commenter expressed concern that not all 
participating States have implemented perinatal quality collaboratives 
(PQC).
    Response: We appreciate commenters' concerns about the initial 
reporting period, however, we believe that maternal morbidity is a 
pressing issue which deserves serious focus and rapid action for 
maternal health improvement. We note that the Maternal Morbidity 
structural measure is being adopted for the Hospital IQR Program at 
this time, meaning hospitals will receive credit for the reporting of 
their measure results, regardless of their responses to the attestation 
question. Use of this measure in the Hospital IQR Program will provide 
useful information to CMS and the public on the number of hospitals 
currently participating in structured Statewide or national Perinatal 
QI Collaboratives and implementing the safety practices. With regards 
to commenters' concerns that beginning reporting as soon as the FY 2023 
payment year could lead to misreporting or unintended consequences, we 
believe collecting data and reporting results for this measure right 
away will provide a critical baseline and we will monitor the data and 
any unintended consequences of the measure as part of standard measure 
maintenance. In locations where a Statewide collaborative is not yet 
launched, hospitals may choose to participate in a national 
collaborative for the Maternal Morbidity structural measure.
    Comment: Several commenters did not support the adoption of a 
Maternal Morbidity structural measure. Commenters felt there was a lack 
of evidence supporting the relationship between participation in 
Statewide or national Perinatal QI Collaboratives and improved 
outcomes, and therefore, questioned the value and usefulness of the 
structural measure on reducing maternal morbidity or informing patient 
decision-making on where to receive care.
    Response: We respectfully disagree that the proposed structural 
measure lacks value. We believe this measure serves as a key first step 
in measuring and promoting quality improvement by encouraging hospitals 
to collaborate with QI organizations and implement safety protocols.
    After consideration of the public comments we received, we are 
finalizing our proposal as proposed.
b. Adoption of the Hybrid Hospital-Wide All-Cause Risk Standardized 
Mortality Measure With Claims and Electronic Health Record Data 
(NQF#3502) Voluntary From July 1, 2022 Through June 30, 2023, and 
Mandatory Beginning July 1, 2023 Through June 30, 2024, Affecting the 
FY 2026 Payment Determination and Subsequent Years
(1) Background
    Estimates using data from 2008 to 2011 suggest that more than 
210,000 patients die each year from preventable harm in hospitals.\917\ 
While we do not expect overall hospital mortality rates to be zero, 
studies have shown that quality of care relates to mortality within 30 
days of hospital admission and that high and variable mortality rates 
across hospitals indicate opportunities for 
improvement.918 919 In addition to the harm to individuals, 
their families, and caregivers resulting from preventable death, there 
are also significant financial costs to the healthcare system 
associated with high and variable mortality 
rates.920 921 922 While capturing monetary savings for 
preventable mortality events is challenging, using two recent estimates 
of the number of deaths due to preventable medical errors, and assuming 
an average of 10 lost years of life per death (valued at $75,000 per 
year in lost quality adjusted life years), the annual direct and 
indirect cost of potentially preventable deaths could be

[[Page 45366]]

as much as $73.5 to $735 billion.923 924 925
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    \917\ James JT. A new, evidence-based estimate of patient harms 
associated with hospital care. Journal of patient safety. 2013; 
9(3):122-128.
    \918\ Peterson ED, Roe MT, Mulgund J, et al. Association between 
hospital process performance and outcomes among patients with acute 
coronary syndromes. JAMA. 2006; 295(16):1912-1920.
    \919\ Writing Group for the Checklist- I.C.U. Investigators, 
Brazilian Research in Intensive Care Network. Effect of a quality 
improvement intervention with daily round checklists, goal setting, 
and clinician prompting on mortality of critically ill patients: A 
randomized clinical trial. JAMA. 2016; 315(14):1480-1490.
    \920\ Institute of Medicine 2000. To Err Is Human: Building a 
Safer Health System. Washington, DC: The National Academies Press. 
Available at: https://www.nap.edu/resource/9728/To-Err-is-Human-
1999_report-brief.pdf.
    \921\ Classen DC, Resar R, Griffin F, et al. `Global trigger 
tool' shows that adverse events in hospitals may be ten times 
greater than previously measured. Health Affairs. 2011; 30(4):581-
589.
    \922\ Andel C, Davidow SL, Hollander M, Moreno DA. The economics 
of health care quality and medical errors. Journal of health care 
finance. 2012; 39(1):39-50.
    \923\ Institute of Medicine 2000. To Err Is Human: Building a 
Safer Health System. Washington, DC: The National Academies Press. 
https://www.nap.edu/resource/9728/To-Err-is-Human-1999_report-
brief.pdf.
    \924\ Classen DC, Resar R, Griffin F, et al. `Global trigger 
tool' shows that adverse events in hospitals may be ten times 
greater than previously measured. Health Affairs. 2011; 30(4):581-
589.
    \925\ Andel C, Davidow SL, Hollander M, Moreno DA. The economics 
of health care quality and medical errors. Journal of health care 
finance. 2012; 39(1):39-50.
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    Condition-specific mortality measures previously adopted into the 
Hospital IQR and Hospital VBP Programs support quality improvement work 
targeted toward patients with a set of common medical conditions, such 
as stroke, heart failure, acute myocardial infarction, or pneumonia. 
Following the implementation of condition-specific measures, national 
hospital mortality rates for the measured conditions and/or procedures 
have declined.\926\ Now, we are interested in also measuring hospital 
performance across a broader set of patients and across more areas of 
the hospital.
---------------------------------------------------------------------------

    \926\ Suter LG, Li SX, Grady JN, et al. National patterns of 
risk-standardized mortality and readmission after hospitalization 
for acute myocardial infarction, heart failure, and pneumonia: 
Update on publicly reported outcomes measures based on the 2013 
release. Journal of general internal medicine. 2014; 29(10):1333-
1340.
---------------------------------------------------------------------------

    We developed a hybrid hospital-wide, all-cause, risk-standardized 
mortality measure that uses claims data to define the measure cohort 
and a combination of data from electronic health records (EHRs) and 
claims for risk adjustment (Hybrid Hospital-Wide All-Cause Risk 
Standardized Mortality Measure (hereinafter referred to as the ``Hybrid 
HWM measure'')). As more patients are included, a hospital-wide 
mortality measure also captures the performance for smaller volume 
hospitals that would otherwise not have sufficient cases to receive 
measure score or performance information for condition- or procedure-
specific mortality measures. As developed, the Hybrid HWM measure 
addresses the Meaningful Measures Framework quality priority of 
``Promoting Effective Treatment to Reduce Risk-Adjusted Mortality.''
    The measure developer under contract with us engaged several 
stakeholder groups, including a Technical Work Group and a Patient and 
Family Work Group, as well as a national, multi-stakeholder Technical 
Expert Panel (TEP) consisting of providers, patients, and other 
stakeholders. These groups provided feedback on the measure concept, 
outcome, cohort, risk model variables, and the reporting of measure 
results. The measure developer also solicited stakeholder feedback 
during measure development as required in the Measures Management 
System (MMS) Blueprint, including two public comment periods.\927\
---------------------------------------------------------------------------

    \927\ CMS Measures Management System Blueprint (Blueprint v 
16.0). CMS. 2020 . Available at: https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/MMS/Downloads/Blueprint.pdf.
---------------------------------------------------------------------------

    The Hybrid HWM measure uses claims and EHR data to move toward 
greater use of EHR data for quality measurement. This approach aligns 
with stakeholder feedback on the importance of including clinical data 
that is available to the clinical care team at the time treatment is 
rendered to account for patients' severity of illness, rather than 
relying solely on data from claims in outcome measures (80 FR 49702 
through 49703). This approach also aligns with our goal to move towards 
digital quality measures (dQMs) to reduce provider data collection 
burden and to provide more rapid performance feedback on quality 
measures, as discussed further in section IX.A. of the preamble of this 
final rule.
    The Hybrid HWM measure uses a set of core clinical data elements 
from hospitals' EHRs, similar to those used in the Hybrid Hospital-Wide 
Readmission Measure with Claims and Electronic Health Record Data (NQF 
#2879), which was adopted in the Hospital IQR Program in the FY2020 
IPPS/LTCH PPS final rule (84 FR 42467). These core clinical data 
elements are data that hospitals routinely collect, that can be 
feasibly extracted from hospital EHRs, and that can be utilized as part 
of specific quality outcome measures.\928\ The data elements are the 
values for a set of vital signs and common laboratory tests collected 
at the time the patient initially presents to the hospital. They are 
used, in addition to claims data, for risk adjustment of patients' 
severity of illness (for Medicare FFS beneficiaries who are aged 
between 65 and 94 years). We refer readers to section IX.C.5.b.(7). of 
the preamble of this final rule for more detail on the core clinical 
data elements used in this measure.
---------------------------------------------------------------------------

    \928\ 2013 Core Clinical Data Elements Technical Report (Version 
1.1). 2015. Available at: https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/HospitalQualityInits/Measure-Methodology. Accessed January 2021.
---------------------------------------------------------------------------

    The Hybrid Hospital-Wide All-Cause Risk Standardized Mortality 
Measure (MUC17-196) was included in a publicly available document 
entitled ``2017 Measures Under Consideration List'' (available at: 
http://www.qualityforum.org/WorkArea/linkit.aspx?LinkIdentifier=id&ItemID=86527). The NQF MAP Hospital 
Workgroup reviewed the measure and noted that it is an important 
measure for patient safety and that the measure could help reduce 
deaths due to medical errors.\929\ The MAP expressed concern regarding 
the potential unintended consequences of unnecessary interventions for 
patients at the end of life.\930\ The measure developer addressed this 
issue based upon TEP and patient work group input to remove patients 
from the cohort who are at the end of life and for whom survival is 
unlikely to be the goal of care. Specifically, the measure does not 
include patients enrolled in hospice in the 12 months prior to 
admission, on admission, or within 2 days of admission. The measure 
also does not include patients admitted primarily for cancer that are 
enrolled in hospice at any time during the admission, those admitted 
primarily for metastatic cancer, and those admitted for specific 
diagnoses with limited survival.
---------------------------------------------------------------------------

    \929\ Measure Applications Partnership. MAP 2018 Considerations 
for Implementing Measures in Federal Programs: Hospitals. 
Washington, DC: NQF; 2018. Available at: http://www.qualityforum.org/WorkArea/linkit.aspx?LinkIdentifier=id&ItemID=87083.
    \930\ Measure Applications Partnership. MAP 2018 Considerations 
for Implementing Measures in Federal Programs: Hospitals. 
Washington, DC: NQF; 2018. Available at: http://www.qualityforum.org/WorkArea/linkit.aspx?LinkIdentifier=id&ItemID=87083.
---------------------------------------------------------------------------

    The MAP additionally requested that the NQF assess whether the 
measure has appropriate clinical and social risk factors in its risk 
adjustment model and addresses necessary exclusions. The MAP noted that 
appropriate risk adjustment and exclusions are necessary to ensure the 
measure does not disproportionately penalize facilities who may see 
more complex patients (for example, academic medical centers or safety 
net providers) or who may have smaller volumes of patients (for 
example, rural providers). We subsequently submitted the measure for 
initial endorsement by the NQF and presented analyses to NQF on the 
impact of social risk factors. Specifically, we assessed the 
relationship between two social risk factor variables (Medicare-
Medicaid dual-eligibility status and the AHRQ-validated socioeconomic 
status (SES) index score) and the outcome (mortality). We also examined 
the effect of adding either of these variables into the risk adjustment 
model on model performance and hospital results. We concluded that 
correlations between measure scores for models with and

[[Page 45367]]

without social risk variables were near 1.0, model performance metrics 
were unchanged, and in most divisions the social risk variables did not 
have statistically significant association with the risk of mortality 
in a multivariable model. For the division in which AHRQ SES was 
associated with mortality, further analyses indicated that adjusting 
for AHRQ SES would remove hospital-level effects that may reflect 
lower-quality care provided to patients with low SES status. Based on 
these results, the measure as endorsed by NQF does not adjust for these 
social risk factors. The measure is risk-adjusted to account for case 
mix and service mix differences to prevent disproportionately 
penalizing facilities.\931\ NQF fully reviewed the measure, including 
risk adjustment, and endorsed the measure with the risk adjustment, as 
specified. As presented to NQF, we also noted that all exclusions were 
determined by careful clinical review and have been made based on 
clinically relevant decisions and to ensure accurate calculation of the 
measure. The NQF assessed the exclusions and supported the measure for 
endorsement.\932\
---------------------------------------------------------------------------

    \931\ Measure Applications Partnership. MAP 2018 Considerations 
for Implementing Measures in Federal Programs: Hospitals. 
Washington, DC: NQF; 2018. Available at: http://www.qualityforum.org/WorkArea/linkit.aspx?LinkIdentifier=id&ItemID=87083.
    \932\ National Quality Forum. Available at: https://www.qualityforum.org/QPS/3502.
---------------------------------------------------------------------------

    The MAP noted this measure used EHR data to support additional 
factors in the risk adjustment model. Given the variability in EHR 
systems, the MAP recommended that the NQF standing committee reviewing 
the measure pay special attention to the ability to consistently obtain 
EHR data across hospitals. We approached risk variable selection from 
the perspective of ensuring a parsimonious list of clinical EHR 
variables that would minimize hospital burden to report the data and 
provide face validity from a clinical perspective. As candidate risk 
variables, the core clinical data elements (CCDE) are consistently 
captured, captured with a standard definition, and entered into the 
electronic health record in a structured field and can be feasibly 
extracted, as shown during development and testing, and subsequently 
presented to NQF.\933\
---------------------------------------------------------------------------

    \933\ 2013 Core Clinical Data Elements Technical Report (Version 
1.1). 2015; https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/HospitalQualityInits/Measure-Methodology. Accessed January 2021.
---------------------------------------------------------------------------

    The MAP further suggested that condition-specific mortality 
measures may be more actionable for providers and informative for 
consumers.\934\ We note that by adopting the Hybrid HWM measure, we 
intend to offer additional benefits when reported with condition- or 
procedure-specific measures, such as: (1) Providing scores and 
performance information for smaller hospitals; (2) providing an overall 
hospital-level signal for consumers; and (3) providing yearly updates 
using a 1-year measurement period, unlike condition- or procedure-
specific measures that use 3 years of claims data. Upon review, the MAP 
expressed their conditional support for rulemaking pending endorsement 
from the NQF.\935\ Thereafter, the NQF endorsed the Hybrid HWM measure 
on October 23, 2019.\936\ The MAP also recommended the Hybrid HWM 
measure have a voluntary reporting period before mandatory 
implementation.\937\ Our finalized proposal to adopt the Hybrid HWM 
measure includes beginning with a 1-year voluntary reporting period, as 
further detailed later in section IX.C.5.b.(9).(a). of this final rule.
---------------------------------------------------------------------------

    \934\ Measure Applications Partnership. MAP 2018 Considerations 
for Implementing Measures in Federal Programs: Hospitals. 
Washington, DC: NQF; 2018. Available at: http://www.qualityforum.org/WorkArea/linkit.aspx?LinkIdentifier=id&ItemID=87083.
    \935\ Measure Applications Partnership. MAP 2018 Considerations 
for Implementing Measures in Federal Programs: Hospitals. 
Washington, DC: NQF; 2018. Available at: http://www.qualityforum.org/WorkArea/linkit.aspx?LinkIdentifier=id&ItemID=87083.
    \936\ National Quality Forum. Available at: https://www.qualityforum.org/QPS/3502.
    \937\ Measure Applications Partnership. MAP 2018 Considerations 
for Implementing Measures in Federal Programs: Hospitals. 
Washington, DC: NQF; 2018. Available at: http://www.qualityforum.org/WorkArea/linkit.aspx?LinkIdentifier=id&ItemID=87083.
---------------------------------------------------------------------------

    In the FY 2019 IPPS/LTCH PPS final rule, we described the potential 
future inclusion of the Hybrid HWM measure in the Hospital IQR Program 
and requested public feedback on the measure. Many stakeholders 
expressed support for the measure, with many commenters commending the 
use of EHR data. CMS also responded to stakeholder feedback on the 
measure methodology, validity, and concept (83 FR 41581 through 41588).
(2) Overview of Measure
    The Hybrid HWM measure is an outcome measure that captures 
hospital-level, risk-standardized mortality within 30 days of hospital 
admission for most conditions or procedures. It does not have a 
traditional numerator and denominator like a core process measure (for 
example, percentage of adult patients with diabetes aged 18 to 75 years 
receiving one or more hemoglobin A1c tests per year). The measure is 
reported as a single summary score, derived from the results of risk-
adjustment models for 15 mutually exclusive service-line divisions 
(categories of admissions grouped based on similar discharge diagnoses 
or procedures), with a separate risk model for each of the 15 service-
line divisions. The 15 service-line divisions include: nine non-
surgical divisions and six surgical divisions. The non-surgical 
divisions are: Cancer; cardiac; gastrointestinal; infectious disease; 
neurology; orthopedics; pulmonary; renal; and other. The surgical 
divisions are: Cancer; cardiothoracic; general; neurosurgery; 
orthopedics; and other. Hospitalizations are eligible for inclusion in 
the measure if the patient was hospitalized at a non-Federal, short-
term acute care hospital; results will be publicly reported as part of 
the Hospital IQR Program.
    To compare mortality performance across hospitals, the measure 
accounts for differences in patient characteristics (patient case mix) 
as well as differences in the medical services provided and procedures 
performed by hospitals (hospital service mix). In addition, the Hybrid 
HWM measure employs a combination of administrative claims data and 
clinical EHR data to enhance clinical case mix adjustment with 
additional clinical data. As described previously, the measure is 
reported as a single summary score, derived from the results of risk-
adjustment models for 15 mutually exclusive service-line divisions. The 
overall risk-standardized mortality rate (measure score) will not 
always reflect a result from each of the 15 divisions for hospitals 
that do not have a sufficient number of admissions for each service-
line division. As a result, some hospitals' overall scores would be 
based on fewer than 15 divisions because of differences in their case 
mix.
    Our goal is to more comprehensively measure the mortality rates of 
hospitals, including to improve the ability to measure mortality rates 
in smaller volume hospitals. The cohort definition attempts to capture 
as many admissions as possible for which survival would be a reasonable 
indicator of quality and for which adequate risk adjustment is 
possible. We assume survival would be a reasonable indicator of quality 
for admissions fulfilling two criteria: (1) Survival is presumably the 
primary goal of the patient when they enter the hospital; and (2) the 
hospital can reasonably influence the patient's chance of survival 
through quality of care. The Hybrid HWM measure would provide 
information to hospitals that

[[Page 45368]]

can facilitate quality improvement efforts and would expand upon 
condition- and procedure-specific measures by including more settings, 
types of care, and types of patients. In addition, the Hybrid HWM 
measure would provide transparency about the quality of care in 
clinical areas not captured in the current condition- and procedure-
specific measures.
    Additional information on the specifications of the Hybrid HWM 
measure can be found in the Core Clinical Data Elements and Hybrid 
Measure folder on the CMS website at: http://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/HospitalQualityInits/Measure-Methodology.html and on the eCQI resource 
center website at: https://ecqi.healthit.gov/pre-rulemaking-eh-cah-ecqms..\938\
---------------------------------------------------------------------------

    \938\ We note that while the above link will allow readers to 
access the information, the following link is a more direct 
approach: https://ecqi.healthit.gov/ecqm/eh/pre-rulemaking/1/cms844v2?qt-tabs_pre_rule_measure=0.
---------------------------------------------------------------------------

(3) Data Sources
    The Hybrid HWM measure uses three main sources of data for the 
calculation of the measure: (1) Medicare Part A claims data; (2) a set 
of core clinical data elements from a hospital's EHR; and (3) mortality 
status obtained from the Medicare Enrollment Database. The measure uses 
claims and enrollment data to identify index admissions included in the 
Hybrid HWM measure cohort, in the risk-adjustment model, and to assess 
the 30-day mortality outcome. The measure uses one year of Part A 
Medicare administrative claims data from Medicare FFS beneficiaries 
aged between 65 and 94 years for the performance period. The measure 
uses Part A data from the 12 months prior to the index admission for 
risk adjustment, as well as core clinical data elements from each 
hospital's EHR for eligible patient admissions. The core clinical data 
elements are the values for a set of vital signs and common laboratory 
tests collected on patients admitted to acute care hospitals. The 
measure also requires a set of linking variables that are present in 
both the EHR and claims data, which allows us to match each patient's 
core clinical data elements to the claim for the relevant admission. We 
refer readers to the methodology report available on the CMS website 
for the list of linking variables and more detailed discussion.
(4) Outcome
    The outcome of interest for the Hybrid HWM measure is all-cause 30-
day mortality. We define all-cause mortality as death from any cause 
within 30 days of the index hospital admission date.
(5) Cohort
    The Hybrid HWM measure cohort consists of Medicare FFS 
beneficiaries, aged between 65 and 94 years, discharged from a non-
Federal, short-term acute care hospital, within the 1-year measurement 
period (July 1 to June 30 of each year). The measure was developed 
using ICD-9 codes, and then re-specified and re-tested using ICD-10 
data. The Hybrid HWM measure cohort uses the Agency for Healthcare 
Research and Quality (AHRQ) Clinical Classification Software (CCS) 
\939\ to group numerous diagnostic and procedural ICD-10 codes into the 
clinically meaningful categories defined by the AHRQ grouper. We made 
modifications to these AHRQ CCSs based on risk of mortality, as 
described in the Hybrid Hospital-Wide (All-Condition, All-Procedure) 
Risk-Standardized Mortality Measure with Electronic Health Record 
Extracted Risk Factors Measure Methodology Report Version 2.0.\940\ The 
Hybrid HWM measure uses those CCS categories as part of cohort 
specification and risk-adjustment, including the 15 service-line risk 
models.
---------------------------------------------------------------------------

    \939\ Clinical Classifications Software Refined (CCSR) https://www.hcup-us.ahrq.gov/toolssoftware/ccsr/ccs_refined.jsp.
    \940\ Hybrid Hospital-Wide (All-Condition, All-Procedure) Risk-
Standardized Mortality Measure with Electronic Health Record 
Extracted Risk Factors Measure Methodology Report Version 2.0, 
available at: http://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/HospitalQualityInits/Measure-Methodology.html.
---------------------------------------------------------------------------

    For the AHRQ CCSs and individual ICD-10-CM codes that define the 
measure development cohort, we refer readers to the Hybrid Hospital-
Wide (All-Condition, All-Procedure) Risk-Standardized Mortality Measure 
with Electronic Health Record Extracted Risk Factors Measure 
Methodology Report Version 2.0.\941\
---------------------------------------------------------------------------

    \941\ Hybrid Hospital-Wide (All-Condition, All-Procedure) Risk-
Standardized Mortality Measure with Electronic Health Record 
Extracted Risk Factors Measure Methodology Report Version 2.0, 
available at: http://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/HospitalQualityInits/Measure-Methodology.html.
---------------------------------------------------------------------------

(6) Inclusion and Exclusion Criteria
    The Hybrid HWM measure cohort currently includes Medicare FFS 
patients who--
     Were enrolled in Medicare FFS Part A for the 12 months 
prior to the date of admission and during the index admission;
     Have not been transferred from another inpatient facility;
     Were admitted for acute care (do not have a principal 
discharge diagnosis of a psychiatric disease or do not have a principal 
discharge diagnosis of ``rehabilitation care; fitting of prostheses and 
adjustment devices'');
     Are between 65 and 94 years of age;
     Are not enrolled in hospice at the time of or in the 12 
months prior to their index admission;
     Are not enrolled in hospice within 2 days of admission;
     Are without a principal diagnosis of cancer and enrolled 
in hospice during their index admission;
     Are without any diagnosis of metastatic cancer; and
     Are without a discharge diagnosis that is present on 
admission (POA) for a condition for which hospitals have limited 
ability to influence survival, including: Anoxic brain damage; 
persistent vegetative state; prion diseases such as Creutzfeldt-Jakob 
disease, Cheyne-Stokes respiration; brain death; respiratory arrest; or 
cardiac arrest without a secondary diagnosis of acute myocardial 
infarction.
    The measure currently excludes any of the following index 
admissions for patients:
     With inconsistent or unknown vital status;
     Discharged against medical advice;
     With an admission for crush injury, burn, intracranial 
injury, skull and face fractures, open wounds of head, neck, and trunk, 
or spinal cord injury; or
     With an admission in a low-volume CCS (within a particular 
service-line division), defined as equal to or less than 100 patients 
with that principal diagnosis across all hospitals.
    The Hybrid HWM measure assigns each index admission to one of the 
mutually exclusive service-line divisions. For details on how each 
admission is assigned to a specific service-line division, and for a 
complete description and rationale of the inclusion and exclusion 
criteria, we refer readers to the Hybrid Hospital-Wide (All-Condition, 
All-Procedure) Risk-Standardized Mortality Measure with Electronic 
Health Record Extracted Risk Factors Measure Methodology Report Version 
2.0.\942\
---------------------------------------------------------------------------

    \942\ Hybrid Hospital-Wide (All-Condition, All-Procedure) Risk-
Standardized Mortality Measure with Electronic Health Record 
Extracted Risk Factors Measure Methodology Report Version 2.0, 
available at: http://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/HospitalQualityInits/Measure-Methodology.html.
---------------------------------------------------------------------------

(7) Risk Adjustment
    The Hybrid HWM measure adjusts for both case mix differences 
(clinical status

[[Page 45369]]

of the patient, accounted for by adjusting for age and comorbidities) 
and service mix differences (the types of conditions and procedures 
cared for and procedures conducted by the hospital, accounted for by 
the discharge CMS condition category and AHRQ CCS). Patient 
comorbidities are based on inpatient hospital administrative claims 
during the 12 months prior to and including the index admission derived 
from ICD-10 codes grouped into the CMS condition categories (CMS-CCs). 
Risk variable coefficients vary by service-line division. We used 
version 22 943 944 of the CMS-CC map (for more information 
about our risk-adjustment model software, we refer readers to the Risk 
Adjustment page on the CMS website at: https://www.cms.gov/Medicare/Health-Plans/MedicareAdvtgSpecRateStats/Risk-Adjustors.html.)
---------------------------------------------------------------------------

    \943\ Pope GC, Ellis RP, Ash AS, et al. Diagnostic cost group 
hierarchical condition category models for Medicare risk adjustment. 
Final Report to the Health Care Financing Administration under 
Contract Number 500-95-048. 2000; http://www.cms.hhs.gov/Reports/downloads/pope_2000_2.pdf. Accessed February 25, 2020.
    \944\ Pope GC, Kautter J, Ingber MJ, et al. Evaluation of the 
CMS-HCC Risk Adjustment Model: Final Report. 2011; https://www.cms.gov/Medicare/Health-Plans/MedicareAdvtgSpecRateStats/downloads/evaluation_risk_adj_model_2011.pdf. Accessed February 25, 
2020.
---------------------------------------------------------------------------

    The Hybrid HWM measure also includes the core clinical data 
elements in the case mix adjustment. The core clinical data elements 
are values for lab values and vital signs derived from information 
captured in the EHR during the index admission only, as described in 
the FY 2016 IPPS/LTCH PPS final rule (80 FR 49699). The core clinical 
data elements are clinical information meant to reflect a patient's 
clinical status upon arrival to the hospital. The table lists the 10 
specific elements used in the proposed Hybrid HWM measure.
[GRAPHIC] [TIFF OMITTED] TR13AU21.281

    The core clinical data elements utilize EHR data, therefore, using 
the Measure Authoring Tool (MAT)--a web-based tool that allows the 
authoring of eCQMs using a standardized data model and Clinical Quality 
Language (CQL) expressions \945\--we developed and tested a MAT output 
and identified value sets for extraction of the core clinical data 
elements, which are available at the eCQI Resource Center: https://ecqi.healthit.gov/pre-rulemaking-eh-cah-ecqms. For more details on how 
the risk variables in each measure were chosen, we refer readers to the 
Hybrid Hospital-Wide (All-Condition, All-Procedure) Risk-Standardized 
Mortality Measure with Electronic Health Record Extracted Risk Factors 
Measure Methodology Report Version 2.0.\946\
---------------------------------------------------------------------------

    \945\ The Measure Authoring Tool (MAT) is a publicly available, 
web-based tool for measure developers to create eMeasures. The MAT 
now operates under the direction of the Centers for Medicare and 
Medicaid Services. For more information on the MAT, please visit: 
www.emeasuretool.cms.gov.
    \946\ Hybrid Hospital-Wide (All-Condition, All-Procedure) Risk-
Standardized Mortality Measure with Electronic Health Record 
Extracted Risk Factors Measure Methodology Report Version 2.0, 
available at: http://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/HospitalQualityInits/Measure-Methodology.html.
---------------------------------------------------------------------------

    The proposed Hybrid HWM measure was initially specified to use core 
clinical data elements that are similar to, but not precisely the same 
as, those used in the Hybrid Hospital-Wide Readmission Measure (Hybrid 
HWR measure) with Claims and Electronic Health Record Data measure (NQF 
#2879), for which we are currently collecting data from hospitals on a 
voluntary basis through June 30, 2023 (84 FR 42465). Since the Hybrid 
HWM measure was described in the FY 2019 IPPS/LTCH PPS final rule (83 
FR 41581 through 41588), we have updated the core clinical data 
elements for the Hybrid HWM measure to include hematocrit instead of 
hemoglobin to better align with the Hybrid HWR measure. Hemoglobin and 
hematocrit values are highly correlated and interchangeable with 
respect to their impact in the Hybrid HWM measure's risk model. The 
Pearson correlation coefficients of hemoglobin to hematocrit ranged 
from 0.88-0.97, depending on service-line division. We believe this 
alignment will increase the ease of reporting on both measures.
    With this update, hospitals will already collect nine of the ten 
core clinical data elements used in the Hybrid HWM measure for 
reporting on the Hybrid HWR measure, with platelets being the only 
additional data element used specifically for the Hybrid HWM measure. 
For more detail about the core clinical data elements used in the 
Hybrid Hospital-Wide Readmission Measure with Claims and Electronic 
Health Record Data measure (NQF #2879), we refer readers to our 
discussion in the FY 2020 IPPS/LTCH PPS final rule (84 FR 42465 through 
42479) and the Hybrid Hospital-Wide Readmission Measure with Electronic 
Health Record Extracted Risk Factors report (available at: https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/HospitalQualityInits/Measure-Methodology.html.)
    We will update the measure specifications annually for the measure 
to incorporate new and revised ICD-10 codes effective October 1 of each 
year after clinical review as necessary. We

[[Page 45370]]

will also update and publicly release the MAT output annually as 
necessary to include any updates to the electronic specifications, 
which includes value sets for the measure-specific data elements.
(8) Measure Calculation
    Index admissions are assigned to one of 15 mutually exclusive 
service-line divisions consisting of related conditions or procedures. 
For each service-line division, the standardized mortality ratio (SMR) 
is calculated as the ratio of the number of ``predicted'' deaths to the 
number of ``expected'' deaths at a given hospital. In other words, for 
each hospital, the numerator of the ratio is the number of deaths 
within 30 days predicted based on the hospital's performance with its 
observed case mix and service mix, and the denominator is the number of 
deaths expected based on the nation's performance with that hospital's 
case mix and service mix. This approach is analogous to a ratio of 
``observed'' to ``expected'' used in other types of statistical 
analyses.
    A hospital-wide composite SMR is then created by pooling the 
service-line SMRs for each hospital using an inverse variance-weighted 
mean. The inverse variance-weighted mean can be interpreted as a 
weighted average of all SMRs that takes into account the precision of 
SMRs. To produce the RSMR, the composite SMR is multiplied by the 
national observed mortality rate. For additional details regarding the 
measure specifications to calculate the RSMR, we refer readers to the 
Hybrid Hospital-Wide (All-Condition, All-Procedure) Risk-Standardized 
Mortality Measure with Electronic Health Record Extracted Risk Factors: 
Measure Methodology Report Version 2.0.\947\
---------------------------------------------------------------------------

    \947\ Hybrid Hospital-Wide (All-Condition, All-Procedure) Risk-
Standardized Mortality Measure with Electronic Health Record 
Extracted Risk Factors Measure Methodology Report Version 2.0. 
Available at: http://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/HospitalQualityInits/Measure-Methodology.html.
---------------------------------------------------------------------------

    We also note an important distinguishing factor about hybrid 
measures as compared to eCQMs: CMS must calculate hybrid measure 
results to determine hospitals' risk-adjusted rates relative to 
national rates using data from all reporting hospitals. With a hybrid 
measure, hospitals submit data extracted from the EHR, and CMS performs 
the measure calculations and disseminates results.
    During development and testing of the Hybrid HWM measure, we 
demonstrated that the core clinical data elements were feasibly 
extracted from hospital EHRs. We also demonstrated that the use of the 
core clinical data elements to risk-adjust the Hybrid HWM measure 
results in excellent discrimination (as in, the ability to distinguish 
patients with a low risk of mortality from those at high risk of 
mortality) of the measure, as assessed by the c-statistic. C-statistics 
ranged from 0.82 to 0.95, depending on the service line division. The 
adjusted intraclass correlation coefficient (ICC), which assesses 
reliability of the RSMR, also demonstrated high reliability at 
0.7748.\948\
---------------------------------------------------------------------------

    \948\ Landis JR, Koch GG. The measurement of observer agreement 
for categorical data. Biometrics. 1977:159-174.
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(9) Data Submission
(a) Reporting and Submission Timeframes for Proposed Voluntary and 
Mandatory Reporting Periods
    For this measure, we will start with voluntary reporting in 
response to the MAP recommendation before requiring data submission. We 
believe that taking an incremental approach to implementing this 
measure will allow hospitals more time to update and validate their 
systems, to ensure data mapping is accurate and complete, to implement 
workflow changes as necessary to better prepare for submitting data, 
and to increase familiarity with data submission for hybrid quality 
measures when the Hybrid HWM measure becomes required. We proposed a 
stepwise approach in which we would first accept data submissions for 
the Hybrid HWM measure during a voluntary reporting period. In this 
period, we will collect data on the Hybrid HWM measure in accordance 
with, and to the extent permitted by, the HIPAA Privacy and Security 
Rules (45 CFR parts 160 and 164, Subparts A, C, and E), and other 
applicable law. This voluntary reporting period will include four 
quarters of data. Specifically, the voluntary reporting period will run 
from July 1, 2022 through June 30, 2023. Hospitals that elect to submit 
data should do so according to the requirements described in this 
section and in the FY 2021 IPPS/LTCH PPS final rule (85 FR 58940 
through 58942). Under previously established policy, hospitals must 
submit the core clinical data elements and linking variables within 3 
months following the end of the applicable reporting period 
(submissions are required no later than the first business day 3 months 
following the end of the reporting period).
    Mandatory reporting will begin with the reporting period which runs 
from July 1, 2023 through June 30, 2024, affecting the FY 2026 payment 
determination and for subsequent years. Hospitals will be required to 
submit the core clinical data elements and linking variables within 3 
months following the end of the applicable reporting period 
(submissions will be required no later than the first business day 3 
months following the end of the reporting period). This mandatory 
reporting period for the Hybrid HWM measure aligns with that of the 
Hybrid Hospital-Wide Readmission Measure with Claims and Electronic 
Health Record Data (NQF #2879) that was finalized in the FY 2020 IPPS/
LTCH PPS final rule (84 FR 42465 through 42479).
    Notably, while we finalized two voluntary reporting periods for the 
Hybrid Hospital-Wide Readmission measure (84 FR 42465 through 42479), 
we only proposed to have one voluntary reporting period for the Hybrid 
HWM measure, which will coincide with the second voluntary reporting 
period for the Hybrid Hospital-Wide Readmission measure. We believe one 
voluntary reporting period is sufficient for the Hybrid HWM measure 
because hospitals will already have two separate opportunities to learn 
how to report the core clinical data elements for the Hybrid Hospital-
Wide Readmission measure, which mostly align with the Hybrid HWM 
measure core clinical data elements as described previously. Therefore, 
hospitals will have the opportunity to familiarize themselves with the 
reporting requirements and process for the core clinical data elements 
prior to the Hybrid HWM measure voluntary reporting period.
(b) File Type
    Beginning with the proposed voluntary reporting period using data 
from July 1, 2022 through June 30, 2023, we proposed that hospitals use 
Quality Reporting Data Architecture (QRDA) Category I files for each 
Medicare FFS beneficiary aged between 65 and 94 years. Submission of 
data to CMS using QRDA I files is the current EHR data and measure 
reporting standard adopted for eCQMs implemented in the Hospital IQR 
Program (84 FR 42506, 85 FR 58940). This same standard will be used for 
reporting the core clinical data elements to the CMS data receiving 
system via the QualityNet Secure Portal (also referred to as the 
Hospital Quality Reporting (HQR) System). Specifically, to successfully 
submit the Hybrid HWM measure, hospitals will need to submit the core 
clinical data elements included in the Hybrid HWM measure, as

[[Page 45371]]

described in the measure specifications, for all Medicare FFS 
beneficiaries aged between 65 and 94 years discharged from an acute 
care hospitalization in the 1-year measurement period (July 1 to June 
30 of each year). We note this aligns with the measurement period for 
the Hybrid HWR measure (84 FR 42465 through 42479).
(c) Data Thresholds
    For us to be able to calculate the Hybrid HWM measure results, each 
hospital will need to report vital signs for 90 percent or more of the 
hospital admissions for Medicare FFS patients, aged between 65 and 94 
years old discharged in the measurement period (as determined from the 
claims submitted to CMS for admissions that ended during the same 
reporting period). Vital signs are measured on nearly every adult 
patient admitted to an acute care hospital and should be present for 
nearly 100 percent of discharges (identified in Medicare FFS claims 
submitted during the same period). In addition, calculating the measure 
with more than 10 percent of hospital discharges missing these data 
elements could cause poor reliability of the measure score and 
instability of hospitals' results from measurement period to 
measurement period.
    Hospitals will also need to report the laboratory test results for 
90 percent or more of hospital admissions for nonsurgical patients, 
meaning those not included in the surgical divisions of the Hybrid HWM 
measure. For many patients in the surgical divisions admitted following 
elective surgery, there are no laboratory values available in the 
appropriate time window. Therefore, there is no submission requirement 
for the surgical divisions. However, hospitals should submit lab values 
for those patients in surgical divisions with lab values available 
within the appropriate time window. Laboratory values submitted will be 
included in the risk adjustment model.
(d) Linking Variables and Other Data Elements
    Hospitals will also be required to successfully submit the 
following six linking variables that are necessary in order to merge 
the core clinical data elements with the CMS claims data to calculate 
the measure:
     CMS Certification Number;
     Health Insurance Claims Number or Medicare Beneficiary 
Identifier;
     Date of birth;
     Sex;
     Admission date; and
     Discharge date.

The six linking variables required for linking EHR and claims data 
should be routinely captured and available for nearly every adult 
patient admitted to an acute care hospital.
    Because these linking variables are required for billing, they 
should be present for all Medicare FFS patients, and are, therefore, 
ideally suited to support merging claims and EHR data. However, 
hospitals will meet Hospital IQR Program requirements if they submit 
linking variables on 95 percent or more of discharges with a Medicare 
FFS claim for the same hospitalization during the measurement period.
(10) Public Reporting
(a) Voluntary Reporting Period
    We will not publicly report data collected during the voluntary 
reporting period. Hospitals that submit data for this measure during 
the voluntary reporting period will receive confidential hospital-
specific reports that detail submission results from the applicable 
reporting period, as well as the Hybrid HWM measure results assessed 
from merged files created by our merging of the EHR data elements 
submitted by each participating hospital with claims data from the same 
set of index admissions. Hospitals voluntarily reporting will receive 
information and instructions on the use of the electronic 
specifications for this measure, have an opportunity to test extraction 
and submission of data to CMS, and receive feedback reports from CMS, 
available via the QualityNet Secure Portal (also referred to as the 
Hospital Quality Reporting (HQR) System), with details on the success.
(b) Mandatory Reporting
    We proposed mandatory data submission, including public reporting 
of the Hybrid HWM measure, beginning with the data from the July 1, 
2023 through June 30, 2024 reporting period, affecting the FY 2026 
payment determination and for subsequent years. We anticipate this data 
will be included in the July 2025 refresh of the Care Compare website 
or its successor website.
    The EHR data will be merged with the associated claims data, and 
then Hybrid HWM measure results will be shared with hospitals in the 
confidential hospital-specific feedback reports planned for the spring 
of 2025, providing hospitals a 30-day review period prior to public 
reporting. Thereafter, in subsequent reporting years, we will follow a 
similar operational timeline for EHR data submissions, availability of 
hospital specific reports, and public reporting on the Care Compare 
website or its successor website.
    We refer readers to section IX.C.9.f. of the preamble of this final 
rule for more details and proposals related to data submission 
requirements for hybrid measures, including the Hybrid HWM measure.
    We invited public comment on this proposal.
    Comment: Many commenters supported adoption of the Hybrid HWM 
measure into the Hospital IQR Program. Some commenters noted their 
appreciation of the benefits of the Hybrid HWM measure, such as 
providing a more comprehensive picture of mortality rates than the 
condition-specific mortality measures, and, particularly for low-volume 
hospitals not captured by condition-specific mortality measures, 
providing information on the effects of COVID-19 on 30-day mortality 
nationally.
    Response: We thank the commenters for their support.
    Comment: Several commenters expressed concern regarding the 
administrative burden of reporting the Hybrid HWM measure and 
recommended ways to minimize the burden of submitting the data. 
Specifically, commenters recommended completely aligning the data 
requirements for the two hybrid measures (Hybrid HWM and Hybrid HWR), 
and suggested that hospitals should be able to submit the CCDE and 
linking variables needed for both measures in a single submission, such 
as through a single QRDA file such as is currently used to submit 
eCQMs.
    Response: We thank the commenters for their recommendations on 
reducing the administrative burden of the Hybrid HWM measure. We note 
that we aligned the specifications and data requirements for the two 
hybrid measures as much as possible, with the Hybrid HWM measure adding 
only one additional CCDE. We clarify that we intend to allow hospitals 
to submit a patient's CCDE and linking variables for both measures 
using a single submission to further minimize provider burden related 
to reporting of these measures.
    Comment: Several commenters recommended modifications to the Hybrid 
HWM measure cohort and exclusion criteria. Some commenters expressed 
support for the current exclusion criteria as appropriately excluding 
patients for whom hospitals have limited ability to prevent death. A 
few commenters suggested that the exclusion criteria be expanded and 
that the specifications be updated to more adequately address patient 
preferences

[[Page 45372]]

regarding life support treatments. Additionally, several commenters 
requested clarification on and further justification for the age range 
of patients included in the Hybrid HWM measure cohort as well as any 
differences between this measure and the Hybrid HWR measure cohort.
    Response: We appreciate the commenters' feedback. We believe that 
the mortality measure should only include patients for whom hospitals 
can meaningfully influence survival and we believe the measure, as 
currently specified, achieves this objective. As proposed, in addition 
to the exclusions for hospice and cancer, the measure specifications 
also exclude patients with numerous principal or secondary discharge 
diagnoses POA for conditions for which hospitals have limited ability 
to influence survival, and therefore, death would not be a quality 
signal.\949\ These conditions were selected with independent clinical 
expert input. For more details, we refer readers to the measure Data 
Dictionary and particularly the Survival NonInclusion tab available at: 
https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/HospitalQualityInits/Measure-Methodology.html. While we 
agree patient preferences regarding life support and ``do not 
resuscitate'' (DNR) orders are important to consider, they are 
currently differentially reported by hospitals, making them unreliable 
at this time for risk adjustment. CMS will continue to monitor coding 
patterns around these codes.
---------------------------------------------------------------------------

    \949\ Glennon G, Triche E, Wang Y, et al. Hybrid Hospital-Wide 
(All-Condition, All-Procedure) Risk-Standardized Mortality Measure 
with Electronic Health Record Extracted Risk Factors Methodology 
Report Version 2.0. March 2020. https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/HospitalQualityInits/Measure-Methodology.
---------------------------------------------------------------------------

    We note that the age ranges do differ between the Hybrid HWM 
measure and the Hybrid HWR measure. The Hybrid HWR measure includes all 
FFS beneficiaries 65 and older who meet the rest of the cohort 
criteria. For the Hybrid HWM measure, patients over the age of 94 are 
not included to avoid holding hospitals responsible for the survival of 
the oldest elderly patients, who may be less likely to have survival as 
a primary goal. We refer readers to the measure specifications for both 
measures available at: https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/HospitalQualityInits/Measure-Methodology.html.
    Comment: A number of commenters requested additional information 
regarding the data requirements for the Hybrid HWM measure. 
Specifically, a commenter requested clarification on the percentage of 
admissions requiring inclusion of lab results for the Hybrid HWM 
measure versus the Hybrid HWR measure. Several commenters specifically 
asked for the public posting of the measure methodology so hospitals 
and vendors can begin to familiarize themselves with it.
    Response: We thank the commenters for their input. For the Hybrid 
HWM measure, hospitals are required to report vital signs for 90 
percent or more of the hospital admissions for Medicare FFS patients, 
aged between 65 and 94 years old discharged in the measurement period, 
and laboratory test results for 90 percent or more of hospital 
admissions for nonsurgical patients, meaning those not included in the 
surgical divisions of the Hybrid HWM measure. For the Hybrid HWR 
measure, hospitals are required to report vital signs for 90 percent or 
more of the hospital discharges for Medicare FFS patients, aged 65 
years or older (no upper age limit) in the measurement period (as 
determined from the claims submitted to CMS for admissions that ended 
during the same reporting period); and submit laboratory test results 
for 90 percent or more of discharges for nonsurgical patients, meaning 
those not included in the surgical specialty cohort of the Hybrid HWR 
measure. Additional information on the specifications of the Hybrid HWM 
measure can be found on the eCQI resource center website at: https://ecqi.healthit.gov/eh-cah?qt-tabs_eh=3&globalyearfilter=2022 and for the 
Hybrid HWR measure also on the QualityNet website: https://qualitynet.cms.gov/inpatient/measures/hybrid/resources.
    Comment: Several commenters supported the inclusion of data from 
the EHR to improve risk adjustment and measure validity. Commenters 
noted the benefits of risk adjustment include an increased likelihood 
of fair comparisons of provider performance and recognition of social 
determinants of health. However, several commenters felt the current 
risk adjustment approach was insufficient in preventing 
disproportionate penalties for safety-net providers and academic 
medical centers that treat greater proportions of vulnerable patients, 
urged CMS to conduct additional social risk factor testing approaches 
such as multi-level models or testing social factors prior to clinical 
variables, and recommended adjustment for social determinants of 
health. A commenter recommended CMS test the feasibility of using non-
clinical EHR-derived data elements to inform development of a risk 
adjustment approach for social risk factors. Additionally, several 
commenters recommended the following additional risk factors be added 
to the measure: ``code status'', which the commenter expressed is 
strongly associated with mortality, particularly at the facility level, 
pre- and post-admission functional and cognitive status, and lactate 
and procalcitonin as indicators of disease severity. A commenter also 
expressed support for the inclusion of EHR data and suggested the need 
for oversight of the data entry process to ensure reliable data.
    Response: We thank the commenters for their support of moving 
toward more digital measurement and inclusion of EHR data to improve 
risk adjustment. With regards to the inclusion of social risk factors, 
our analysis of the fully aligned claims-only version of the HWM 
measure using data from July 1, 2016-June 30, 2017 found that adding 
risk variables into the multivariate model again attenuates the effect 
size for most divisions (the odds ratios for most divisions are close 
to 1 in the multivariate model), with the exception of the surgical 
cancer division that comprises only 2 percent of the cohort.\950\ 
Furthermore, we found that adjusting for either social risk factor had 
little impact on measure scores; measure scores calculated with and 
without social risk factors were highly correlated. We continue to be 
committed to better understanding the relationships between social risk 
factors, patient outcomes, and quality of care. We refer readers to 
section IX.B. of this final rule for more information regarding CMS' 
efforts to measure and improve health equity.
---------------------------------------------------------------------------

    \950\ National Quality Forum. Claims-Only Hospital-Wide (All-
Condition, All-Procedure) Risk-Standardized Mortality Measure (NQF 
#3504) and Hybrid Hospital-Wide (All-Condition, All-Procedure) Risk-
Standardized Mortality Measure. NQF #3502. Available at https://www.qualityforum.org/Qps/QpsTool.aspx.
---------------------------------------------------------------------------

    With regards to the specific clinical risk adjustment factors 
included in the Hybrid HWM measure, we believe the risk adjustment 
approach is adequate for accounting for case mix and service mix. Risk 
model testing using data from July 1, 2016-June 30, 2017 showed good 
model discrimination, predictive ability, and model fit.\951\ We 
approached risk variable selection from the perspective

[[Page 45373]]

of ensuring a parsimonious list of clinical EHR variables that would 
minimize hospital burden to report the data and provide face validity 
from a clinical perspective. As candidate risk variables, the CCDE are 
consistently captured, captured with a standard definition, and entered 
into the electronic health record in a structured field and can be 
feasibly extracted, as shown during development and testing, and 
subsequently presented to NQF. We will continue to evaluate the risk 
adjustment approach and specific risk factors, including those 
recommended by commenters such as code status, cognitive and functional 
status, and disease severity indicators, during regular measure 
maintenance as additional CCDE are better captured in the EHR and meet 
these guiding principles.
---------------------------------------------------------------------------

    \951\ Glennon G, Triche E, Wang Y, et al. Hybrid Hospital-Wide 
(All-Condition, All-Procedure) Risk-Standardized Mortality Measure 
with Electronic Health Record Extracted Risk Factors Methodology 
Report Version 2.0. March 2020. https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/HospitalQualityInits/Measure-Methodology.
---------------------------------------------------------------------------

    With regards to data entry oversight, the data elements included in 
the risk model represent clinical data used in the provision of 
clinical care. They were selected due to their regular occurrence 
within usual clinical workflow as well as their standardization, 
reproducibility, and ability to be validly extracted from the EHR; 
therefore, we are confident in the ability of facilities to reliably 
report this data.
    Comment: Several commenters did not support the adoption of the 
Hybrid HWM measure. A few commenters questioned the validity of the 
Hybrid HWM measure and requested a more robust face validity assessment 
and an analysis of the correlation of the HWM measure with the HWR 
measure. The commenters felt there was insufficient evidence to support 
a hospital-wide mortality outcome or to demonstrate that hospitals can 
directly or indirectly impact mortality rates within 30 days of an 
inpatient admission via a process, intervention, or service that could 
be attributed to an individual hospital. Several commenters felt the 
condition-specific mortality measures already in use in CMS programs 
were sufficient and/or more actionable than a hospital-wide measure, 
and adding a hospital-wide mortality measure meant a single mortality 
event could count against a hospital across more than one measure. A 
few commenters recommended that we adapt the condition-specific 
measures into hybrid measures to eventually replace the Hybrid HWM in 
the Hospital IQR Program. Additionally, several commenters questioned 
the usefulness of the Hybrid HWM measure to hospitals and patients 
given the limited variation in performance scores and perceived limits 
in hospitals' ability to understand and improve quality based upon 
claims data.
    Response: We thank the commenters for their input. The Hybrid HWM 
measure was NQF endorsed in June 2019 following review by the NQF 
Scientific Methods Panel and recommendation for endorsement by the 
Patient Safety Standing Committee.\952\ The face validity and empiric 
validity testing results submitted to NQF for measure endorsement 
support the validity of the Hybrid HWM measure. In terms of face 
validity, 5 of 6 respondents (83 percent) to the Technical Expert Panel 
(TEP) survey indicated that they somewhat, moderately, or strongly 
agreed, with the following statement: ``The risk-standardized hospital 
visits rates obtained from the Hybrid HWM measure, as specified, can be 
used to distinguish between better and worse quality facilities.'' 
Empiric validity testing, performed in the claims-based hospital-wide 
mortality measure that is identical to the Hybrid measure except for 
the addition of the CCDE in the Hybrid version, demonstrates a 
relationship between Hospital Wide Mortality and nurse-to-bed ratio, as 
well as to the condition-specific mortality rates in the Overall 
Hospital Quality Star Rating Mortality Group Score.
---------------------------------------------------------------------------

    \952\ National Quality Forum, Consensus Standards Approval 
Committee Web Meetings: Fall 2019 Meeting Summary. https://www.qualityforum.org/About_NQF/CSAC/Meetings/2019_CSAC_Meetings.aspx.
---------------------------------------------------------------------------

    In terms of variation, while we recognize that many hospitals may 
be categorized as ``no different than the national average'', the 
variation in performance (submitted to NQF based on data from July 1, 
2016-June 30, 2017) between the hospitals with the lowest mortality 
rates (risk-standardized mortality rate or RSMR of 3.95 percent) and 
the hospitals with the highest mortality rate (RSMR of 8.7 percent) 
shows there is a clear quality gap. Specifically, the best performing 
hospital (RSMR of 3.95 percent) is performing 43 percent better than an 
average performer (or has about 30 fewer deaths per 1000 patients 
compared to the average performer), while the worst performing hospital 
(8.70 percent) is performing 25 percent worse than an average performer 
(or has 18 more deaths per 1000 patients). We believe this information 
is important for hospitals to understand and improve their quality and 
for patient decision-making.
    We agree that the condition- and procedure-specific mortality 
measures provide valuable information to many hospitals to focus their 
quality improvement efforts. We interpret the commenters to be 
referring to the condition-specific mortality measures in the Hospital 
VBP Program (Pneumonia (PN) 30-Day Mortality Rate (Updated Cohort) (76 
FR 26495 through 26511); Heart Failure (HF) 30-Day Mortality Rate (76 
FR 26495 through 26511); Coronary Artery Bypass Grafting (CABG) 30-Day 
Mortality Rate (81 FR 56996 through 56998); Chronic Obstructive 
Pulmonary Disease (COPD) 30-Day Mortality Rate (80 FR 49557 through 
49558); and Acute Myocardial Infarction (AMI) 30-Day Mortality Rate (76 
FR 26495)). We encourage hospitals to consider their results on those 
measures together with their Hybrid HWM measure results and the 
individual service line results within the Hybrid HWM. We also note 
that the Hybrid HWM measure offers the additional advantage of 
measuring mortality rates in smaller volume hospitals and provides an 
important balancing measure for CMS' existing Hybrid HWR measure.
    Comment: Many commenters supported the proposal to conduct a 
voluntary reporting period for the Hybrid HWM measure prior to 
mandatory reporting, to allow hospitals time to gain familiarity with 
the measure and submission process. Several commenters suggested that 
during the voluntary reporting period, we monitor closely for 
unintended consequences and also evaluate and make public any issues 
with EHR data extraction or submission and measure validity. Several 
commenters felt it was premature to adopt mandatory reporting of the 
Hybrid HWM measure and recommended CMS implement an additional 
voluntary reporting period or delay mandatory reporting by an 
additional year, citing concerns such as hospital and vendor readiness, 
the capabilities of the QualityNet system to receive the large amount 
of data that would be submitted, the need to consider additional risk 
adjustment once data are collected through voluntary reporting, and 
confirmation of the benefit of the added effort of hybrid measure 
reporting.
    Response: We agree with commenters that a voluntary reporting 
period will allow hospitals time to gain experience with submitting the 
Hybrid HWM measure, and we believe one voluntary reporting period will 
be sufficient. We disagree that it is premature to implement mandatory 
reporting of the measure the following year, noting the mandatory 
reporting does not begin until FY 2026 payment determination (data 
period July 1, 2023 through June 30, 2024). The Hybrid HWM measure is 
closely aligned with the Hybrid HWR measure which utilizes nine of the 
ten CCDEs required for the Hybrid HWM

[[Page 45374]]

measure. One hundred and forty-nine hospitals have already successfully 
participated in the first voluntary reporting period for the Hybrid 
HWR, and therefore, we are confident that hospitals can continue to 
improve their data collection and submission systems throughout the 
second Hybrid HWR and the Hybrid HWM voluntary reporting periods. With 
regards to data submission to the CMS Hospital Quality Reporting (HQR) 
system (formerly referred to as the QualityNet system or QualityNet 
Secure Portal), we believe CMS systems are fully capable of receiving 
all the required data files. We are committed to continuing to improve 
these systems and responding to stakeholder feedback during voluntary 
and mandatory reporting.
    Comment: A few commenters requested that CMS seek stakeholder 
feedback on options for how the measure will be publicly reported.
    Response: We appreciate commenters' suggestion. In the FY 2022 
IPPS/LTCH PPS proposed rule, where we proposed this measure, we 
solicited comments on all aspects of this measure, including public 
reporting, but did not receive any specific suggestions on how the 
measure data would be publicly reported. We also generally encourage 
stakeholders to submit such comments via rulemaking or through our 
outreach and education efforts, such as through webinars, national 
provider calls, stakeholder listening sessions, as well as through 
other collaborative engagements with stakeholders.
    After consideration of the public comments we received, we are 
finalizing our proposal as proposed.
c. Adoption of the COVID-19 Vaccination Coverage Among HCP Measure 
Beginning With Shortened Reporting Period From October 1, 2021 Through 
December 31, 2021, Affecting the CY 2021 Reporting Period/FY 2023 
Payment Determination, and for Subsequent Years
(1) Background
    On January 31, 2020, the Secretary of the U.S. Department Health 
and Human Services declared a public health emergency (PHE) for the 
United States in response to the global outbreak of SARS-CoV-2, a novel 
(new) coronavirus that causes a disease named ``coronavirus disease 
2019'' (COVID-19).\953\ COVID-19 is a contagious respiratory 
infection\954\ that can cause serious illness and death. Older 
individuals and those with underlying medical conditions are considered 
to be at higher risk for more serious complications from COVID-19.\955\
---------------------------------------------------------------------------

    \953\ U.S. Dept of Health and Human Services, Office of the 
Assistant Secretary for Preparedness and Response. (2020). 
Determination that a Public Health Emergency Exists. Available at: 
https://www.phe.gov/emergency/news/healthactions/phe/Pages/2019-nCoV.aspx.
    \954\ Centers for Disease Control and Prevention. (2020). Your 
Health: Symptoms of Coronavirus. Available at: https://www.cdc.gov/coronavirus/2019-ncov/symptoms-testing/symptoms.html.
    \955\ Centers for Disease Control and Prevention. (2020). Your 
Health: Symptoms of Coronavirus. Available at https://www.cdc.gov/coronavirus/2019-ncov/symptoms-testing/symptoms.html.
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    As stated in the proposed rule, as of April 2, 2021 the U.S. 
reported over 30 million cases of COVID-19 and over 550,000 COVID-19 
deaths.\956\ Hospitals and health systems saw significant surges of 
COVID-19 patients as community infection levels increased.\957\ From 
December 2, 2020 through January 30, 2021, more than 100,000 Americans 
were in the hospital with COVID-19 at the same time.\958\ As of July 
21, 2021, the U.S. has reported over 34 million cases of COVID-19 and 
over 607,000 COVID-19 deaths.\959\
---------------------------------------------------------------------------

    \956\ This information has been updated from the proposed rule 
to reflect current data from the Centers for Disease Control and 
Prevention. (2020). CDC COVID Data Tracker. Available at: https://covid.cdc.gov/covid-data-tracker/#cases_casesper100klast7days.
    \957\ Associated Press. Tired to the Bone. Hospitals Overwhelmed 
with Virus Cases. November 18, 2020. Accessed on December 16, 2020, 
at https://apnews.com/article/hospitals-overwhelmed-coronavirus-cases-74a1f0dc3634917a5dc13408455cd895. Also see: New York Times. 
Just how full are U.S. intensive care units? New data paints an 
alarming picture. November 18, 2020. Accessed on December 16, 2020, 
at: https://www.nytimes.com/2020/12/09/world/just-how-full-are-us-intensive-care-units-new-data-paints-an-alarming-picture.html.
    \958\ US Currently Hospitalized [bond] The COVID Tracking 
Project. Accessed January 31, 2021 at: https://covidtracking.com/data/charts/us-currently-hospitalized.
    \959\ Centers for Disease Control and Prevention. (2021). CDC 
COVID Data Tracker. Available at: https://covid.cdc.gov/covid-data-tracker/#cases_casesper100klast7days.
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    Evidence indicates that COVID-19 primarily spreads when individuals 
are in close contact with one another.\960\ The virus is typically 
transmitted through respiratory droplets or small particles created 
when someone who is infected with the virus coughs, sneezes, sings, 
talks or breathes.\961\ Thus, the Centers for Disease Control and 
Prevention advises that infections mainly occur through exposure to 
respiratory droplets when a person is in close contact with someone who 
has COVID-19.\962\ Experts believe that COVID-19 spreads less commonly 
through contact with a contaminated surface.\963\ Subsequent to the 
publication of the proposed rule, the CDC has confirmed that the three 
main ways that COVID-19 is spread are: (1) Breathing in air when close 
to an infected person who is exhaling small droplets and particles that 
contain the virus; (2) Having these small droplets and particles that 
contain virus land on the eyes, nose, or mouth, especially through 
splashes and sprays like a cough or sneeze; and (3) Touching eyes, 
nose, or mouth with hands that have the virus on them.\964\ According 
to the CDC, those at greatest risk of infection are persons who have 
had prolonged, unprotected close contact (that is, within 6 feet for 15 
minutes or longer) with an individual with confirmed SARS-CoV-2 
infection, regardless of whether the individual has symptoms.\965\ 
Although infections through inhalation at distances greater than six 
feet from an infectious source are less likely than at closer 
distances, the phenomenon has been repeatedly documented under certain 
preventable circumstances. These transmission events have involved the 
presence of an infectious person exhaling virus indoors for an extended 
time (more than 15 minutes and in some cases hours) leading to virus 
concentrations in the air space sufficient to transmit infections to 
people more than 6 feet away, and in some cases to people who have 
passed through that space soon after the infectious person left. 
Personal protective equipment (PPE) and other infection-control 
precautions can reduce the likelihood of transmission in health care 
settings, but COVID-19 can still spread between health care personnel 
(HCP) and patients, or from patient to patient given the close contact 
that may occur during the provision of care.\966\ The CDC has 
emphasized that health

[[Page 45375]]

care settings, including long-term care settings, can be high-risk 
places for COVID-19 exposure and transmission.\967\
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    \960\ Centers for Disease Control and Prevention. (2021). How 
COVID-19 Spreads. Accessed on April 3, 2021 at: https://www.cdc.gov/coronavirus/2019-ncov/prevent-getting-sick/how-covid-spreads.html.
    \961\ Centers for Disease Control and Prevention (2021). How 
COVID-19 Spreads. Accessed on April 3, 2021 at: https://www.cdc.gov/coronavirus/2019-ncov/prevent-getting-sick/how-covid-spreads.html.
    \962\ Centers for Disease Control and Prevention (2021). How 
COVID-19 Spreads. Accessed on April 3, 2021 at: https://www.cdc.gov/coronavirus/2019-ncov/prevent-getting-sick/how-covid-spreads.html.
    \963\ Centers for Disease Control and Prevention. (2021). How 
COVID-19 Spreads. Accessed on April 3, 2021 at: https://www.cdc.gov/coronavirus/2019-ncov/prevent-getting-sick/how-covid-spreads.html.
    \964\ Centers for Disease Control and Prevention. (2021). How 
COVID-19 Spreads. Accessed on July 15, 2021 at: https://www.cdc.gov/coronavirus/2019-ncov/prevent-getting-sick/how-covid-spreads.html.
    \965\ Centers for Disease Control and Prevention. (2021). When 
to Quarantine. Accessed on April 2, 2021 at: https://www.cdc.gov/coronavirus/2019-ncov/if-you-are-sick/quarantine.html.
    \966\ Centers for Disease Control and Prevention. (2021). 
Interim U.S. Guidance for Risk Assessment and Work Restrictions for 
Healthcare Personnel with Potential Exposure to COVID-19. Accessed 
on April 2 at: https://www.cdc.gov/coronavirus/2019-ncov/hcp/faq.html#Transmission.
    \967\ Dooling, K, McClung, M, et al. ``The Advisory Committee on 
Immunization Practices' Interim Recommendations for Allocating 
Initial Supplies of COVID-19 Vaccine--United States, 2020.'' Morb 
Mortal Wkly Rep. 2020; 69(49): 1857-1859.
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    Vaccination is a critical part of the nation's strategy to 
effectively counter the spread of COVID-19 and ultimately helps restore 
societal functioning.\968\ On December 11, 2020, the FDA issued the 
first Emergency Use Authorization (EUA) for a COVID-19 vaccine in the 
U.S.\969\ Subsequently, FDA issued EUAs for additional COVID-19 
vaccines.\970\
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    \968\ Centers for Disease Control and Prevention. (2020). COVID-
19 Vaccination Program Interim Playbook for Jurisdiction Operations. 
Accessed on December 18 at: https://www.cdc.gov/vaccines/imz-managers/downloads/COVID-19-Vaccination-Program-Interim_Playbook.pdf.
    \969\ U.S. Food and Drug Administration. (2021). Pfizer-BioNTech 
COVID-19 Vaccine. Available at https://www.fda.gov/emergency-preparedness-and-response/coronavirus-disease-2019-covid-19/pfizer-biontech-covid-19-vaccine.
    \970\ U.S. Food and Drug Administration. (2020). Pfizer-BioNTech 
COVID-19 Vaccine EUA Letter of Authorization. Available at https://www.fda.gov/media/144412/download; U.S. Food and Drug 
Administration. (2020). Moderna COVID-19 Vaccine EUA Letter of 
Authorization. Available at https://www.fda.gov/media/144636/download; U.S. Food and Drug Administration. (2021). Janssen COVID-
19 Vaccine EUA Letter of Authorization. Available at https://www.fda.gov/media/146303/download.
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    FDA determined that the vaccines met the statutory criteria for 
issuance of an EUA. The totality of the available data provided clear 
evidence that the vaccines may be effective to prevent COVID-19, and 
that the known and potential benefits of the vaccines, when used as 
authorized to prevent COVID-19, outweighed the known and potential 
risks.\971\
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    \971\ U.S. Food and Drug Administration. (2020). Pfizer-BioNTech 
COVID-19 Vaccine EUA Letter of Authorization. Available at https://www.fda.gov/media/144412/download Tech COVID-19 Vaccine EUA Letter 
of Authorization (fda.gov); U.S. Food and Drug Administration. 
(2020). ModernaTx, Inc. COVID-19 Vaccine EUA Letter of 
Authorization. Available at: https://www.fda.gov/media/144636/download; U.S. Food and Drug Administration. (January 2020). 
Guidance Document: Emergency Use Authorization of Medical Products 
and Related Authorities. Accessed on December 17, 2020, at: https://www.fda.gov/regulatory-information/search-fda-guidance-documents/emergency-use-authorization-medical-products-and-related-authorities#scope.
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    As part of its national strategy to address COVID-19, the Biden 
Administration stated on March 25, 2021 that it would work with states 
and the private sector to execute an aggressive vaccination strategy 
and has outlined a goal of administering 200 million shots in 100 
days.\972\ Although the goal of the U.S. government is to ensure that 
every American who wants to receive a COVID-19 vaccine can receive one, 
Federal agencies recommended that early vaccination efforts focus on 
those critical to the PHE response, including HCP providing direct care 
to patients with COVID-19, and individuals at highest risk for 
developing severe illness from COVID-19.\973\ For example, the CDC's 
Advisory Committee on Immunization Practices (ACIP) recommended that 
HCP should be among those individuals prioritized to receive the 
initial, limited supply of the COVID-19 vaccine given the potential for 
transmission in health care settings and the need to preserve health 
care system capacity.\974\ Research suggests most states followed this 
recommendation,\975\ and HCP began receiving the vaccine in mid-
December of 2020.\976\
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    \972\ The White House. Remarks by President Biden on the COVID-
19 Response and the State of Vaccinations. March 29, 2021. Accessed 
at https://www.whitehouse.gov/briefing-room/speeches-remarks/2021/03/29/remarks-by-president-biden-on-the-covid-19-response-and-the-state-of-vaccinations/.
    \973\ Health and Human Services, Department of Defense. (2020) 
From the Factory to the Frontlines: The Operation Warp Speed 
Strategy for Distributing a COVID-19 Vaccine. Accessed December 18 
at: https://www.hhs.gov/sites/default/files/strategy-for-distributing-covid-19-vaccine.pdf; Centers for Disease Control 
(2020). COVID-19 Vaccination Program Interim Playbook for 
Jurisdiction Operations. Accessed December 18 at: https://www.cdc.gov/vaccines/imz-managers/downloads/COVID-19-Vaccination-Program-Interim_Playbook.pdf.
    \974\ Dooling, K, McClung, M, and et al. ``The Advisory 
Committee on Immunization Practices' Interim Recommendations for 
Allocating Initial Supplies of COVID-19 Vaccine--United States, 
2020.'' Morb. Mortal Wkly Rep. 2020; 69(49): 1857-1859. ACIP also 
recommended that long-term care residents be prioritized to receive 
the vaccine, given their age, high levels of underlying medical 
conditions, and congregate living situations make them high risk for 
severe illness from COVID-19.
    \975\ Kates, J, Michaud, J, Tolbert, J. ``How Are States 
Prioritizing Who Will Get the COVID-19 Vaccine First?'' Kaiser 
Family Foundation. December 14, 2020. Accessed on December 16 at 
https://www.kff.org/policy-watch/how-are-states-prioritizing-who-will-get-the-covid-19-vaccine-first/.
    \976\ Associated Press. `Healing is Coming:' US Health Workers 
Start Getting Vaccine. December 15, 2020. Accessed on December 16 
at: https://apnews.com/article/us-health-workers-coronavirus-vaccine-56df745388a9fc12ae93c6f9a0d0e81f.
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    Frontline healthcare workers, such as those employed in acute care 
hospitals, are being prioritized for vaccination in most locations. 
There are approximately 18 million healthcare workers in the United 
States.\977\ As of July 2, 2021, the CDC reported that over 328 million 
doses of the COVID-19 vaccine had been administered, and approximately 
155.9 million people had received a complete vaccination course.\978\ 
Subsequent to the publication of the proposed rule, on June 3, 2021 the 
White House confirmed that there was sufficient vaccine supply for all 
Americans.\979\
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    \977\ CDC/The National Institute for Occupational Safety and 
Health (NIOSH). Health Care Workers. Accessed on February 18, 2021 
at: https://www.cdc.gov/niosh/topics/healthcare/
default.html#:~:text=HEALTHCARE%20WORKERS,-
Related%20Pages&text=Healthcare%20is%20the%20fastest%2Dgrowing,of%20t
he%20healthcare%20work%20force.
    \978\ This information has been updated from the proposed rule 
to reflect current data from the CDC. COVID Data Tracker. COVID-19 
Vaccinations in the United States. Available at: https://covid.cdc.gov/covid-data-tracker/#vaccinations.
    \979\ Press Briefing by White House COVID-19 Response Team and 
Public Health Officials [bond] The White House. Accessed on July 21, 
2021 at https://www.whitehouse.gov/briefing-room/press-briefings/2021/06/03/press-briefing-by-white-house-covid-19-response-team-and-public-health-officials-40/.
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    We believe it is important to incentivize and track HCP vaccination 
in acute care facilities through quality measurement to protect health 
care workers, patients, and caregivers, and to help sustain the ability 
of hospitals to continue serving their communities throughout the PHE 
and beyond. Therefore, in the FY 2022 IPPS/LTCH PPS proposed rule (86 
FR 25571 through 25575) we proposed to adopt a new measure, COVID-19 
Vaccination Coverage Among HCP, beginning with a shortened reporting 
period from October 2021 through December 2021. The CY 2021 Reporting 
Period for the FY 2023 Payment Determination is shorter than the 
reporting period we proposed for subsequent years to expedite data 
collection of this measure in response to the current PHE. The measure 
will assess the proportion of a hospital's health care workforce that 
has been vaccinated against COVID-19.
    Although at this time data to show the effectiveness of COVID-19 
vaccines to prevent asymptomatic infection or transmission of SARS-CoV-
2 are limited, we believe hospitals should track the level of 
vaccination among their HCP as part of their efforts to assess and 
reduce the risk of transmission of COVID-19 within their facilities. 
HCP vaccination can potentially reduce illness that leads to work 
absence and limit disruptions to care.\980\ Data from influenza 
vaccination demonstrates that provider uptake of the vaccine is 
associated with that provider recommending vaccination to 
patients,\981\ and we believe HCP

[[Page 45376]]

COVID-19 vaccination in hospitals could similarly increase uptake among 
that patient population.
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    \980\ Centers for Disease Control and Prevention. Overview of 
Influenza Vaccination among Health Care Personnel. October 2020. 
(2020) Accessed March 16, 2021 at: https://www.cdc.gov/flu/toolkit/long-term-care/why.htm.
    \981\ Measure Applications Committee Coordinating Committee 
Meeting Presentation. March 15, 2021. (2021) Accessed March 16, 2021 
at: http://www.qualityforum.org/Project_Pages/MAP_Coordinating_Committee.aspx.
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    We also believe that publishing the HCP vaccination rates will be 
helpful to many patients, including those who are at high-risk for 
developing serious complications from COVID-19, as they choose 
facilities from which to seek treatment. Under CMS' Meaningful Measures 
Framework, the COVID-19 measure addresses the quality priority of 
``Promoting Effective Prevention and Treatment of Chronic Disease'' 
through the Meaningful Measures Area of ``Preventive Care.''
(2) Overview of Measure
    The COVID-19 Vaccination Coverage Among HCP measure is a process 
measure developed by the CDC to track COVID-19 vaccination coverage 
among HCP in facilities such as acute care facilities.
(a) Measure Specifications
    The denominator is the number of HCP eligible to work in the 
healthcare facility for at least one day during the reporting period, 
excluding persons with contraindications to COVID-19 vaccination that 
are described by the CDC.\982\
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    \982\ Centers for Disease Control and Prevention. 
Contraindications and precautions. (2021) Accessed March 15, 2021 
at: https://www.cdc.gov/vaccines/covid-19/info-by-product/clinical-considerations.html#Contraindications.
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    The numerator is the cumulative number of HCP eligible to work in 
the health care facility for at least one day during the reporting 
period and who received a completed vaccination course against COVID-19 
since the date the vaccine was first available or on a repeated 
interval if revaccination is recommended.\983\ Vaccination coverage for 
the purposes of this measure is defined as the estimated percentage of 
HCP eligible to work at acute care hospitals for at least one day who 
received a completed vaccination course.\984\ A completed vaccination 
course may require one or more doses depending on the EUA for the 
specific vaccine used. We refer readers to https://www.cdc.gov/nhsn/nqf/index.html for more details on the measure specifications.
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    \983\ Measure Applications Partnership Coordinating Committee 
Meeting Presentation. March 15, 2021. (2021) Accessed March 16, 2021 
at: http://www.qualityforum.org/Project_Pages/MAP_Coordinating_Committee.aspx.
    \984\ We note that in the FY 2022 IPPS/LTCH PPS proposed rule, 
in this sentence, we inadvertently referred to ``IPFs'' instead of 
acute care hospitals (86 FR 25573).
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(b) Review by the Measure Applications Partnership (MAP)
    The COVID-19 Vaccination Coverage Among HCP measure was included on 
the publicly available ``List of Measures under Consideration for 
December 21, 2020'' (MUC List), a list of measures under consideration 
for use in various Medicare programs.\985\ When the MAP Hospital 
Workgroup convened on January 11, 2021, it reviewed the measures on the 
MUC List, including the COVID-19 Vaccination Coverage Among HCP 
measure. \986\ The MAP recognized that the proposed measure represents 
a promising effort to advance measurement for an evolving national 
pandemic and that it would bring value to the Hospital IQR Program 
measure set by providing transparency about an important COVID-19 
intervention to help prevent infections in HCP and patients.\987\ The 
MAP also stated that collecting information on COVID-19 vaccination 
coverage among HCP and providing feedback to facilities will allow 
facilities to benchmark coverage rates and improve coverage in their 
facility, and that reducing rates of COVID-19 in healthcare personnel 
may reduce transmission among patients and reduce instances of staff 
shortages due to illness.\988\
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    \985\ National Quality Forum. List of Measures Under 
Consideration for December 21, 2020. Accessed at: https://www.cms.gov/files/document/measures-under-consideration-list-2020-report.pdf on January 12, 2021.
    \986\ The MUC List and the MAP referred to the measure as the 
``SARS-CoV-2 Vaccination Coverage Among Healthcare Personnel.''
    \987\ Measure Applications Partnership. MAP Preliminary 
Recommendations 2020-2021. Accessed on January 24, 2021 at: http://www.qualityforum.org/Project_Pages/MAP_Hospital_Workgroup.aspx.
    \988\ Measure Applications Partnership. MAP Preliminary 
Recommendations 2020-2021. Accessed on January 24, 2021 at: http://www.qualityforum.org/Project_Pages/MAP_Hospital_Workgroup.aspx.
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    In its preliminary review, the MAP Hospital Workgroup did not 
support this measure for rulemaking, subject to potential for 
mitigation.\989\ To mitigate its concerns, the MAP Hospital Workgroup 
believed that the measure needed well-documented evidence, finalized 
specifications, testing, and NQF endorsement prior to 
implementation.\990\ Subsequently, the MAP Coordinating Committee met 
on January 25, 2021, to review and make a recommendation on the COVID-
19 Vaccination Coverage Among HCP measure. In the 2020-2021 MAP Final 
Recommendations, the MAP offered conditional support for rulemaking 
contingent on CMS bringing the measure back to the MAP once the 
specifications are further refined specifically saying that ``the 
incomplete specifications require immediate mitigation and further 
development should continue.''\991\ In its final report, the MAP noted 
that the measure would add value to the program measure set by 
providing visibility into an important intervention to limit COVID-19 
infections in healthcare personnel and the patients for whom they 
provide care.\992\ The spreadsheet of final recommendations no longer 
cited concerns regarding evidence, testing, or NQF endorsement.\993\
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    \989\ Measure Applications Partnership. MAP Preliminary 
Recommendations 2020-2021. Accessed on January 24, 2021 at: http://www.qualityforum.org/Project_Pages/MAP_Hospital_Workgroup.aspx.
    \990\ Measure Applications Partnership. MAP Preliminary 
Recommendations 2020-2021. Accessed on January 24, 2021 at: http://www.qualityforum.org/Project_Pages/MAP_Hospital_Workgroup.aspx.
    \991\ Measure Applications Partnership. 2020-2021 MAP Final 
Recommendations. Accessed on February 23, 2021 at: http://www.qualityforum.org/Project_Pages/MAP_Hospital_Workgroup.aspx.
    \992\ Measure Applications Partnership. 2020-2021 Measure 
Applications Partnership. 2020-2021 Considerations for Implementing 
Measures Final Report--Clinicians, Hospitals, and PAC-LTC. Accessed 
on March 12, 2021 at: https://www.qualityforum.org/Publications/2021/03/MAP_2020-2021_Considerations_for_Implementing_Measures_Final_Report_-_Clinicians,_Hospitals,_and_PAC-LTC.aspx.
    \993\ Measure Applications Partnership. 2020-2021 MAP Final 
Recommendations. Accessed on February 18 at: NQF: Measure 
Applications Partnership (qualityforum.org).
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    In response to the MAP final recommendation request that CMS bring 
the measure back to the MAP once the specifications are further 
refined, CMS and the CDC met with MAP Coordinating committee on March 
15, 2021. CMS and the CDC provided additional information to the MAP 
Coordinating Committee at that meeting to address vaccine availability, 
the alignment of the COVID-19 Vaccination Coverage Among HCP measure as 
closely as possible with the Influenza HCP vaccination measure (NQF 
#0431) specifications, and the definition of HCP used in the measure. 
At this meeting, CMS and the CDC also presented preliminary findings 
from the testing of the numerator of COVID-19 Vaccination Coverage 
Among HCP, which is currently in process. These preliminary findings 
showed that the numerator data should be feasible and reliable. Testing 
of the numerator of the number of healthcare personnel vaccinated 
involves a comparison vaccination data collected by the CDC directly 
from long-term care facilities (LTCFs) through NHSN with vaccination 
data independently reported to the CDC through the Federal pharmacy

[[Page 45377]]

partnership program for delivering vaccination to LTC facilities. These 
are two completely independent data collection systems. In initial 
analyses of the first month of vaccination from December 2020 to 
January 2021, the number of healthcare workers vaccinated in 
approximately 1,200 facilities, which had data from both systems the 
number of healthcare personnel vaccinated, was highly correlated 
between these 2 systems with a correlation coefficient of nearly 90 
percent in the second two weeks of reporting.\994\ Because of the high 
correlation across a large number of facilities and high number of HCP 
within those facilities receiving at least one dose of the COVID-19 
vaccine, we believe this data indicates the measure is feasible and 
reliable for use in the Hospital IQR Program.
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    \994\ For more information on testing results and other measure 
updates, please see the Meeting Materials (including Agenda, 
Recording, Presentation Slides, Summary, and Transcript) of the 
March 15, 2021 meeting available at https://www.qualityforum.org/ProjectMaterials.aspx?projectID=75367.
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    We value the recommendations of the MAP and considered these 
recommendations carefully. Section 1890A(a)(4) of the Act, as added by 
section 3014(b) of the Affordable Care Act, requires the Secretary to 
take into consideration input from multi-stakeholder groups in 
selecting quality and efficiency measures. While we value input from 
the MAP, we believe it is important to propose the measure as quickly 
as possible to address the urgency of the COVID-19 PHE and its impact 
on vulnerable populations. CMS continues to engage with the MAP to 
mitigate concerns and appreciates the MAP's conditional support for the 
measure.
(3) NQF Endorsement
    Under section 1886(s)(4)(D)(i) of the Act, unless the exception of 
subclause (ii) applies, measures selected for the quality reporting 
program must have been endorsed by the entity with a contract under 
section 1890(a) of the Act. The NQF currently holds this contract. 
Section 1886(s)(4)(D)(ii) of the Act provides an exception to the 
requirement for NQF endorsement of measures: in the case of a specified 
area or medical topic determined appropriate by the Secretary for which 
a feasible and practical measure has not been endorsed by the entity 
with a contract under section 1890(a) of the Act, the Secretary may 
specify a measure that is not so endorsed as long as due consideration 
is given to measures that have been endorsed or adopted by a consensus 
organization identified by the Secretary.
    This measure is not NQF-endorsed and has not been submitted to NQF 
for endorsement consideration. The CDC, in collaboration with CMS, is 
planning to submit the measure for consideration in the NQF Fall 2021 
measure cycle.
    Because this measure is not NQF-endorsed, we considered other 
available measures. We found no other feasible and practical measures 
on the topic of COVID-19 vaccination among HCP, therefore we believe 
the exception in section 1186(s)(4)(D)(ii) of the Act applies.
(4) Data Submission and Reporting
    Given the time-sensitive nature of this measure in light of the 
PHE, we proposed that for the FY 2023 program year, the reporting 
period would be from October 1, 2021 through December 31, 2021. The 
reporting period we proposed is shorter than the reporting period for 
subsequent years to expedite data collection for this measure in order 
to respond to the current PHE. Thereafter, we proposed quarterly 
reporting deadlines for the Hospital IQR Program beginning with the CY 
2022 reporting period/FY 2024 payment determination and for subsequent 
years.
    To report this measure, we proposed that hospitals would collect 
the numerator and denominator for the COVID-19 Vaccination Coverage 
Among HCP measure for at least one self-selected week during each month 
of the reporting quarter and submit the data to the NHSN Healthcare 
Personal Safety (HPS) Component before the quarterly deadline to meet 
Hospital IQR Program requirements. While we believe that it would be 
ideal to have HCP vaccination data for every week of each month, we are 
mindful of the time and resources that hospitals would need to report 
the data. Thus, in collaboration with the CDC, we determined that data 
from at least one week of each month would be sufficient to obtain a 
reliable snapshot of vaccination levels among a hospital's healthcare 
personnel while balancing the costs of reporting. If a hospital submits 
more than one week of data in a month, the most recent week's data will 
be used to calculate the measure. For example, if first and third week 
data are submitted, third week data will be used. If first, second, and 
fourth week data are submitted, fourth week data will be used. Each 
quarter, the CDC will calculate a single quarterly COVID-19 HCP 
vaccination coverage rate for each hospital, which will be calculated 
by taking the average of the data from the three weekly rates submitted 
by the hospital for that quarter. CMS will publicly report each 
quarterly COVID-19 HCP vaccination coverage rate as calculated by the 
CDC.
    As described in section IX.C.9.j., hospitals will report the number 
of HCP eligible to have worked at the facility during the self-selected 
week that the hospital reports data for in NHSN (denominator) and the 
number of those HCP who have received a complete course of a COVID-19 
vaccination (numerator) during the same self-selected week.
    We invited public comment on this proposal.
    Comment: Many commenters supported our proposal to adopt the COVID-
19 Vaccination Coverage Among HCP Measure. Commenters acknowledged that 
evidence confirms vaccination of HCP effectively reduces infection, and 
consumers deserve information on vaccination coverage among HCP when 
choosing where to receive care. Some commenters noted that the entire 
health care team, not just physicians, have daily contact with patients 
and measuring vaccination status of all HCP protects both patients and 
staff.
    Response: We thank commenters for their support of the measure and 
agree that vaccination remains important as the PHE continues.
    Comment: Many commenters noted that, presently, all COVID-19 
vaccines are authorized through an EUA. Some of these commenters 
expressed that individuals remain hesitant to receive vaccination 
during the EUA and the measure is premature until such time that a 
vaccine has received full FDA approval. A few commenters stated that 
these vaccines have been available and deployed for a short amount of 
time and there is not currently sufficient information available to 
include a vaccination measure in quality reporting programs. Several 
commenters worried that the country lacks experience with these 
vaccines, and the measure proposal is premature. Several commenters 
asserted that, until vaccines receive full FDA approval, CMS lacks the 
information necessary to include this measure in the Hospital IQR 
Program. A few commenters believed that the measure should be endorsed 
by the National Quality Forum (NQF) before it is adopted in the 
program. A few commenters recommended a delay indefinitely until 
vaccines receive full FDA approval or NQF endorsement.
    Response: While we support widespread vaccination coverage, we also 
understand that some HCP may be concerned about receiving the COVID-19 
vaccine prior to the vaccine receiving full FDA approval. We refer 
readers to

[[Page 45378]]

the FDA website for additional information related to FDA's process for 
evaluating an Emergency Use Authorization (EUA) request at https://www.fda.gov/vaccines-blood-biologics/vaccines/emergency-use-authorization-vaccines-explained. While we recognize there are 
differences between EUA authorization and full FDA approval, we note 
that the process for each is scientifically rigorous. Each vaccine 
manufacturer that received EUA authorization enrolled tens of thousands 
of participants in randomized clinical trials, which is similar to what 
is required for full FDA approval.\995\ Manufacturers submit the same 
robust and rigorous data for both an EUA authorization and full FDA 
approval, and more than 330 million doses of COVID-19 vaccines 
authorized by EUAs have been administered.\996\ We believe these 
vaccines to be proven safe and effective.
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    \995\ Harvard Law Petrie-Flom Center. ``What's the Difference 
Between Vaccine Approval (BLA) and Authorization (EUA)?'' June 15, 
2021. Available at: https://blog.petrieflom.law.harvard.edu/2021/06/15/whats-the-difference-between-vaccine-approval-bla-and-authorization-eua/.
    \996\ Centers for Disease Control and Prevention. (2021). CDC 
COVID Data Tracker: COVID-19 Vaccinations in the United States. 
Available at: https://covid.cdc.gov/covid-data-tracker/#vaccinations 
(Accessed on July 19, 2021).
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    We further emphasize that the COVID-19 Vaccination Coverage Among 
HCP measure is a process measure that assesses HCP vaccination coverage 
rates, not an outcome measure for which hospitals are held directly 
accountable for a particular outcome, and does not require HCP to 
receive the vaccination. We believe that given the current COVID-19 PHE 
and the need for continued monitoring and surveillance following the 
PHE, it is important to adopt this measure as quickly as possible to 
allow tracking and reporting of the COVID-19 Vaccination Coverage Among 
HCP measure. This tracking would allow hospitals to identify the 
appropriateness and effectiveness of their initiatives to improve 
vaccination coverage and would provide consumers with important 
information.
    Because of this, we believe it is appropriate to use the exception 
provided in section 1886(b)(3)(B)(viii)(IX)(bb) of the Act. That 
exception allows for, in the case of a specified area or medical topic 
determined appropriate by the Secretary for which a feasible and 
practical measure has not been endorsed by the entity with a contract 
under section 1890(a) of the Act, the Secretary may specify a measure 
that is not so endorsed as long as due consideration is given to 
measures that have been endorsed or adopted by a consensus organization 
identified by the Secretary. We note that there is no NQF endorsed 
measure on the topic of COVID-19 vaccination coverage among healthcare 
personnel, but the CDC, in collaboration with CMS, is planning to 
submit the measure for consideration in the NQF 2021 measure cycle. The 
intent of adopting the COVID-19 Vaccination Coverage Among HCP measure 
is to collect and report data that will support public health tracking 
and provide patients, beneficiaries, and their caregivers with 
important information to support informed decision making. For these 
reasons, we believe that it is appropriate to collect and report these 
data as soon as possible.
    Comment: Some commenters requested that, given the relatively new 
roll-out of COVID-19 vaccination, CMS work with the CDC to continue to 
refine the measure as new evidence comes forward about vaccination 
during the PHE. A few commenters encouraged CMS to continue to update 
the measure as new evidence on COVID-19 continues to arise.
    Response: We thank the commenters for their suggestions. We will 
continue to work closely with the CDC and will consider any updates to 
the measure in future rulemaking as appropriate.
    Comment: Several commenters expressed concern that the future 
potential for booster vaccines is unknown and asserted it is premature 
to adopt the measure before this information is available. Some 
commenters requested clarification as to how the measure may change 
should boosters be needed. Several commenters stated that, while CMS 
aims to closely align the measure with the Influenza Vaccination 
Coverage Among HCP (NQF #0431) measure, the measures differ as the flu 
is seasonal in nature and requires a single vaccine while multiple 
doses or boosters may be required for COVID-19 as the evidence for 
appropriate vaccination course is determined over time.
    Response: We thank the commenters for their feedback. With regard 
to commenters stating that it is premature to adopt the measure, we 
believe that COVID-19 vaccines are a crucial tool for slowing the 
spread of disease and death among residents, staff, and the general 
public. Based on the FDA's review, evaluation of the data, and its 
decision to authorize three vaccines for emergency use, these vaccines 
meet FDA's standards for an EUA for safety and effectiveness to prevent 
COVID-19 disease and related serious outcomes, including 
hospitalization and death.\997\ The combination of vaccination, 
universal source control (wearing masks), social distancing, and 
handwashing offers further protection from COVID-19.\998\ Since the 
publication of the proposed rule, the emergence of coronavirus variants 
have resulted in an 84% increase in new virus cases. Given the EUA 
decisions by the FDA and the continued PHE, we disagree that adoption 
of the measure is premature, and believe our proposal to add the COVID-
19 Vaccination Coverage among HCP measure to the Hospital IQR Program 
is appropriate and necessary for patient safety.
---------------------------------------------------------------------------

    \997\ U.S. Food and Drug Administration. COVID-19 Vaccines. 
(2021). Available at: https://www.fda.gov/emergency-preparedness-and-response/coronavirus-disease-2019-covid-19/covid-19-vaccines.
    \998\ Centers for Disease Control and Prevention. Guidance for 
Unvaccinated People: How to Protect Yourself & Others. June 11, 
2021. Available at https://www.cdc.gov/coronavirus/2019-ncov/prevent-getting-sick/prevention.html. Accessed June 24, 2021.
---------------------------------------------------------------------------

    We appreciate commenter's concerns about the potential need for 
boosters. The COVID-19 Vaccination Coverage Among HCP measure is a 
measure of a completed vaccination course (as defined in section 
IX.C.9.c.(2).(a). of the FY 2022 IPPS/LTCH PPS proposed rule (86 FR 
25573)) and does not address booster shots. Currently, the need for 
COVID-19 booster doses has not been established, and no additional 
doses are currently recommended for HCP.\999\ We do not have enough 
information to comment on the details of the booster vaccination or the 
associated data collection. However, we believe that the numerator is 
sufficiently broad to include potential future boosters as part of a 
``complete vaccination course'' and therefore the measure is 
sufficiently specified to address boosters.
---------------------------------------------------------------------------

    \999\ Centers for Disease Control and Prevention. Vaccine 
Administration. Available at https://www.cdc.gov/vaccines/covid-19/clinical-considerations/covid-19-vaccines-us.html. Accessed June 25, 
2021.
---------------------------------------------------------------------------

    Comment: Some commenters expressed concern that the COVID-19 
Vaccination Coverage Among HCP measure is intended to align with the 
Influenza Vaccination Coverage Among HCP (NQF #0431) measure but 
asserted that the measure specifications for COVID-19 vaccination are 
more complex than those for influenza vaccination, noting that the 
Influenza Vaccination Coverage Among HCP (NQF #0431) measure does not 
have to address full versus partial vaccination status (and whether and 
how to account for partial vaccination), the potential need for 
boosters, or the approval status of vaccines.

[[Page 45379]]

    Response: We acknowledge that while the CDC has sought to align 
this measure with the Influenza Vaccination Coverage Among HCP measure 
(NQF #0431),\1000\ these are different public health initiatives, and 
different vaccines, and therefore the measure specifications are not in 
complete alignment. As the commenter has noted, the reporting 
requirements for the numerator of the COVID-19 Vaccination Coverage 
Among HCP measure are due to the fact that some COVID-19 vaccines 
require two doses to reach full vaccination status, while some COVID-19 
vaccines require only one dose. The measures are aligned with respect 
to the reporting mechanism used to report data (the NHSN) and key 
components of the measure specifications (for example, the definition 
of the denominator), but the measures allow for important differences 
to reflect the reality that the circumstances around vaccine 
administration (that the commenter points out) are not identical.
---------------------------------------------------------------------------

    \1000\ Measure Applications Committee Coordinating Committee 
Meeting Presentation. March 15, 2021. (2021) Accessed March 16, 2021 
at: http://www.qualityforum.org/Project_Pages/MAP_Coordinating_Committee.aspx.
---------------------------------------------------------------------------

    Comment: Several commenters opposed any requirement for HCP to 
receive vaccines. A few commenters noted that HCP may have legitimate 
reasons to decline vaccination, including contraindications, and should 
not be required to receive vaccination as a condition of continued 
employment. Some commenters encouraged CMS to consider vaccination 
exclusions other than medical contraindications, including for 
pregnancy or immunocompromised individuals, until there are more data 
available on vaccination for those individuals. A commenter noted that 
indications and contraindications have changed throughout the PHE and 
may necessarily continue to change based on ongoing research. The 
commenter stated that hospital human resources databases and records 
cannot accurately capture individuals who decline the vaccine or the 
reason for the declination, which may impact accuracy of reporting. 
Several commenters asserted that factors outside of their control, 
including regional differences in vaccination rates, could put 
hospitals in those areas at a disadvantage.
    Response: We agree with the commenters who note that HCP may have 
legitimate reasons to decline vaccination, including a 
contraindication, and this measure does not require HCP to receive the 
vaccine. The intent of adopting the COVID-19 Vaccination Coverage Among 
HCP measure is to collect and report data that will support public 
health tracking and provide patients, beneficiaries, and their 
caregivers important information to support informed decision making. 
For these reasons, we believe that it is appropriate to collect and 
report these data as soon as possible.
    As noted in the measure specifications,\1001\ HCP who are 
determined to have a medical contraindication specified by FDA labeling 
or authorization, CDC, or ACIP recommendations are excluded from the 
denominator of this measure. The CDC and FDA consider contraindications 
to vaccination with COVID-19 vaccines to be: (1) Severe allergic 
reaction (for example, anaphylaxis) after a previous dose or to a 
component of the COVID-19 vaccine; or (2) immediate allergic reaction 
of any severity to a previous dose or known (diagnosed) allergy to a 
component of the vaccine.\1002\ For example, as stated in the FDA-
authorized Fact Sheets for two COVID-19 vaccines, ``the decision to 
administer the [Pfizer/Moderna] COVID-19 Vaccine to an individual with 
a history of myocarditis or pericarditis should take into account the 
individual's clinical circumstances.'' \1003\ We also recognize that 
there are reasons, including religious objections or concerns regarding 
an individual provider's specific health status, that may lead 
individual HCP to decline vaccination. We emphasize that this measure 
does not mandate vaccines, it only requires reporting of vaccination 
rates for successful program participation. We do not expect 100 
percent vaccination coverage among HCP. However, we do believe that 
coverage rates are meaningful data for patients and beneficiaries to 
use in choosing a hospital, and can also be used for public health 
tracking.
---------------------------------------------------------------------------

    \1001\ Centers for Disease Control and Prevention. Measure 
Specification: NHSN COVID-19 Vaccination Coverage. Available at: 
https://www.cdc.gov/nhsn/pdfs/nqf/covid-vax-hcpcoverage-508.pdf.
    \1002\ Centers for Disease Control and Prevention. 
Contraindications and Precautions. Available at: https://www.cdc.gov/vaccines/covid-19/clinical-considerations/covid-19-vaccines-us.html#Contraindications; Food and Drug Administration. 
COVID-19 Vaccines. Available at: https://www.fda.gov/emergency-preparedness-and-response/coronavirus-disease-2019-covid-19/covid-19-vaccines.
    \1003\ Food and Drug Administration. Pfizer-BioNTech COVID-19 
Vaccine. Available at: https://www.fda.gov/emergency-preparedness-and-response/coronavirus-disease-2019-covid-19/pfizer-biontech-covid-19-vaccine#additional; Food and Drug Administration. Moderna 
COVID-19 Vaccine. Available at: https://www.fda.gov/emergency-preparedness-and-response/coronavirus-disease-2019-covid-19/moderna-covid-19-vaccine.
---------------------------------------------------------------------------

    Comment: Other commenters noted that vaccine mandates may push HCP 
to leave their jobs. Some commenters stated that vaccination has become 
a political flashpoint and mandates could drive further vaccine 
hesitancy. A few commenters noted that, if the health care system moves 
to mandate vaccination, it would be redundant to any employer or State-
level vaccine requirements. A few commenters expressed concerns about 
the potential impact of State legislation or regulation that may limit 
or prohibit employers from requiring vaccination or requesting vaccine 
status from HCP.
    Response: We reiterate that the COVID-19 Vaccination Coverage Among 
HCP measure does not require or mandate HCP to receive the vaccination, 
it only requires reporting of vaccination rates for successful program 
participation. We believe that the unprecedented risks associated with 
the COVID-19 PHE warrant direct attention, especially because HCP are 
working directly with and in close proximity to patients. To support a 
comprehensive vaccine administration strategy, we encourage hospitals 
to voluntarily engage in the provision of appropriate and accessible 
education and vaccine-offering activities. Many hospitals across the 
country are educating staff, patients, and patient representatives, 
participating in vaccine distribution programs, and voluntarily 
reporting vaccine administration. The CDC has a number of resources 
\1004\ available to providers to assist in building vaccine confidence. 
CMS also has a web page to help providers, including hospitals, find 
resources related to the COVID-19 vaccines.\1005\ There are a number of 
toolkits and videos providers can use to stay informed and to educate 
their employees, patients and communities about the COVID-19 vaccines.
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    \1004\ Centers for Disease Control and Prevention. Building 
Confidence in COVID-19 Vaccines. Available at https://www.cdc.gov/vaccines/covid-19/vaccinate-with-confidence.html.
    \1005\ Centers for Medicare and Medicaid Services. Coronavirus 
(COVID-19) Partner Resources. Available at: https://www.cms.gov/outreach-education/partner-resources/coronavirus-covid-19-partner-resources.
---------------------------------------------------------------------------

    With regard to concerns about state-level legislation that may 
limit a hospital's ability to require vaccination or request vaccine 
status from HCP, we reiterate that the COVID-19 Vaccination Coverage 
Among HCP measure does not require HCP to receive the vaccination and 
is a process measure that assesses HCP vaccination coverage rates, not 
an outcome measure for which hospitals are held directly accountable 
for a particular outcome. While we are aware

[[Page 45380]]

that at least one state has enacted legislation that prohibits 
employers from requiring employees to disclose immunization 
status,\1006\ we are not aware of any state legislation that prohibits 
employers from requesting voluntary reporting of immunization status. 
We again note that this measure does not require HCP to receive a 
COVID-19 vaccine and it does not require HCP to report their 
vaccination status. Additionally, the Equal Employment Opportunity 
Commission (EEOC) released updated and expanded technical assistance on 
May 28, 2021,\1007\ stating that Federal equal employment opportunity 
(EEO) laws do not prevent an employer from requiring all employees 
physically entering the workplace to be vaccinated for COVID-19, so 
long as the employer complies with the reasonable accommodation 
provisions of the Americans with Disabilities Act (ADA) and Title VII 
of the Civil Rights Act of 1964 and other EEO considerations. 
Therefore, we do not believe that this measure conflicts with any 
Federal or state-level requirements and believe that it is appropriate 
to require hospitals to report these data.
---------------------------------------------------------------------------

    \1006\ Montana House Bill 0702 (enacted May 7, 2021). Bill text 
available at: https://leg.mt.gov/bills/2021/billpdf/HB0702.pdf. Bill 
status including enactment available at: http://laws.leg.mt.gov/
legprd/
LAW0203W$BSRV.ActionQuery?P_SESS=20211&P_BLTP_BILL_TYP_CD=HB&P_BILL_N
O=0702&P_BILL_DFT_NO=&P_CHPT_NO=&Z_ACTION=Find&P_ENTY_ID_SEQ2=&P_SBJT
_SBJ_CD=&P_ENTY_ID_SEQ=.
    \1007\ U.S. Equal Employment Opportunity Commission. What You 
Should Know About COVID-19 and the ADA, the Rehabilitation Act, and 
Other EEO Laws. Available at https://www.eeoc.gov/wysk/what-you-should-know-about-covid-19-and-ada-rehabilitation-act-and-other-eeo-laws. Accessed June 25, 2021.
---------------------------------------------------------------------------

    Comment: Many commenters expressed concern with the HCP definition 
and believed it to be too broad. Several commenters asserted that the 
measure, which defines HCP as all individuals receiving a direct 
paycheck from the hospital regardless of clinical responsibility or 
patient contact, will be difficult to accurately capture. A few 
commenters anticipated challenges of accurately counting HCP who work 
at multiple hospitals or facilities and requested clarification of how 
to address those HCPs. A few commenters stated that many hospitals will 
be unable to include an accurate count of adult students/trainees, 
volunteers, and contractors in the measure denominator. Some commenters 
recommended that the definition of HCP be narrowed to apply to only 
clinicians or direct employees. A commenter suggested that CMS include 
all HCPs in the denominator, including those with contraindications, 
along with an explanation in public reporting.
    Response: We recognize commenters' concerns regarding reporting 
burden associated with the specifications of this measure specifically 
around the definition of HCP. We note that given the highly infectious 
nature of the COVID-19 virus, we believe it is important to encourage 
all personnel within the hospital, regardless of patient contact, role, 
or employment type, to receive the COVID-19 vaccination to prevent 
outbreaks within the hospital which may affect resource availability 
and have a negative impact on patient access to care.
    We also note that CDC's guidance for entering data requires 
submission of HCP count at the facility level,\1008\ and the measure 
requires reporting consistent with that guidance. Hospitals should 
count HCP working in all inpatient or outpatient units that are 
physically attached to the inpatient site and share the same CCN, 
regardless of the size or type of unit.\1009\ Hospitals should also 
count HCP working in inpatient and outpatient departments that are 
affiliated with the specific hospital (such as sharing medical 
privileges or patients), regardless of distance from the hospital and 
also share the same CCN.\1010\ The decision to include or exclude HCP 
from the hospital's HCP vaccination counts should be based on whether 
individuals meet the specified NHSN criteria and are physically working 
in a location that is considered any part of the on-site hospital that 
is being monitored.\1011\ Additionally, the CDC has provided a number 
of resources including a tool called the Data Tracking Worksheet for 
COVID-19 Vaccination among Healthcare Personnel to help hospitals log 
and track the number of HCP who are vaccinated for COVID-19. Hospitals 
would enter COVID vaccination data for each HCP in the tracking 
worksheet, and select a reporting week, and the data to be entered into 
the NHSN will automatically be calculated on the Reporting 
Summary.\1012\
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    \1008\ COVID-19 Vaccination Non-LTC Healthcare Personnel TOI 
(cdc.gov).
    \1009\ Centers for Disease Control and Prevention. Measure 
Specification: NHSN COVID-19 Vaccination Coverage. Available at: 
https://www.cdc.gov/nhsn/pdfs/nqf/covid-vax-hcpcoverage-508.pdf.
    \1010\ Ibid.
    \1011\ Centers for Disease Control and Prevention. CMS Reporting 
Requirements FAQs. Accessed June 2, 2021 at: https://www.cdc.gov/nhsn/PDFs/CMS/faq/FAQs-CMS-Reporting-Requirements.pdf.
    \1012\ Data Tracking Worksheet for COVID-19 Vaccination among 
Healthcare Personnel at https://www.cdc.gov/nhsn/hps/weekly-covid-vac/index.html.
---------------------------------------------------------------------------

    With regard to the recommendation that all HCP, including those 
with contraindications, should be captured in the measure denominator, 
we highlight that some hospitals may opt to include all eligible HCP in 
the denominator. We note that the measure specifications as proposed 
permit hospitals to exclude HCP with contraindications to the vaccine 
as described by the CDC.\1013\ We also note that, similar to the 
specifications of the Influenza Vaccination Coverage Among HCP (NQF 
#0431) measure, the COVID-19 Vaccination Coverage Among HCP measure 
specifications as proposed acknowledge that HCP may have 
contraindications to vaccination and, as such, may decline 
vaccination.\1014\ We further recognize that hospitals may decide to 
exclude these HCP from the measure denominator, and the measure 
specifications as proposed permit such exclusion. The intent of the 
measure is to capture the vaccination rate within hospitals so that 
patients have information available on HCP vaccination to inform their 
health care decisions.
---------------------------------------------------------------------------

    \1013\ Centers for Disease Control and Prevention. 
Contraindications and Precautions. Available at: https://www.cdc.gov/vaccines/covid-19/clinical-considerations/covid-19-vaccines-us.html#Contraindications.
    \1014\ Centers for Disease Control and Prevention. Measure 
Specification: NHSN COVID-19 Vaccination Coverage. Available at: 
https://www.cdc.gov/nhsn/pdfs/nqf/covid-vax-hcpcoverage-508.pdf.
---------------------------------------------------------------------------

    Comment: Many commenters expressed concern that the measure is 
operationally and logistically burdensome. Several commenters believed 
that reporting the data for one week each month is overly burdensome. 
Several commenters stated that HCP are not always vaccinated by their 
employers, which makes tracking difficult. A few of these commenters 
noted that many hospitals keep employee electronic health records 
outside of their facility electronic health record system, which 
complicates tracking. A few commenters noted that reporting HCP 
vaccination is especially challenging in States that lack immunization 
registries. Some commenters noted that HHS already facilitates 
reporting and suggested that hospitals should be permitted to continue 
using existing state or Federal resources for reporting.
    Response: We appreciate commenters' concerns regarding reporting 
frequency, however we disagree that the frequency is overly burdensome 
or that hospitals should report once per quarter instead of one week 
per month, because we believe that important public health

[[Page 45381]]

initiatives outweigh this burden. We proposed that hospitals report at 
least one self-selected week during each month of the reporting quarter 
and submit the data to the NHSN Healthcare Personnel Safety (HPS) 
Component before the quarterly deadline. We proposed that for each 
quarter, the CDC would calculate a single quarterly COVID-19 HCP 
vaccination coverage rate for each hospital by taking the average of 
the data from the three weekly rates submitted by the hospital for that 
quarter. CMS would publicly report each quarterly COVID-19 HCP 
vaccination coverage rate as calculated by the CDC. We believe that 
reporting these data on a frequent interval would increase their value 
by allowing the CDC to better track these important public health data 
while also being a valuable quality measure that supports consumer 
choice and hospital improvement initiatives. Consistent monthly 
vaccination reporting by hospitals via the NHSN will help patients and 
their caregivers identify hospitals that have potential issues with 
vaccine confidence or slow uptake among staff. Implementation of 
voluntary COVID-19 vaccine education and vaccination programs in 
hospitals will help protect patients and staff.\1015\
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    \1015\ Centers for Disease Control and Prevention. Updated 
Healthcare Infection Prevention and Control Recommendations in 
Response to COVID-19 Vaccination. Available at: https://www.cdc.gov/coronavirus/2019-ncov/hcp/infection-control-after-vaccination.html. 
Accessed June 26, 2021.
---------------------------------------------------------------------------

    With regard to commenters' concerns about reporting burden, we 
acknowledge there is burden associated with reporting this measure (see 
section XII.B.7.f. and section I.K. of Appendix A of this final rule). 
However, we believe the importance of collecting and reporting data on 
COVID-19 vaccination coverage among HCP is sufficiently beneficial to 
outweigh this burden. We do recognize that this measure may lead to 
duplicative reporting if hospitals voluntarily report COVID-19 HCP 
vaccination information to other data reporting systems in addition to 
this measure requirement via the NHSN, and we are collaborating with 
other HHS agencies, including the CDC to minimize reporting burden to 
the extent feasible.
    Comment: Several commenters opposed the shortened reporting period 
beginning October 1, 2021 and instead recommended CMS delay reporting 
until at least CY 2022. A few commenters questioned the value of data 
reported in CY 2021 that will impact the FY 2023 program year.
    Response: We appreciate commenters' concerns about the shortened 
reporting period. However, we believe that given the current COVID-19 
PHE and the need for continued monitoring and surveillance, it is 
important to adopt this measure as quickly as possible to allow 
tracking and reporting of COVID-19 HCP vaccination coverage. The 
commenters are correct that data reported in the first shortened 
reporting period of CY 2021 will impact the FY 2023 program year. Since 
the declaration of the PHE, COVID-19 has significantly impacted the 
healthcare system, and we believe that these effects are likely to 
continue even after such a time as the PHE for COVID-19 expires. We 
believe that the measure data reported by hospitals will remain 
relevant to the Hospital IQR Program in future program years.
    Comment: Many commenters expressed concern with beginning to report 
the measure in October 2021. Some commenters cited operational concerns 
and noted there is insufficient time for hospitals to prepare for 
reporting. Several commenters requested that, should the measure be 
adopted, CMS implement voluntary reporting for the first year. Some 
commenters suggested that hospitals not be required to report this 
measure data until January 2022. Other commenters urged CMS to delay 
reporting until at least October 2022.
    Response: We recognize commenters' concerns about operational 
requirements of reporting. However, we believe that given the current 
COVID-19 PHE as well as the need for continued monitoring and 
surveillance, it is important to adopt this measure as quickly as 
possible to allow tracking and reporting of COVID-19 Vaccination 
Coverage Among HCP measure. Therefore, we believe it is appropriate to 
adopt the measure at this time.
    Comment: Many commenters opposed public reporting of the COVID-19 
Vaccination Coverage Among HCP measure data. Some commenters 
recommended the measure data should not be publicly reported until the 
vaccines receive full FDA approval and NQF endorsement. A few 
commenters noted that, due to the unique nature of the PHE and the 
relatively limited experience administering vaccines, the measure data 
should not be publicly reported. A commenter requested that CMS 
reconsider how the measure is calculated for public reporting. They 
supported the concept of reporting one quarter of data but noted that, 
because the measure will provide information for a single point in 
time, it will quickly become outdated in the rapidly changing COVID-19 
landscape, and thus would not be meaningful, nor would it reflect 
safety or quality of care. They recommend that after the first refresh, 
rather than calculating a summary measure of the COVID-19 vaccination 
coverage from the 3 monthly modules of data reported for the quarter 
during each refresh and adding one additional quarter of data to the 
measure calculation during each advancing refresh, until the point that 
four full quarters of data is reached, to use an alternate approach. 
They recommend updating the information monthly with only the most 
recent data, such that the measure would be consumed as the most recent 
quarter of data refreshed quarterly. They caution that averaging over 
12 months would result in the dilution of the most recent, and 
potentially more meaningful information, and may actually discourage 
higher provider vaccine uptake rates since it would be harder to change 
performance on this measure. A few commenters worried that publicly 
reporting the measure data could misrepresent vaccination rates at 
hospitals and may further drive vaccine hesitancy.
    Response: We recognize commenter's concerns about public reporting 
and understand that a rolling average of data may not accurately 
represent a hospital's most recent COVID-19 vaccination data as 
improvements over time could be less apparent given the inclusion of 
older data. Based on these concerns, and as previously stated, we will 
not finalize our plan to add one additional quarter of data during each 
advancing refresh, until the point that four full quarters of data is 
reached and then report the measure using four rolling quarters of data 
as proposed. As opposed to averaging over four rolling quarters, we 
will instead update the public reporting to use quarterly reporting to 
only report the most recent quarter of data, which allows the most 
recent quarter data to be displayed without combining it with older 
quarters of data. This would result in information that is more up to 
date and meaningful and not diluted with older data. We reiterate that 
this modification of our proposal does not affect the data collection 
schedule established for submitting data to NHSN for the COVID-19 
vaccination measure. This would simply update the data that are 
displayed for the public reporting purposes.
    We also understand that some HCP may be hesitant to receive the 
COVID-19 vaccine. The intent of adopting the COVID-19 Vaccination 
Coverage Among HCP measure is to collect and report data that will 
support public health tracking and provide patients,

[[Page 45382]]

beneficiaries, and their caregivers information to support informed 
decision making. We believe that it is appropriate and important to 
collect and report these data and to make the data publicly available 
in light of the public interest.
    Comment: A commenter disagreed with data cited from the CDC in the 
FY 2022 IPPS/LTCH PPS proposed rule on the spread and manner of 
transmission of COVID-19.
    Response: We reiterate our close work with CDC and note that all 
data on the spread and manner of transmission of COVID-19 cited in the 
proposed rule came directly from the CDC.\1016\
---------------------------------------------------------------------------

    \1016\ Centers for Disease Control and Prevention. How COVID-19 
Spreads. Available at: https://www.cdc.gov/coronavirus/2019-ncov/prevent-getting-sick/how-covid-spreads.html.
---------------------------------------------------------------------------

    Comment: A commenter recommended that CMS include reporting of 
pertussis vaccines in addition to the COVID-19 Vaccination Coverage 
Among HCP measure.
    Response: We thank the commenter for this suggestion.
    After consideration of the public comments we received, we are 
finalizing our proposal to adopt the COVID-19 Vaccination Coverage 
Among HCP measure beginning with a shortened reporting period from 
October 1, 2021 through December 31, 2021 for the FY 2023 payment 
determination, and continuing with quarterly reporting deadlines for 
the CY 2022 reporting period/FY 2024 payment determination and 
subsequent years. We are also finalizing our proposal to publicly 
report the measure, which will begin with the October 2022 Care Compare 
refresh, or as soon as technically feasible, using data collected from 
Q4 2021 (October 1, 2021 through December 31, 2021). However, based on 
public comment, we are finalizing a modification to our proposal. We 
will not finalize our plan to add one additional quarter of data during 
each advancing refresh, until the point that four full quarters of data 
is reached and then report the measure using four rolling quarters of 
data. Instead, we will only report the most recent quarter of data. 
This would result in more meaningful information that is up to date and 
not diluted with older data.
d. Adoption of Two Medication-Related Adverse Event Electronic Clinical 
Quality Measures Beginning With the CY 2023 Reporting Period/FY 2025 
Payment Determination
    In the FY 2022 IPPS/LTCH PPS proposed rule (86 FR 25575 through 
25579), we proposed to add two new medication-related adverse event 
electronic clinical quality measures (eCQMs) to the Hospital IQR 
Program measure set, beginning with the CY 2023 reporting period/FY 
2025 payment determination: (1) Hospital Harm--Severe Hypoglycemia eCQM 
(NQF #3503e); \1017\ and (2) Hospital Harm--Severe Hyperglycemia eCQM 
(NQF #3533e).\1018\ We believe these medication-related adverse event 
measures are valuable patient safety measures and focus on high-
priority measurement areas and patient outcomes. The measures were 
developed in a manner that allows them to be reported independently, 
but they can be considered balancing measures if a hospital chooses to 
report on both measures. This section includes additional details on 
each of the eCQMs.
---------------------------------------------------------------------------

    \1017\ CMS eCQM Measure ID: CMS816v1.
    \1018\ CMS eCQM Measure ID: CMS871v1.
---------------------------------------------------------------------------

(1) Hospital Harm--Severe Hypoglycemia eCQM (NQF #3503e) Beginning With 
the CY 2023 Reporting Period/FY 2025 Payment Determination
(a) Background
    Hypoglycemia is defined as a blood glucose level of less than or 
equal to 70 mg/dL.\1019\ Hypoglycemic events are among the most common 
adverse drug events in hospitals.1020 1021 1022 1023 
Hypoglycemia can cause a wide range of symptoms, including mild 
symptoms of dizziness, sweating, and confusion to more severe symptoms 
such as seizure, tachycardia, or loss of 
consciousness.1024 1025 Most individuals with hypoglycemia 
recover fully, but in rare instances, hypoglycemia can progress to coma 
and death.\1026\
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    \1019\ American Diabetes Association. Diabetes Care in the 
Hospital: Standards of Medical Care in Diabetes--2018. Diabetes Care 
2018; 41(Suppl. 1):S144-S151 (available at: https://care.diabetesjournals.org/content/diacare/41/Supplement_1/S144.full.pdf).
    \1020\ Lipska KJ, Ross JS, Wang Y, et al. National trends in US 
hospital admissions for hyperglycemia and hypoglycemia among 
medicare beneficiaries, 1999 to 2011. JAMA Intern Med. 2014; 
174(7):1116-1124. doi:10.1001/jamainternmed.2014.1824.
    \1021\ McCoy RG, Lipska KJ, Herrin J, Jeffery MM, Krumholz HM, 
Shah ND. Hospital Readmissions among Commercially Insured and 
Medicare Advantage Beneficiaries with Diabetes and the Impact of 
Severe Hypoglycemic and Hyperglycemic Events. J Gen Intern Med. 
2017; 32(10):1097-1105. doi:10.1007/s11606-017-4095-x.
    \1022\ Office of the Inspector General (OIG). (2010). Adverse 
Events in Hospitals: National Incidence Among Medicare 
Beneficiaries. Available at: https://oig.hhs.gov/oei/reports/oei-06-09-00090.pdf.
    \1023\ Wexler, D.J., Meigs, J.B., Cagliero, E., Nathan, D.M., & 
Grant, R.W. (2007). Prevalence of hyper and hypoglycemia among 
inpatients with diabetes: A national survey of 44 U.S. hospitals. 
Diabetes Care, 30(2): 367-369.
    \1024\ Umpierrez GE, Hellman R, Korytkowski MT, et al. 
Management of Hyperglycemia in Hospitalized Patients in Non-Critical 
Care Setting: An Endocrine Society Clinical Practice Guideline. J 
Clin Endocrinol Metab. 2012;97(1):16-38.
    \1025\ Turchin, A., Matheny, M.E., Shubina, M., Scanlon, J.V., 
Greenwood, B., & Pendergrass, M.L. (2009). Hypoglycemia and clinical 
outcomes in patients with diabetes hospitalized in the general ward. 
Diabetes Care, 32(7): 1153-57.
    \1026\ Diabetes Control and Complications Trial Research Group. 
(1993). The effect of intensive treatment of diabetes on the 
development and progression of long-term complications in insulin 
dependent diabetes mellitus. New England Journal of Medicine, 
329(14): 977-86.
---------------------------------------------------------------------------

    In a study examining clinical outcomes associated with hypoglycemia 
in hospitalized people with diabetes, patients who had at least one 
hypoglycemic episode (a blood glucose level of less than 50 mg/dL) were 
hospitalized 2.8 days longer than patients who did not experience 
hypoglycemia.\1027\ Another retrospective cohort study showed 
hospitalized patients with diabetes who experienced hypoglycemia (a 
blood glucose level of less than 70 mg/dL) had higher medical costs (by 
38.9 percent), longer length of stay (by 3.0 days), and higher odds of 
being discharged to a skilled nursing facility (odds ratio 1.58; 95 
percent Confidence Interval 1.48-1.69) than patients with diabetes 
without hypoglycemia (p <0.01 for all).\1028\ Hypoglycemia is 
associated with higher in-hospital mortality, increased length of stay, 
and consequently, increased resource utilization.\1029\
---------------------------------------------------------------------------

    \1027\ Turchin, A., Matheny, M.E., Shubina, M., Scanlon, J.V., 
Greenwood, B., & Pendergrass, M.L. (2009). Hypoglycemia and clinical 
outcomes in patients with diabetes hospitalized in the general ward. 
Diabetes Care, 32(7): 1153-57.
    \1028\ Curkendall, S.M., Natoli, J.L., Alexander, C.M., 
Nathanson, B.H., Haidar, T., & Dubois, R.W. (2009). Economic and 
clinical impact of inpatient diabetic hypoglycemia. Endocrine 
Practice, 15(4): 302-312.
    \1029\ Krinsley, J.S., Schultz, M.J., Spronk, P.E., van Braam 
Houckgeest, F., van der Sluijs, J.P., Melot, C. & Preiser, J.C. 
(2011). Mild hypoglycemia is strongly associated with increased 
intensive care unit length of stay. Ann Intensive Care, 1, 49.
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    The rate of severe hypoglycemia (a blood glucose level of less than 
40 mg/dL) varies across hospitals, indicating an opportunity for 
improvement in care.1030 1031 1032 1033 Severe hypoglycemia 
rates have been reported to range from 2.3-5 percent of

[[Page 45383]]

hospitalized patients with diabetes, and from 0.4 percent of non-
intensive care unit (ICU) patient days to 1.9 percent of ICU patient 
days.1034 1035 1036 Severe hypoglycemic events are largely 
avoidable by careful use of anti-diabetic medication and close 
monitoring of blood glucose values.1037 1038 1039
---------------------------------------------------------------------------

    \1030\ Hospital Harm--Severe Hypoglycemia (NQF #3503e) Available 
at: http://www.qualityforum.org/ProjectTemplateDownload.aspx?SubmissionID=3503.
    \1031\ Cook, C.B., Kongable, G.L., Potter, D.J., Abad, V.J., 
Leija, D.E., & Anderson, M. (2009). Inpatient glucose control: A 
glycemic survey of 126 U.S. hospitals. Journal of Hospital Medicine, 
4(9): E7- E14.
    \1032\ Egi M, Bellomo R, Stachowski E, et al. Hypoglycemia and 
outcome in critically ill patients. Mayo Clin Proc. 2010; 85(3):217-
224. doi:10.4065/mcp.2009.0394.
    \1033\ Krinsley JS, Grover A. Severe hypoglycemia in critically 
ill patients: risk factors and outcomes. Crit Care Med. 2007 Oct; 
35(10):2262-7.
    \1034\ Nirantharakumar, K., Marshall, T., Kennedy, A., 
Narendran, P., Hemming, K., & Coleman, J.J. (2012). Hypoglycemia is 
associated with increased length of stay and mortality in people 
with diabetes who are hospitalized. Diabetic Medicine, 29(12): e445-
e448.
    \1035\ Wexler, D.J., Meigs, J.B., Cagliero, E., Nathan, D.M., & 
Grant, R.W. (2007). Prevalence of hyper and hypoglycemia among 
inpatients with diabetes: A national survey of 44 U.S. hospitals. 
Diabetes Care, 30(2): 367-369.
    \1036\ Cook, C.B., Kongable, G.L., Potter, D.J., Abad, V.J., 
Leija, D.E., & Anderson, M. (2009). Inpatient glucose control: A 
glycemic survey of 126 U.S. hospitals. Journal of Hospital Medicine, 
4(9): E7- E14.
    \1037\ American Diabetes Association. Diabetes Care in the 
Hospital: Standards of Medical Care in Diabetes--2018. Diabetes Care 
2018; 41(Suppl. 1):S144-S151 (available at: https://care.diabetesjournals.org/content/diacare/41/Supplement_1/S144.full.pdf).
    \1038\ Umpierrez GE, Hellman R, Korytkowski MT, et al. 
Management of Hyperglycemia in Hospitalized Patients in Non-Critical 
Care Setting: An Endocrine Society Clinical Practice Guideline. J 
Clin Endocrinol Metab. 2012; 97(1):16-38.
    \1039\ Maynard G, Kulasa K, Ramos P, et al. Impact of a 
Hypoglycemia Reduction Bundle and a Systems Approach to Inpatient 
Glycemic Management. Endocr Pract. 2015; 21(4):355-367.
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    Although there are many occurrences of hypoglycemia in hospital 
settings and many such events are preventable, there is currently no 
measure in a CMS quality program that quantifies how often hypoglycemic 
events happen to patients while in inpatient acute care. The AHRQ 
identified insulin and other hypoglycemic agents as high-alert 
medications and associated adverse drug events to be included as a 
measure in the Medicare Patient Safety Monitoring System (MPSMS), 
signifying the importance of measuring this hospital 
harm.1040 1041 Unlike the MPSMS, which relies on chart-
abstracted data, the Hospital Harm--Severe Hypoglycemia eCQM identifies 
hypoglycemic events using direct extraction of structured data from the 
EHR. In addition, the National Action Plan for Adverse Drug Event 
Prevention highlighted the opportunity that exists for healthcare 
quality reporting measures and meaningful utilization of EHR data to 
advance prevention of hypoglycemic adverse drug events.\1042\
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    \1040\ Classen, DC, Jaser, L., Budnitz, D.S. (2010). Adverse 
Drug Events among Hospitalized Medicare Patients: Epidemiology and 
national estimates from a new approach to surveillance. Joint 
Commission Journal on Quality and Patient Safety, 36(1): 12-21.
    \1041\ New System Aims To Improve Patient Safety Monitoring. 
Content last reviewed October 2016. Agency for Healthcare Research 
and Quality, Rockville, MD. Available at: https://archive.ahrq.gov/news/blog/ahrqviews/new-system-aims-to-improve-patient-safety-monitoring.html.
    \1042\ Office of Disease Prevention and Health Promotion. 
(2014). National Action Plan for Adverse Drug Event Prevention. 
Available at: https://health.gov/hcq/pdfs/ADE-Action-Plan-508c.pdf.
---------------------------------------------------------------------------

    To address gaps in measurement, we developed the Hospital Harm--
Severe Hypoglycemia eCQM, an outcome measure that would identify the 
rates of severe hypoglycemic events using direct extraction of 
structured data from the EHR. We believe this measure will provide 
reliable and timely measurement of the rate at which severe 
hypoglycemia events occur in the setting of hospital administration of 
antihyperglycemic medications during hospitalization, which will create 
transparency for providers and patients with respect to variation in 
rates of these events among hospitals. We believe that adopting this 
measure, which focuses on in-hospital severe hypoglycemic events in the 
setting of hospital-administered antihyperglycemic medications, has the 
potential to reduce preventable harm. Therefore, we proposed to adopt 
the Hospital Harm--Severe Hypoglycemia eCQM (NQF #3503e) beginning with 
the CY 2023 reporting period/FY 2025 payment determination.
(b) Overview of Measure
    The Hospital Harm--Severe Hypoglycemia eCQM identifies the 
proportion of patients who experienced a severe hypoglycemic event, 
defined as a glucose test result of less than 40 mg/dL, within 24 hours 
of the administration of an antihyperglycemic agent, which indicates 
harm to a patient.\1043\ The measure is intended to facilitate safer 
patient care, not only by promoting adherence to recommended clinical 
guidelines, but also by incentivizing hospitals to track and improve 
their practices of appropriate dosing and adequate monitoring of 
patients receiving glycemic control agents. Hospitals could use this 
measure to track and improve their practices of appropriate dosing and 
adequate monitoring of patients receiving glycemic control agents, and 
to avoid patient harm that can lead to increased risk of mortality and 
disability. This measure addresses the quality priority of ``Making 
Care Safer by Reducing Harm Caused in the Delivery of Care'' through 
the Meaningful Measure Area of ``Preventable Healthcare Harm.'' \1044\
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    \1043\ Hospital Harm--Severe Hypoglycemia (NQF #3503e). 
Available at: http://www.qualityforum.org/ProjectTemplateDownload.aspx?SubmissionID=3503.
    \1044\ CMS' Meaningful Measures Framework can be found at: 
https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/QualityInitiativesGenInfo/MMF/General-info-Sub-Page.
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    This measure is a re-specification of another hypoglycemia measure 
originally endorsed by the NQF, Glycemic Control--Hypoglycemia (NQF 
#2363).\1045\ The original measure was not implemented as an eCQM 
because, at that time, limitations in the MAT did not allow for 
accurate expression of the Quality Data Model (QDM) components to 
express the measure logic or syntax as specified.\1046\ Upgrades to the 
MAT have allowed the measure to be re-specified, producing accurate 
expression of the measure logic in CQL format to create a measure that 
can now be implemented.
---------------------------------------------------------------------------

    \1045\ Glycemic Control--Hyperglycemia NQF #2363. Available at: 
http://www.qualityforum.org/QPS/2363e.
    \1046\ Hospital Harm--Severe Hypoglycemia (NQF #3503e) Available 
at: http://www.qualityforum.org/ProjectTemplateDownload.aspx?SubmissionID=3503.
---------------------------------------------------------------------------

    The Hospital Harm--Severe Hypoglycemia (MUC18-109) measure was 
included in the publicly available ``List of Measures Under 
Consideration for December 1, 2018.'' \1047\ This measure was reviewed 
by the NQF MAP Hospital Workgroup in December 2018 and received 
conditional support pending NQF review and re-endorsement once the 
revised measure is fully tested.1048 1049 MAP stakeholders 
expressed concerns about the low glucose value (less than 40 mg/dL), 
the defined lab tests (for example, point-of-care vs. lab values), and 
the feasibility of the subsequent lab test for glucose within 5 minutes 
of the low glucose result. MAP stakeholders agreed that severe 
hypoglycemia events are largely avoidable by careful use of 
antihyperglycemic medications and blood glucose monitoring. The MAP 
recommended continuously assessing the low blood glucose threshold of 
<40mg/dL for defining harm events to assess unintended 
consequences.\1050\

[[Page 45384]]

The MAP Coordinating Committee, which provides direction to the MAP 
workgroups, concurred with the recommendations of the MAP Hospital 
Workgroup. The measure was fully tested in six hospitals with two 
different EHR vendors (Epic and Cerner) at thresholds found to be 
feasible, reliable, valid, and scientifically acceptable by the NQF 
Patient Safety Standing Committee and was subsequently endorsed by the 
NQF Consensus Standards Advisory Committee (CSAC) in the Spring of 
2019.1051 1052
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    \1047\ Measures Under Consideration List December 1, 2018. 
Available at http://www.qualityforum.org/WorkArea/linkit.aspx?LinkIdentifier=id&ItemID=88812.
    \1048\ 2018-2019 Spreadsheet of Final Recommendations to HHS and 
CMS. Available at: http://www.qualityforum.org/ProjectMaterials.aspx?projectID=75369.
    \1049\ National Quality Forum, Measure Applications Partnership, 
MAP 2019 Considerations for Implementing Measures in Federal 
Programs: Hospitals. Available at: http://www.qualityforum.org/Publications/2019/02/MAP_2019_Considerations_for_Implementing_Measures_Final_Report_-_Hospitals.aspx.
    \1050\ Measure Applications Partnership, December 2018 NQF MAP 
Hospital Workgroup Preliminary Recommendations. Available at: http://www.qualityforum.org/ProjectMaterials.aspx?projectID=75369.
    \1051\ NQF October 2019 CSAC Endorsement. Available at: http://www.qualityforum.org/WorkArea/linkit.aspx?LinkIdentifier=id&ItemID=91440.
    \1052\ NQF Patient Safety Standing Committee Memo to Consensus 
Standards Advisory Committee. Spring 2019 Cycle. Available at: 
http://www.qualityforum.org/WorkArea/linkit.aspx?LinkIdentifier=id&ItemID=91278.
---------------------------------------------------------------------------

(c) Data Sources
    The measure is an eCQM that uses data collected through the EHR. 
The measure is designed to be calculated by the hospitals' certified 
electronic health record technology (CEHRT) using the patient-level 
data submitted by hospitals to CMS.
(d) Measure Calculation
    The Hospital Harm--Severe Hypoglycemia eCQM is an outcome measure 
that assesses the rate at which severe hypoglycemia events (blood 
glucose test result less than 40 mg/dL) caused by hospital 
administration of medications occur in the acute care hospital setting. 
The measure calculates the proportion of patients who are at risk and 
who had a low blood glucose test result (less than 40 mg/dL) and no 
subsequent confirmatory blood glucose within 5 minutes and in the 
normal range (greater than 80 mg/dL). Patients at risk include those 
who had an antihyperglycemic medication administered in the hospital 
within the 24 hours prior to the harm event. The measure counts only 
one severe hypoglycemia event per patient admission. We refer readers 
to the measure specifications for more detail: https://ecqi.healthit.gov/pre-rulemaking-eh-cah-ecqms.
(e) Measure Cohort
    The measure's cohort includes all patients ages 18 years and older 
at the start of the encounter, and for whom at least one 
antihyperglycemic medication was administered during the encounter.
(f) Denominator
    The measure denominator includes all patients 18 years or older 
discharged from an inpatient hospital encounter during the measurement 
period who were administered at least one antihyperglycemic medication 
during their hospital stay. The measure includes inpatient admissions 
for patients admitted from either the emergency department or 
observation status, who subsequently became an inpatient. There are no 
denominator exclusions for this measure.
(g) Numerator
    The numerator for this measure is the number of hospitalized 
patients with a blood glucose test result of less than 40 mg/dL 
(indicating severe hypoglycemia) with no repeat glucose test result 
greater than 80 mg/dL within 5 minutes of the initial low glucose test, 
and where an antihyperglycemic medication was administered within 24 
hours prior to the low glucose result. We specified a glucose threshold 
of less than 40 mg/dL to identify only cases of severe hypoglycemia. We 
excluded a single severe hypoglycemic event with a repeat test of over 
80 mg/dL within 5 minutes to avoid counting false positives (for 
example, from bedside point-of-care tests of capillary blood that might 
have returned an initial erroneous result). There are no other 
numerator exclusions for this measure.
(h) Risk Adjustment
    We note risk adjustment is not applicable to the Hospital Harm-
Severe Hypoglycemia eCQM. In the case of the Hospital Harm--Severe 
Hypoglycemia eCQM, there is evidence indicating that most hypoglycemic 
events of this severity (<40 mg/dL) are 
avoidable.1053 1054 1055 1056 Although specific patients may 
be particularly vulnerable to hypoglycemia in certain settings (for 
example, due to organ failure and not related to administration of 
diabetic agents), the most common causes are lack of caloric intake, 
overuse of anti-diabetic agents, or both.1057 1058 1059 
These causes are largely controllable in hospital environments, and 
risk can be reduced by following best practices. We will continue to 
evaluate the appropriateness of risk adjustment in measure 
reevaluation.
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    \1053\ Cook, C.B., Kongable, G.L., Potter, D.J., Abad, V.J., 
Leija, D.E., & Anderson, M. (2009). Inpatient glucose control: A 
glycemic survey of 126 U.S. hospitals. Journal of Hospital Medicine, 
4(9): E7-E14.
    \1054\ Moghissi, E.S., Korytkowski, M.T., DiNardo, M., et al. 
(2009). American Association of Clinical Endocrinologists and 
American Diabetes Association Consensus Statement on Inpatient 
Glycemic Control. Diabetes Care, 32(6):1119-1131.
    \1055\ Office of the Inspector General (OIG). (2010). Adverse 
Events in Hospitals: National Incidence Among Medicare 
Beneficiaries. Available at: https://oig.hhs.gov/oei/reports/oei-06-09-00090.pdf.
    \1056\ Wexler, D.J., Meigs, J.B., Cagliero, E., Nathan, D.M., & 
Grant, R.W. (2007). Prevalence of hyper and hypoglycemia among 
inpatients with diabetes: A national survey of 44 U.S. hospitals. 
Diabetes Care, 30(2): 367-369.
    \1057\ American Diabetes Association. Diabetes Care in the 
Hospital: Standards of Medical Care in Diabetes--2018. Diabetes Care 
2018; 41(Suppl. 1):S144-S151 (available at: https://care.diabetesjournals.org/content/diacare/41/Supplement_1/S144.full.pdf).
    \1058\ Maynard G, Kulasa K, Ramos P, et al. Impact of a 
Hypoglycemia Reduction Bundle and a Systems Approach to Inpatient 
Glycemic Management. Endocr Pract. 2015;21(4):355-367.
    \1059\ Milligan PE, Bocox MC, Pratt E, Hoehner CM, Krettek JE, 
Dunagan WC. Multifaceted approach to reducing occurrence of severe 
hypoglycemia in a large healthcare system. Am J Health Syst Pharm 
2015;72:1631-1641.
---------------------------------------------------------------------------

    For more information on the Hospital Harm--Severe Hypoglycemia 
eCQM, we refer readers to the measure specifications available on the 
eCQI Resource Center website at: https://ecqi.healthit.gov/pre-rulemaking-eh-cah-ecqms.
    We invited public comment on this proposal.
    Comment: Many commenters supported adopting the Hospital Harm--
Severe Hypoglycemia eCQM in the Hospital IQR Program. Commenters 
expressed their belief that the measure will improve both transparency 
and patient outcomes. A commenter highlighted that the measure can be 
easily implemented. A few commenters support the inclusion of the 
measure and emphasized the importance of glycemic control for reducing 
patient harm.
    Response: We thank commenters for their support of and input on the 
inclusion of Hospital Harm--Severe Hypoglycemia (NQF #3503e) in the 
Hospital IQR Program measure set beginning with the CY 2023 reporting 
period/FY 2025 payment determination. We agree that this measure 
captures important quality information that is critical to patient 
safety and improving patient outcomes.
    Comment: A commenter expressed support for the measure, but 
requested we conduct additional testing. A few commenters did not 
support the inclusion of Hospital Harm--Severe Hypoglycemia due the 
level of testing and requested that the measure undergo additional 
testing for feasibility and validity prior to finalization.
    Response: We thank the commenters for their input and feedback on 
this measure. Measure testing was done in compliance with the NQF 
requirements for eCQM development. The Hospital Harm--Severe 
Hypoglycemia eCQM was tested in 6 hospitals representing two EHR 
systems that provided a good representation of hospitals across the 
country. This aligns with NQF's

[[Page 45385]]

recommendation to conduct eCQM testing in more than one EHR system. 
Empirical results also showed that the measure exhibited high 
feasibility, reliability, and data element validity. The thresholds 
were found to be feasible, reliable, valid, and scientifically 
acceptable by the NQF Patient Safety Standing Committee and the measure 
was endorsed by the NQF Consensus Standards Advisory Committee (CSAC) 
in the Spring of 2019.\1060\
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    \1060\ National Quality Forum. Patient Safety Final Technical 
Report--Spring 2019 Cycle. (2020, February). Available at: https://www.qualityforum.org/Publications/2020/02/Patient_Safety_Final_Technical_Report_-_Spring_2019_Cycle.aspx.
---------------------------------------------------------------------------

    Comment: Several commenters supported the measure, but requested 
CMS delay the inclusion of the eCQM to allow additional time for 
hospitals to implement the measure. A commenter requested an 18 month 
delay, while others requested one additional year, recommending 
inclusion beginning with the CY 2024 reporting period/FY 2026 payment 
determination. A few commenters requested additional time to pilot the 
measure before formally adopting it into the Hospital IQR Program.
    Response: We thank commenters for their support and input. We 
emphasize that the measure was proposed for inclusion beginning in the 
CY 2023 reporting period/FY 2025 payment determination, which will 
allow hospitals at least one year to prepare and implement the measure. 
We direct readers to the eCQI Resource Center (available at: https://ecqi.healthit.gov/pre-rulemaking-eh-cah-ecqms) for the specifications 
for this eCQM, several other eCQMs being finalized, as well as those we 
sought comment on in the FY 2022 IPPS/LTCH PPS proposed rule (86 FR 
25070).
    Comment: Several commenters shared feedback on the adoption of 
Hospital Harm--Severe Hypoglycemia as a balancing measure to Hospital 
Harm--Severe Hyperglycemia. A few noted their support for the measure, 
recommending that we allow hospitals to choose which of the two 
measures to report. A commenter recommended CMS require reporting of 
both eCQMs. A few commenters noted that they could not support the 
adoption of these balancing measures as they believed they were not 
actually aligned.
    Response: We thank commenters for their feedback. Hospitals will be 
able to report the Severe Hyperglycemia and Severe Hypoglycemia 
measures independently. Balancing measures are measures that can be 
used to demonstrate that an improvement in one area is not negatively 
impacting improvement in another area. For example, we can use these 
measures to assess whether an improvement in the number of severe 
hyperglycemia events ties to an increase in the number of severe 
hypoglycemia events. For that reason, while the two measures may not 
measure the same exact thing, we consider them to be balancing 
measures. We believe that both measures, regardless of the denominator 
used, will trend downward as improvements are made. Additionally, 
hospitals may self-select to report on one, both, or neither of these 
two eCQMs and select other eCQMs. While we do not require reporting of 
both measures at this time, we strongly encourage reporting of both. We 
will take commenters' recommendations to require one or both measures 
into future consideration.
    Comment: A few commenters raised concern about the performance gap, 
as they felt the measure testing results showed little variation across 
the test sites.
    Response: We thank the commenters for their feedback on this 
measure. The empirical results indicate over three-fold variation in 
measure rates across 6 test hospitals, which suggests a performance gap 
with room for improvement for this serious harm event.\1061\ We will 
continue to evaluate and refine the measure through implementation as 
necessary.
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    \1061\ We refer readers to the NQF website for the measure 
specifications including testing information, available at: https://nqfappservicesstorage.blob.core.windows.net/proddocs/27/Spring/2019/measures/3503/shared/3503.zip.
---------------------------------------------------------------------------

    Comment: A few commenters raised concerns that the measure does not 
include risk adjustment. A commenter requested that CMS continue to 
reevaluate the need for risk adjustment after the measure is 
implemented. Another commenter could not support the measure without 
appropriate risk adjustment.
    Response: We thank the commenters for their feedback. We note that 
this measure was endorsed by NQF without risk-adjustment,\1062\ due to 
a high level of preventability as specified (for example, ``severe 
hypoglycemia'' is specified as values <40 mg/dL). While specific 
patients may be more vulnerable to hypoglycemia in certain settings, 
the most common causes are lack of sufficient caloric intake, excessive 
or poor timing of anti-diabetic agents, or both.\1063\ These causes are 
largely controllable in hospital environments and risk can be reduced 
by following clinical best practices.\1064\ Therefore, we believe risk 
adjustment is not warranted in this case. We will continue to evaluate 
the appropriateness of risk adjustment as necessary.
---------------------------------------------------------------------------

    \1062\ National Quality Forum. Patient Safety Final Technical 
Report--Spring 2019 Cycle. (2020, February). Available at: https://www.qualityforum.org/Publications/2020/02/Patient_Safety_Final_Technical_Report_-_Spring_2019_Cycle.aspx.
    \1063\ American Diabetes Association. 14. Diabetes care in the 
hospital: Standards of Medical Care in Diabetes 2018. Diabetes Care 
2018;41(Suppl. 1):S144-S151.
    \1064\ Ibid.
---------------------------------------------------------------------------

    Comment: A few commenters recommended that we incorporate 
continuous glucose monitoring (CGM) as an option for measurement and 
include additional glucose monitoring data.
    Response: We thank the commenters for this feedback. In the measure 
specifications as proposed, the glucose lab value set includes code 
concepts that are nonspecific to the monitoring device used to collect 
the glucose level, which can include CGM test results.\1065\ We may 
consider clarifying the language in the Guidance section of the measure 
specification.
---------------------------------------------------------------------------

    \1065\ The Glucose Lab Test value set is available at: https://vsac.nlm.nih.gov/valueset/2.16.840.1.113762.1.4.1045.134.
---------------------------------------------------------------------------

    Comment: A commenter recommended that we provide sufficient 
guidance on the time windows for ``day.''
    Response: We thank the commenter for their feedback. As indicated 
in the measure specifications as proposed, the time window is 24 
hours.\1066\ For more detailed information and measure guidance, we 
refer readers to the measure specifications available on the eCQI 
Resource Center (available at: https://ecqi.healthit.gov/pre-rulemaking-eh-cah-ecqms).
---------------------------------------------------------------------------

    \1066\ Hospital Harm--Severe Hypoglycemia eCQM specifications 
are available in the eCQI Resource Center at: https://ecqi.healthit.gov/ecqm/eh/pre-rulemaking/1/cms816v1.
---------------------------------------------------------------------------

    Comment: A few commenters recommended a change to the blood glucose 
level threshold for severe hypoglycemia. A few felt the threshold 
should be raised to the American Diabetes Association (ADA) definition 
of at least 54 mg/dL. A commenter felt the threshold should be raised 
to 70 mg/dL to have a greater impact. Another commenter felt that the 
measure is not truly an outcome measure.
    Response: We thank the commenters for their input. The threshold of 
40 mg/dL as specified for this measure aligns with that of a prior NQF-
endorsed measure (Glycemic Control--

[[Page 45386]]

Hypoglycemia (NQF #2363)),\1067\ has received confirmation from the 
TEP,\1068\ and helps to reduce false positives.\1069\ This threshold is 
also in line with the empirical literature regarding severe 
hypoglycemia.1070 1071 1072 Therefore, we believe that this 
threshold makes the measure an appropriate outcome measure for acute 
inpatient care among patients with diabetes, as values less than 40 mg/
dL are typically associated with severe symptoms requiring external 
assistance for recovery.\1073\ We will continue to monitor the 
threshold and revise the measure as necessary.
---------------------------------------------------------------------------

    \1067\ Glycemic Control--Hypoglycemia (NQF #2363) specifications 
are available at: https://www.qualityforum.org/QPS/2363e.
    \1068\ Summary of Technical Expert Panel (TEP) Meetings March 
2017 through January 2019 Hospital Harm eCQMs. June 2019; 17.
    \1069\ Krinsley JS, Grover A. Severe hypoglycemia in critically 
ill patients: risk factors and outcomes. Crit Care Med. 2007 Oct; 
35(10):2262-7.
    \1070\ Cook, C. B., Kongable, G. L., Potter, D. J., Abad, V. J., 
Leija, D. E., & Anderson, M. (2009). Inpatient glucose control: a 
glycemic survey of 126 U.S. hospitals. Journal of Hospital Medicine, 
4(9), E7-E14. https://doi.org/10.1002/jhm.533.
    \1071\ Egi, M., Bellomo, R., Stachowski, E., French, C. J., 
Hart, G. K., Taori, G., Hegarty, C., & Bailey, M. (2010). 
Hypoglycemia and Outcome in Critically Ill Patients. Mayo Clinic 
Proceedings, 85(3), 217-224. https://doi.org/10.4065/mcp.2009.0394.
    \1072\ Krinsley, J. S., & Grover, A. (2007). Severe hypoglycemia 
in critically ill patients: Risk factors and outcomes*. Critical 
Care Medicine, 35(10), 2262-2267. https://doi.org/10.1097/01.ccm.0000282073.98414.4b.
    \1073\ American Diabetes Association. Diabetes Care in the 
Hospital: Standards of Medical Care in Diabetes--2018. Diabetes Care 
2018; 41(Suppl. 1):S144-S151 (available at: https://care.diabetesjournals.org/content/diacare/41/Supplement_1/S144.full.pdf).
---------------------------------------------------------------------------

    After consideration of the public comments we received, we are 
finalizing our proposal as proposed.
(2) Hospital Harm--Severe Hyperglycemia eCQM (NQF #3533e) Beginning 
With the CY 2023 Reporting Period/FY 2025 Payment Determination
(a) Background
    Hyperglycemia is common among hospitalized patients, especially 
those with preexisting diabetes.1074 1075 Hyperglycemia can 
also affect individuals with no prior history of diabetes and may be 
induced by medications such as steroids, or parenteral (intravenous) or 
enteral (tube) feeding.\1076\ Severe hyperglycemia, or an extremely 
elevated blood glucose level, is associated with a range of harms, 
including increased in-hospital mortality, infection rates, and 
hospital length of 
stay.1077 1078 1079 1080 1081 1082 1083 1084 1085 The rate 
of severe hyperglycemia varies across hospitals, which suggests there 
are opportunities for improvement in inpatient glycemic 
management.1086 1087 Rates of inpatient severe hyperglycemic 
events can be considered an indicator for quality of hospital care, 
since inpatient hyperglycemia is largely avoidable with proper glycemic 
management.1088 1089 1090 The use of evidence-based 
standardized protocols and insulin management protocols have been shown 
to improve glycemic control and safety.1091 1092 It should 
be noted that this measure does not aim to measure overall glucose 
control in hospitalized patients; rather, our goal is to assess the 
occurrence and extent of severe hyperglycemia.
---------------------------------------------------------------------------

    \1074\ Swanson CM, Potter DJ, Kongable GL, Cook CB. Update on 
Inpatient Glycemic Control in Hospitals in the United States. Endocr 
Pract. 2011; 17(6):853-861.
    \1075\ Umpierrez GE, Hellman R, Korytkowski MT, et al. 
Management of Hyperglycemia in Hospitalized Patients in Non-Critical 
Care Setting: An Endocrine Society Clinical Practice Guideline. J 
Clin Endocrinol Metab. 2012;97(1):16-38.
    \1076\ American Diabetes Association. Diabetes Care in the 
Hospital: Standards of Medical Care in Diabetes--2018. Diabetes Care 
2018; 41(Suppl. 1):S144-S151 (available at: https://care.diabetesjournals.org/content/diacare/41/Supplement_1/S144.full.pdf).
    \1077\ American Diabetes Association. Diabetes Care in the 
Hospital: Standards of Medical Care in Diabetes--2018. Diabetes Care 
2018; 41(Suppl. 1):S144-S151 (available at: https://care.diabetesjournals.org/content/diacare/41/Supplement_1/S144.full.pdf).
    \1078\ Corsino L, Dhatariya K, Umpierrez G. Management of 
diabetes and hyperglycemia in hospitalized patients. In Endotext 
[internet]. Available from http://www.ncbi.nlm.nih.gov/books/NBK279093/. Last Updated on October 1, 2017, Last Accessed 19 
December 2019.
    \1079\ Pasquel FJ, Spiegelman R, McCauley M, et al. 
Hyperglycemia During Total Parenteral Nutrition: An Important Marker 
of Poor Outcome and Mortality in Hospitalized Patients. Diabetes 
Care. 2010;33(4):739-741.
    \1080\ Falciglia M, Freyberg RW, Almenoff PL, D'Alessio DA, 
Render ML. Hyperglycemia-Related Mortality in Critically Ill 
Patients Varies with Admission Diagnosis. Crit Care Med. 2009; 
37(12):3001-3009.
    \1081\ Lee LJ, Emons MF, Martin SA, et al. Association of Blood 
Glucose Levels with In-Hospital Mortality and 30-Day Readmission in 
Patients Undergoing Invasive Cardiovascular Surgery. Curr Med Res 
Opin. 2012; 28(10):1657-1665.
    \1082\ King JT, Jr., Goulet JL, Perkal MF, Rosenthal RA. 
Glycemic Control and Infections in Patients with Diabetes Undergoing 
Noncardiac Surgery. Ann Surg. 2011; 253(1):158-165.
    \1083\ Jackson RS, Amdur RL, White JC, Macsata RA. Hyperglycemia 
is Associated with Increased Risk of Morbidity and Mortality after 
Colectomy for Cancer. J Am Coll Surg. 2012; 214(1):68-80.
    \1084\ Umpierrez GE, Hellman R, Korytkowski MT, et al. 
Management of Hyperglycemia in Hospitalized Patients in Non-Critical 
Care Setting: An Endocrine Society Clinical Practice Guideline. J 
Clin Endocrinol Metab. 2012; 97(1):16-38.
    \1085\ Krinsley, J.S., Schultz, M.J., Spronk, P.E., van Braam 
Houckgeest, F., van der Sluijs, J.P., Melot, C. & Preiser, J.C. 
(2011). Mild hypoglycemia is strongly associated with increased 
intensive care unit length of stay. Ann Intensive Care, 1, 49.
    \1086\ Swanson CM, Potter DJ, Kongable GL, Cook CB. Update on 
Inpatient Glycemic Control in Hospitals in the United States. Endocr 
Pract. 2011; 17(6):853-861.
    \1087\ Cook, C.B., Kongable, G.L., Potter, D.J., Abad, V.J., 
Leija, D.E., & Anderson, M. (2009). Inpatient glucose control: A 
glycemic survey of 126 U.S. hospitals. Journal of Hospital Medicine, 
4(9): E7- E14.
    \1088\ Maynard G, Kulasa K, Ramos P, et al. Impact of a 
Hypoglycemia Reduction Bundle and a Systems Approach to Inpatient 
Glycemic Management. Endocr Pract. 2015; 21(4):355-367.
    \1089\ Umpierrez GE, Hellman R, Korytkowski MT, et al. 
Management of Hyperglycemia in Hospitalized Patients in Non-Critical 
Care Setting: An Endocrine Society Clinical Practice Guideline. J 
Clin Endocrinol Metab. 2012; 97(1):16-38.
    \1090\ Donihi AC, DiNardo MM, DeVita MA, Korytkowski MT. Use of 
a Standardized Protocol to Decrease Medication Errors and Adverse 
Events Related to Sliding Scale Insulin. Qual Saf Health Care. 2006; 
15(2):89-91.
    \1091\ Maynard G, Kulasa K, Ramos P, et al. Impact of a 
Hypoglycemia Reduction Bundle and a Systems Approach to Inpatient 
Glycemic Management. Endocr Pract. 2015; 21(4):355-367.
    \1092\ Donihi AC, DiNardo MM, DeVita MA, Korytkowski MT. Use of 
a Standardized Protocol to Decrease Medication Errors and Adverse 
Events Related to Sliding Scale Insulin. Qual Saf Health Care. 2006; 
15(2):89-91.
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(b) Overview of Measure
    The intent of this measure is to track and improve practices of 
appropriate glycemic control and medication management of patients, and 
to avoid patient harm leading to increased risk of mortality and 
disability. This eCQM assesses the number of inpatient hospital days 
with a severe hyperglycemic event among the total qualifying hospital 
days for patients 18 years and older who have a diagnosis of diabetes 
mellitus and who either received at least one anti-diabetic medication 
during the hospital admission, or who had an elevated blood glucose 
level (>200 mg/dL) during their hospital admission. A severe 
hyperglycemic event is defined as a day in which a patient's blood 
glucose result was greater than 300 mg/dL, or a day in which a blood 
glucose value was not documented and was preceded by 2 consecutive days 
during which at least one glucose value was 200 mg/dL or greater.\1093\ 
This measure addresses the quality priority of ``Making Care Safer by 
Reducing Harm Caused in the Delivery of Care'' through the Meaningful 
Measure Area of ``Preventable Healthcare Harm.'' \1094\
---------------------------------------------------------------------------

    \1093\ Hospital Harm--Severe Hyperglycemia (NQF #3533e). 
Available at: http://www.qualityforum.org/ProjectTemplateDownload.aspx?SubmissionID=3533.
    \1094\ CMS' Meaningful Measures Framework can be found at: 
https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/QualityInitiativesGenInfo/MMF/General-info-Sub-Page.
---------------------------------------------------------------------------

    The Hospital Harm--Severe Hyperglycemia in Hospitalized Patients 
(Hospital Harm--Severe Hyperglycemia) (MUC2019-26) measure was included 
in the publicly available ``List of

[[Page 45387]]

Measures Under Consideration for December 1, 2019.'' \1095\ The MAP 
Hospital Workgroup reviewed the measure in December 2019 and the MAP 
Coordinating Committee reviewed the measure in January 2020. The 
measure received conditional support for rulemaking pending NQF 
endorsement.\1096\ The MAP recommended monitoring the implementation of 
the measure using the severe high blood glucose threshold of >300 mg/dL 
for defining harm events to assess for unintended measurement 
consequences, such as hypoglycemia.\1097\ The Hospital Harm--Severe 
Hyperglycemia measure has been found to be both reliable and valid by 
the NQF Scientific Methods Panel as well as the NQF Patient Safety 
Standing Committee in the Fall 2019 measure evaluation 
cycle.1098 1099 1100 As with all quality measures we 
develop, testing was performed to confirm the measure feasibility, 
reliability, and validity of the numerator, using clinical adjudicators 
who validated the EHR data compared with medical chart-abstracted data. 
Testing was completed using measure output from the MAT in multiple 
hospitals, using multiple EHR systems, with the measure shown to be 
both reliable and valid. In July 2020, the NQF endorsed the Hospital 
Harm--Severe Hyperglycemia measure.\1101\
---------------------------------------------------------------------------

    \1095\ Measures Under Consideration List December 1, 2019. 
Available at: http://www.qualityforum.org/WorkArea/linkit.aspx?LinkIdentifier=id&ItemID=91406.
    \1096\ 2019-2020 MAP Final Recommendations. Available at: http://www.qualityforum.org/WorkArea/linkit.aspx?LinkIdentifier=id&ItemID=91911.
    \1097\ 2019-2020 MAP Final Recommendations. Available at: http://www.qualityforum.org/WorkArea/linkit.aspx?LinkIdentifier=id&ItemID=91911.
    \1098\ NQF Scientific Methods Panel October 2019 Meeting Summary 
Available at: http://www.qualityforum.org/WorkArea/linkit.aspx?LinkIdentifier=id&ItemID=91486.
    \1099\ 2019-2020 MAP Final Recommendations. Available at: http://www.qualityforum.org/WorkArea/linkit.aspx?LinkIdentifier=id&ItemID=91911.
    \1100\ NQF Patient Safety Standing Committee. Meeting Summary--
Measure Evaluation #1 and #2--Fall 2019 Cycle (Available at: http://www.qualityforum.org/WorkArea/linkit.aspx?LinkIdentifier=id&ItemID=92225) 2019-2020 MAP Final 
Recommendations. Available at: http://www.qualityforum.org/WorkArea/linkit.aspx?LinkIdentifier=id&ItemID=91911.
    \1101\ Patient Safety Final Report--Fall 2019 Cycle. Available 
at: https://www.qualityforum.org/Publications/2020/09/Patient_Safety_Final_Report_-_Fall_2019_Cycle.aspx.
---------------------------------------------------------------------------

    This measure is a re-specification of another hyperglycemia measure 
originally endorsed by the NQF, Glycemic Control--Hyperglycemia (NQF 
#2362). Similar to the proposed Glycemic Control--Hypoglycemia (NQF 
#2363) measure, the original hyperglycemic measure was not implemented 
as an eCQM because, at that time, limitations in the MAT did not allow 
for accurate expression of the QDM components to express the measure 
logic or syntax as specified.1102 1103 Upgrades to the MAT 
have allowed the measure to be re-specified, producing accurate 
expression of the measure logic in CQL format to create a new measure 
that can now be implemented. We believe that this measure, which 
focuses specifically on severe hyperglycemic events in the hospital 
setting, has the potential to reduce preventable harm. Therefore, we 
proposed to adopt the Hospital Harm--Severe Hyperglycemia eCQM (NQF 
#3533e) beginning with the CY 2023 reporting period/FY 2025 payment 
determination.
---------------------------------------------------------------------------

    \1102\ Glycemic Control--Hyperglycemia (NQF #2362e). Available 
at: http://www.qualityforum.org/QPS/2362e.
    \1103\ Hospital Harm--Severe Hyperglycemia (NQF #3533e). 
Available at: http://www.qualityforum.org/ProjectTemplateDownload.aspx?SubmissionID=3533.
---------------------------------------------------------------------------

(c) Data Sources
    The measure is an eCQM that uses data collected through the EHR. 
The measure is designed to be calculated by the hospitals' CEHRT using 
the patient-level data submitted by hospitals to CMS.
(d) Measure Calculation
    The Hospital Harm--Severe Hyperglycemia eCQM is an outcome measure 
that assesses the number of hospital days with a severe hyperglycemic 
event among the total qualifying hospital days for at risk inpatient 
encounters. A severe hyperglycemic event is defined in the measure as a 
blood glucose result >300 mg/dL, or a day in which a blood glucose 
value was not documented, and it was preceded by 2 consecutive days 
where at least one glucose value was >=200 mg/dL.
(e) Denominator
    The denominator of at-risk encounters includes discharges from an 
inpatient hospital admission for all patients 18 years and older at the 
start of the measurement period, as well as--
     A diagnosis of diabetes that starts before or during the 
encounter;
     Administration of at least one dose of insulin or any 
anti-diabetic medication during the encounter; or
     Presence of at least one blood glucose value >200 mg/dL at 
any time during the encounter.
    The eCQM includes inpatient encounters which began in the emergency 
department or in observation status.
    The denominator is the total number of eligible days across all 
encounters that match the initial population criteria. This measure 
does not count the first 24-hour period after admission to the hospital 
(including the emergency department) or the last time period before the 
discharge, if it was less than 24 hours. By excluding the first 24 
hours of admission, the measure allows for correction of severe 
hyperglycemia that was present on admission. By excluding the last time 
period before discharge if it was less than 24 hours, the measure 
accounts for the fact that hospitals may not always be able to check 
glucose during the last time period, especially if it is only a few 
hours long. Eligible encounters that exceed 10 days are truncated to 
equal 10 days.
(f) Numerator
    The numerator is the total number of hyperglycemic days across all 
encounters. Hospital days are measured in 24-hour periods, starting 
from the time of arrival at the hospital (including the emergency 
department). Days with a hyperglycemic event are defined as either--
     A day with at least one blood glucose value >300 mg/dL; or
     A day in which a blood glucose value was not documented, 
and it was preceded by 2 consecutive days where at least one glucose 
value is >=200 mg/dL.
    The measure does not count >300 mg/dL events the first 24-hour 
period after hospital arrival for admitted patients (including the 
emergency department) or the last time period before discharge, if it 
was less than 24 hours.
(g) Risk Adjustment
    We note risk adjustment is not applicable to the Hospital Harm--
Severe Hyperglycemia eCQM. In the case of the Hospital Harm--Severe 
Hyperglycemia eCQM, there is evidence indicating that most 
hyperglycemic events of this severity (>300 mg/dL) are 
avoidable.1104 1105 1106 The rate of

[[Page 45388]]

inpatient severe hyperglycemia events can be considered a marker for 
quality of hospital care, since inpatient severe hyperglycemia is 
largely avoidable with proper glycemic 
management.1107 1108 1109 We will continue to evaluate the 
appropriateness of risk adjustment in measure reevaluation.
---------------------------------------------------------------------------

    \1104\ Maynard G, Kulasa K, Ramos P, et al. Impact of a 
Hypoglycemia Reduction Bundle and a Systems Approach to Inpatient 
Glycemic Management. Endocr Pract. 2015; 21(4):355-367.
    \1105\ Umpierrez GE, Hellman R, Korytkowski MT, et al. 
Management of Hyperglycemia in Hospitalized Patients in Non-Critical 
Care Setting: An Endocrine Society Clinical Practice Guideline. J 
Clin Endocrinol Metab. 2012;97(1):16-38.
    \1106\ Donihi AC, DiNardo MM, DeVita MA, Korytkowski MT. Use of 
a Standardized Protocol to Decrease Medication Errors and Adverse 
Events Related to Sliding Scale Insulin. Qual Saf Health Care. 
2006;15(2):89-91.
    \1107\ Maynard G, Kulasa K, Ramos P, et al. Impact of a 
Hypoglycemia Reduction Bundle and a Systems Approach to Inpatient 
Glycemic Management. Endocr Pract. 2015;21(4):355-367.
    \1108\ Umpierrez GE, Hellman R, Korytkowski MT, et al. 
Management of Hyperglycemia in Hospitalized Patients in Non-Critical 
Care Setting: An Endocrine Society Clinical Practice Guideline. J 
Clin Endocrinol Metab. 2012;97(1):16-38.
    \1109\ Donihi AC, DiNardo MM, DeVita MA, Korytkowski MT. Use of 
a Standardized Protocol to Decrease Medication Errors and Adverse 
Events Related to Sliding Scale Insulin. Qual Saf Health Care. 
2006;15(2):89-91.
---------------------------------------------------------------------------

    For more information on the Hospital Harm--Severe Hyperglycemia 
eCQM, we refer readers to the measure specifications available on the 
eCQI Resource Center website at: https://ecqi.healthit.gov/pre-rulemaking-eh-cah-ecqms.
    We invited public comment on this proposal.
    Comment: Many commenters expressed support for the inclusion of the 
Hospital Harm--Severe Hyperglycemia eCQM into the Hospital IQR Program 
measure set. Commenters noted their belief that the measure will 
increase transparency, drive improvements in care, and improve patient 
outcomes. A commenter appreciated that this measure can be applied 
broadly to various sized hospitals, and another commenter highlighted 
that this measure will expand the number of eCQMs available to rural 
and specialty hospitals for quality reporting. A commenter noted this 
measure is in alignment with the goals put forth in the National Action 
Plan for Adverse Drug Event Prevention (Action Plan). Commenters 
supported adoption of the measure and appreciated our commitment to 
align eCQMs in the Hospital IQR Program with the Promoting 
Interoperability Program.
    Response: We thank commenters for their support and input. We agree 
that this measure, which captures important quality information that is 
critical to patient safety and improving patient outcomes, should be 
included in the Hospital IQR Program measure set.
    Comment: Many commenters provided feedback on the implementation 
timeline for the measure. A few commenters agreed that the CY 2023 
reporting period/FY 2025 payment determination is a reasonable and 
appropriate timeline for a new measure, while several commenters 
believed that the measure should be delayed. A commenter requested an 
18 month delay, while others requested one additional year, 
recommending inclusion beginning with the CY 2024 reporting period and 
the FY 2026 payment determination.
    Response: We thank the commenters for their support and input. The 
measure was proposed for inclusion beginning in the CY 2023 reporting 
period/CY 2025 payment determination, which will allow hospitals at 
least one year to prepare and implement the measure. We direct readers 
to the eCQI Resource Center (available at: https://ecqi.healthit.gov/pre-rulemaking-eh-cah-ecqms) for measure specifications for this eCQM, 
several other eCQMs being finalized, as well as those we sought comment 
on in the FY 2022 IPPS/LTCH PPS proposed rule (86 FR 25070).
    Comment: A few commenters asked for clarification on the proposed 
timeline for public reporting.
    Response: In the FY 2021 IPPS/LTCH PPS final rule, we finalized 
public reporting of eCQM data beginning with eCQM data reported by 
hospital for the CY 2021 reporting period/FY 2023 payment determination 
and for subsequent years (85 FR 58959). Consistent with our adopted 
policy, we plan to initially publish CY 2021 reporting period/FY 2023 
payment determination eCQM data, of which there will be two quarters of 
data (for that payment determination year) on https://data.medicare.gov, or its successor website, before publishing it on 
the Hospital Compare website, or its successor website, sometime in the 
future. We did not propose any changes to this finalized policy in the 
FY 2022 IPPS/LTCH PPS proposed rule (86 FR 20570).
    Comment: Several commenters addressed the concept of adopting the 
Hospital Harm--Severe Hypoglycemia as a balancing measure to Hospital 
Harm--Severe Hyperglycemia. A few noted their support for the measure, 
recommending that we allow hospitals to choose which of the two 
measures to report. A commenter recommended CMS require reporting of 
both eCQMs. A commenter recommended that we require hospitals to report 
on this measure, while a few others preferred that reporting on it be 
kept optional. A few commenters noted that they could not support the 
adoption of these balancing measures as they believed they were not 
aligned.
    Response: We thank commenters for their feedback. Hospitals will be 
able to report the Severe Hyperglycemia and Severe Hypoglycemia 
measures independently. Balancing measures are measures that can be 
used to demonstrate that an improvement in one area is not negatively 
impacting improvement in another area. For example, we can use these 
measures to assess whether an improvement in the number of severe 
hyperglycemia events ties to an increase in the number of severe 
hypoglycemia events. For that reason, while the two measures may not 
measure the same exact thing, we consider them to be balancing 
measures. We believe that both measures, regardless of the denominator 
used, will trend downward as improvements are made. Additionally, we 
note that hospitals may self-select to report on one, both, or neither 
of these two finalized eCQMs and select other eCQMs. While we do not 
require reporting of both measures at this time, we strongly encourage 
reporting of both. We will take commenters' recommendations to require 
one or both measures into future consideration.
    Comment: A few commenters had concerns about the complexity of the 
measure and potential difficulties in measuring severe hyperglycemia in 
patients. A commenter indicated that the introduction of a ``day'' into 
the numerator and denominator will require effort in measure 
calculation. This commenter additionally requested that we provide 
sufficient guidance on the time windows for ``day.'' A few commenters 
also expressed concern about the level of testing, requesting that the 
measure undergo additional testing for feasibility and validity prior 
to finalization.
    Response: We appreciate commenters' feedback and recognize their 
concerns about the complexity of this measure. This measure is modeled 
on a previously NQF-endorsed measure (Glycemic Control--Hyperglycemia 
(NQF #2362)).\1110\ The numerator has been simplified due, in part, to 
the concern of complexity with that previous endorsed measure.\1111\ 
During measure testing, all data elements required for the measure 
calculation were tested for missing data. The missing rate of all 
required data elements was zero percent, suggesting that the measure 
calculation can be both feasible and automated, which

[[Page 45389]]

addresses concerns about the complexity of implementing the measure. As 
indicated in the measure specifications as proposed, the time window is 
24 hours.\1112\ For more detailed information and measure guidance, we 
refer readers to the measure specifications available on the eCQI 
Resource Center (available at: https://ecqi.healthit.gov/pre-rulemaking-eh-cah-ecqms).
---------------------------------------------------------------------------

    \1110\ Glycemic Control--Hyperglycemia (NQF #2362e). Available 
at: http://www.qualityforum.org/QPS/2362e.
    \1111\ Glycemic Control--Severe Hyperglycemia measure 
specifications are available at: https://www.qualityforum.org/QPS/2362e.
    \1112\ Hospital Harm--Severe Hyperglycemia measure 
specifications are available in the eCQI Resource Center at: https://ecqi.healthit.gov/ecqm/eh/pre-rulemaking/1/cms871v1.
---------------------------------------------------------------------------

    Furthermore, measure testing was done in compliance with the NQF 
requirements for eCQM development. The Hospital Harm--Severe 
Hyperglycemia eCQM was tested in six hospitals and three EHR systems 
that had good representation of hospitals across the country. This 
aligns with NQF's recommendation to conduct eCQM testing in more than 
one EHR system. As with all quality measures we develop, testing was 
performed to confirm the measure feasibility, reliability, and validity 
of the numerator, using clinical adjudicators who validated the EHR 
data compared with medical chart-abstracted data. Empirical results 
showed that the measure exhibited high reliability and data element 
validity. Additionally, the measure performance rates across the six 
hospitals that participated in testing ranged from 8.2 percent to 19.5 
percent.\1113\ This variability suggested that the harm rate in some 
sites more than doubled the harm rate in other sites, which we believe 
indicates room for improvement.
---------------------------------------------------------------------------

    \1113\ Hospital Harm--Severe Hyperglycemia Measure Testing 
information is available at: https://www.qualityforum.org/QPS/3533e.
---------------------------------------------------------------------------

    Comment: A few commenters raised concerns that the measure does not 
include risk adjustment. A commenter requested that CMS continue to 
reevaluate the need for risk adjustment after the measure is 
implemented. Another commenter could not support the measure without 
appropriate risk adjustment.
    Response: We thank commenters for their feedback. We note that this 
measure was endorsed by NQF without risk-adjustment.\1114\ Evidence 
exists to show that most hyperglycemic events of this severity (>300 
mg/dL) are avoidable.1115 1116 1117 1118 While certain 
patient health factors can impact glucose levels, clinical practice 
guidelines from the ADA, the Endocrine Society, and others have 
advocated for more intense monitoring and tailored treatment plans for 
higher risk individuals.1119 1120 As various causes for 
hyperglycemic events of this severity are controllable in hospital 
environments and risk can be reduced by adhering to clinical best 
practices, we do not think risk adjustment is warranted.\1121\ Members 
of the measure's TEP and clinical experts including endocrinologists 
all agreed with this decision. We will, however, continue to evaluate 
the appropriateness of risk adjustment for this measure.
---------------------------------------------------------------------------

    \1114\ National Quality Forum. Patient Safety, Fall 2019 Cycle, 
Track 1 Measures: CDP Report. (2020, September).
    \1115\ Momesso DP, Costa Filho RC, Costa JLF, Saddy F, Mesquita 
A, Calomeni M, Silva CDS, Farret J, Vasques ML, Santos AG, Cabral 
APV, Ribeiro D, Reis L, Muino MFM, Vitorino RS, Monteiro CA, Tinoco 
E, Volschan A. Impact of an inpatient multidisciplinary glucose 
control management program. Arch Endocrinol Metab. 2018 
Oct;62(5):514-522. doi: 10.20945/2359-3997000000071. PMID: 30462804.
    \1116\ Umpierrez GE, Smiley D, Hermayer K, Khan A, Olson DE, 
Newton C, et al. Randomized study comparing a basal bolus with a 
basal plus correction insulin regimen for the hospital management of 
medical and surgical patients with type 2 diabetes: Basal plus 
trial. Diabetes Care 2013;36: 2169-74.
    \1117\ Said E, Farid S, Sabry N, Fawzi M. Comparison on efficacy 
and safety of three inpatient insulin regimens for management of 
non-critical patients with type 2 diabetes. Pharmacology & Pharmacy 
2013;4:556-65. DOI: 10.4236/pp.2013.47080.
    \1118\ Schroeder JE, Liebergall M, Raz I, Egleston R, Ben Sussan 
G, Peyser A, et al. Benefits of a simple glycaemic protocol in an 
orthopaedic surgery ward: A randomized prospective study. Diabetes/
Metabolism Research and Reviews 2012;28 (1):71-5. DOI: 10.1002/
dmrr.1217.
    \1119\ American Diabetes Association. Diabetes Care in the 
Hospital: Standards of Medical Care in Diabetes--2020. Diabetes 
Care. 2020 Jan;43(Suppl 1):S193-S202.
    \1120\ Umpierrez GE, Hellman R, Korytkowski MT, et al. 
Management of Hyperglycemia in Hospitalized Patients in Non-Critical 
Care Setting: An Endocrine Society Clinical Practice Guideline. J 
Clin Endocrinol Metab. 2012;97(1):16-38. 
Umpierrez2012EndocrineGlines.
    \1121\ Ilcewicz HN, Hennessey EK, Smith CB. Evaluation of the 
impact of an inpatient hyperglycemia protocol on glycemic control. J 
Pharm Pharm Sci. 2019;22:85-92. Ilcewicz2019GlycemicControl.
---------------------------------------------------------------------------

    Comment: A few commenters recommended that CMS consider changing 
the proposed glucose level benchmark of >=300 mg/dL for severe 
hyperglycemia to >250 mg/dL based on ADA recommendations.
    Response: We appreciate the commenters' feedback and we understand 
the importance of aligning with clinical community standards. The 
measure developer's clinical experts supported using a higher threshold 
to define severe hyperglycemia (>300 mg/dL) as a clearer indication of 
patient harm. The higher threshold will likely improve the 
acceptability among clinicians and avoid the unintended consequence of 
hypoglycemia.
    Comment: Several commenters supported the inclusion of the measure 
into the Hospital IQR Program, with the recommendation to incorporate 
continuous glucose monitoring (CGM) as an option for measurement and to 
include additional glucose monitoring data.
    Response: We thank the commenters for this feedback. In the measure 
specifications as proposed, the glucose lab value set includes code 
concepts that are nonspecific to the monitoring device used to collect 
the glucose level, which can include CGM test results.\1122\ We may 
consider clarifying the language in the Guidance section of the measure 
specification.
---------------------------------------------------------------------------

    \1122\ The Glucose Lab Test value set is available at: https://vsac.nlm.nih.gov/valueset/2.16.840.1.113762.1.4.1045.134.
---------------------------------------------------------------------------

    Comment: A commenter requested that CMS monitor the long-term 
implications of the COVID-19 pandemic before including the measure into 
the Hospital IQR Program, expressing that COVID-19 and a medication 
used to treat COVID-19 (dexamethasone) can cause significant 
hyperglycemia even in patients without a preexisting diagnosis of 
diabetes.
    Response: We thank the commenter for their feedback. We note that 
under our current eCQM reporting requirements, hospitals are not 
specifically required to report on this eCQM--hospitals may self-select 
certain eCQMs. We refer readers to the FY 2021 IPPS/LTCH PPS final rule 
for more information on the current eCQM reporting requirements (85 FR 
58939). We are finalizing our proposal as proposed to adopt this 
measure, but we will monitor the impact of COVID-19 and its treatment 
on measure performance during implementation.
    Comment: A few commenters expressed that there should be sufficient 
guidance for eCQM reporting (specifically, QRDA I data) and 
implementation for a ratio eCQM.
    Response: We thank the commenters for their feedback. We refer 
readers to the measure specifications available on the eCQI Resource 
Center website at: https://ecqi.healthit.gov/pre-rulemaking-eh-cah-ecqms. We reiterate that the data submission requirements, 
Specifications Manual, and submission deadlines are posted on the 
QualityNet website at: http://www.QualityNet.cms.gov (or other 
successor CMS designated websites). The CMS Annual Update for the 
Hospital Quality Reporting Programs (Annual Update) also contains the 
technical specifications used for eCQMs

[[Page 45390]]

and is generally made available the year prior to the reporting period.
    Comment: A few commenters recommended adding new exclusion 
criteria, such as ICU with transient fluctuations in range and patients 
with diabetic ketoacidosis.
    Response: We thank the commenter for their feedback and will 
consider this recommendation during future measure reevaluation.
    After consideration of the public comments we received, we are 
finalizing our proposal as proposed.
6. Removal of Five Hospital IQR Program Measures
    We refer readers to the FY 2016 IPPS/LTCH PPS final rule (80 FR 
49641 through 49643) and the FY 2019 IPPS/LTCH PPS final rule (83 FR 
41540 through 41544) for a discussion of our current measure removal 
factors. In the FY 2022 IPPS/LTCH PPS proposed rule (86 FR 25579 
through 25582), we proposed to remove five measures from the Hospital 
IQR Program across the FY 2023 and FY 2026 payment determinations.
a. Removal of One Measure Under--Removal Factor 3, Availability of a 
More Broadly Applicable Measure (Across Settings, Populations, or the 
Availability of a Measure That Is More Proximal in Time to Desired 
Patient Outcomes for the Particular Topic): Death Among Surgical 
Inpatients With Serious Treatable Complications (CMS PSI-04)
    The Death Among Surgical Inpatients with Serious Treatable 
Complications (CMS PSI-04) measures in-hospital deaths per 1,000 
elective surgical discharges, among 18 through 89 years or obstetric 
patients with serious treatable complications (shock/cardiac arrest, 
sepsis, pneumonia, deep vein thrombosis/pulmonary embolism or 
gastrointestinal hemorrhage/acute ulcer). We refer readers to the FY 
2009 IPPS/LTCH PPS final rule where we adopted the Death Among Surgical 
Patients with Serious Treatable Complications (CMS PSI-04) measure for 
the FY 2010 payment determination and subsequent years (73 FR 48607) 
for more detail on this measure. In the FY 2011 IPPS/LTCH PPS final 
rule, under the RHQDAPU Program (the former title of the Hospital IQR 
Program), we harmonized two FY 2010 RHQDAPU Program quality measures, 
combining PSI-04 and ``Nursing Sensitive--Failure to rescue'' into a 
single measure renamed Death Among Surgical Inpatients with Serious 
Treatable Complications (75 FR 50182). The CMS PSI-04 measure is a 
claims-based measure which uses claims and administrative data to 
calculate the measure without any additional data collection from 
hospitals.
    In the FY 2022 IPPS/LTCH PPS proposed rule (86 FR 25579 through 
25580), we proposed to remove this measure beginning with the CY 2021 
reporting period/FY 2023 payment determination, because of the 
availability of a more broadly applicable measure--Factor 3. 
Specifically, in section IX.C.5.b. of the preamble of the proposed 
rule, we proposed the Hybrid HWM measure (NQF #3502). We refer readers 
to section IX.C.5.b. of the FY 2022 IPPS/LTCH PPS proposed rule and 
this rule for further discussion on the Hybrid HWM measure, including 
data sources, core clinical data elements, and measure calculation.
    The Hybrid HWM measure captures more conditions or procedures than 
CMS PSI-04. The Hybrid HWM measure also captures mortality within 30 
days of hospital admission for most conditions or procedures, compared 
to deaths for surgical discharges (or pregnancy, childbirth, and 
puerperium) as measured by CMS PSI-04. While the CMS PSI-04 measure is 
claims-based, the Hybrid HWM measure uses a hybrid of claims and 
clinical data elements from the EHR. As a result, we believe the Hybrid 
HWM measure is a more broadly applicable measure because it 
incorporates a larger set of conditions and procedures and moves toward 
greater use of EHR data for quality measurement. We note that removal 
of the CMS PSI-04 measure is contingent on the adoption of the Hybrid 
HWM measure.
    We invited public comment on this proposal.
    Comment: Several commenters supported our proposal to remove the 
CMS PSI-04 measure from the Hospital IQR Program measure set. A few 
commenters supported the shift from using a purely claims-based measure 
and believe that more consistent use of EHRs in healthcare and our 
proposal of the Hybrid HWM measure allow for the incorporation of 
larger data sets for greater quality measurement.
    Response: We thank commenters for their support for our proposal. 
We agree that there is substantial value in shifting program measures 
towards digital quality measurement. As noted previously in section 
IX.C.5.b., we are finalizing our proposal to adopt the Hybrid HWM 
measure beginning with voluntary reporting in the CY 2023 reporting 
period and mandatory reporting beginning with the CY 2024 reporting 
period/FY 2026 payment determination and for subsequent years.
    Comment: A number of commenters provided input regarding the 
measure specifications of CMS PSI-04. Some commenters noted concerns 
about measure specifications, but they did not support removal of CMS 
PSI-04 and instead suggested refinements to the measure. A commenter 
recommended that instead of removing CMS PSI-04, it could be improved 
through updates to the current measure specifications. They suggested 
that improvements can be made to the measure specifications through 
refinements in the types of surgical patients and complications 
included in the measure. Furthermore, they believe that the suggested 
improvements could strengthen robustness of the measure. A few 
commenters supported removal of the measure, noting perceived flaws in 
the measure specifications including issues with the measure 
methodology.
    Response: We appreciate commenters' feedback and concerns regarding 
the measure specifications and we thank commenters for their 
recommendations. We continue to support the importance of safety 
measures within our programs and acknowledge that the PSI-04 measure 
provides particular focus and granular data on the care of surgical 
patients, and is a measure that is not used in any other CMS quality 
program. Upon further consideration of the stakeholder feedback to 
retain the measure and consider suggested updates to the measure 
specifications, and in light of our continued commitment to safety, we 
have decided to not finalize our proposal to remove the measure and 
instead retain the measure in the Hospital IQR Program measure set at 
this time while we assess potential measure refinements. We intend to 
work with our measure development contractor to review the 
specifications of the CMS PSI-04 measure and we will continue to seek 
stakeholder feedback on the measure in future communication modes. We 
also note that any future changes to the measure would follow our 
previously finalized policies regarding substantive vs. non-substantive 
changes and we refer readers to the FY 2019 IPPS/LTCH PPS final rule 
(83 FR 41538) for more details.
    Comment: A few commenters raised concerns in respect to the 
clinical specifications of the measure, specifically, the population 
covered in the measure calculation. These commenters noted that the CMS 
PSI-04 measure specifically focuses on surgical outcomes, whereas the 
Hybrid HWM measure examines a more general population, not limited to 
surgery patients.

[[Page 45391]]

    Response: We thank commenters for their input. The Hybrid HWM 
measure has a broad denominator definition that encompasses most 
surgical inpatients with therapeutic operating room procedures, meaning 
that most of the patients captured by the CMS PSI-04 measure would also 
be captured by the Hybrid HWM measure. However, the Hybrid HWM measure 
will report an overall hospital-wide mortality rate, and not a specific 
rate for surgical patients, so we understand and appreciate commenters' 
feedback on the value of retaining the CMS PSI-04 measure. We recognize 
that the more granular level of data provided by the CMS PSI-04 measure 
can continue to help inform hospital quality improvement initiatives. 
In addition, we understand that the measure data from CMS PSI-04 equips 
beneficiaries with more detailed information that is specific to 
surgical care. Therefore, as noted previously, upon consideration of 
commenters' feedback, we are not finalizing our proposal to remove the 
measure and instead are retaining CMS PSI-04 in the Hospital IQR 
Program measure set at this time.
    Comment: A commenter did not support our proposal to remove the CMS 
PSI-04 measure because they believe there is value in it as an 
important patient safety measure. Specifically, this commenter noted 
that there are relatively few patient safety measures reported in the 
Hospital IQR Program or used in other CMS payment programs. 
Furthermore, this commenter noted that patient safety is a significant 
death risk and was therefore a high priority measure for both providers 
and patients. The commenter recommended that we add more patient safety 
measures to the Hospital IQR Program measure set.
    Response: We appreciate the commenter's feedback. As stated 
previously, after consideration of stakeholder concerns, we are not 
finalizing the removal of this measure. We continue to consider patient 
safety and reducing hospital-acquired conditions and adverse events as 
high priorities as reflected in the Meaningful Measures Framework 
quality priority of making care safer by reducing harms caused in the 
delivery of care and in the Meaningful Measure 2.0 Framework priority 
focus on safety. Given our commitment to these priority areas, we also 
proposed and are finalizing for adoption in this FY 2022 IPPS/LTCH PPS 
final rule the Hospital Harm-Severe Hypoglycemia eCQM and the Hospital 
Harm-Severe Hyperglycemia eCQM. We believe these two outcome measures 
will help assess harm reduction efforts, contribute to improvements in 
reducing harm, and enhance hospital performance on patient safety 
outcomes. Additionally, in reference to patient safety measures in 
other programs, we interpret the commenter's reference to ``payment 
programs'' to denote CMS quality programs. We note that, for example, 
the Hospital-Acquired Condition Reduction Program continues to focus on 
patient safety for purposes of measuring the quality of care in 
inpatient care settings. While we are not removing the CMS PSI-04 
measure at this time, we do intend to introduce additional patient 
safety eCQMs into the Hospital IQR Program in the future as measures 
that support our evolving program goals become available, and we have 
been focusing on measure concepts including pressure injury, falls with 
injury, acute kidney injury, and medication related bleeding. We will 
continue working with stakeholders to develop measures that focus on 
quality and safety.
    After consideration of the public comments we received, we are not 
finalizing our proposal to remove the Death Rate Among Surgical 
Inpatients with Serious Treatable Complications (PSI-04) measure 
beginning with the CY 2021 reporting period/FY 2023 payment 
determination.
b. Removal of One Measure Under--Removal Factor 5, Availability of a 
Measure That Is More Strongly Associated With Desired Patient Outcomes 
for the Particular Topic: Exclusive Breast Milk Feeding (PC-05) (NQF 
#0480)
    The Exclusive Breast Milk Feeding (PC-05) eCQM assesses the number 
of newborns exclusively fed breast milk during the newborn's entire 
hospitalization. For more details on the PC-05 measure, we refer 
readers to the FY 2015 IPPS/LTCH PPS final rule in which we adopted the 
measure for the Hospital IQR Program (79 FR 50242 through 50243). In 
the FY 2022 IPPS/LTCH PPS proposed rule (86 FR 255801) we proposed to 
remove PC-05 beginning with the CY 2024 reporting period/FY 2026 
payment determination under removal Factor 5--the availability of a 
measure that is more strongly associated with desired patient outcomes 
for the particular topic.
    Specifically, in keeping with our focus on maternal health, we 
proposed to adopt the Maternal Morbidity structural measure for 
inclusion in the Hospital IQR Program beginning with a shortened CY 
2021 reporting period/FY 2023 payment determination. We refer readers 
to section IX.C.5.a. of the preamble of this final rule for more detail 
on that measure. We believe that the Maternal Morbidity structural 
measure is more strongly aligned with our current focus on maternal 
health than the PC-05 eCQM. The Maternal Morbidity structural measure 
focuses on determining hospital participation in a Statewide or 
national Perinatal QI Collaborative and implementation of patient 
safety practices or bundles within that QI initiative, which includes 
breastfeeding, while PC-05 targets only breastfeeding, a less holistic 
area of maternal health. Improving maternal health and the quality of 
maternal care is a priority for CMS, and we believe that the Maternal 
Morbidity structural measure will help achieve this desired outcome 
more directly than PC-05.
    Further, we believe that removing PC-05 would produce a more 
harmonized and streamlined measure set (83 FR 41539 through 41540). 
Removing this measure from the Hospital IQR Program under removal 
Factor 5 supports the Meaningful Measures Framework because it helps 
the Hospital IQR Program reach a parsimonious set of the most 
meaningful measures available to track patient outcomes and impact (83 
FR 41567). One of the Hospital IQR Program's primary benefits to 
patients and the public is its ability to collect and publicly report 
data for patients to use in making decisions about their care. At the 
same time, maintaining an unnecessarily large or complicated measure 
set including measures that may not be as meaningful to patients 
hampers the Hospital IQR Program's effectiveness at presenting valuable 
data in a useful manner (83 FR 41544). Replacing this measure with one 
that is more strongly associated with broader maternal health goals 
aligns with the Meaningful Measures Framework and allows us to continue 
to effectively promote quality care.
    We note that, in alignment with our focus on encouraging quality of 
care in maternal health, we proposed to include the Maternal Morbidity 
structural measure as early as is practicable. Due to operational 
procedures required to remove PC-05, however, there will be overlap 
with the proposed Maternal Morbidity structural measure in the program 
until PC-05 would be removed. The Maternal Morbidity structural measure 
will have a reporting period beginning on October 1, 2021 through 
December 31, 2021, affecting the FY 2023 payment determination, which 
will overlap with PC-05 until its proposed removal for the CY 2024 
reporting period/FY 2026 payment determination. We note that removal of 
PC-05 measure is contingent on the

[[Page 45392]]

adoption of the Maternal Morbidity structural measure.
    We invited public comment on this proposal.
    Comment: Many commenters supported our proposal to remove PC-05. 
Some commenters supported our proposal to remove PC-05 because removing 
the measure reduces administrative burden. Several commenters supported 
our proposal to remove PC-05 because the Hospital IQR Program is 
adopting the Maternal Morbidity structural measure. A few commenters 
supported our proposal to remove PC-05, because the costs associated 
with the measure outweigh the benefits of retaining it in the Hospital 
IQR Program. A commenter supported our proposal to remove PC-05 because 
of the evidence that exclusive breast feeding within the short 
inpatient interval is not a reliable indicator of long-term breast milk 
feeding success.
    Response: We thank the commenters for their support. We agree and 
believe that removing PC-05 dovetails well with our adoption of the 
Maternal Morbidity measure. While we continue to believe that breast 
feeding is an important topic, we believe removing PC-05 will help 
ensure that we are moving the Hospital IQR Program forward in the least 
burdensome manner possible as we use new measures focused more directly 
on improving maternal morbidity, including the Maternal Morbidity 
structural measure, which is more holistic, that we are finalizing in 
this final rule.
    Comment: A few commenters did not support our proposal to remove 
PC-05, because the Maternal Morbidity structural measure does not 
specifically focus on breastfeeding, and therefore, is not a true 
replacement of PC-05. A few commenters did not support our proposal to 
remove PC-05 because of their concern that removing it would result in 
less focus on and investment in supporting breastfeeding in hospitals. 
They also expressed concern that removing this measure would also 
reduce beneficiaries' ability to see which hospitals are supportive of 
breastfeeding.
    Response: We appreciate commenters' concern and understand the 
commenters' position that retaining the measure may help focus 
attention on breastfeeding. However, we note that the Maternal 
Morbidity structural measure does address breastfeeding. It focuses on 
determining hospital participation in a State or national Perinatal QI 
Collaborative and implementation of patient safety practices or bundles 
within that QI initiative, which includes breastfeeding,\1123\ whereas 
PC-05 targets only breastfeeding, a less holistic area of maternal 
health. Therefore, in an effort to expand our focus on the quality of 
maternal care,1124 1125 we are removing PC-05, which has a 
more narrow focus. We believe removing PC-05 will help ensure that we 
are moving the Hospital IQR Program forward in the least burdensome 
manner possible while continuing to encourage improvement in maternal 
care. We agree that maternal morbidity is an important topic and are 
working with a measure developer to develop a maternal morbidity eCQM 
for potential future use in the Hospital IQR Program.
---------------------------------------------------------------------------

    \1123\ We refer readers to section IX.C.5.a. of the preamble of 
this final rule for more detailed information on the Maternal 
Morbidity structural measure.
    \1124\ HHS Press Office (2020) HHS Outlines New Plans and a 
Partnership to Reduce U.S. Pregnancy-related Deaths. https://www.hhs.gov/about/news/2020/12/03/hhs-outlines-new-plans-to-reduce-us-pregnancy-related-deaths.html.
    \1125\ Office of the Assistant Secretary for Planning and 
Evaluation (2020) HHS Initiative to Improve Maternal Health. https://aspe.hhs.gov/initiative-to-improve-maternal-health.
---------------------------------------------------------------------------

    Comment: A few commenters did not support our proposal to remove 
PC-05 because removal of this measure decreases the number of measures 
in the Hospital IQR Program that focus on maternal care.
    Response: We appreciate the commenters' concern. We note that PC-05 
is not a highly reported measure--in CY 2019 out of over 3,000 IPPS 
hospitals, 265 hospitals submitted eCQM data on PC-05 and 282 had a 
zero-denominator attestation. Nevertheless, we intend to continue to 
work with stakeholders to develop measures that focus on maternal 
health, and plan to introduce them when they become available. As 
discussed in section IX.C.5.a of this final rule, we are finalizing our 
proposal to adopt the Maternal Morbidity structural measure, which all 
hospitals participating in the Hospital IQR Program, will be required 
to report beginning with a shortened reporting period running from 
October 1, 2021 through December 31, 2021. This new measure 
specifically focuses on maternal health.
    Comment: A commenter did not support our proposal to remove PC-05 
because of their belief that removing PC-05 would negatively affect 
vulnerable populations who already have low rates of breastfeeding.
    Response: We appreciate the commenter's concern related to 
disparities. As noted earlier, we are focused on and committed to 
closing the health equity gap as discussed in the Health Equity RFI in 
the proposed rule (86 FR 25554 through 25561) and in section IX.B. of 
this final rule. Specifically regarding the PC-05 measure, as 
mentioned, only 265 hospitals submitted eCQM data on PC-05 for the CY 
2019 reporting period. While not directly focused on breastfeeding, we 
believe that other measures more directly focused on maternal health, 
including maternal morbidity outcome measures such as the eCQM focused 
on severe obstetrics complications previously mentioned, would be 
better able to target the measurement of care quality for vulnerable 
patient populations. We continue to believe that maternal care is a 
topic of vital importance, and we will continue to work with relevant 
stakeholders to identify measures of quality and advance improved 
health outcomes for maternal care.
    Comment: A few commenters did not support our proposal to remove 
PC-05 due to concerns about: (1) Recognizing the hospitals' resource 
expenditure; (2) alignment with other quality reporting initiatives; 
and (3) providing more notice before measure adoptions. A commenter did 
not support our proposal to remove PC-05 because of their belief that 
the removal would discount the investment of resources hospitals must 
expend to operationalize an eCQM. A commenter observed that by removing 
eCQM measures, the Hospital IQR Program falls out of alignment with The 
Joint Commission, such that hospitals face increased burden to report 
on different measures for various programs. A commenter did not support 
our proposal to remove PC-05 and instead suggested that CMS provide a 
one-year prospective schedule with the list of measures they are 
contemplating for removal so that hospitals have time to plan 
accordingly.
    Response: We recognize that hospitals expend resources to 
participate in the Hospital IQR Program. We understand the commenters' 
concern with removing an eCQM that has previously been reported and 
implemented in an existing EHR workflow. We acknowledge that changes to 
the Hospital IQR Program's measure set may be disruptive for hospitals 
that have already operationalized previously adopted measures. We 
appreciate hospitals' efforts to operationalize the PC-05 measure, 
however, we believe removing PC-05 will help ensure that we are moving 
the Hospital IQR Program forward in the least burdensome manner 
possible while continuing to encourage improvement in the quality of 
care provided to patients. Hospitals should feel

[[Page 45393]]

empowered to continue to use eCQMs for their own quality improvement 
processes and do not need CMS to calculate the measure or wait for 
performance feedback reports. Further, we recognize that changing our 
measure set may cause the Hospital IQR Program to fall out of alignment 
with the measure sets of other reporting systems, including The Joint 
Commission's (TJC's) perinatal core measure set which currently 
includes the PC-05 measure. We continue to consider other quality 
monitoring organizations' requirements as we build our own measure set, 
but note that the Hospital IQR Program's measure set is distinct from 
other reporting programs. We also note that other quality reporting 
initiatives may change their requirements. Furthermore, we intend to 
continue to use the notice and comment rulemaking process to adopt and 
remove measures from the Hospital IQR Program to provide stakeholders 
with notice of changes to our measure set.
    We emphasize that the decision to remove measures from the Hospital 
IQR Program is an extension of our goal under the Meaningful Measures 
Framework to continually refine the Hospital IQR Program's measure set 
so as to use a parsimonious set of the most meaningful measures. We 
will continue working to provide hospitals with the education, tools, 
and resources necessary to help reduce eCQM reporting burden and more 
seamlessly account for the removal or addition of eCQMs.
    Comment: A commenter suggested we remove PC-05 before CY 2024 to 
alleviate the burden of maintaining a measure that will be removed.
    Response: We appreciate commenter's suggestion. Because some 
hospitals may have chosen to report on PC-05 over recent years, we 
believe it is important to allow them time to prepare to report on 
different eCQMs.
    After consideration of the public comments we received, we are 
finalizing our proposal as proposed.
c. Removal of Three Measures Under--Removal Factor 8, Costs Associated 
With a Measure Outweigh the Benefit of Its Continued Use in the Program
    In the FY 2022 IPPS/LTCH PPS proposed rule (86 FR 25580 through 
25581) we proposed to remove three measures under removal Factor 8, 
``Costs Associated with a Measure Outweigh the Benefit of its Continued 
Use in the Program.'' These three measures are Admit Decision Time to 
ED Departure Time for Admitted Patients (ED-2); Anticoagulation Therapy 
for Atrial Fibrillation/Flutter (STK-03); and Discharged on Statin 
Medication (STK-06).
(1) Admit Decision Time to ED Departure Time for Admitted Patients (ED-
2)
    In the FY 2016 IPPS/LTCH PPS final rule, we adopted the Admit 
Decision Time to ED Departure Time for Admitted Patients (ED-2) eCQM as 
an option from which hospitals could choose to report to meet the self-
selected eCQM data reporting requirements for the FY 2018 payment 
determination. We refer readers to the FY 2016 IPPS/LTCH PPS final rule 
for more detail on this measure (80 FR 49693 through 49698). The ED-2 
eCQM evaluates the median time in minutes from admit decision time to 
time of departure from the emergency department (ED) for ED patients 
admitted to inpatient status.
    A recently published systematic review by Boudi, et al. of 12 
individual studies examined the association between ED boarding time 
(the time between the admission decision and departure from the ED) and 
in hospital mortality (IHM). Although the authors noted a tendency 
toward an association, they did not find strong evidence for an 
association between ED boarding and IHM.\1126\ Six of the studies 
reviewed showed an association between ED boarding time and IHM, five 
showed no association, and the remaining study demonstrated an 
association for patients admitted to non-ICU wards and no association 
for patients admitted to ICU status.\1127\
---------------------------------------------------------------------------

    \1126\ Boudi Z, Lauque D, Alsabri M, Ostlundh L, Oneyji C, 
Khalemsky A, et al. (2020) Association between boarding in the 
emergency department and in-hospital mortality: A systematic review. 
PLoS ONE 15(4): e0231253. https://doi.org/10.1371/journal.pone.0231253.
    \1127\ Boudi Z, Lauque D, Alsabri M, Ostlundh L, Oneyji C, 
Khalemsky A, et al. (2020) Association between boarding in the 
emergency department and in-hospital mortality: A systematic review. 
PLoS ONE 15(4): e0231253. https://doi.org/10.1371/journal.pone.0231253.
---------------------------------------------------------------------------

    The authors indicated there is variability in what is considered a 
cut-off time to define extended ED boarding time or prolonged ED LOS 
and stated that, in the U.S., prolonged ED visits have been defined as 
over 6 hours.\1128\ In several of the studies in this systematic review 
demonstrating an association between ED boarding and IHM, the 
researchers compared mortality between patients with a boarding time 
period of less than 6 hours and those with a boarding time period equal 
or greater than 6 hours (360 minutes). We compared these timeframes to 
hospital performance data for the chart-abstracted version of ED-
2,\1129\ using the most recent data in the Care Compare downloadable 
data base for timely and effective care from January 1, 2019 through 
December 31, 2019. Those results show that the national average for the 
ED-2 median reported boarding times is 101 minutes; the ED-2 90th 
percentile is 31 minutes; and only 37 out of 4,028 (0.92 percent) 
hospitals that reported on ED-2 had an ED-2 median time equal to or 
greater than 360 minutes. Thus, the Care Compare data indicate that 
most hospitals do not report median boarding times that correspond with 
this 6-hour cutoff.
---------------------------------------------------------------------------

    \1128\ The authors note there is a lack of a unique cut-off time 
to define EDB and state that, ``[f]urther well-controlled, 
international multicenter studies are needed to demonstrate . . . 
whether there is a specific EDB time cut-off that results in 
increased IHM.''
    \1129\ The chart-abstracted version of ED-2 was finalized for 
removal in the FY 2019 IPPS/LTCH PPS final rule for the FY 2022 
payment determination (83 FR 41567).
---------------------------------------------------------------------------

    Boudi's systematic review is consistent with previous research 
finding conflicting results related to the association between ED 
crowding and inpatient mortality. For example, a study by Derose, et 
al. found no association between measures indicating ED crowding and 
inpatient mortality after controlling for patient 
characteristics.\1130\
---------------------------------------------------------------------------

    \1130\ Derose S, Gabayan G, Chiu V, Yiu S, Sun B. (2014) 
Emergency Department Crowding Predicts Admission Length-of-Stay But 
Not Mortality in a Large Health System. Med Care. 2014 July; 52(7): 
602-611. doi:10.1097/MLR.0000000000000141. This study of the impact 
of ED system crowding measures on outcomes concluded that, after 
controlling for patient characteristics, there was no association 
between measures of ED crowding and inpatient mortality.
---------------------------------------------------------------------------

    In light of the inconsistency in research findings, we reassessed 
the value of retaining the ED-2 eCQM in the Hospital IQR Program and 
proposed to remove this measure, beginning with the CY 2024 reporting 
period/FY 2026 payment determination, under Factor 8, ``The costs 
associated with a measure outweigh the benefit of its continued use in 
the program.'' Pursuant to removal Factor 8, we strive to ensure that 
the Hospital IQR Program measure set continues to promote improved 
health outcomes for beneficiaries while minimizing the overall costs 
associated with the program (83 FR 41540). We believe that costs are 
multifaceted and include not only the burden associated with reporting, 
but also the costs associated with implementing and maintaining the 
program. For healthcare providers, the costs include maintaining the 
general administrative knowledge needed to report this measure as well 
as the costs associated with implementing

[[Page 45394]]

and maintaining measure specifications in hospitals' EHR systems for 
all the eCQMs available for use in the Hospital IQR Program (83 FR 
41568). We also recognize that CMS expends resources when maintaining 
information collection systems and analyzing reported data. Removing 
these measures will reduce provider and program costs alike. Given that 
recent studies indicate an inconclusive association between ED boarding 
times and adverse outcomes such as in-hospital mortality, the cost of 
the current expenditure outweighs the benefit of continued used of ED-
2. Additionally, due to the operational limitations of introducing and 
removing eCQMs associated with the lifecycle of such measures, we 
proposed to remove this measure beginning with the CY 2024 reporting 
period/FY 2026 payment determination.
    We invited public comments on this proposal.
    Comment: Many commenters supported our proposal to remove the ED-2 
eCQM. Some commenters appreciated that the removal would reduce burden 
on hospitals and others agreed that the costs associated with ED-2 
outweigh the benefit of its continued use in the Hospital IQR Program. 
A few commenters questioned whether boarding times accurately reflect 
quality of care and some suggested that quality of care is more 
impacted by external factors such as access to behavioral health 
treatment, patterns of primary care deliver, and nursing shortages.
    Response: We thank the commenters for the support of our proposal 
to remove the ED-2 eCQM. While we continue to believe that prolonged ED 
board times is an important issue, we agree that the Admit Decision 
Time to ED Departure Time for Admitted Patients measure has had 
inconclusive associations with adverse outcomes such as in-hospital 
mortality and the quality of care in the inpatient setting.\1131\ We 
acknowledge the commenters' perspective that other factors, in addition 
to boarding times, impact outcomes and note that this measure was not 
intended to suggest otherwise. We note that we will continue measuring 
ED boarding times in the outpatient setting via the OP-18: Median Time 
from ED Arrival to ED Departure for Discharged ED Patients (NQF #0496) 
measure, in the Hospital Outpatient Quality Reporting (OQR) Program (75 
FR 72094). We appreciate the commenters' feedback and will take it into 
consideration as we continually refine the measure sets for our quality 
programs.
---------------------------------------------------------------------------

    \1131\ Boudi Z, Lauque D, Alsabri M, Ostlundh L, Oneyji C, 
Khalemsky A, et al. (2020) Association between boarding in the 
emergency department and in-hospital mortality: A systematic review. 
PLoS ONE 15(4): e0231253. https://doi.org/10.1371/journal.pone.0231253.
---------------------------------------------------------------------------

    Comment: Several commenters did not support the proposal to remove 
ED-2. Many disagreed with the conclusion drawn regarding the relation 
between ED boarding and in-hospital mortality (IHM) as discussed in the 
Boudi, et al. article. Several commenters also expressed their belief 
that the measure is reliable, informative, and assesses a critical area 
of care.
    Response: We thank the commenters for their feedback. We agree that 
ED boarding is an important area of care, and as noted earlier, we will 
continue measuring ED boarding times in the outpatient setting via the 
OP-18: Median Time from ED Arrival to ED Departure for Discharged ED 
Patients measure (NQF #0496) (75 FR 72094). We recognize and appreciate 
the commenters' concerns about ED boarding of patients being associated 
with events such as ambulance diversion, preventable medical errors, 
lower patient satisfaction, and patient morbidity and mortality. While 
a number of studies assess the impacts of ED boarding, it is worth 
noting that reported impacts of ED boarding may vary by clinical 
condition, clinical interventions, and inpatient admission 
location.1132 1133
---------------------------------------------------------------------------

    \1132\ Boudi Z, Lauque D, Alsabri M, Ostlundh L, Oneyji C, 
Khalemsky A, et al. (2020) Association between boarding in the 
emergency department and in-hospital mortality: A systematic review. 
PLoS ONE 15(4): e0231253. https://doi.org/10.1371/journal.pone.0231253 Boudi, et al. and Derose, et al.).
    \1133\ Derose S, Gabayan G, Chiu V, Yiu S, Sun B. (2014) 
Emergency Department Crowding Predicts Admission Length-of-Stay But 
Not Mortality in a Large Health System. Med Care. 2014 July; 52(7): 
602-611. doi:10.1097/MLR.0000000000000141. This study of the impact 
of ED system crowding measures on outcomes concluded that, after 
controlling for patient characteristics, there was no association 
between measures of ED crowding and inpatient mortality.
---------------------------------------------------------------------------

    However, as discussed in the proposed rule, we believe that ED 
boarding times have inconclusive associations with adverse outcomes 
such as in-hospital mortality. While the metanalysis by Boudi, et al., 
did find an association between prolonged ED boarding times and 
mortality in some of the included studies, Boudi et al. reported that 
this finding was inconsistent across studies, leading the authors to 
note that there was only a tendency toward an association, as opposed 
to strong evidence for an association between ED boarding and in-
hospital mortality.\1134\ Those studies that did demonstrate a tendency 
toward an association found the association was more evident when ED 
boarding times exceeded 6 hours, 360 minutes.\1135\ As we discussed in 
the proposed rule (86 FR 25580 through 25581), the most recently 
available data in the Care Compare downloadable data base for timely 
and effective care from January 1, 2019 through December 31, 2019 
showed that the national average for the ED-2 median reported boarding 
times is 101 minutes for Hospital IQR Program hospitals; the ED-2 90th 
percentile is 31 minutes; and only 37 out of 4,028 (0.92 percent) 
hospitals that reported on ED-2 had a median time equal to or greater 
than 360 minutes. The data from Care Compare suggests that for most 
hospitals, reported median ED boarding times are not in excess of 6 
hours. This coupled with most literature demonstrating an association 
between mortality and ED boarding times in excess of 6 hours, limits 
the value of the ED-2 measure for demonstrating opportunities to 
further decrease ED boarding times to a level that would significantly 
impact mortality rates.
---------------------------------------------------------------------------

    \1134\ Boudi Z, Lauque D, Alsabri M, Ostlundh L, Oneyji C, 
Khalemsky A, et al. (2020) Association between boarding in the 
emergency department and in-hospital mortality: A systematic review. 
PLoS ONE 15(4): e0231253. https://doi.org/10.1371/journal.pone.0231253.
    \1135\ Boudi Z, Lauque D, Alsabri M, Ostlundh L, Oneyji C, 
Khalemsky A, et al. (2020) Association between boarding in the 
emergency department and in-hospital mortality: A systematic review. 
PLoS ONE 15(4): e0231253. https://doi.org/10.1371/journal.pone.0231253.
---------------------------------------------------------------------------

    Comment: Several commenters disagreed with our use of removal 
Factor 8, noting their belief that the benefit of retaining an 
established measure does not outweigh the costs associated with the 
measure. A few commenters specifically noted their belief that this 
measure is beneficial because of the correlation between ED boarding 
times and patient clinical outcomes, beyond just in-hospital mortality. 
Several commenters expressed that they continued to find value in the 
measure, do not find it burdensome to collect, and were concerned that 
removing the measure discounts the investment of resources hospitals 
have expended in operationalizing ED-2.
    Response: Despite our proposal to remove ED-2, we continue to 
believe that patient care and flow in the ED is an important topic, in 
part because prolonged ED boarding times can impact outcomes other than 
mortality. We agree with commenters that ED boarding time is an 
important issue, and we remind readers that it is assessed in

[[Page 45395]]

the Hospital OQR Program via the OP-18: Median Time from ED Arrival to 
ED Departure for Discharged ED Patients measure(75 FR 72094). We also 
support hospitals implementing interventions to minimize ED boarding 
time to minimize the adverse impact of ED boarding times independent of 
the requirements of the Hospital IQR Program. We will continue to work 
with relevant stakeholders to identify measures of quality and advance 
improved health outcomes for ED patients. As described in an earlier 
response, the benefit of maintaining the ED-2 measure in the Hospital 
IQR Program is limited, because most hospitals median ED boarding times 
are not in excess of 6 hours, limiting the value of the ED-2 measure 
for demonstrating opportunities to further decrease ED boarding times 
to a level that would significantly impact mortality rates. This, 
coupled with most literature demonstrating an association between 
mortality and ED boarding times in excess of 6 hours, limits the value 
of the ED-2 measure for demonstrating opportunities to further decrease 
ED boarding times to a level that would significantly impact mortality 
rates. Therefore, we believe the benefit of maintaining the measure is 
outweighed by the costs associated with maintaining it.
    In addition, we acknowledge the commenters' concern regarding 
removing an eCQM that has previously been reported and implemented in 
an existing EHR workflow, and we recognize the time, effort, and 
resources that hospitals expend on reporting these measures. We 
appreciate hospitals' efforts to operationalize the ED-2 measure. We 
respectfully disagree that removing the ED-2 eCQM would not reduce some 
burden on providers and their health IT vendors. Focusing on a more 
streamlined measure set gives hospitals and their health IT vendors 
more time and resources to accommodate new reporting requirements by 
reducing measure maintenance and specification requirements. Removing 
targeted measures from the Hospital IQR Program is consistent with our 
goal under the Meaningful Measures Framework to continually refine the 
measure set as appropriate. We believe removing ED-2 will help ensure 
that we are moving forward in the least burdensome manner possible 
while maintaining a parsimonious set of the most meaningful quality 
measures and while continuing to incentivize improvement in the quality 
of care provided to patients. We will continue working to provide 
hospitals with the education, tools, and resources necessary to help 
reduce eCQM reporting burden and more seamlessly account for the 
removal or addition of eCQMs.
    Comment: A few commenters were concerned about the timeline for and 
timeliness of removing ED-2. A commenter questioned why we would remove 
an eCQM in light of our goal in the Meaningful Measures Framework 2.0 
to fully transition to digital quality measures (dQMs) by 2025. Another 
commenter expressed concern that the measure data had not yet been 
publicly reported and recommended that we wait to remove the measure 
until after the public has had an opportunity to evaluate the measure 
data. Another suggested we remove ED-2 before CY 2024 to alleviate the 
burden of maintaining a measure that will be removed.
    Response: Pursuant to Meaningful Measures 2.0, we are indeed 
emphasizing digital quality measurement and are working toward fully 
digital quality measurement by 2025.\1136\ However, our goal to 
transition to digital quality measures runs parallel with our goal of 
moving the program forward in the least burdensome manner possible 
while maintaining a parsimonious set of the most meaningful quality 
measures and continuing to incentivize improvement in the quality of 
care provided to patients. Consistent with these goals, we believe it 
is appropriate to remove certain eCQMs to develop a more streamlined 
measure set. As some hospitals may have chosen to report on ED-2 over 
recent years, we believe it is important to allow them time to prepare 
to report on different eCQMs. We acknowledge that the eCQM data has not 
yet been publicly reported. We refer readers to 85 FR 58953 through 
58959 for a more detailed discussion of the Hospital IQR Program's plan 
and policy for publicly reporting eCQM data. Nonetheless, in keeping 
with our initial proposal, and our goal of maintaining a parsimonious 
measure set, we continue to believe it is appropriate to remove ED-2 at 
this time. We appreciate commenters' suggestions and will take them 
into consideration as we continually refine the measure sets for our 
quality programs.
---------------------------------------------------------------------------

    \1136\ Meaningful Measures 2.0: Moving from Measure Reduction to 
Modernization. Available at: https://www.cms.gov/meaningful-measures-20-moving-measure-reduction-modernization.
---------------------------------------------------------------------------

    Comment: A commenter did not support the removal of ED-2 because it 
was concerned that its removal would disincentivize hospitals from 
maintaining low ED boarding times.
    Response: We appreciate the commenter's concern, but respectfully 
disagree that the removal will result in hospitals not working to 
maintain low boarding time. We are confident that hospitals are 
committed to providing high quality care to patients, and we do not 
have any indication that they will stop trying to reduce emergency 
department board times. However, we encourage commenters to submit any 
evidence suggesting that removing this measure leads to a reduction in 
desired clinical behavior. We will continue to monitor for stakeholder 
feedback about reduction in desired clinical behavior. We support 
hospitals continuing to use the ED-2 eCQM for their own quality 
improvement activities even if the measure is not part of the Hospital 
IQR Program's measure set, including to improve ED boarding times, 
especially for those that can continue to use it at a minimal cost. 
Additionally as mentioned earlier, we continue to encourage hospitals 
to focus on improving ED boarding times in the outpatient setting; we 
will continue measuring ED boarding times in the Hospital OQR Program 
setting via the OP-18: Median Time from ED Arrival to ED Departure for 
Discharged ED Patients measure (75 FR 72094).
    Comment: A few commenters did not support our proposal to remove 
ED-2 due to concerns it would reduce the options for reporting. A 
commenter specified that rural and critical access hospitals would be 
particularly affected.
    Response: We thank the commenters for their feedback. We 
acknowledge that facilitating quality improvement for rural hospitals, 
small hospitals, and critical access hospitals\1137\ and can present 
unique challenges and is a high priority under the Meaningful Measures 
Framework. We highlight that we are finalizing our proposal to adopt 
the Hospital Harm--Severe Hyperglycemia eCQM and the Hospital Harm--
Severe Hypoglycemia into the Hospital IQR Program measure set, which 
commenters supported in part because it would expand the number of 
eCQMs available to rural and specialty hospitals. We refer readers to 
sections IX.C.5.d.1. and IX.C.5.d.2. for more detail on our finalized 
proposals to adopt the Hospital Harm--Severe Hypoglycemia eCQM and 
Hospital Harm--Severe Hyperglycemia eCQM.

[[Page 45396]]

We intend to introduce additional eCQMs into the program and will work 
with stakeholders to consider and develop measures that are appropriate 
for use by small and rural hospitals.
---------------------------------------------------------------------------

    \1137\ We note that under section 1886(b)(3)(B)(viii) of the 
Act, only subsection (d) hospitals are required to submit data to 
the Hospital IQR Program. Critical access hospitals participate in 
the electronic reporting of CQMs under the Promoting 
Interoperability Program.
---------------------------------------------------------------------------

    Comment: A commenter observed that by removing eCQM measures, the 
Hospital IQR Program falls out of alignment with The Joint Commission, 
such that hospitals face increased burden to report on different 
measures for various programs. A few commenters recommended that CMS 
provide a one-year prospective schedule with the list of measures they 
are considering for removal so that hospitals have time to plan 
accordingly.
    Response: We recognize that by changing our measure set, the 
Hospital IQR Program and measure sets of other reporting systems become 
misaligned. We seek to align efforts as much as possible, but the 
Hospital IQR Program is separate and distinct from The Joint 
Commission. While we intend to continue to consider other quality 
monitoring organizations' requirements in building our own measure set, 
the decision to remove measures from the Hospital IQR Program is an 
extension of our goal under the Meaningful Measures Framework to 
continually refine the Program's measure set so as to use a 
parsimonious set of the most meaningful measures.
    We acknowledge the commenters' concern with removing an eCQM that 
has previously been reported and implemented in an existing EHR 
workflow, and we recognize the time, effort, and resources that 
hospitals expend on reporting these measures. However, the decision to 
remove measures from the Hospital IQR Program is an extension of our 
goal under the Meaningful Measures Framework to continually refine the 
measure set so as to use a parsimonious set of the most meaningful 
measures. Additionally, we direct the commenter to the MAP (https://www.qualityforum.org/map/) and its review of potential measures for 
removal. We intend to continue to use the notice and comment rulemaking 
process to adopt and remove measures from the Hospital IQR Program to 
provide stakeholders with notice of changes to our measure set. We will 
continue working to provide hospitals with the education, tools, and 
resources necessary to help reduce eCQM reporting burden and more 
seamlessly account for the removal or addition of eCQMs.
    After consideration of the public comments we received, we are 
finalizing our proposal as proposed.
(2) Stroke-Related Electronic Clinical Quality Measures (eCQMs)
    In the FY 2022 IPPS/LTCH PPS proposed rule (86 25581 through 25582) 
we proposed to remove two stroke-related eCQMs:
     Anticoagulation Therapy for Atrial Fibrillation/Flutter 
(STK-03) (adopted in the set of eCQMs from which hospitals self-select 
for Hospital IQR Program reporting in the FY 2016 IPPS/LTCH PPS final 
rule, 80 FR 49693 through 49698); and
     Discharged on Statin Medication (STK-06) (adopted in the 
set of eCQMs from which hospitals self-select for Hospital IQR Program 
reporting in the FY 2016 IPPS/LTCH PPS final rule, 80 FR 49693 through 
49698).
    We proposed to remove STK-03 and STK-06 under removal Factor 8, 
``the costs associated with a measure outweigh the benefit of its 
continued use in the program.'' Under removal Factor 8, we strive to 
ensure that the Hospital IQR Program measure set aligns with the 
Meaningful Measures Framework goal of promoting improved health 
outcomes for beneficiaries while minimizing the overall costs 
associated with the program (83 FR 41540). We assessed the relative 
costs and benefits for both measures as described in detail in this 
rule.
    As we assessed the relative benefits of these measures, we 
recognized that our measure set contains a high proportion of stroke 
related eCQMs. As previously finalized in the FY 2021 IPPS/LTCH PPS 
final rule (85 FR 58931), we have a total of nine eCQMs, four of which 
are stroke related. In order to achieve a more parsimonious measure 
set, we believe it is appropriate to reduce the portfolio of stroke-
related eCQMs. We continue to believe that ensuring appropriate 
pharmacotherapy for stroke patients is an important topic and we will 
continue to work with relevant stakeholders to identify measures of 
quality and advance improved health outcomes for stroke patients. 
Within the eCQM portfolio of stroke measures, we identified STK-03 and 
STK-06 as candidates for removal based on specific considerations 
described in this rule.
    For STK-03 specifically, the patient population (patients 
prescribed anticoagulation therapy, which is a type of antithrombotic 
therapy), can be considered a subpopulation of the global population of 
ischemic stroke patients captured under the STK-02 eCQM, which measures 
the number of patients prescribed antithrombotic therapy at hospital 
discharge.\1138\ Further, the results of our internal review of the CY 
2019 eCQM reporting indicate that fewer hospitals chose to report STK-
03 than any of the other remaining three stroke-related eCQMs. In 
contrast, STK-02 was the most reported of the four stroke-related eCQMs 
for the CY 2019 eCQM reporting period. Though the STK-02 eCQM does not 
provide the same level of granularity as the STK-03 eCQM, we believe 
that the low reporting rate of STK-03 coupled with the overlap in 
patient populations means that the benefits of maintaining both 
measures in the Hospital IQR Program measure set has been reduced. 
Given these reduced benefits, we now believe that the costs associated 
with this measure outweigh the benefits of retaining this measure in 
the Hospital IQR Program measure set.
---------------------------------------------------------------------------

    \1138\ D. Becker. 2013 Antithrombotic Drugs: Pharmacology and 
Implications for Dental Practice. Anesth Prog. 2013 Summer; 60(2): 
72-80. Available at: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3683884/.
---------------------------------------------------------------------------

    For STK-06 specifically, which assesses percentage of patients 
discharged on statin medication, we found that the updated 2019 
American Heart Associations (AHA)/American Stroke Association (ASA) 
stroke guidelines on antiplatelet treatment indicate that STK-06 is not 
the most suitable measure for improving patient outcomes in stroke 
treatment during the acute period.1139 1140 We believe the 
body of evidence supporting the benefits of retaining STK-06 has been 
weakened by the findings of the AHA/ASA stroke guidelines. This is 
because the strongest recommendations and quality of evidence are for 
administration of aspirin in patients with Acute Ischemic Stroke within 
24 to 48 hours after onset. Furthermore, there is only moderate quality 
evidence to continue STK-06, the measure of ischemic stroke patients 
who are prescribed or continue to take statin medication at hospital 
discharge.1141 1142

[[Page 45397]]

Lastly, other measures like STK-02, Discharged on Antithrombotic 
Therapy, and STK-05, Antithrombotic Therapy by The End of Hospital Day 
2, already support our efforts to improve care and patient outcomes in 
the acute period. Taken together we believe that the benefit of 
retaining STK-06 has been reduced. Given these reduced benefits, we now 
believe that the costs associated with this measure outweigh the 
benefits of retaining this measure in the Hospital IQR Program measure 
set.
---------------------------------------------------------------------------

    \1139\ Kennedy J, Hill MD, Ryckborst KJ, Eliasziw M, Demchuk AM, 
Buchan AM; FASTER Investigators. Fast Assessment of Stroke and 
Transient Ischaemic Attack to Prevent Early Recurrence (FASTER): A 
randomised controlled pilot trial. Lancet Neurol. 2007; 6:961-969. 
doi:10.1016/S1474-4422(07)70250-8.
    \1140\ Yoshimura S, Uchida K, Daimon T, Takashima R, Kimura K, 
Morimoto T; on behalf of the ASSORT Trial Investigator. Randomized 
controlled trial of early versus delayed statin therapy in patients 
with acute ischemic stroke: ASSORT Trial (Administration of Statin 
on Acute Ischemic Stroke Patient). Stroke. 2017;48:3057-3063. 
doi:10.1161/STROKEAHA.117.017623.
    \1141\ Powers WJ, Rabinstein AA, Ackerson T, Adeoye OM, 
Bambakidis NC, Becker K, Biller J, Brown M, Demaerschalk BM, Hoh B, 
Jauch EC, Kidwell CS, Leslie-Mazwi TM, Ovbiagele B, Scott PA, Sheth 
KN, Southerland AM, Summers DV, Tirschwell DL; on behalf of the 
American Heart Association Stroke Council. Guidelines for the early 
management of patients with acute ischemic stroke: 2019 update to 
the 2018 guidelines for the early management of acute ischemic 
stroke: A guideline for healthcare professionals from the American 
Heart Association/American Stroke Association. Stroke. 2019; 
50:e344-e418 doi: 10.1161/STR.0000000000000211.
    \1142\ Sandercock PA, Counsell C, Tseng MC, Cecconi E. Oral 
antiplatelet therapy for acute ischaemic stroke. Cochrane Database 
Syst Rev. 2014:CD000029. doi: 10.1002/14651858.CD000029.pub3.
---------------------------------------------------------------------------

    We believe that costs are multifaceted and include the burden 
associated with reporting as well as costs related to program 
implementation and maintenance, which are applicable both to providers 
and CMS (83 FR 41540). Removing STK-03 and STK-06 under Factor 8 will 
eliminate costs associated with implementing and maintaining these 
measures for the Hospital IQR Program. For healthcare providers, the 
costs associated with STK-03 and STK-06 include maintaining the general 
administrative knowledge needed to report these measures as well as the 
costs associated with implementing and maintaining measure 
specifications in hospitals' EHR systems for all the eCQMs available 
for use in the Hospital IQR Program (83 FR 41568). We also recognize 
that CMS expends resources when maintaining information collection 
systems and analyzing reported data. Removing these measures will 
reduce provider and program costs alike.
    In summary, removing STK-03 and STK-06 will reduce the costs 
associated with them in the Hospital IQR Program while still 
maintaining an efficient measure set that continues to effectively 
promote quality care. Removing STK-03 and STK-06 supports using a 
parsimonious set of the most meaningful measures available to track 
patient outcomes and impact, in keeping with the Meaningful Measures 
Framework (83 FR 41567). Maintaining an unnecessarily large or 
complicated measure set including measures that are not meaningful to 
consumers and caregivers hampers the Hospital IQR Program's 
effectiveness (83 FR 41544). Additionally, due to the operational 
feasibility of introducing and removing eCQMs, we proposed to remove 
both measures beginning with the CY 2024 reporting period/FY 2026 
payment determination.
    We invited public comment on these proposals. We address the 
comments on each measure separately below.
(a) Anticoagulation Therapy for Atrial Fibrillation/Flutter (STK-03)
    Comment: Many commenters generally supported our proposal to remove 
STK-03. Several commenters supported our proposal to remove STK-03 
because removing the measure reduces administrative burden, and a few 
commenters specifically agreed with removing it under removal Factor 8 
because they agreed that costs associated with the measure outweigh the 
benefits of retaining it in the Hospital IQR Program. A commenter 
supported our proposal to remove STK-03 because the removal will add 
balance to the core set of eCQMs available for reporting.
    Response: We thank the commenters for their support of our proposal 
to remove STK-03. While we agree with commenters that removal Factor 8 
would be an appropriate way to remove the STK-03 eCQM, we are not 
finalizing our proposal because we agree with the more compelling 
rationale provided by commenters to retain the STK-03 eCQM. Most 
notably, commenters identified two reasons to retain STK-03 in addition 
to STK-02. First, commenters highlighted their belief that the STK-02 
measure does not specifically target prescribing of anticoagulation 
therapy. Commenters expressed their concern that removing STK-03 could 
thereby result in fewer stroke patients receiving appropriate 
anticoagulant therapy. Second, commenters identified that STK-03 
distinguishes between the general category of antithrombotic therapy 
and the specific subset of anticoagulant therapy, whereas STK-02 does 
not ensure that stroke patients with atrial fibrillation are 
appropriately prescribed an anticoagulant as guidelines recommend. In 
addition, other commenters emphasized that ischemic stroke patients are 
not all the same, and that their treatment protocols might vary. For 
example, patients with non-cardioembolic ischemic stroke should be 
treated with antiplatelet medication, rather than anticoagulation. Upon 
further consideration of commenter feedback, we have decided not to 
finalize our proposal to remove STK-03 eCQM. These specific comments 
and our responses are discussed in more detail later in section.
    Comment: A number of commenters did not support our proposal to 
remove STK-03. Commenters asserted their belief that the STK-02 measure 
does not specifically target prescribing of anticoagulation therapy to 
patients at discharge. Commenters identified that ischemic stroke 
patients are not all the same, noting their belief that patients with 
non-cardioembolic ischemic stroke should be treated with antiplatelet 
medication, rather than anticoagulation. Commenters also pointed out 
the distinction that the STK-03 eCQM makes between the general category 
of antithrombotic therapy and the specific subset of anticoagulant 
therapy, whereas STK-02 does not ensure that stroke patients with 
atrial fibrillation are appropriately prescribed an anticoagulant as 
guidelines recommend. Commenters expressed their belief that 
anticoagulation has historically been dramatically underutilized for 
stroke prevention in patients with atrial fibrillation, such that 
prescribing it at discharge is an important opportunity to improve 
appropriate use in these patients. Commenters were concerned that 
removing STK-03 could result in fewer stroke patients receiving 
appropriate anticoagulant therapy.
    Response: We appreciate commenters' concerns. We have confidence 
that hospitals are committed to providing good quality care to stroke 
patients, and we do not have any indication that they will stop doing 
so in these areas for which the quality of care has become standard 
practice. After considering stakeholder concerns, we will retain the 
STK-03 eCQM in the Hospital IQR Program's measure set and are thus not 
finalizing the removal in this final rule.
    Comment: A commenter observed that by removing the STK-03 eCQM 
measure, the Hospital IQR Program falls out of alignment with The Joint 
Commission, such that hospitals face increased burden to report on 
different programs for various programs.
    Response: We recognize that by changing our measure set, the 
Hospital IQR Program and measure sets of other reporting systems become 
misaligned. We seek to align efforts as much as possible, but the 
Hospital IQR Program is separate and distinct from The Joint 
Commission. While we intend to continue to consider other quality 
monitoring organizations' requirements in building our own measure set, 
the decision to remove measures from the Hospital IQR Program is an 
extension of our goal under the Meaningful Measures Framework to 
continually refine the Program's measure set so as to use a 
parsimonious set of the most meaningful measures. However, we note that 
after consideration of stakeholder

[[Page 45398]]

concerns, we are not finalizing our proposal to remove this measure.
    Comment: A few commenters expressed concern about the proposed 
removal timeline. A commenter recommended a 1-year prospective schedule 
of measures contemplated for removal, and a commenter recommended a 
measure removal date prior to the CY 2024 reporting period.
    Response: We appreciate commenters' suggestions and will take them 
into consideration as we continually refine the measure sets for our 
quality programs. We note that after consideration of stakeholder 
concerns, we are not finalizing our proposal to remove this measure.
    Comment: A commenter did not support our proposal to remove STK-03 
because of their belief that this removal would magnify racial 
inequities in prescription and treatment that non-white stroke patients 
face.
    Response: We appreciate the commenter's concern related to racial 
disparities. As noted earlier, we are focused on and committed to 
closing the health equity gap as seen in the Health Equity RFI in the 
proposed rule (86 FR 25554 through 25561) and in section IX.B of this 
final rule. We wish to clarify that STK-03 is not stratified by race 
which limits the ability of the measure to directly capture or address 
racial disparities. However, we note that after consideration of 
stakeholder concerns, we are not finalizing our proposal to remove this 
measure.
    Comment: Several commenters did not support our proposal to remove 
STK-03 because they believed that removing it would decrease the number 
of available eCQMs for hospitals to choose from and discounts the 
investment of resources hospitals must expend to operationalize an 
eCQM.
    Response: As discussed earlier, after consideration of stakeholder 
concerns, we are not finalizing our proposal to remove this measure. We 
note that we are finalizing our proposal to adopt two additional eCQMs 
and refer readers to sections IX.C.5.d.1. and IX.C.5.d.2. for more 
detail on our finalized proposals to adopt the Hospital Harm-Severe 
Hypoglycemia eCQM and Hospital Harm--Severe Hyperglycemia eCQM. 
Furthermore, we reiterate that we intend to introduce additional eCQMs 
into the program as ones that support our evolving program goals become 
available.
    After consideration of the public comments we received, we are not 
finalizing our proposal to remove the Anticoagulation Therapy for 
Atrial Fibrillation/Flutter (STK-03) eCQM. We thank the commenters for 
their comments and suggestions, which we will take into consideration 
when assessing what changes, if any, should be incorporated into this 
important measure for the future.
(b) Discharged on Statin Medication (STK-06)
    Comment: Many commenters expressed support for our proposal to 
remove the STK-06 eCQM from Hospital IQR Program measure set. Several 
commenters stated the proposal would reduce unnecessary administrative 
and reporting burden and expressed appreciation for CMS' efforts to 
continually review the measure set and balance the core set of eCQMs 
reported to CMS.
    Response: We thank commenters for their support of the proposal to 
remove STK-06 from the Hospital IQR Program.
    Comment: A few commenters did not support our proposal to remove 
the STK-06 measure due to concern that small hospitals lack other eCQMs 
to report based upon their patient population.
    Response: We acknowledge that facilitating quality improvement for 
small hospitals can present unique challenges. We direct readers to 
section IX.C.5.d. where we are finalizing our proposal to adopt the 
Hospital Harm-Severe Hyperglycemia eCQM and the Hospital Harm-Severe 
Hypoglycemia eCQM into the Hospital IQR Program measures set in part 
because it would expand the number of eCQMs available for reporting. We 
also acknowledge that there are situations in which a hospital may have 
few or zero patients that meet the denominator criteria of a particular 
eCQM (79 FR 50323 through 50324). We remind readers of the Hospital IQR 
Program's zero denominator declaration and case threshold exemption 
policies, finalized in the FY 2016 IPPS/LTCH PPS final rule. 
Utilization of a zero denominator declaration and case threshold 
exemption are considered as part of the criteria for successful 
submissions when reporting eCQMs for the Hospital IQR Program (80 FR 
49695). We later clarified that hospitals are permitted to enter a 
value of zero to demonstrate that they had no clinical cases (81 FR 
57153). We also refer readers to section IX.C.9.e.3. of this final rule 
for our zero denominator declaration and case threshold exemption 
policy, which states hospitals can continue to meet the reporting 
requirements by submitting data via zero denominator declaration or 
case threshold exemption (82 FR 38387). It remains our goal to expand 
EHR-based quality reporting in the Hospital IQR Program, which we 
believe will ultimately provide more flexibility for hospitals to 
choose measures that are most representative of their patient 
populations.
    Comment: A commenter did not support our proposal due to the 
investment of time and resources previously incurred to implement the 
measure.
    Response: We acknowledge the time, effort, and resources that 
hospitals expend on implementing eCQMs. As discussed in the proposed 
rule, we believe that costs are multifaceted and include the burden 
associated with reporting as well as costs related to program 
implementation and maintenance, which are applicable both to providers 
and CMS (83 FR 41540). Removing STK-06 under Factor 8 will eliminate 
costs associated with implementing and maintaining these measures for 
the Hospital IQR Program. For healthcare providers, the costs 
associated with STK-06 include maintaining the general administrative 
knowledge needed to report these measures as well as the costs 
associated with implementing and maintaining measure specifications in 
hospitals' EHR systems for all the eCQMs available for use in the 
Hospital IQR Program (83 FR 41568). We also recognize that CMS expends 
resources when maintaining information collection systems and analyzing 
reported data. Removing these measures will reduce provider and program 
costs alike. In summary, removing STK-06 will reduce the costs 
associated with them in the Hospital IQR Program while still 
maintaining an efficient measure set that continues to effectively 
promote quality care. Removing STK-06 supports using a parsimonious set 
of the most meaningful measures available to track patient outcomes and 
impact, in keeping with the Meaningful Measures Framework (83 FR 
41567). Maintaining an unnecessarily large or complicated measure set 
including measures that are not meaningful to consumers and caregivers 
hampers the Hospital IQR Program's effectiveness (83 FR 41544).
    Comment: A few commenters expressed concern about the date proposed 
for measure removal. A commenter recommended a one-year prospective 
schedule of measures contemplated for removal, and a commenter 
recommended the removal of the STK-06 measure removal date prior to the 
CY 2024 reporting period.
    Response: We establish program requirements considering all 
hospitals that participate in the Hospital IQR Program at a national 
level, which involves a wide spectrum of capabilities and resources 
with respect to eCQM

[[Page 45399]]

reporting. In establishing our eCQM policies, we must balance the needs 
of hospitals with variable preferences and capabilities. We recognize 
that some hospitals and health IT vendors may prefer earlier removal in 
order to forgo maintenance on those eCQMs proposed for removal (83 FR 
41569). We believe our proposal would spare hospitals that have already 
allocated and expended resources in preparation for the CY 2023 
reporting period. We developed our proposal to remove STK-06 from the 
eCQM measure set beginning with the CY 2024 reporting period/FY 2026 
payment determination in response to stakeholder feedback for more time 
to prepare for changes to eCQM reporting requirements, including 
changes to the eCQM measure set (83 FR 41573).
    Comment: A few commenters opposed removal of STK-06 due to concern 
that removal of the measure does not align with current clinical 
guidelines and recommended measure modification to improve the 
measure's utility.
    Response: We acknowledge the commenters' perspective but disagree 
and believe the 2019 updated American Heart Association/American Stroke 
Association stroke guidelines on antiplatelet treatment indicate that 
STK-06 is not the most suitable measure for improving patient outcomes 
in stroke treatment during the acute period. As stated in the proposed 
rule (86 FR 25581 through 25582) we found that the updated 2019 
American Heart Associations (AHA)/American Stroke Association (ASA) 
stroke guidelines on antiplatelet treatment indicate that STK-06 is not 
the most suitable measure for improving patient outcomes in stroke 
treatment during the acute period.1143 1144 We believe the 
body of evidence supporting the benefits of retaining STK-06 has been 
weakened by the findings of the AHA/ASA stroke guidelines. This is 
because the strongest recommendations and quality of evidence are for 
administration of aspirin in patients with Acute Ischemic Stroke within 
24 to 48 hours after onset. Furthermore, there is only moderate quality 
evidence to continue STK-06, the measure of ischemic stroke patients 
who are prescribed or continue to take statin medication at hospital 
discharge.1145 1146 Lastly, other measures like STK-02, 
Discharged on Antithrombotic Therapy, and STK-05, Antithrombotic 
Therapy by The End of Hospital Day 2, already support our efforts to 
improve care and patient outcomes in the acute period. Taken together 
we believe that the benefit of retaining STK-06 has been reduced. Given 
these reduced benefits, we believe that the costs associated with this 
measure outweigh the benefits of retaining this measure in the Hospital 
IQR Program measure set. In order to move the program forward in the 
least burdensome manner while maintaining a parsimonious set of the 
most meaningful quality measures, we believe it is appropriate to 
remove the STK-06 eCQM. We do not have plans to modify the measure 
specifications at this point, but we appreciate commenters' suggestions 
and will take them into consideration.
---------------------------------------------------------------------------

    \1143\ Kennedy J, Hill MD, Ryckborst KJ, Eliasziw M, Demchuk AM, 
Buchan AM; FASTER Investigators. Fast Assessment of Stroke and 
Transient Ischaemic Attack to Prevent Early Recurrence (FASTER): a 
randomised controlled pilot trial. Lancet Neurol. 2007; 6:961-969. 
doi:10.1016/S1474-4422(07)70250-8.
    \1144\ Yoshimura S, Uchida K, Daimon T, Takashima R, Kimura K, 
Morimoto T; on behalf of the ASSORT Trial Investigator. Randomized 
controlled trial of early versus delayed statin therapy in patients 
with acute ischemic stroke: ASSORT Trial (Administration of Statin 
on Acute Ischemic Stroke Patient). Stroke. 2017;48:3057-3063. 
doi:10.1161/STROKEAHA.117.017623.
    \1145\ Powers WJ, Rabinstein AA, Ackerson T, Adeoye OM, 
Bambakidis NC, Becker K, Biller J, Brown M, Demaerschalk BM, Hoh B, 
Jauch EC, Kidwell CS, Leslie-Mazwi TM, Ovbiagele B, Scott PA, Sheth 
KN, Southerland AM, Summers DV, Tirschwell DL; on behalf of the 
American Heart Association Stroke Council. Guidelines for the early 
management of patients with acute ischemic stroke: 2019 update to 
the 2018 guidelines for the early management of acute ischemic 
stroke: a guideline for healthcare professionals from the American 
Heart Association/American Stroke Association. Stroke. 2019; 
50:e344-e418 doi: 10.1161/STR.0000000000000211.
    \1146\ Sandercock PA, Counsell C, Tseng MC, Cecconi E. Oral 
antiplatelet therapy for acute ischaemic stroke. Cochrane Database 
Syst Rev. 2014:CD000029. doi: 10.1002/14651858.CD000029.pub3.
---------------------------------------------------------------------------

    Comment: A commenter expressed concern about possible reporting 
burden if there is misalignment of eCQM measure options for hospitals 
reporting to CMS and The Joint Commission.
    Response: We acknowledge the comment and recognize that changing 
our measure set may cause the Hospital IQR Program to fall out of 
alignment with measure sets of other reporting systems. We seek to 
align efforts, but the Hospital IQR Program is separate and distinct 
from The Joint Commission. While we intend to continue to consider 
other quality monitoring organizations' requirements in building our 
own measure set, the decision to remove measures from the Hospital IQR 
Program is an extension of our goal under the Meaningful Measures 
Framework to continually refine the Program's measure set so as to use 
a parsimonious set of the most meaningful measures.
    After consideration of the public comments we received, we are 
finalizing our proposal as proposed.
7. Summary of Previously Finalized and New Hospital IQR Program 
Measures
a. Summary of Previously Finalized and New Hospital IQR Program 
Measures for the FY 2023 Payment Determination
    This table summarizes the previously finalized and newly finalized 
Hospital IQR Program measure set for the FY 2023 Payment Determination:
BILLING CODE 4120-01-P

[[Page 45400]]

[GRAPHIC] [TIFF OMITTED] TR13AU21.282


[[Page 45401]]


b. Summary of Previously Finalized and New Hospital IQR Program 
Measures for the FY 2024 Payment Determination
    This table summarizes the previously finalized and newly finalized 
Hospital IQR Program measure set for the FY 2024 Payment Determination 
and Subsequent Years:

[[Page 45402]]

[GRAPHIC] [TIFF OMITTED] TR13AU21.283


[[Page 45403]]


c. Summary of Previously Finalized and New Hospital IQR Program 
Measures for the FY 2025 Payment Determination
    This table summarizes the previously finalized and newly finalized 
Hospital IQR Program measure set for the FY 2025 payment determination:

[[Page 45404]]

[GRAPHIC] [TIFF OMITTED] TR13AU21.284


[[Page 45405]]


d. Summary of Previously Finalized and New Hospital IQR Program 
Measures for the FY 2026 Payment Determination
    This table summarizes the previously finalized and newly finalized 
Hospital IQR Program measure set for the FY 2026 payment determination:

[[Page 45406]]

[GRAPHIC] [TIFF OMITTED] TR13AU21.285


[[Page 45407]]


BILLING CODE 4120-01-C
8. Future Considerations
    We seek to develop a comprehensive set of quality measures to be 
available for widespread use for informed decision-making and quality 
and cost improvements through the inpatient hospital setting. 
Additionally, the emergence of COVID-19 has highlighted various impacts 
on measure outcomes and care of patients, which we believe are 
important to address. We have identified potential future measures or 
topics for future development, which we believe address areas that are 
important to stakeholders, but which are not currently covered in the 
Hospital IQR Program measure set. Therefore, we sought stakeholder 
feedback on potential new measures and future considerations for the 
Hospital IQR Program. These are discussed in more detail later in this 
section.
a. Potential Future Development and Inclusion of a 30-Day, All-Cause 
Mortality Measure for Patients Admitted With COVID-19 Infection
    We are working to learn more about the impact of the COVID-19 
infection on measure outcomes, particularly readmission and mortality 
measures, and about how the burden of the PHE for COVID-19 influences 
hospitals' ability to care for patients. To support our efforts, we are 
considering the potential future inclusion of a new hospital-level 
measure of all-cause mortality for Medicare beneficiaries admitted with 
COVID-19 infection (COVID-19 mortality measure). Such a measure would 
likely be similar to other hospital-level mortality measures currently 
in use in CMS programs, such as the AMI and Heart Failure 30-day 
mortality measures adopted for the Hospital IQR Program in the CY 2007 
OPPS/ASC final rule (71 FR 68201) and the Pneumonia 30-day mortality 
measure adopted for the Hospital IQR Program in the FY 2008 IPPS/LTCH 
PPS final rule (72 FR 47346 through 47351). These measures were later 
adopted for HVBP in the FY 2011 Hospital VBP final rule (76 FR 26497 
through 26511). For example, the measure would likely be constructed 
with the measure cohort including patients admitted with COVID-19 based 
on principal or in select cases based on secondary diagnoses, the 
outcome being mortality within a specified number of days from 
admission (such as 30 days), and risk adjustment based on clinical 
factors and constructed using hierarchical modelling. The measure would 
use administrative claims data; however, development and reporting data 
would not include the January 1, 2020 through June 30, 2020 data 
excluded in the blanket ECE issued in response to the PHE for COVID-19.
    Public reporting of this measure would not be feasible until at 
least FY 2023 due to the time required for measure development, 
testing, and production, as well as statutorily required pre-rulemaking 
(inclusion on the Measures Under Consideration list for public comment 
and review by the MAP) and notice and comment rulemaking. To inform our 
measure development, we sought public comment in the FY 2022 IPPS/LTCH 
PPS proposed rule (86 FR 25588) on the potential future inclusion of a 
COVID-19 mortality measure in the Hospital IQR Program. Specifically, 
we sought input on:
     The timeline and approach for implementing a COVID-19 
mortality measure. We seek stakeholder comment on balancing the 
priority of obtaining rapid information to improve quality of care for 
patients during the COVID-19 pandemic with the potential benefits of a 
phased approach to implementation, that might include, for example, a 
dry run, voluntary reporting, and/or confidential reporting prior to 
public reporting on the Care Compare website;
     The population (type of patients) to include in the COVID-
19 mortality measure cohort. Specifically, diagnosis codes for 
principal diagnosis of COVID-19, and other key diagnoses, such as 
pneumonia or sepsis, if COVID-19 is coded as a secondary diagnosis 
present on admission;
     The potential inclusion of both Medicare FFS beneficiaries 
and Medicare Advantage patients, as feasible;
     Risk factors we should consider adjusting for in the 
measure, such as clinical risk factors or comorbidities available in 
administrative claims data; and
     The potential stratification of measure results, as 
feasible, such as by social risk factors, geographic location, and/or 
prevalence or burden of COVID-19 disease, and how to define these 
characteristics.
    We received comments on this topic.
    Comment: Several commenters supported the future development of a 
COVID-19 mortality measure. Commenters agreed with the proposed 
approach of initially having the COVID-19 mortality measure be 
confidentially reported.
    Response: We thank commenters for their support of the potential 
inclusion of a COVID-19 mortality measure into the Hospital IQR Program 
measure set. We will continue to seek stakeholder input if this measure 
moves forward with development.
    Comment: Several commenters shared concerns regarding potential 
specifications for such a measure, particularly the cohort overlap and 
potential for risk adjustment. Many commenters stated that further 
research is needed to understand COVID-19's relationship to existing 
condition-specific and proposed measures. Specifically, a few 
commenters indicated that the cohort captured in a COVID-19 morality 
measure could potentially overlap with the Hybrid HWM measure cohort, 
making the development of a COVID-19 mortality measure redundant. 
Further, they noted that the development of a COVID-19 mortality 
measure is reactionary to the current pandemic and that there is no 
universally agreed upon standard of care for COVID-19 patients. 
Additionally, commenters stated that it may not be worth the time and 
resources to develop a COVID-19 mortality measure given the decline in 
COVID-19-related deaths. Some commenters disagreed with the development 
of a COVID-19 mortality measure expressing concerns regarding 
sufficient model risk-adjustment. These commenters were concerned about 
the ability to adopt a risk-adjustment methodology that would account 
for various underlying factors that attributed to being at high-risk 
for COVID-19 infection and the need for risk-adjustment and 
stratification methodologies to be adequately tested.
    Response: We thank the commenters for their feedback. We agree that 
the rapidly evolving nature of the COVID-19 PHE presents unique 
challenges to measurement. However, given the significant impact of 
COVID-19 on patients and hospitals, we also believe it is critical to 
measure the impact of COVID-19 on quality outcomes in order to provide 
information necessary to improve the quality of care for patients. We 
will continue to analyze additional COVID-19 data as it becomes 
available to better understand the relationship between COVID-19 and 
outcomes such as mortality.
    Comment: A few commenters recommended that a potential future 
COVID-19 mortality measure be fully vetted and endorsed by the National 
Quality Forum (NQF) before inclusion into the Hospital IQR Program.
    Response: We thank commenters for their recommendation.
    We will continue to analyze additional data as it becomes 
available. Any future proposal to implement such a measure would be 
announced through notice and comment rulemaking.

[[Page 45408]]

b. Potential Future Inclusion of a Hospital-Level, Risk Standardized 
Patient Reported Outcomes Measure Following Elective Primary Total Hip 
and/or Total Knee Arthroplasty
(1) Background
    Approximately 6 million adults aged 65 or older suffer from 
osteoarthritis in the U.S.\1147\ Osteoarthritis accounts for more than 
half of all arthritis-related hospitalizations,\1148\ and in 2013 there 
were approximately 1,023,000 hospitalizations for osteoarthritis.\1149\ 
Hip and knee osteoarthritis is one of the leading causes of disability 
among non-institutionalized adults,\1150\ and roughly 80 percent of 
patients with osteoarthritis have some limitation in mobility.\1151\ 
Elective total hip arthroplasty (THA) and total knee arthroplasty (TKA) 
are most commonly performed for degenerative joint disease or 
osteoarthritis, which affects more than 30 million Americans.\1152\ THA 
and TKA offer significant improvement in quality of life by decreasing 
pain and improving function in a majority of patients, without 
resulting in a high risk of complications or 
death.1153 1154 1155 1156 However, not all patients 
experience benefit from these procedures.\1157\ Many patients note that 
their preoperative expectations for functional improvement have not 
been met.1158 1159 1160 1161 In addition, clinical practice 
variation has been well documented in the 
U.S.,1162 1163 1164 readmission and complication rates vary 
across hospitals,1165 1166 and international experience 
documents wide hospital-level variation in patient-reported outcome 
measure results following THA and TKA.\1167\ For example, data from the 
United Kingdom demonstrates that there is a greater than 15 percent 
difference across hospitals in the proportion of patients showing 
improvement after surgery.1168 1169
---------------------------------------------------------------------------

    \1147\ Arthritis Foundation. Arthritis By the Numbers Book of 
Trusted Facts and Figures. 2018: https://www.arthritis.org/Documents/Sections/About-Arthritis/arthritis-facts-stats-figures.pdf. Accessed March 8, 2019.
    \1148\ Levit K, Stranges E, Ryan K, Elixhauser A. HCUP Facts and 
Figures, 2006: Statistics on Hospital-based Care in the United 
States. 2008. http://www.hcup-us.ahrq.gov/reports.jsp.
    \1149\ Torio CM, BJ,. National inpatient hospital costs: the 
most expensive conditions by payer, 2013. HCUP statistical brief 
#204. Healthcare Cost and Utilization Project (HCUP) Statistical 
Briefs. Rockville, MD, Agency for Healthcare Research and Quality. 
https://www.hcup-us.ahrq.gov/reports/statbriefs/sb204-Most-Expensive-Hospital-Conditions.pdf Accessed February 2021.
    \1150\ Guccione AA, Felson DT, Anderson JJ, et al. The effects 
of specific medical conditions on the functional limitations of 
elders in the Framingham Study. American journal of public health. 
1994;84(3):351-358.
    \1151\ Michaud CM, McKenna MT, Begg S, et al. The burden of 
disease and injury in the United States 1996. Population health 
metrics. 2006;4:11.
    \1152\ Centers for Disease Control and Prevention (CDC). 
Osteoarthritis (OA). https://www.cdc.gov/arthritis/basics/osteoarthritis.htm. Accessed March 8, 2019.
    \1153\ Rissanen P, Aro S, Slatis P, Sintonen H, Paavolainen P. 
Health and quality of life before and after hip or knee 
arthroplasty. The Journal of arthroplasty. 1995;10(2):169-175.
    \1154\ Wiklund I, Romanus B. A comparison of quality of life 
before and after arthroplasty in patients who had arthrosis of the 
hip joint. The Journal of bone and joint surgery. American volume. 
1991;73(5):765-769.
    \1155\ Laupacis A, Bourne R, Rorabeck C, et al. The effect of 
elective total hip replacement on health-related quality of life. 
The Journal of bone and joint surgery. American volume. 
1993;75(11):1619-1626.
    \1156\ Ritter MA, Albohm MJ, Keating EM, Faris PM, Meding JB. 
Comparative outcomes of total joint arthroplasty. The Journal of 
arthroplasty. 1995;10(6):737-741.
    \1157\ National Joint Registry. National Joint Registry for 
England and Wales 9th Annual Report 2012. available at 
www.njrcentre.org.uk: National Joint Registry;2012.
    \1158\ Suda AJ, Seeger JB, Bitsch RG, Krueger M, Clarius M. Are 
patients' expectations of hip and knee arthroplasty fulfilled? A 
prospective study of 130 patients. Orthopedics. 2010;33(2):76-80.
    \1159\ Ghomrawi HM, Franco Ferrando N, Mandl LA, Do H, Noor N, 
Gonzalez Della Valle A. How Often are Patient and Surgeon Recovery 
Expectations for Total Joint Arthroplasty Aligned? Results of a 
Pilot Study. HSS journal: The musculoskeletal journal of Hospital 
for Special Surgery. 2011;7(3):229-234.
    \1160\ Harris IA, Harris AM, Naylor JM, Adie S, Mittal R, Dao 
AT. Discordance between patient and surgeon satisfaction after total 
joint arthroplasty. The Journal of arthroplasty. 2013;28(5):722-727.
    \1161\ Jourdan C, Poiraudeau S, Descamps S, et al. Comparison of 
patient and surgeon expectations of total hip arthroplasty. PloS 
one. 2012;7(1):e30195.
    \1162\ Roos EM. Effectiveness and practice variation of 
rehabilitation after joint replacement. Current opinion in 
rheumatology. 2003;15(2):160-162.
    \1163\ Anderson FA, Jr., Huang W, Friedman RJ, Kwong LM, 
Lieberman JR, Pellegrini VD, Jr. Prevention of venous 
thromboembolism after hip or knee arthroplasty: findings from a 2008 
survey of US orthopedic surgeons. The Journal of arthroplasty. 
2012;27(5):659-666 e655.
    \1164\ American Academy of Orthopaedic Surgeons (AAOS). 
Preventing Venous Thromboembolic Disease in Patients Undergoing 
Elective Hip and Knee Arthroplasty: Evidence-Based Guideline and 
Evidence Report. 2011.
    \1165\ Suter LG, Grady JN, Lin Z, et al. 2013 Measure Updates 
and Specifications: Elective Primary Total Hip Arthroplasty (THA) 
And/OR Total Knee Arthroplasty (TKA) All-Cause Unplanned 30-Day 
Risk-Standardized Readmission Measure (Version 2.0). March 2013.
    \1166\ Suter LG, Parzynski CS, Grady JN, et al. 2013 Measures 
Update and Specifications: Elective Primary Total Hip Arthroplasty 
(THA) AND/OR Total Knee Arthroplasty (TKA) Risk-Standardized 
Complication Measure (Version 2.0). March 2013; Available at: http://qualitynet.org/.
    \1167\ Rolfson O. Patient-reported Outcome Measures and Health-
economic Aspects of Total Hip Arthroplasty: A study of the Swedish 
Hip Arthroplasty Register. 2010. https://gupea.ub.gu.se/handle/2077/23722. Accessed July 20, 2013.
    \1168\ National Health System: The Information Centre for Health 
and Social Care. HESonline Hospital Episode Statistics: Proms Data. 
http://www.hesonline.nhs.uk/Ease/ContentServer?siteID=1937&categoryID=1295, 2012.
    \1169\ Neuburger J, Hutchings A, van der Meulen J, Black N. 
Using patient-reported outcomes (PROs) to compare the providers of 
surgery: Does the choice of measure matter? Medical care. 
2013;51(6):517-523.
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    Peri-operative care and care coordination across provider groups 
and specialties have important effects on clinical 
outcomes.1170 1171 The goal of a hospital-level outcome 
measure is to capture the full spectrum of care to incentivize 
collaboration and shared responsibility for improving patients' health 
and reducing the burden of their disease. THA and TKA procedures 
provide a suitable environment for optimizing care, as there are many 
studies indicating how hospitals and providers can improve outcomes of 
their patients by addressing aspects of pre-, peri-, and postoperative 
care.1172 1173 1174 1175 1176 1177
---------------------------------------------------------------------------

    \1170\ Feng J, Novikov D, Anoushiravani A, Schwarzkopf R. Total 
knee arthroplasty: improving outcomes with a multidisciplinary 
approach. J Multidiscip Healthc. 2018;11:63-73.
    \1171\ Saufl N, Owens A, Kelly I, Merrill B, Freyaldenhouen L. A 
multidisciplinary approach to total joint replacement. Journal of 
Perianesthesia Nursing. 2007;22(3):195.
    \1172\ Monticone M, Ferrante S, Rocca B, et al. Home-based 
functional exercises aimed at managing kinesiophobia contribute to 
improving disability and quality of life of patients undergoing 
total knee arthroplasty: a randomized controlled trial. Archives of 
physical medicine and rehabilitation. 2013;94(2):231-239.
    \1173\ Brown K, Topp R, Brosky JA, Lajoie AS. Prehabilitation 
and quality of life three months after total knee arthroplasty: A 
pilot study. Perceptual and motor skills. 2012;115(3):765-774.
    \1174\ Choong PF, Dowsey MM, Stoney JD. Does accurate anatomical 
alignment result in better function and quality of life? Comparing 
conventional and computer-assisted total knee arthroplasty. The 
Journal of arthroplasty. 2009;24(4):560-569.
    \1175\ Galea MP, Levinger P, Lythgo N, et al. A targeted home- 
and center-based exercise program for people after total hip 
replacement: A randomized clinical trial. Archives of physical 
medicine and rehabilitation. 2008;89(8):1442-1447.
    \1176\ McGregor AH, Rylands H, Owen A, Dore CJ, Hughes SP. Does 
preoperative hip rehabilitation advice improve recovery and patient 
satisfaction? The Journal of arthroplasty. 2004;19(4):464-468.
    \1177\ Moffet H, Collet JP, Shapiro SH, Paradis G, Marquis F, 
Roy L. Effectiveness of intensive rehabilitation on functional 
ability and quality of life after first total knee arthroplasty: A 
single-blind randomized controlled trial. Archives of physical 
medicine and rehabilitation. 2004;85(4):546-556.
---------------------------------------------------------------------------

    Due to the absence of large scale and uniformly collected patient-
reported outcome (PRO) data available from patients undergoing elective 
primary THA/TKA, in November 2015 CMS established an incentivized, 
voluntary PRO data collection opportunity within the Comprehensive Care 
for Joint Replacement (CJR) model to support measure development. 
Requirements for successful submission of PRO data for eligible 
elective primary THA/TKA procedures were identified by CMS in the 2015 
CJR final rule (80 FR 73274).

[[Page 45409]]

This Hospital-Level, Risk-Standardized Patient-Reported Outcomes 
Following Elective Primary Total Hip and/or Total Knee Arthroplasty 
performance measure (THA/TKA) (THA/TKA PRO-PM) was developed and tested 
using PRO and risk variable data collected from and submitted by CJR 
participant hospitals. PRO data from the first few performance years 
for the CJR model revealed hospital-level variation in these outcomes 
across U.S. hospitals, although the full degree and extent of variation 
is unknown.
    In October 2017, we launched the Meaningful Measures Framework to 
identify high priority areas for quality measurement that improve 
patient outcomes while also reducing burden on providers.\1178\ The 
initiative captures the agency's vision in evaluating and streamlining 
regulations with a goal to reduce unnecessary cost and burden, increase 
efficiencies, and improve beneficiary experience. The scope of the 
Meaningful Measures Framework continues to evolve as the health care 
environment continues to change. Meaningful Measures 2.0 is currently 
underway and aims to promote better collection and integration of 
patients' voices by incorporating PRO measures that are embedded into 
the clinical workflow, are easy to use, and reduce reporting 
burden.\1179\ The THA/TKA PRO-PM is fully developed aligns with these 
Meaningful Measures 2.0 goals.
---------------------------------------------------------------------------

    \1178\ CMS' Meaningful Measures Framework can be found at: 
https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/QualityInitiativesGenInfo/MMF/General-info-Sub-Page.
    \1179\ https://www.cms.gov/meaningful-measures-20-moving-measure-reduction-modernization.
---------------------------------------------------------------------------

    Elective THA/TKAs are important, effective procedures performed on 
a broad population, and the patient outcomes for these procedures (such 
as pain, mobility, and quality of life) can be measured in a 
scientifically sound 
way,1180 1181 1182 1183 1184 1185 1186 1187 1188 1189 1190 1191 1192
 are influenced by a range of improvements in 
care,1193 1194 1195 1196 1197 1198 1199 1200 and demonstrate 
hospital-level variation even after patient case mix 
adjustment.1201 1202 Further, THA/TKA procedures are 
specifically intended to improve function and reduce pain, making PROs 
a meaningful outcome metric to assess.\1203\
---------------------------------------------------------------------------

    \1180\ Alviar MJ, Olver J, Brand C, Hale T, Khan F. Do patient-
reported outcome measures used in assessing outcomes in 
rehabilitation after hip and knee arthroplasty capture issues 
relevant to patients? Results of a systematic review and ICF linking 
process. J Rehabil Med. 2011;43(5):374-381.
    \1181\ Alviar MJ, Olver J, Brand C, et al. Do patient-reported 
outcome measures in hip and knee arthroplasty rehabilitation have 
robust measurement attributes? A systematic review. J Rehabil Med. 
2011;43(7):572-583.
    \1182\ Bauman S, Williams D, Petruccelli D, Elliott W, de Beer 
J. Physical activity after total joint replacement: a cross-
sectional survey. Clin J Sport Med. 2007;17(2):104-108.
    \1183\ Collins NJ, Roos EM. Patient-reported outcomes for total 
hip and knee arthroplasty: Commonly used instruments and attributes 
of a ``good'' measure. Clin Geriatr Med. 2012;28(3):367-394.
    \1184\ Jones CA, Beaupre LA, Johnston DW, Suarez-Almazor ME. 
Total joint arthroplasties: Current concepts of patient outcomes 
after surgery. Rheum Dis Clin North Am. 2007;33(1):71-86.
    \1185\ Lau RL, Gandhi R, Mahomed S, Mahomed N. Patient 
satisfaction after total knee and hip arthroplasty. Clin Geriatr 
Med. 2012;28(3):349-365.
    \1186\ Liebs TR, Herzberg W, Ruther W, Russlies M, Hassenpflug 
J, Multicenter Arthroplasty Aftercare Project M. Quality-adjusted 
life years gained by hip and knee replacement surgery and its 
aftercare. Archives of physical medicine and rehabilitation. 
2016;97(5):691-700.
    \1187\ Montin L, Leino-Kilpi H, Suominen T, Lepisto J. A 
systematic review of empirical studies between 1966 and 2005 of 
patient outcomes of total hip arthroplasty and related factors. J 
Clin Nurs. 2008;17(1):40-45.
    \1188\ Papalia R, Del Buono A, Zampogna B, Maffulli N, Denaro V. 
Sport activity following joint arthroplasty: A systematic review. Br 
Med Bull. 2012;101:81-103.
    \1189\ Rolfson O, Rothwell A, Sedrakyan A, et al. Use of 
patient-reported outcomes in the context of different levels of 
data. J Bone Joint Surg Am. 2011;93 Suppl 3:66-71.
    \1190\ Suter LG, Potteiger J, Cohen DB, Lin Z, Drye EE, Bernheim 
SM. Environmental Scan/Literature Review: Total Hip and Total Knee 
Arthroplasty Patient-Reported Outcome Measure. Report prepared for 
Centers for Medicare & Medicaid Services. 2012.
    \1191\ Thorborg K, Roos EM, Bartels EM, Petersen J, Holmich P. 
Validity, reliability and responsiveness of patient-reported outcome 
questionnaires when assessing hip and groin disability: A systematic 
review. BJSM online. 2010;44(16):1186-1196.
    \1192\ White D, Master H. Patient Reported Measures of Physical 
Function in Knee Osteoarthritis. Rheum Dis Clin North Am. 
2016;42(2):239-252.
    \1193\ Brown K, Topp R, Brosky JA, Lajoie AS. Prehabilitation 
and quality of life three months after total knee arthroplasty: A 
pilot study. Perceptual and motor skills. 2012;115(3):765-774.
    \1194\ Choong PF, Dowsey MM, Stoney JD. Does accurate anatomical 
alignment result in better function and quality of life? Comparing 
conventional and computer-assisted total knee arthroplasty. The 
Journal of arthroplasty. 2009;24(4):560-569.
    \1195\ Galea MP, Levinger P, Lythgo N, et al. A targeted home- 
and center-based exercise program for people after total hip 
replacement: A randomized clinical trial. Arch Phys Med Rehabil. 
2008;89(8):1442-1447.
    \1196\ Kim K, Anoushiravani A, Chen K, et al. Perioperative 
Orthopedic Surgical Home: Optimizing Total Joint Arthroplasty 
Candidates and Preventing Readmission. Journal of Arthroplasty. 
2019;34(7):S91-S96.
    \1197\ McGregor AH, Rylands H, Owen A, Dore CJ, Hughes SP. Does 
preoperative hip rehabilitation advice improve recovery and patient 
satisfaction? The Journal of arthroplasty. 2004;19(4):464-468.
    \1198\ Moffet H, Collet JP, Shapiro SH, Paradis G, Marquis F, 
Roy L. Effectiveness of intensive rehabilitation on functional 
ability and quality of life after first total knee arthroplasty: A 
single-blind randomized controlled trial. Arch Phys Med Rehabil. 
2004;85(4):546-556.
    \1199\ Monticone M, Ferrante S, Rocca B, et al. Home-based 
functional exercises aimed at managing kinesiophobia contribute to 
improving disability and quality of life of patients undergoing 
total knee arthroplasty: A randomized controlled trial. Arch Phys 
Med Rehabil. 2013;94(2):231-239.
    \1200\ Walters M, Chambers M, Sayeed Z, Anoushiravani A, El-
Othmani M, Saleh K. Reducing Length of Stay in Total Joint 
Arthroplasty Care. Orthopedic Clinics of North America. 
2016;47(4):653-660.
    \1201\ Bozic KJ, Grosso LM, Lin Z, et al. Variation in hospital-
level risk-standardized complication rates following elective 
primary total hip and knee arthroplasty. JBJS. 2014;96(8):640-647.
    \1202\ M[auml]kel[auml] KT, Peltola M, Sund R, Malmivaara A, 
H[auml]kkinen U, Remes V. Regional and hospital variance in 
performance of total hip and knee replacements: A national 
population-based study. Annals of medicine. 2011;43(sup1):S31-S38.
    \1203\ Liebs T, Herzberg W, Gluth J, et al. Using the patient's 
perspective to develop function short forms specific to total hip 
and knee replacement based on WOMAC function items. Bone Joint J. 
2013;95(B):239-243.
---------------------------------------------------------------------------

(2) Overview of Measure
    The THA/TKA PRO-PM reports the hospital-level risk-standardized 
improvement rate (RSIR) in PROs following elective primary THA/TKA for 
Medicare FFS beneficiaries aged 65 years and older.
    Substantial clinical improvement would be measured by achieving a 
pre-defined improvement in score on joint-specific PRO instruments, 
measuring hip or knee pain and functioning, from the preoperative 
assessment (data collected 90 to 0 days before surgery) to the 
postoperative assessment (data collected 300 to 425 days following 
surgery). For additional details regarding the measure specifications, 
we refer readers to the Patient-Reported Outcomes (PROs) Following 
Elective Primary Total Hip and/or Total Knee Arthroplasty: Hospital-
Level Performance Measure--Measure Methodology Report, available on the 
CMS website at: https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/HospitalQualityInits/Measure-Methodology).
    Several stakeholder groups were engaged throughout the development 
process of the THA/TKA PRO-PM, as required in the Measures Management 
System (MMS) Blueprint,\1204\ including a Technical Advisory Group 
(TAG), a Patient Working Group, and a national, multi-stakeholder 
Technical Expert Panel (TEP) consisting of a diverse set of 
stakeholders, including providers and patients. These groups were 
convened by the measure developer under contract with CMS and who 
provided feedback on the measure concept,

[[Page 45410]]

outcome, cohort, risk model variables, reporting results, and data 
collection. We also received multiple public comments used to support 
the development of this measure in the 2015 CJR final rule (80 FR 
73274).
---------------------------------------------------------------------------

    \1204\ CMS Measures Management System Blueprint (Blueprint v 
16.0). CMS. 2020. Available at: https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/MMS/Downloads/Blueprint.pdf.
---------------------------------------------------------------------------

    The THA/TKA PRO-PM (MUC20-0003) was included in the publicly 
available ``2020 Measures Under Consideration List.'' \1205\ The MAP 
supported the measure, as referenced in the 2020-2021 Final 
Recommendations report to HHS and CMS.\1206\ This measure was submitted 
for NQF review in March 2020.\1207\ In November 2020, the NQF endorsed 
the THA/TKA PRO-PM (NQF #3559).
---------------------------------------------------------------------------

    \1205\ 2020 Measures Under Consideration List. Available at 
https://www.cms.gov/media/492911.
    \1206\ MAP 2020-2021 Considerations for Implementing Measures 
Final Report--Clinicians, Hospitals, and PAC-LTC. NQF. 2021. 
Available at: https://www.qualityforum.org/Publications/2021/03/MAP_2020-2021_Considerations_for_Implementing_Measures_Final_Report_-_Clinicians,_Hospitals,_and_PAC-LTC.aspx.
    \1207\ NQF Quality Positioning System. Available at https://www.qualityforum.org/QPS.
---------------------------------------------------------------------------

(3) Data Sources
    The THA/TKA PRO-PM uses four sources of data for the calculation of 
the measure: (1) PRO data; (2) claims data; (3) Medicare enrollment and 
beneficiary data; and (4) U.S. Census Bureau survey data. The measure 
uses PRO and limited patient-level risk factor data collected by 
hospitals preoperatively and postoperatively. The measure includes two 
joint-specific PRO instruments--the Hip dysfunction and Osteoarthritis 
Outcome Score for Joint Replacement (HOOS, JR) for completion by THA 
recipients and the Knee injury and Osteoarthritis Outcome Score for 
Joint Replacement (KOOS, JR) for completion by TKA recipients--from 
which scores are used to assess substantial clinical improvement. 
Additionally, hospitals submit either the Patient-Reported Outcomes 
Measurement Information System (PROMIS)-Global or the Veterans RAND 12-
Item Health Survey (VR-12), from which Mental Health subscale 
preoperative scores and used for risk adjustment. Claims data are used 
to identify eligible elective primary THA/TKA procedures for the 
measure cohort and additional variables for risk adjustment and 
accounting for response bias, including patient demographics and 
clinical comorbidities up to 12 months prior to surgery. The Medicare's 
Enrollment Database (EDB) identifies Medicare FFS enrollment and race, 
and the Master Beneficiary Summary File allows for determination of 
dual eligibility status. Demographic information from the U.S. Census 
Bureau's American Community Survey \1208\ allows for derivation of the 
Agency for Healthcare Research and Quality (AHRQ) socioeconomic status 
(SES) index score.
---------------------------------------------------------------------------

    \1208\ American Community Survey, available at: https://www.census.gov/programs-surveys/acs.
---------------------------------------------------------------------------

(4) Outcome
    In response to extensive feedback from orthopedic experts to 
capture PRO data for the many patients whose ``12-month'' postoperative 
appointments actually occur in months 10 to 14 (300 to 425 days) 
following surgery, the THA/TKA PRO-PM was modified slightly to reflect 
a longer postoperative assessment period. Specifically, the 
postoperative assessment period was extended from 270 to 365 days in 
initial development to 300 to 425 days.
    The measure outcome (numerator) is the risk-standardized proportion 
of patients undergoing elective primary THA/TKA who meet or exceed a 
substantial clinical improvement threshold between preoperative and 
postoperative assessments on two joint-specific PRO instruments. The 
measure outcome will assess patient improvement in PROs using the HOOS, 
JR following elective primary THA and the KOOS, JR following elective 
primary TKA. PRO data will be collected 90 to zero days prior to 
surgery and 300 to 425 days following surgery. These PRO collection 
periods align with typical patient visits prior to and following 
surgery.
    The measure outcome defines patient improvement as a binary outcome 
(``Yes''/``No'') of meeting or exceeding the pre-defined improvement 
threshold between preoperative and postoperative assessments on the 
joint-specific PRO instruments: Specifically, for THA patients, meeting 
or exceeding the threshold of 22 points on the HOOS, JR and, for TKA 
patients, meeting or exceeding the threshold of 20 points on the KOOS, 
JR.
(5) Cohort
    The measure cohort (denominator) is Medicare FFS beneficiaries aged 
65 years and older undergoing elective primary THA/TKA procedures as 
inpatients in acute care hospitals. We are aware that elective primary 
THA/TKA procedures are increasingly occurring in hospital outpatient 
and ambulatory surgical center settings and we are evaluating options 
to address measurement of those procedures and settings.
(6) Inclusion and Exclusion Criteria
    The THA/TKA PRO-PM includes patients who are--
     Enrolled in Medicare FFS Part A and Part B for the 12 
months prior to the date of the index admission and enrolled in Part A 
during the index admission;
     Aged 65 or older; and
     Discharged alive from non-Federal short-term acute care 
hospital.
    The measure includes only elective primary THA/TKA procedures 
(patients with fractures and revisions are not included).
    The measure excludes patients with staged procedures, defined as 
more than one elective primary THA or TKA performed on the same patient 
during distinct hospitalizations during the measurement period.
(7) Risk Adjustment
    The risk model was developed with clinically relevant risk 
variables identified by public comment in the 2015 CJR final rule (80 
FR 73274), the TEP, and expert orthopedic consultants and supported by 
empirical analyses, and includes risk variables collected with PRO data 
by hospitals in the CJR model. The preoperative score of the Mental 
Health subscale from two global PRO instruments (the PROMIS-Global or 
the VR-12) collected with CJR PRO data is included as a risk variable. 
In addition, the risk model includes a validated, one-question patient-
reported assessment of health literacy--the Single Item Literacy 
Screener questionnaire.
    Furthermore, since poorly or incompletely collected PRO data may be 
asymmetrically distributed across lower socioeconomic or disadvantaged 
populations and thus potentially affect measure scores, the measure 
developer used empirical analyses and stakeholder input to develop an 
approach to account for response bias in the measure calculation. The 
approach uses comorbidities and social risk factors--including non-
White race, dual eligibility, and AHRQ SES index lowest quartile--to 
predict response to the PRO survey. Weighting the responders based on 
their likelihood of response (given their patient characteristics) 
helps reduce non-response bias when calculating the RSIR.
    For additional details regarding the approach to risk adjustment 
and the full risk model, we refer readers to the Patient-Reported 
Outcomes (PROs) Following Elective Primary Total Hip and/or Total Knee 
Arthroplasty: Hospital-Level Performance Measure--Measure Methodology 
Report), available at: https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/HospitalQualityInits/Measure-Methodology).

[[Page 45411]]

(8) Measure Calculation
    The hospital-level THA/TKA PRO-PM measure result is calculated by 
aggregating all patient-level results across the hospital. At the 
hospital level, this measure would be calculated and presented as a 
RSIR, producing a performance measure per hospital which accounts for 
patient case mix, addresses potential non-response bias, and represents 
a measure of quality of care following primary elective THA and TKA. 
Response rates for PRO data for this measure would be calculated as the 
percentage of elective primary THA or TKA procedures for which complete 
and matched preoperative and postoperative PRO data have been submitted 
divided by the total number of eligible THA or TKA procedures performed 
at each hospital and may be reported with measure results for 
transparency.
    As described in section IX.C.8.b.(7). of the preamble of this final 
rule, the measure developer under contract with CMS convened several 
stakeholder groups, including providers and patients, throughout 
measure development. Providers noted that there was a need for 
sufficient time and resources for initial set up and resources needed 
to collect data either internally or externally. As a result, we are 
considering a phased implementation approach for this measure. For 
example, similar to other novel measures recently adopted, such as the 
Hybrid HWR measure finalized for inclusion in the Hospital IQR Program 
in the FY 2020 IPPS/LTCH PPS final rule (84 FR 42465), we are 
considering first allowing hospitals to submit their data voluntarily 
before it would become mandatory for reporting as part of the Hospital 
IQR Program.
    We are considering three different implementation approaches. One 
approach would be that hospitals collect their own data and send to CMS 
for measure calculation. Another approach would be that collection 
would occur by an external entity, such as through a vendor or CMS. 
Lastly, hospitals could collect their own data and send their data to a 
registry or other entity for storage, standardization, and submission 
to CMS for measure calculation.
    We received feedback from patients and providers that they would 
like to utilize their PRO results as part of the shared decision-making 
process and had a desire for flexible data collection modes (telephone, 
paper, electronic). Patients were more willing to report data if they 
knew the survey was from their provider, they understood the importance 
and use of the survey, and they had access to their own survey 
responses.
    Providers expressed concerns over survey fatigue, resources needed 
to collect data, and integration with EHRs. We understand the 
importance of aligning data collection and data submission efforts for 
hospital reporting of PRO data and providing a way for hospitals to 
integrate the collection into EHRs so the PRO data are available at the 
point of care.
    In the FY 2022 IPPS/LTCH PPS proposed rule (86 FR 25588 through 
25592), we invited public comment on the possible future inclusion of 
the THA/TKA PRO-PM in the Hospital IQR Program.
    We also invited public comment on other aspects of the measure 
related to future implementation. Specifically, we sought public 
comment on the following:
     A phased approach to implementation, including voluntary 
followed by mandatory reporting, and the timing/duration of such 
reporting periods.
     The mechanism of data collection and submission, including 
anticipated barriers and solutions to data collection and submission.
     The required thresholds for the quantity of data (that is, 
number of completed PRO instruments) hospitals should submit for 
voluntary and mandatory reporting.
     The application of the THA/TKA PRO-PM measure to settings 
such as hospital outpatient departments, ambulatory surgical centers, 
or hospital inpatient procedures followed by observation stays, such as 
through aligned PRO-PMs across the relevant measurement programs; CMS 
recognizes that over time, more THA and TKA procedures may be performed 
outside of the inpatient setting; as finalized in the CY 2021 OPPS/ASC 
final rule, THA and TKA procedures have been removed from CMS' 
inpatient only (IPO) procedure list (82 FR 59385, 84 FR 61355) and 
added to the ASC covered procedures list (CPL) (84 FR 61388, 85 FR 
86146).
    We received comments on these topics.
    Comment: Many commenters expressed support for the future inclusion 
of the THA/TKA PRO-PM in the Hospital IQR Program. Specifically, a 
commenter agreed with the usefulness of a PRO-PM as it captures the 
full spectrum of a patient's care. A commenter noted that PRO-PMs are 
essential to determining if value-based payment models are measuring 
and incentivizing improvements in outcomes important to patients. 
Several commenters highlighted the importance of joint-specific PROMs 
to effectively assess a patient's postoperative goals, demonstrate the 
effectiveness of the patient care delivered, and provide insight to 
quality improvement barriers. A few commenters stated that PROs for 
THA/TKA ensures that patients are experiencing functional improvement 
as a result of their surgery as interpreted by the patients' 
themselves.
    Response: We thank the commenters for their support.
    Comment: A few commenters recommended that THA/TKA PRO-PM should be 
at the physician level. A commenter recommended PROMs be included in 
other non-joint specific conditions as they are appreciated by patients 
and providers. A commenter noted the importance of the patient's 
perspective on survey timing. A commenter stated that we should 
consider additional exclusion criterions such as stroke, cardiac 
events, and dementia during the measurement window, as these conditions 
will negatively impact outcomes and PROM scores. A few commenters 
recommended we consider incentivizing THA/TKA PRO-PM data collection to 
increase collection rates. A commenter noted we should further analyze 
survey response rates. A commenter recommended we consider the 
potential long-term impact on patients and hospitals as more PRO-PMs 
are implemented. A few commenters suggested that we publicly report 
improvement scores on Care Compare, to encourage hospitals to 
demonstrate functional improvements of patients. A commenter stated 
that we should wait until the public health emergency is over to 
implement a PRO-PM in the Hospital IQR Program.
    Response: We thank the commenters for their support of the THA/TKA 
PRO-PM and will take all recommendations and input under consideration. 
With regard to the comment on PROMs for non-joint specific conditions, 
we agree that PROMs are an important aspect of patient-centered 
healthcare and will continue to emphasize the patient voice as 
prioritized under our Meaningful Measures 2.0 Framework. Meaningful 
Measures 2.0 is currently underway and aims to promote better 
collection and integration of patients' voices by incorporating PRO 
measures that are embedded into the clinical workflow, are easy to use, 
and reduce reporting burden.\1209\ Regarding survey response

[[Page 45412]]

rates, we will continue to engage stakeholders to address response 
rates concerns. We will also continue to monitor the impact of the 
COVID-19 pandemic on potential data reporting.
---------------------------------------------------------------------------

    \1209\ https://www.cms.gov/meaningful-measures-20-moving-measure-reduction-modernization.
---------------------------------------------------------------------------

    Comment: Commenters expressed concern that the inclusion of the 
THA/TKA PRO-PM in the Hospital IQR Program could create burden at the 
hospital and provider level. A commenter stated that the measure would 
cause significant financial burden to hospitals to collect pre- and 
postoperative assessments. A few commenters inquired on the additional 
staff resources required and the impact on clinical workflows this 
measure will have. Several commenters requested CMS consider the data 
collection, reporting, and implementation burden on providers and 
hospitals; many cited hospitals' experience in the CJR model as 
evidence supporting the challenges associated with implementing PRO-
PMs. A commenter also stated that the measure risk adjustment 
variables, in particular, create additional workload as they must be 
collected 0-90 days preoperatively. Several commenters noted that 
response rates are a challenge to applying PRO measurement in routine 
clinical care. A few commenters expressed concerns with survey fatigue, 
highlighting the impact on response rates a PRO-PM may have on other 
measures, such as the HCAHPS Survey, because patients have so many 
surveys to fill out. A commenter suggested that we release feedback on 
the voluntary reported measure under the CJR model before adopting it 
into the Hospital IQR Program's measure set.
    Response: With respect to the burden imposed by potential 
implementation of this measure, we are carefully considering public 
comments and are seeking to advance patient-centered measurement with 
as little burden as possible to providers and patient. While PRO-PMs 
require providers to integrate data collection into clinical workflows, 
this integration provides opportunity for PROs to inform clinical 
decision making and benefits patients by engaging them in discussions 
about potential outcomes. We thank commenters for their suggestions and 
will take them into consideration. Further, the PROM instruments used 
to calculate pre- and postoperative scores for this THA/TKA PRO-PM were 
carefully considered, with extensive stakeholder input from clinicians, 
to be low burden and joint specific. The clinicians felt, and data 
demonstrated, that joint-specific functional status tools such as the 
HOOS, JR and KOOS, JR are more relevant for clinical decision making 
and are more responsive than PROMs that are not as specific. In 
addition, this measure was developed with extensive input from 
patients, who indicated strong support for a PRO-PM following elective 
primary THA and TKA. We will continue to evaluate data collection 
burden for the THA/TKA PRO-PM and will take this feedback into 
consideration as we shape future measures.
    Regarding survey fatigue, we designed the measure to illuminate a 
patient's pain and functional status before and after a THA or TKA, 
which is different than other surveys such as HCAHPS that captures 
patient experience. With regard to the comment that the THA/TKA PRO-PM 
may have a reporting impact on other measures, such as HCAHPS, we 
anticipate a minimal impact to other measures as the THA/TKA PRO-PM's 
eligible population is procedure-specific which reduces the likelihood 
of the same patient receiving the HCAHPS and PROMs. Additionally, the 
THA/TKA PRO-PM preoperative assessment (90 to 0 days before surgery) 
and postoperative assessment (300 to 425 days following surgery) 
timeframe is different than HCAHPS, which is two weeks after a hospital 
visit.
    Comment: A few commenters supported the extension of the 
postoperative assessment from 270-365 to 300-425 days. Commenters noted 
that this timeframe assesses long-term impacts of the procedure and 
demonstrates that we can develop and implement measures capturing 
quality beyond 90 days following surgery. A commenter expressed concern 
with collecting PRO data 300 to 425 days following surgery and 
recommended the postoperative data collection window be 12 to 16 weeks 
to increase response rates.
    Response: In development of the THA/TKA PRO-PM, the measure 
developer conducted extensive stakeholder engagement to inform the 
postoperative assessment window. This timeframe allows for full 
recovery from both THA and TKA and increases opportunity for PRO 
response.
    Comment: Several commenters expressed concern about the THA/TKA 
PRO-PM data collection and submission and offered potential solutions. 
Several commenters recommended CMS allow the use of Qualified Clinical 
Data Registries (QCDRs), such as the American Joint Replacement 
Registry (AJRR), as an efficient mechanism for data submission of the 
THA/TKA PRO-PM. Commenters also cited the benefit of utilizing 
registries with integrated PROM collection tools to reduce the burden 
for hospitals to collect PROM data. A commenter suggested to have the 
flexibility of either self-reporting or choosing a registry to reduce 
administrative burden rather than being forced to use one registry over 
another.
    Response: We thank commenters for highlighting potential solutions 
for PRO data collection and submission and will consider these 
recommendations in planning for any potential future proposal of this 
measure.
    Comment: Several commenters recommended we consider disadvantaged 
populations within the measure specifications and implementation. A 
commenter recommended that the response bias approach be critically 
evaluated to ensure consideration of language and other socioeconomic 
barriers that may impact survey completion and response. Another 
commenter suggested we consider the impact that PRO-PMs may have on 
vulnerable populations, including people with limited health literacy, 
before the measure is implemented in a CMS program. Another commenter 
recommended that we compare the patient characteristics, including 
socioeconomic demographics, between responders and non-responders and 
requested we consider alternate approaches to accounting for response 
bias. A commenter noted surprise that the non-response bias had little 
impact on the measure results and recommended additional analyses to 
empirically test whether individual hospitals results changed based on 
weighting for non-response bias. Another commenter recommended efforts 
be put into place to encourage lower socioeconomic and disadvantaged 
populations to complete surveys and ensure they have the ability to 
complete them. A commenter recommended we consider stratifying the 
measure results by quintiles of rates of dual eligible status, similar 
to the approach taken in the payment calculation of the HRRP. A few 
commenters noted the importance of risk adjustment in outcome measures, 
including PRO-PMs. A commenter specifically noted support for the 
continued collection of the Veterans RAND 12 Item Health Survey (VR-12) 
or Patient-Reported Outcomes Measurement Information System Scale--
Global Health Fixed Length Short Form (PROMIS-10) as well as the other 
patient-reported questionnaires for back pain, other joint pain, and 
health literacy, as are currently collected in the component of CJR 
that includes voluntary PRO and risk variable data collection.\1210\ A 
commenter

[[Page 45413]]

recommended we consider dual eligibility in the risk model. Finally, a 
few commenters noted the importance of incorporation of socioeconomic 
factors in the risk adjustment model during in measure implementation 
to avoid unintended consequences, including intentionally choosing or 
avoiding patients based on their health status.
---------------------------------------------------------------------------

    \1210\ Centers for Medicare & Medicaid Services (CMS), HHS, 
Medicare Program; Comprehensive Care for Joint Replacement Payment 
Model for Acute Care Hospitals Furnishing Lower Extremity Joint 
Replacement Services. Final Rule With Comment Period. Federal 
Register, 2015. 80: p. 73494-73495.
---------------------------------------------------------------------------

    Response: We agree with commenters that considering the unique 
experience of populations with social risk factors is important. The 
approach used in development for potential non-response bias (inverse 
probability weighting) considers patient characteristics, including 
non-white race, dual eligibility, and the AHRQ SES index score. The 
AHRQ SES index score considers aspects of socioeconomic status, and is 
computed using US census data and considers factors including zip code, 
median household income, percentage of persons below the Federal 
poverty line, unemployment, education, property value, and percentage 
of persons in crowded households.\1211\ Although preferred language 
spoken is not a variable currently included in the non-response bias 
approach, the potential measure includes health literacy in the risk 
model. We appreciate the comments regarding the importance of 
considering disadvantaged populations within the measure specifications 
and implementation and we will continue to assess the impact of social 
risk factors on the potential measure and response rates over time.
---------------------------------------------------------------------------

    \1211\ Chapter 1: Creation of New Race-Ethnicity Codes and 
Socioeconomic Status (SES) Indicators for Medicare Beneficiaries. 
January 2008. Agency for Healthcare Research and Quality, Rockville, 
MD. http://archive.ahrq.gov/research/findings/final-reports/medicareindicators/medicareindicators1.html.
---------------------------------------------------------------------------

    Regarding non-response bias and the measure results, as noted in 
the Measure Methodology Report,\1212\ the comparison of hospital RSIRs 
for risk-adjusted model of SCB improvement with and without stabilized 
inverse probability weighting suggests that the results are not 
sensitive to the weighting adjustment. However, due to the high 
proportion of non-responders, we considered it important to account for 
the differences in characteristics of responders and non-responders 
found in the literature and empirically in the development testing 
data. Given non-response bias may be a factor for the THA/TKA PRO-PM 
due to associations with non-response including social risk and health 
status, we recommend continued inclusion of response bias adjustment 
for the potential measure results and will consider the recommended 
analysis in the future.
---------------------------------------------------------------------------

    \1212\ Balestracci K, Suter LG, Lin Z, Kurkurina et al. 2021 
Patient-Reported Outcomes (PROs) Following Elective Primary Total 
Hip and/or Total Knee Arthroplasty: Hospital-Level Performance 
Measure Methodology Report (Version 1.0). March 2021. https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/HospitalQualityInits/Measure-Methodology.
---------------------------------------------------------------------------

    As discussed in section IX.B. of this final rule, we are committed 
to measuring and improving health equity and addressing social risk 
factors in quality measurement. Regarding dual eligibility, the measure 
developer, under contract to CMS, performed an additional assessment of 
the impact of social risk as captured by dual eligibility, the AHRQ SES 
Index (socioeconomic status), and non-white race, after the risk model 
was finalized. The addition of each of these three social risk 
variables provided no statistically significant change to the measure's 
model performance, variable coefficients, or the model outcome. These 
variables were not included in the present model, but the developer 
believes future assessment in reevaluation will be important. These 
social risk variables were, however, statistically significantly 
associated with response to PRO surveys--whether patient-reported 
outcomes were obtained for patients undergoing primary elective THA/
TKA--and so were included in the calculation of stabilized inverse 
probability weights used to account for potential response bias. We 
will continue to assess the impact of social risk factors on this 
potential measure's results and response rates over time.
    Comment: Several commenters supported the future inclusion of the 
THA/TKA PRO-PM as part of mandatory reporting in the Hospital IQR 
Program. Commenters expressed a desire for a phased implementation 
approach of voluntary prior to mandatory reporting to allow hospitals 
to have adequate time to incorporate PROM collection in their workflows 
and to integrate collection into their EHR system. A commenter 
mentioned that smaller facilities will need several years to coordinate 
the collection and reporting of the data required for this measure.
    Response: We thank commenters for their support of future inclusion 
in the Hospital IQR Program and recommendations for a phased 
implementation approach. We discuss potential future inclusion of this 
measure now to allow more time and notice for providers to make the 
necessary enhancements to their clinical workflows. Any proposals 
regarding inclusion of the potential measure in a CMS program would be 
announced via notice and comment rulemaking.
    Comment: A few commenters recommended we lower the THA/TKA PRO-PM 
reporting thresholds, as the 80 percent reporting threshold for the 
THA/TKA PROMs in the CJR payment model is too high and some hospitals 
are unable to meet it due to difficulty in collecting PROMs. A 
commenter expressed concern with gaming that can be caused through 
selective reporting. Another commenter recommended we consider a 
minimum number of cases a year that hospitals need to report.
    Response: We thank commenters for their feedback. We will consider 
applying feedback received from these stakeholders to any future 
reporting of this measure.
    Comment: Several commenters expressed support for the implementing 
the measure across different quality programs and settings. 
Specifically, a commenter encouraged we implement consistent PROM 
reporting requirements across different quality programs, including for 
outpatient and physician quality reporting programs. Another commenter 
urged swift implementation of the measure to the Hospital Value-Based 
Purchasing (VBP) Program. Several commenters expressed support for the 
expansion of the THA/TKA PRO-PM to additional care settings such as 
hospital outpatient departments and ambulatory surgical centers. A 
commenter expressed appreciation of CMS' potential application of the 
PRO-PM in other healthcare settings, noting that the measure should be 
site agnostic and include home care or outpatient physical therapy 
settings. A few commenters encouraged and praised CMS for their 
mindfulness and forward thinking in monitoring the changes in 
healthcare delivery settings, noting the migration of services to the 
ambulatory setting. A commenter noted that the expansion of this 
measure to other settings will allow for transparency of provider 
quality in this important measurement area. A few commenters suggested 
stratifying data based on the site of service (inpatient, outpatient 
and ASCs). A commenter added that additional time may be necessary for 
ASCs and outpatient settings to develop the policies/procedures to 
collect and report the data.
    Response: We thank commenters for their support of expanding this 
measure to other programs and settings. We agree

[[Page 45414]]

that monitoring physician practice trends is important. We will 
consider these recommendations in planning for any future proposal of 
this measure.
    We will continue to consider the public comments we received and 
any future stakeholder input on the potential future inclusion of the 
THA/TKA PRO-PM in the Hospital IQR Program. Any proposals regarding 
inclusion of the measure in a CMS program would be announced via notice 
and comment rulemaking.
c. Potential Future Efforts To Address Health Equity in the Hospital 
IQR Program
    Significant and persistent inequities in health care outcomes exist 
in the United States.\1213\ Inequities in the social determinants of 
health affecting these groups, such as poverty and healthcare access, 
are interrelated and influence a wide range of health and quality-of-
life outcomes and risks. Therefore, we are committed to achieving 
equity in health care outcomes, including by improving data collection 
to better measure and analyze disparities across programs and 
policies.\1214\ Please see Closing the Health Equity Gap in CMS Quality 
Programs--A Request for Information, in section IX.B. of the preamble 
of the proposed rule, for additional information about our current 
disparity methods and its potential expansion.
---------------------------------------------------------------------------

    \1213\ United States Department of Health and Human Services. 
``Healthy People 2020: Disparities. 2014.'' Available at: https://www.healthypeople.gov/2020/about/foundation-health-measures/Disparities.
    \1214\ Centers for Medicare Services. CMS Quality Strategy. 
(2016). https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/QualityInitiativesGenInfo/Downloads/CMS-Quality-Strategy.pdf.
---------------------------------------------------------------------------

    We have also identified potential opportunities specific to the 
Hospital IQR Program where we could leverage current measures or 
develop new measures to address the gap in existing health inequities. 
These opportunities include the stratification of HWR measure data by 
both dual eligibility and race and ethnicity, and the inclusion of a 
structural measure assessing the degree of hospital leadership 
engagement in health equity performance data.
(1) Potential Future Confidential Stratified Reporting for the 
Hospital-Wide All-Cause Unplanned Readmission Measure Using Both Dual 
Eligibility and Race/Ethnicity
(a) Background
    As described in section IX.B. of the preamble of this final rule, 
where we discuss Closing the Health Equity Gap in CMS Hospital Quality 
Programs--A Request for Information, we currently provide hospitals 
with confidential, hospital-specific reports (HSRs) containing 
performance results of six condition-specific readmission measures 
stratified by dual-eligibility status (82 FR 41589, 84 FR 42497 through 
42500).
(b) Potential Future Expansion of Hospital-Wide All-Cause Unplanned 
Readmission (HWR) Measure Data and Stratification
    In the FY 2022 IPPS/LTCH PPS proposed rule (86 FR 25592), we sought 
comment on potentially expanding our efforts to provide results of the 
Within- and Across-Hospital Disparity Methods to promote health equity 
and improve healthcare quality. Specifically, we sought comment on the 
idea of stratifying the performance results of the Hospital-Wide All-
Cause Unplanned Readmission (HWR claims-only) measure (NQF #1789) by 
dual eligibility and indirectly estimated race and ethnicity, as 
described in section IX.B. of the preamble of this final rule. We also 
sought comment on the idea of stratifying said performance results by 
disability status and seek suggestions for appropriate measures of 
disability status that could be derived from administrative data or 
self-reporting for this purpose. Results would be presented if 
technically feasible, adequately representative, and statistically 
reliable.
    We believe that concurrently reporting equity results for the HWR 
claims-only measure in addition to the six condition-specific measures 
already stratified by dual eligibility would be advantageous as the 
measures often provide complimentary insights about different 
dimensions of hospital quality.\1215\ In addition, the HWR claims-only 
measure includes a larger patient population, allowing hospitals that 
may be too small to have meaningful results for condition-specific 
measures to receive stratified results for the HWR claims-only measure. 
Stratification of the HWR claims-only measure, by both dual 
eligibility, indirectly estimated race and ethnicity, and potentially 
by disability status would provide additional information regarding 
disparities measured within individual hospitals and across hospitals 
nationally.
---------------------------------------------------------------------------

    \1215\ Rosen AK, Chen Q, Shwartz M, Pilver C, Mull HJ, Itani KF, 
Borzecki A. Does Use of a Hospital-wide Readmission Measure Versus 
Condition-specific Readmission Measures Make a Difference for 
Hospital Profiling and Payment Penalties? Med Care. 2016 
Feb;54(2):155-61. doi: 10.1097/MLR.0000000000000455. PMID: 26595224.
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    We are considering an incremental approach to public reporting, 
first providing the HWR claims-only measure stratification results (by 
both dual eligibility and race/ethnicity) in confidential HSRs. This 
approach would allow stakeholders an opportunity to become more 
familiar with, and gain comfort with, interpreting stratified results 
for the HWR claims-only measure using both dual eligibility and 
indirect estimation of race and ethnicity, prior to anticipated future 
public reporting of stratified measure data. Any proposal to display 
stratified quality measure data for any measures on the Care Compare 
website, or expand stratified reporting to additional social risk 
factors, would be made through future rulemaking. We anticipate being 
able to provide the data in the HSRs in spring 2022. We intend to 
consider feedback on potential disability status stratification for 
future updates of these measures.
    We invited public comment on the following:
     The possibility of confidentially reporting in HSRs 
stratified results using indirectly estimated race and ethnicity, dual 
eligibility status and potentially by disability status, for the 
Hospital-wide Readmission claims-only measure, using both methods 
(within and across hospitals).
     The possibility of publicly reporting stratified results 
using indirectly estimated race and ethnicity, dual eligibility and 
potentially by disability status, publicly on Care Compare, after at 
least one year of confidential reporting for the Hospital-Wide 
Readmission claims-only measure.
(2) Potential Future Reporting of a Structural Measure To Assess the 
Degree of Hospital Leadership Engagement in Health Equity Performance 
Data
    To ensure that all Medicare patients receive excellent care, 
regardless of individual characteristics, such as dual eligibility 
status, race, ethnicity, and disability status, we believe that 
organizational leadership and culture can play an essential role in 
advancing equity goals. The Agency for Healthcare Research and Quality 
(AHRQ) \1216\ and The Joint Commission (TJC) \1217\ have

[[Page 45415]]

both published information on the important role of health care 
organizational leadership in setting an organizational culture of 
quality and safety. We are committed to supporting health care 
organizations in building a culture of equity that focuses on educating 
and empowering their workforce to recognize and eliminate health 
disparities. Hospital leadership can be instrumental in setting 
specific, measurable, attainable, relevant, and time-based goals, to 
assess progress towards achieving equity priorities and ensuring care 
is equally accessible to all individuals.
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    \1216\ Agency for Healthcare Research and Quality. Leadership 
Role in Improving Safety. 2019. https://psnet.ahrq.gov/primer/leadership-role-improving-safety.
    \1217\ The Joint Commission. Sentinel Event Alert. 2009 Aug. 
27;(43):1-3 https://www.jointcommission.org/-/media/deprecated-unorganized/imported-assets/tjc/system-folders/topics-library/sea_43pdf.pdf?db=web&hash=595C815B483DA56EDF745A94F95326F4.
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    To improve public transparency, we sought comment on the potential 
future collection of one or more attestation-based structural 
measure(s), to be developed, assessing priority domains related to 
organizational commitment to health equity including:
     The degree to which the hospital organization regularly 
examines existing algorithms for the presence of bias, and regularly 
shares these findings with the hospital organization's leadership and 
board of directors;
     The presence of the hospital organizational disparities 
impact statement, along the lines of what is discussed in the CMS 
publication ``Building an Organizational Response to Health 
Disparities: Disparities Impact Statement'' \1218\ which identifies and 
prioritizes actionable steps towards addressing health disparities;
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    \1218\ Centers for Medicare and Medicaid Services. Building an 
Organizational Response to Health Disparities. 2018. https://www.cms.gov/About-CMS/Agency-Information/OMH/Downloads/Disparities-Impact-Statement-508-rev102018.pdf.
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     The presence of an updated language access plan,\1219\ as 
defined by the CMS Office of Minority Health, to competently care for 
individuals with limited English proficiency;
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    \1219\ Centers for Medicare and Medicaid Services. Building an 
Organizational Response to Health Disparities: Guide to Developing a 
Language Access Plan. 2018. https://www.cms.gov/About-CMS/Agency-Information/OMH/Downloads/Language-Access-Plan.pdf. A language 
access plan is defined as a document that spells out how to provide 
services to individuals who are non-English speaking or have limited 
English proficiency.
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     The presence of an updated communication access 
plan,\1220\ as described by the CMS Office of Minority Health, to 
competently care for individuals who have visual or sensory 
disabilities;
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    \1220\ Centers for Medicare and Medicaid Services. Improving 
Communication Access for Individuals Who Are Blind or Have Low 
Vision. https://www.cms.gov/files/document/omh-visual-sensory-disabilities-brochure-508c.pdf.
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     The degree to which the hospital's electronic health 
record system has capabilities to collect demographic data elements 
(such as race, ethnicity, sex, sexual orientation and gender identity 
(SOGI), primary language, and disability status) in alignment with 
national data collection \1221\ and interoperable exchange standards; 
1222 1223 and
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    \1221\ 2015 Edition Cures Update certification criteria 
Demographic Data. 45 CFR 170.315(a)(5).
    \1222\ 2015 Edition Cures Update Certification Criteria 
Standardized API for Patient and Population Services. 45 CFR 
170.315(g)(10).
    \1223\ 2015 Edition Cures Update Certification Criteria United 
States Core Data for Interoperability (USCDI). 45 CFR 213.
---------------------------------------------------------------------------

     The degree to which the hospital conducts staff training 
on best practices in collection of demographic information.
    We believe these types of organizational commitment structural 
measure(s) would build on the current health disparities reporting, and 
support hospitals in quality improvement, efficient, effective use of 
resources, and leveraging available data. As defined by AHRQ, 
structural measures aim to ``give consumers a sense of a health care 
provider's capacity, systems, and processes to provide high-quality 
care.'' \1224\ We acknowledge that collection of this structural 
measure may impose administrative and/or reporting requirements for 
hospitals. To allow stakeholders an opportunity to become more familiar 
with, and gain comfort with, components of the structural measure 
related to organizational commitment to health equity performance, we 
envision an incremental approach to required reporting, starting first 
with a voluntary reporting period. Any future technical specifications 
or plans to display results of the structural measure on Care Compare 
or successor website would be made through future rulemaking. We sought 
feedback from stakeholders on conceptual and measurement priorities for 
better illuminating organizational commitment to health equity, 
including review of hospital outcomes stratified by social risk 
factors. We also sought feedback on an appropriate measure regarding 
organizational commitment to health equity and accessibility for 
individuals with intellectual and developmental disabilities.
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    \1224\ Agency for Healthcare Research and Quality. Types of 
Health Care Quality Measures. 2015. https://www.ahrq.gov/talkingquality/measures/types.html.
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    We received comments on these topics.
    Comment: Several commenters supported the creation and 
dissemination of measures stratified by dual eligibility, disability, 
and imputed race and ethnicity. They noted that publicly reporting the 
Hospital-Wide Readmission (HWR) stratified by dual eligibility and 
race/ethnicity would provide facilities with information to target 
quality improvement strategies. Commenters noted that reporting 
stratified data publicly could have unintended consequences such as 
patient selection or confusion for consumers and the public. Many 
commenters suggested that implementation of health equity measures 
should be incremental and allow for confidential reporting until 
providers become used to the new reporting requirements, including the 
imputation methodology. A commenter suggested that CMS provide material 
and documentation to aid in the appropriate interpretation of results.
    Several commenters expressed concern about the lack of accuracy and 
actionability of imputed data. They stated that stratified results 
should only be publicly available for self-reported race and ethnicity 
and recommended against using imputed data in reporting and payment 
programs. Others recommended only using indirect methods of calculating 
race and ethnicity for confidential reporting. Several commenters also 
requested more detailed information on the methodology used to impute 
race and ethnicity. A commenter recommended against using imputed race 
and ethnicity for confidential reporting.
    Numerous commenters expressed concern that additional reporting 
requirements would negatively impact providers with increased 
administrative burden. Many commenters requested that CMS work closely 
with both providers, stakeholders, patients, and organizations such as 
the NQF in the development of stratified health equity measures, to 
ensure that such measures provide actionable insights and do not unduly 
burden or negatively impact providers.
    Commenters also supported the collection and use of additional 
social risk factors such as language or LGBTQ status. A commenter 
recommended CMS collect data that are actionable, such as ICD-10-CM 
codes on social risk factors. Additionally, a commenter highlighted 
that several factors such as access to food, housing or transportation 
could impact racial and ethnic disparity results, and that collecting 
and accounting for such factors could allow CMS to better estimate the 
effect of structural racism on health disparities. Another commenter 
requested additional information on what CMS intends to use to measure 
disability status.
    Response: We appreciate the feedback, recommendation and request

[[Page 45416]]

for additional information. We will take into consideration the 
feedback, recommendations, and requests for additional information as 
we develop future plans.
    Comment: While numerous commenters supported potential future 
reporting of health equity outcome measures specific to the Hospital 
IQR Program, many expressed concerns that the proposed structural 
measure related to organizational commitment to health equity was too 
broadly defined to result in meaningful or actionable data. Several 
commenters asked for additional clarification and specificity on how a 
potential health equity structural measure would be constructed. A 
commenter highlighted the need for a demonstrated linkage between such 
a measure and the improvement of patient outcomes. Some commenters 
expressed a preference for outcomes-based approaches to measuring 
health equity rather than structural concepts. They noted that outcome 
variables better relay the experience of patients, offer clear goals 
for care givers, and help hospitals better identify whether they are 
providing equal care than process based measures, which often focus on 
organizational initiatives. Others noted that a localized, focused 
approach unique to a hospital's specific situation is better suited to 
accomplish health equity.
    Many commenters expressed a desire that CMS engage extensively with 
stakeholders in the construction of health equity reporting measures to 
fit reporting requirements and provide actionable data relevant to 
providers' needs. Another commenter suggested that CMS coordinate 
across government agencies to ensure that measurement and reporting 
requirements were standardized as much as possible to aid in data 
collection.
    Many commenters provided feedback that additional reporting 
requirements would increase administrative and financial burden on 
providers due to necessary upgrades to reporting tools and staff 
training requirements.
    Several commenters highlighted the need to test the health equity 
score structural measure to ensure feasibility and data integrity. For 
example, some commenters noted it is challenging to collect accurate 
and consistent race/ethnicity information at the time of admission to 
the hospital. Several commenters highlighted NQF endorsement as an 
important component of measure validity and reliability in the future.
    Numerous commenters also supported the collection and use of 
additional equity-related predictor variables such as LGBTQ status, 
disability, housing and food insecurity status, transportation needs, 
and public safety. In addition, some comments highlighted other efforts 
currently underway to address health disparities and suggested that CMS 
examine currently available datasets as potential sources to develop 
health equity measures.
    Other commenters encouraged CMS to take a measured, incremental 
approach in the construction and implementation of structural health 
equity measures in the Hospital IQR Program, on the basis that upgrades 
to EHRs, staff training, and the lack of standardized data collection 
all present barriers to quick implementation. Multiple commenters 
suggested that disparity measures should be confidentially reported 
until the measures' validity, reliability, and impact can be verified.
    A commenter indicated that there were already certain 
accreditations and other programs that address cultural components of 
health equity and encouraged CMS to conduct a thorough review of 
current efforts underway before mandating the reporting of certain 
measures that would increase administrative burden. Other comments 
expressed doubt that the measure framework proposed by CMS was 
adequately supported by evidence linking it to positive clinical 
outcomes and improved patient experiences, and that aggregated data 
sets do not provide actionable or insightful data for providers. One 
comment argued that a decentralized method that encourages providers to 
develop an approach unique to their situation would yield more positive 
outcomes compared to a centralized approach.
    Many commenters expressed overall support of CMS' goals to improve 
health care outcomes for Medicare beneficiaries and supported reporting 
HWR stratified by dual eligibility, imputed race/ethnicity, and 
disability to identify and understand disparities. However, other 
commenters expressed concern that some factors that might negatively 
impact a providers' performance within a health equity measure, such as 
geographic economic variables, were outside the providers' control.
    Response: We appreciate the feedback regarding approaches for 
measuring organizational commitment to health equity and concerns 
expressed by the commenters regarding measuring health equity in our 
hospital quality measurement programs. We will consider the feedback, 
recommendations, and requests for additional information should we 
propose a structural measure to assess the degree of hospital 
leadership engagement in health equity performance data in future 
rulemaking.
9. Form, Manner, and Timing of Quality Data Submission
a. Background
    Sections 1886(b)(3)(B)(viii)(I) and (b)(3)(B)(viii)(II) of the Act 
state that the applicable percentage increase for FY 2015 and each 
subsequent year shall be reduced by one-quarter of such applicable 
percentage increase (determined without regard to sections 
1886(b)(3)(B)(ix), (xi), or (xii) of the Act) for any subsection (d) 
hospital that does not submit data required to be submitted on measures 
specified by the Secretary in a form and manner, and at a time, 
specified by the Secretary. In order to successfully participate in the 
Hospital IQR Program, hospitals must meet specific procedural, data 
collection, submission, and validation requirements. Previously, the 
applicable percentage increase for FY 2007 and each subsequent fiscal 
year until FY 2015 was reduced by 2.0 percentage points for subsection 
(d) hospitals failing to submit data in accordance with the previous 
description. In accordance with the statute, the FY 2022 payment 
determination will begin the eighth year that the Hospital IQR Program 
will reduce the applicable percentage increase by one-quarter of such 
applicable percentage increase.
b. Maintenance of Technical Specifications for Quality Measures
    For each Hospital IQR Program payment determination, we require 
that hospitals submit data on each specified measure in accordance with 
the measure's specifications for a particular period of time. We refer 
readers to the FY 2019 IPPS/LTCH PPS final rule (83 FR 41538) in which 
we summarized how the Hospital IQR Program maintains the technical 
measure specifications for quality measures and the subregulatory 
process for incorporation of nonsubstantive updates to the measure 
specifications to ensure that measures remain up-to-date. We did not 
propose any changes to these policies in the proposed rule.
    The data submission requirements, Specifications Manual, and 
submission deadlines are posted on the QualityNet website at: http://www.QualityNet.cms.gov (or other successor CMS designated websites). 
The CMS Annual Update for the Hospital Quality Reporting Programs 
(Annual Update) contains the technical

[[Page 45417]]

specifications used for electronic clinical quality measures (eCQMs). 
The Annual Update contains updated measure specifications for the year 
prior to the reporting period. For example, for the CY 2021 reporting 
period/FY 2023 payment determination, hospitals submitted eCQM data 
using the May 2020 Annual Update and any applicable addenda. Updates 
include code updates, logic corrections, alignment with current 
clinical guidelines, and additional guidance for hospitals and 
electronic health record (EHR) vendors. The Annual Update and 
implementation guidance documents are available on the Electronic 
Clinical Quality Improvement (eCQI) Resource Center website at: https://ecqi.healthit.gov/.
    Hospitals must register and submit quality data through the 
QualityNet Secure Portal (also referred to as the Hospital Quality 
Reporting (HQR) System). The QualityNet Secure Portal is safeguarded in 
accordance with the HIPAA Privacy and Security Rules to protect 
submitted patient information. See 45 CFR parts 160 and 164, subparts 
A, C, and E.
    We also refer readers to section VIII.A. of this final rule where 
we requested information on potential actions and priority areas that 
would enable the continued transformation of our quality measurement 
enterprise toward greater digital capture of data and use of the FHIR 
standard (as described in that section).
c. Procedural Requirements
    The Hospital IQR Program's procedural requirements are codified in 
regulation at 42 CFR 412.140. We refer readers to these codified 
regulations for participation requirements, as further explained by the 
FY 2014 IPPS/LTCH PPS final rule (78 FR 50810 through 50811) and the FY 
2017 IPPS/LTCH PPS final rule (81 FR 57168). In the FY 2022 IPPS/LTCH 
PPS proposed rule (86 FR 25594), we proposed to: (1) Update references 
to the QualityNet website, and (2) use the term ``QualityNet security 
official'' instead of ``QualityNet Administrator''.
(1) Updates to References to the QualityNet Website in the Hospital IQR 
Program Regulation Text
    In November 2020, we launched a redesigned QualityNet website, and 
updated the URL from QualityNet.org to QualityNet.cms.gov.\1225\ As a 
result, we proposed to update the references to this CMS resource in 
the Hospital IQR Program regulation text. Specifically, we proposed to 
remove reference to the QualityNet.org URL in two places:
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    \1225\ QualityNet Migration from QualityNet.org to 
QualityNet.cms.gov. Available at: https://qualitynet.cms.gov/news/5fa2f7ccfa00d50025576586.
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     At 42 CFR 412.140(a)(1) by revising the sentence from 
``Register on QualityNet.org, before it begins to report data'' to 
``Register on the QualityNet website, before it begins to report 
data''; and
     At 42 CFR 412.140(c)(2)(i) by revising the sentence from 
``Specific requirements for submission of a request for an exception 
are available on QualityNet.org'' to ``Specific requirements for 
submission of a request for an exception are available on the 
QualityNet website.''
    We believe that updating the references to remove a specific URL 
allows for future iterations and updates to the website as technology 
evolves over time.
    We invited public comment on our proposals to update references to 
the QualityNet website at 42 CFR 412.140(a)(1) and 42 CFR 
412.140(c)(2)(i). We received no comments on this proposal. We are 
finalizing our proposal as proposed.
(2) Updates to References to QualityNet Administrator
    The previously finalized QualityNet security administrator 
requirements, including setting up a QualityNet account and the 
associated timelines, are described at 42 CFR 412.140(a)(2), 42 CFR 
412.140(e)(2)(iii), and in the FY 2012 IPPS/LTCH PPS final rule (76 FR 
51639 through 51640).
    In the FY 2022 IPPS/LTCH PPS proposed rule (86 FR 25594), we 
proposed to use the term ``QualityNet security official'' instead of 
``QualityNet Administrator'' or ``QualityNet System Administrator.'' 
This update in terminology would not change the individual's 
responsibilities or add burden, and would align with the Hospital 
Outpatient Quality Reporting (OQR) Program and other programs.\1226\ 
The term ``security official'' would refer to ``the individual(s)'' who 
have responsibilities for security and account management requirements 
for a hospital's QualityNet account.
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    \1226\ Medicare Program; CY 2021 Medicare hospital outpatient 
prospective payment system. 85 FR 86182.
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    Therefore, we proposed to revise existing language at 42 CFR 
412.140(a)(2) by replacing ``QualityNet Administrator'' with 
``QualityNet security official.'' The revised paragraph (a)(2) will 
read: ``Identify and register a QualityNet security official as part of 
the registration process under paragraph (a)(1) of this section.''
    In addition, we proposed to revise existing language at 42 CFR 
412.140(e)(2)(iii) by replacing ``QualityNet system administrator'' 
with ``QualityNet security official.'' The revised paragraph 
(e)(2)(iii) will read: ``Contact information for the hospital's chief 
executive officer and QualityNet security official, including each 
individual's name, email address, telephone number, and physical 
mailing address.''
    We invited public comment on our proposals to update references to 
the QualityNet security official at 42 CFR 412.140(a)(2) and 42 CFR 
412.140(e)(2)(iii).
    Comment: A commenter supported our proposals because it believes 
the updates would help simplify and streamline processes.
    Response: We thank the commenter for its support.
    After consideration of the public comment received, we are 
finalizing our proposal as proposed.
d. Data Submission Requirements for Chart-Abstracted Measures
    We refer readers to the FY 2012 IPPS/LTCH PPS final rule (76 FR 
51640 through 51641), the FY 2013 IPPS/LTCH PPS final rule (77 FR 53536 
through 53537), and the FY 2014 IPPS/LTCH PPS final rule (78 FR 50811) 
for details on the Hospital IQR Program data submission requirements 
for chart-abstracted measures. We did not propose any changes to these 
policies in the proposed rule.
e. Reporting and Submission Requirements for eCQMs
(1) Background
    For a discussion of our previously finalized eCQMs and policies, we 
refer readers to the FY 2014 IPPS/LTCH PPS final rule (78 FR 50807 
through 50810; 50811 through 50819), the FY 2015 IPPS/LTCH PPS final 
rule (79 FR 50241 through 50253; 50256 through 50259; and 50273 through 
50276), the FY 2016 IPPS/LTCH PPS final rule (80 FR 49692 through 
49698; and 49704 through 49709), the FY 2017 IPPS/LTCH PPS final rule 
(81 FR 57150 through 57161; and 57169 through 57172), the FY 2018 IPPS/
LTCH PPS final rule (82 FR 38355 through 38361; 38386 through 38394; 
38474 through 38485; and 38487 through 38493), FY 2019 IPPS/LTCH PPS 
final rule (83 FR 41567 through 41575; 83 FR 41602 through 41607), FY 
2020 IPPS/LTCH PPS final rule (84 FR 42501 through 42506), and the FY 
2021 IPPS/LTCH PPS final rule (85 FR 58932 through 58940).
    In the FY 2018 IPPS/LTCH PPS final rule (82 FR 38368 through 
38361), we

[[Page 45418]]

finalized eCQM reporting and submission requirements such that 
hospitals were required to report only one, self-selected calendar 
quarter of data for four self-selected eCQMs for the CY 2018 reporting 
period/FY 2020 payment determination. Those reporting requirements were 
extended to the CY 2019 reporting period/FY 2021 payment determination 
in the FY 2019 IPPS/LTCH PPS final rule (83 FR 41603 through 41604), as 
well as to the CY 2020 reporting period/FY 2022 payment determination 
and the CY 2021 reporting period/FY 2023 payment determination in the 
FY 2020 IPPS/LTCH PPS final rule (84 FR 42501 through 42503).
    In the FY 2020 IPPS/LTCH PPS final rule (84 FR 42503 through 
42505), we finalized that for the CY 2022 reporting period/FY 2024 
payment determination, hospitals would be required to report one, self-
selected calendar quarter of data for: (a) Three self-selected eCQMs 
and (b) the Safe Use of Opioids--Concurrent Prescribing eCQM (Safe Use 
eCQM), for a total of four eCQMs.\1227\
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    \1227\ We refer readers to the CY 2022 Hospital Outpatient 
Prospective Payment System (OPPS) and Ambulatory Surgical Center 
(ASC) Payment System proposed rule where we requested public input 
for potential measure updates as we prepare for NQF re-endorsement 
of the endorsed Safe Use of Opioids--Concurrent Prescribing eCQM and 
to potentially inform any future rulemaking regarding this measure.
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    In the FY 2021 IPPS/LTCH PPS final rule, we finalized a progressive 
increase in the number of required reported quarters of eCQM, from one 
self-selected quarter of data to four quarters of data over a three-
year period (85 FR 58939). For the CY 2021 reporting period/FY 2023 
payment determination, hospitals are required to report two self-
selected calendar quarters of data for each of the four self-selected 
eCQMs. For the CY 2022 reporting period/FY 2024 payment determination, 
hospitals are required to report three self-selected calendar quarters 
of data for each required eCQM: (a) Three self-selected eCQMs, and (b) 
the Safe Use of Opioids eCQM. For the CY 2023 reporting period/FY 2025 
payment determination and subsequent years, hospitals are required to 
report four calendar quarters of data for each required eCQM: (a) Three 
self-selected eCQMs, and (b) the Safe Use of Opioids eCQM. We also 
clarified in the FY 2021 IPPS/LTCH PPS final rule that until hospitals 
are required to report all four quarters of data beginning with the CY 
2023 reporting period/FY 2025 payment determination, they may submit 
either consecutive or nonconsecutive self-selected quarters of data (85 
FR 58939). While we did not propose any changes to these policies in 
the FY 2022 IPPS/LTCH PPS proposed rule (86 FR 25595), we would like to 
clarify in case there is any confusion that beginning with the CY 2021 
reporting period/FY 2023 payment determination, the self-selected eCQMs 
must be the same eCQMs across quarters in a given reporting year.
(2) Updates to Certification Requirements for eCQM Reporting
    In the FY 2022 IPPS/LTCH PPS proposed rule (86 FR 255945 through 
25595), we proposed a date after which Hospital IQR Program 
participants must use technology certified to the 2015 Edition Cures 
Update and clarifying the policy that certified technology must support 
the reporting requirements for all available eCQMs.
(a) Requirements for the Use of Technology Certified to the 2015 
Edition Cures Update Criteria Beginning With the CY 2023 Reporting 
Period/FY 2025 Payment Determination
(i) Background
    In the FY 2019 IPPS/LTCH PPS final rule (83 FR 41604 through 
41607), we finalized a policy to require hospitals to use the 2015 
Edition certification criteria for the CY 2019 reporting period/FY 2021 
payment determination and subsequent years to align the Hospital IQR 
Program with the Medicare Promoting Interoperability Program. In May 
2020, the ONC 21st Century Cures Act final rule (85 FR 25642 through 
25961) updated the 2015 Edition of health IT certification criteria 
(``2015 Edition Cures Update''). The 2015 Edition Cures Update revises 
the clinical quality measurement criterion at 45 CFR 170.315(c)(3) to 
refer to CMS QRDA Implementation Guides (IGs) and removes the Health 
Level 7 (HL7[supreg]) QRDA standard from the relevant health IT 
certification criteria (85 FR 25686). The revision was responsive to 
industry feedback that the health IT certified to the prior ``CQMs-
report'' criterion was only or primarily being used to submit eCQMs for 
CMS reporting programs (85 FR 25688). These updates were finalized to 
reduce burden on health IT developers under the ONC Health IT 
certification program (85 FR 25686) and have no impact on providers' 
existing reporting practices for CMS programs.
    The ONC 21st Century Cures Act final rule provided health IT 
developers up to 24 months from May 1, 2020 to make technology 
certified to the updated and/or new criteria available to their 
customers (85 FR 25670). On November 4, 2020, ONC issued an interim 
final rule with comment entitled ``Information Blocking and the ONC 
Health IT Certification Program: Extension of Compliance Dates and 
Timeframes in Response to the COVID-19 Public Health Emergency'' 
(hereafter, ``ONC interim final rule'') (85 FR 70064). In the ONC 
interim final rule ONC extended the compliance deadline for the update 
to the Clinical Quality Measures-Report criterion until December 31, 
2022 (85 FR 70075). During the period until December 31, 2022, health 
IT developers are expected to continue supporting technology certified 
to the prior version of the ONC certification criteria for use by their 
customers (85 FR 84816).
    In the CY 2021 PFS final rule (85 FR 84825 through 84828), we 
finalized our proposal to expand flexibility under the Hospital IQR 
Program for the CY 2020 reporting period/FY 2022 payment determination 
and for subsequent years to allow hospitals to use either: (1) 
Technology certified to the 2015 Edition criteria as was previously 
finalized for reporting eCQMs in the FY 2019 IPPS/LTCH PPS final rule 
(83 FR 41537 through 41608), or (2) certified technology updated 
consistent with the 2015 Edition Cures Update as finalized in the ONC 
21st Century Cures Act final rule (85 FR 25642 through 25961). We 
adopted this flexible approach to encourage hospitals to be early 
implementers of the 2015 Edition Cures Update while remaining in 
compliance with Hospital IQR Program data submission requirements and 
maintaining alignment with requirements in the Medicare Promoting 
Interoperability Program.
(ii) Finalized Policy Regarding Use of the 2015 Edition Cures Update 
for eCQM Data Submission
    In the proposed rule, beginning with the CY 2023 reporting period/
FY 2025 payment determination and subsequent years, we proposed to 
require hospitals to use only certified technology updated consistent 
with the 2015 Edition Cures Update to submit data for the Hospital IQR 
Program data. We refer readers to the ONC 21st Century Cures Act final 
rule for additional information about the updates included in the 2015 
Edition Cures Update (85 FR 25665).
    We invited public comment on our proposal.
    Comment: Several commenters supported the proposal to require use 
of technology certified to the 2015 Edition Cures Update beginning with 
the CY 2023 reporting period/FY 2025 payment determination. Commenters 
recommended CMS monitor vendor and hospital progress to ensure the 
transition to the 2015 Edition Cures

[[Page 45419]]

Update remains feasible and exercise flexibility if there are health IT 
developer issues beyond the hospitals' control.
    Response: We thank commenters for their support. We will continue 
to work with ONC to monitor the availability of EHR technology 
certified to the 2015 Edition Cures Update.
    Comment: Several commenters did not support required use of the 
2015 Edition Cures Update beginning with the CY 2023 reporting period 
citing insufficient time for hospitals to prepare and test for the 
requirement and concern about health IT developers' timeline to develop 
and deploy the technology. A few commenters recommended delaying the 
required use of the 2015 Edition Cures Update until the CY 2024 
reporting period or the CY 2025 reporting period. Several commenters 
did not express support or disapproval of the proposal but recommended 
CMS provide adequate time for health IT developers to provide updated 
certified health IT to hospitals and provide more time for hospitals to 
operationalize and test technology updated to the 2015 Edition Cures 
Update for accuracy. A commenter recommended CMS continue flexibility 
for hospitals in the choice of certified technology required for use in 
CY 2023 reporting period, and a few commenters recommended CMS delay 
the requirement that hospitals report four calendar quarters of eCQM 
data for the CY 2023 reporting period in response to concerns about 
health IT developer readiness to meet the proposed requirement to use 
the 2015 Edition Cures Update by that time. A commenter recommended CMS 
work with ONC to issue direction to health IT developers on the 
deadline for delivery of complete and timely technology updated 
consistent with the 2015 Edition Cures Update.
    Response: We appreciate commenters' concerns related to sufficient 
time for hospitals to prepare and test the 2015 Edition Cures Update 
after it is made available by their health IT developer; however, we 
respectfully disagree that our proposal provides insufficient time to 
implement. In the CY 2021 PFS final rule, we adopted a policy to allow 
hospitals to use either: (1) Technology certified to the 2015 Edition 
criteria as was previously finalized in the FY 2019 IPPS/LTCH PPS final 
rule (83 FR 41537 through 41608); or (2) certified technology updated 
consistent with the 2015 Edition Cures Update as finalized in the ONC 
21st Century Cures Act final rule (85 FR 25642 through 25961), enabling 
hospitals to implement updates prior to requiring use of technology 
updated to the 2015 Edition Cures Update for the Hospital IQR Program. 
We believe our previously finalized policy allowing use of the 2015 
Edition Cures Update as early as the CY 2020 reporting period provides 
hospitals and health IT developers flexibility and time to adjust. In 
combination with our proposal in this year's proposed rule, hospitals 
and developers have over three years to update and test systems before 
the February 29, 2024 submission deadline for reporting eCQM data for 
the CY 2023 reporting period/FY 2025 payment determination for which 
use of certified technology updated to the 2015 Edition Cures Update is 
required under our final policy. We also wish to clarify that hospitals 
are not required to implement certified health IT consistent with the 
2015 Edition Cures Update by December 31, 2022. Rather, our requirement 
is that hospitals use only certified technology updated consistent with 
the 2015 Edition Cures Update to submit data for the Hospital IQR 
Program data beginning with the CY 2023 reporting period/FY 2025 
payment determination.
    In addition, we understand the updates to the certification 
criteria that ONC finalized in the ONC 21st Century Cures Act final 
rule do not constitute a full new Edition of technology (85 FR 25665), 
as the scope of updates did not warrant implementation of an entirely 
new Edition of certification criteria (85 FR 25664 through 25665). We 
understand the updates build on existing functionality and standards in 
technology certified to the 2015 Edition, which participants in the 
Hospital IQR Program have been using as part of clinical and 
administrative workflows since the CY 2019 reporting period/FY 2021 
payment determination, if not earlier (83 FR 41604 through 41607). We 
note that for quality measure reporting, implementation of the 2015 
Edition Cures Update will not impact hospitals' current eCQM reporting 
practices, and hospitals will continue to implement the required CMS 
annual updates (85 FR 84827). We generally update the measure 
specifications on an annual basis (CMS' Annual Update for the Hospital 
Quality Reporting Programs) to include code updates, logic corrections, 
non-substantive alignments with current clinical guidelines, and 
additional guidance for hospitals and EHR vendors to use in order to 
collect and submit data on eCQMs from hospital EHRs (85 FR 
58932).\1228\ We encourage the use of Certified Health IT Product List 
(CHPL) as discussed in the ONC 21st Century Cures Act final rule (85 FR 
25666), which allows hospitals to identify the specific certification 
status of a product at any given time. We also refer readers to the 
impact analysis presented in the ONC 21st Century Cures Act final rule 
at 85 FR 25912 for more information on the impact of updating health IT 
products.
---------------------------------------------------------------------------

    \1228\ The Annual Update and implementation guidance documents 
are available on the Electronic Clinical Quality Improvement (eCQI) 
Resource Center website at: https://ecqi.healthit.gov/.
---------------------------------------------------------------------------

    We acknowledge commenter's suggestion concerning collaboration with 
Federal partners and the availability of additional flexibility in the 
eCQM reporting manner and timing requirements. As stated previously, we 
intend to work with ONC to monitor the timely availability of EHR 
technology certified to the 2015 Edition Cures Update. We plan to 
monitor the implementation and welcome continued feedback from 
stakeholders through webinars, listservs, and help desk questions.
    Comment: A commenter did not support required use of the 2015 
Edition Cures Update beginning with the CY 2023 reporting period, 
citing the timeline for health IT developers to develop and make these 
solutions available, and hospitals to deploy updated technology, with 
particular concern with the pace of change and its impact on hospitals' 
ability to fully recover from the COVID-19 pandemic.
    Response: We acknowledge these concerns and recognize the burden 
that the COVID-19 PHE has had on the healthcare system. If a hospital 
experiences an extraordinary circumstance that prevents it from 
reporting eCQMs, it is able to submit an individual Extraordinary 
Circumstances Exceptions (ECE) request form. Specifically, in the FY 
2016 IPPS/LTCH PPS final rule, we finalized a policy, effective 
starting with the FY 2018 payment determination, to allow hospitals to 
utilize the existing ECE form (OMB control number 0938-1022 (expiration 
date December 31, 2022)) to request an exception to the Hospital IQR 
Program's eCQM reporting requirement for the applicable program year 
based on hardships preventing a hospital from electronically reporting 
(80 FR 49695 and 49713). We stated that such hardships could include, 
but are not limited to, infrastructure challenges (a hospital must 
demonstrate that it is in an area without sufficient internet access or 
face insurmountable barriers to obtaining infrastructure) or unforeseen 
circumstances, such as health IT developer issues outside of the 
hospital's control (including a health IT developer product losing 
certification (80 FR 49695 and 49713)). We assess a

[[Page 45420]]

hospital's request on an individual basis to determine if an exception 
is merited (80 FR 49695 and 49713). We also refer stakeholders to 
additional eCQM ECE resources on the QualityNet website.\1229\
---------------------------------------------------------------------------

    \1229\ See https://www.qualitynet.org/inpatient/measures/ecqm/participation#tab2.
---------------------------------------------------------------------------

    Comment: Several commenters expressed concerns about product update 
fees passed to providers by vendors, particularly during the PHE.
    Response: We understand commenters' statement about product update 
fees to pertain to the cost of implementing technology consistent with 
the 2015 Edition Cures Update. We recognize that hospitals require 
resources to update workflows and train staff when adopting updated 
certified technology. We understand and wish to highlight that the 
updates to the certification criteria that ONC finalized in the ONC 
21st Century Cures Act final rule do not constitute a full new Edition 
of technology but include updates to Health IT Modules certified to 
existing certification criteria (85 FR 25665). We generally update the 
measure specifications on an annual basis (CMS' Annual Update for the 
Hospital Quality Reporting Programs) to include code updates, logic 
corrections, non-substantive alignments with current clinical 
guidelines, and additional guidance for hospitals and EHR vendors to 
use in order to collect and submit data on eCQMs from hospital EHRs (85 
FR 58932).\1230\
---------------------------------------------------------------------------

    \1230\ The Annual Update and implementation guidance documents 
are available on the Electronic Clinical Quality Improvement (eCQI) 
Resource Center website at: https://ecqi.healthit.gov/.
---------------------------------------------------------------------------

    Comment: A commenter requested we clarify whether outsourcing the 
eCQM functionality is allowed under this proposal.
    Response: We interpret the commenter's request to mean whether 
Hospital IQR Program participants can use certified EHR technology from 
more than one health IT developer to specifically support eCQM data 
reporting, which is permissible. In the FY 2021 IPPS/LTCH PPS final 
rule, we finalized the addition of the EHR Submitter ID to the four key 
elements for file identification beginning with the CY 2021 reporting 
period/FY 2023 payment determination (85 FR 58940). An EHR Submitter ID 
is the ID that is assigned to submitter entities upon registering to 
use the HQR System (formerly referred to as the QualityNet Secure 
Portal) and will be used to upload QRDA I files. Particularly for 
situations when a hospital uses one or more vendors to submit QRDA I 
files via the HQR System, this additional element would prevent the 
risk of a previously submitted file by a different vendor 
unintentionally being overwritten.
    Comment: A commenter recommended we permit hospitals to extract and 
submit data directly to CMS rather than through the service of a 
certified health IT developer.
    Response: We refer readers to the FY 2021 IPPS/LTCH PPS final rule 
(85 FR 58940) for our previously adopted eCQM file format 
specifications, which require that hospitals: (1) Must submit eCQM data 
via the Quality Reporting Document Architecture Category I (QRDA I) 
file format; (2) may use third parties to submit QRDA I files on their 
behalf [although not required]; and (3) may either use abstraction or 
pull the data from noncertified sources in order to then input these 
data into CEHRT for capture and reporting QRDA I files. We also refer 
readers to the FY 2020 IPPS/LTCH PPS final rule (84 FR 42505) where we 
state that certification criteria referenced in the 2015 Edition Base 
EHR definition. We refer readers to the ONC 21st Century Cures Act 
final rule, where the CQM report certification criterion was updated to 
enable users to report a data file that is formatted in accordance with 
the QRDA I standard (85 FR 25686 through 25690). We also highlight that 
we are exploring paths forward into the future of quality measures, 
including the use of FHIR to reduce the burden associated with quality 
measure reporting. We refer readers to section IX.A. for a detailed 
discussion of the potential use of FHIR for quality measure reporting.
    After consideration of the public comments we received, we are 
finalizing our proposal as proposed.
(b) Requiring EHR Technology To Be Certified to All Available eCQMs
    In the FY 2020 IPPS/LTCH PPS final rule (84 FR 42505 through 
42506), we finalized the requirement that EHRs be certified to all 
available eCQMs used in the Hospital IQR Program for the CY 2020 
reporting period/FY 2022 payment determination and subsequent years. We 
did not propose any changes to this policy in the FY 2022 IPPS/LTCH PPS 
proposed rule (86 FR 25070). We note that with the finalization in this 
final rule of our proposal to require hospitals to use the 2015 Edition 
Cures Update beginning with the CY 2023 reporting period/FY 2025 
payment determination, then all available eCQMs used in the Hospital 
IQR Program for the CY 2023 reporting period/FY 2025 payment 
determination and subsequent years would need to be reported using 
certified technology updated to the 2015 Edition Cures Update.
(3) File Format for EHR Data, Zero Denominator Declarations, and Case 
Threshold Exemptions
    We refer readers to the FY 2016 IPPS/LTCH PPS final rule (80 FR 
49705 through 49708) and the FY 2017 IPPS/LTCH PPS final rule (81 FR 
57170) for our previously adopted eCQM file format requirements. Under 
these requirements, hospitals: (1) Must submit eCQM data via the 
Quality Reporting Document Architecture Category I (QRDA I) file 
format, (2) may use third parties to submit QRDA I files on their 
behalf, and (3) may either use abstraction or pull the data from non-
certified sources in order to then input these data into CEHRT for 
capture and reporting QRDA I. Hospitals can continue to meet the 
reporting requirements by submitting data via QRDA I files, zero 
denominator declaration, or case threshold exemption (82 FR 38387).
    More specifically regarding the use of QRDA I files, we refer 
readers to the FY 2017 IPPS/LTCH PPS final rule (81 FR 57169 through 
57170) and the FY 2020 IPPS/LTCH PPS final rule (85 FR 58940), in which 
we stated that we expect QRDA I files to reflect data for one patient 
per file per quarter, and identified the five key elements that are 
utilized to identify the file:
     CMS Certification Number (CCN);
     CMS Program Name;
     EHR Patient ID;
     Reporting period specified in the Reporting Parameters 
Section per the CMS Implementation Guide for the applicable reporting 
year, which is published on the eCQI Resource Center website at: 
https://ecqi.healthit.gov/QRDA; and
     EHR Submitter ID (beginning with the CY 2021 reporting 
period/FY 2023 payment determination).
    We did not propose any changes to these policies in the proposed 
rule.
(4) Submission Deadlines for eCQM Data
    We refer readers to the FY 2015 IPPS/LTCH PPS final rule (79 FR 
50256 through 50259), the FY 2016 IPPS/LTCH PPS final rule (80 FR 49705 
through 49709), and the FY 2017 IPPS/LTCH PPS final rule (81 FR 57169 
through 57172) for our previously adopted policies to align eCQM data 
reporting periods and submission deadlines for both the Hospital IQR 
and Medicare Promoting Interoperability Programs. In the FY 2017 IPPS/
LTCH PPS final rule (81 FR 57172), we finalized the alignment of the 
Hospital IQR Program eCQM submission deadline with that of the Medicare 
Promoting Interoperability

[[Page 45421]]

Program--the end of two months following the close of the calendar 
year--for the CY 2017 reporting period/FY 2019 payment determination 
and subsequent years. We note the submission deadline may be moved to 
the next business day if it falls on a weekend or Federal holiday. We 
did not propose any changes to these policies in the proposed rule.
f. Data Submission and Reporting Requirements for Hybrid Measures
    In the proposed rule, we proposed that hybrid measures comply with 
the same certification requirements and timeline as eCQMs. This 
provision is in alignment with the updates, as previously discussed, 
for eCQMs requiring the use of certified technology updated consistent 
with the 2015 Edition Cures Update beginning with the CY 2023 reporting 
period/CY 2025 payment determination.
(1) Background
    The Hospital IQR Program recently adopted hybrid measures into the 
program's measure set. In the FY 2018 IPPS/LTCH PPS final rule (82 FR 
38350 through 38355), we finalized voluntary reporting of the Hybrid 
Hospital-Wide Readmission (HWR) measure for the CY 2018 reporting 
period. In the FY 2020 IPPS/LTCH PPS final rule, we finalized the 
adoption of the Hybrid HWR measure for the Hospital IQR Program (84 FR 
42465 through 42481) such that, beginning with the FY 2026 payment 
determination, hospitals are required to report on the Hybrid HWR 
measure (84 FR 42479). We also finalized several requirements related 
to data submission and reporting requirements for hybrid measures under 
the Hospital IQR Program (84 FR 42506 through 42508). We also refer 
readers to section VIII.C.5.b. of the preamble of this final rule for 
more information on the adoption of the Hybrid Hospital-Wide Mortality 
measure.
(2) Certification and File Format Requirements
(a) Background
    We refer readers to the FY 2020 IPPS/LTCH PPS final rule (84 FR 
19498 through 19499), the FY 2021 IPPS/LTCH PPS final rule (85 FR 
58941), and the CY 2021 PFS final rule (85 FR 84472) for our previously 
adopted policies regarding certification and file format requirements 
for hybrid measures in the Hospital IQR Program.
    In the CY 2021 PFS final rule (85 FR 84825 through 84828), we 
finalized flexibility to allow hospitals to use either: (1) Technology 
certified to the 2015 Edition criteria as was previously finalized in 
the FY 2019 IPPS/LTCH PPS final rule (83 FR 41537 through 41608) or (2) 
certified technology updated consistent with the 2015 Edition Cures 
Update as finalized in the ONC 21st Century Cures Act final rule (85 FR 
25642 through 25961, 85 FR 50271), beginning with the CY 2020 reporting 
period/FY 2022 payment determination and subsequent years. The Hospital 
IQR Program offers flexibility to meet hybrid measure submission 
requirements to facilitate successful reporting during a period of 
transition from the requirement to solely use the 2015 Edition 
certified technology to the requirement to solely use the 2015 Edition 
Update certified technology. This flexibility applies to all Hospital 
IQR Program measures which use EHR data elements to calculate measure 
rates, including eCQMs and hybrid measures.
(b) Finalized Changes to the Certification Requirements for Hybrid 
Measure Reporting Beginning With the CY 2023 Reporting Period/FY 2025 
Payment Determination
    In the FY 2022 IPPS/LTCH PPS proposed rule (86 FR 25596 through 
25597), to align with the health IT certification requirements for eCQM 
reporting, we proposed to require hospitals to use only certified 
technology that has been updated consistent with the 2015 Edition Cures 
Update to submit hybrid measure data beginning with the CY 2023 
reporting period/FY 2025 payment determination and for subsequent 
years. We refer readers to our previous discussion for more detail on 
the finalized changes to the certification requirements for eCQMs.
    We believe the 2015 Edition Cures Update will enhance 
interoperability and patients' access to their electronic health 
information, consistent with section 4006(a) of the 21st Century Cures 
Act (Pub. L. 114-255, enacted December 13, 2016). Health IT developers 
have until December 31, 2022 (the date finalized in the ONC interim 
final rule) to make technology certified to the updated criteria 
available to their customers. After this date, only certified 
technology updated to the 2015 Edition Cures Update will be considered 
certified by ONC and could be used by health care providers to report 
for the Hospital IQR Program. We refer readers to section 
VIII.F.11.a.4. of the preamble of this final rule where the same 
finalized requirements are discussed for the Medicare Promoting 
Interoperability Program.
    We invited public comment on our proposal.
    Comment: Most commenters supported our proposal that, for hybrid 
measures, technology must be certified under the ONC Health IT 
Certification Program in accordance with the 2015 Edition Cures Update, 
as finalized in the ONC 21st Century Cures Act final rule (85 FR 
25665). Commenters indicated their belief that requiring use of the 
2015 Edition Cures Update will support standardization and quality 
measurement while also facilitating interoperability.
    Response: We agree and thank the commenters for their support.
    Comment: Several commenters raised potential concerns of the 
readiness of health IT vendors and hospitals to transition to the 2015 
Edition Cures Update. Specifically, commenters are concerned with 
vendors being able to complete, and providers being able to adopt and 
implement, the changes associated with the 2015 Edition Cures Update by 
December 31, 2022.
    Response: We appreciate the commenters' concerns. We refer readers 
to section IX.9.e.2.(a).(ii). where we previously responded to these 
similar concerns raised by commenters for eCQMs. We reiterate that 
hospitals are not required to implement certified health IT consistent 
with the 2015 Edition Cures Update by December 31, 2022. Rather, our 
requirement is that hospitals use only certified technology updated 
consistent with the 2015 Edition Cures Update to submit data for the 
Hospital IQR Program data beginning with the CY 2023 reporting period/
FY 2025 payment determination.
    Comment: A commenter expressed concern with health IT developers 
potentially passing the cost of the update on to clients to guarantee 
meeting required deadlines.
    Response: We thank the commenter for sharing its concern. We refer 
readers to section IX.9.e.2.(a).(ii). where we previously responded to 
this similar concern raised by commenters for eCQMs.
    After consideration of the public comments we received, we are 
finalizing our proposal as proposed.
(3) Additional Submission Requirements
    In the FY 2020 IPPS/LTCH PPS final rule (84 FR 42507), we finalized 
allowing hospitals to meet the hybrid measure reporting and submission 
requirements by submitting any combination of data via QRDA I files, 
zero denominator declarations, and/or case threshold exemptions. We 
also finalized applying similar zero denominator declaration and case 
threshold exemption policies to hybrid

[[Page 45422]]

measure reporting as we allow for eCQM reporting (84 FR 42507 through 
42508).
    We note that the ONC 21st Century Cures Act final rule revises the 
clinical quality measurement criterion at 45 CFR 170.315(c)(3) to refer 
to CMS QRDA IGs and removes the HL7[supreg] QRDA standard requirements 
(85 FR 25645). We encourage all hospitals and their health IT vendors 
to submit QRDA I files early, and to use one of the pre-submission 
testing tools for electronic reporting, such as submitting test files 
to the Hospital Quality Reporting (HQR) System, to allow additional 
time for testing and make sure all required data files are successfully 
submitted by the deadline.\1231\ We did not propose any changes to 
these policies in the proposed rule.
---------------------------------------------------------------------------

    \1231\ We recently decommissioned the Pre-Submission Validation 
Application (PSVA) tool within the HQR System because the system 
itself now performs the same functions that the PSVA tool previously 
did.
---------------------------------------------------------------------------

(4) Submission Deadlines for Hybrid Measures
    We refer readers to the FY 2020 IPPS/LTCH PPS final rule (84 FR 
42508), where we finalized submission deadlines for hybrid measures. We 
did not propose any changes to these policies in the proposed rule.
g. Sampling and Case Thresholds for Chart-Abstracted Measures
    We refer readers to the FY 2011 IPPS/LTCH PPS final rule (75 FR 
50221), the FY 2012 IPPS/LTCH PPS final rule (76 FR 51641), the FY 2013 
IPPS/LTCH PPS final rule (77 FR 53537), the FY 2014 IPPS/LTCH PPS final 
rule (78 FR 50819), and the FY 2016 IPPS/LTCH PPS final rule (80 FR 
49709) for details on our sampling and case thresholds for the FY 2016 
payment determination and subsequent years. We did not propose any 
changes to these policies in the proposed rule.
h. HCAHPS Administration and Submission Requirements
    We refer readers to the FY 2011 IPPS/LTCH PPS final rule (75 FR 
50220), the FY 2012 IPPS/LTCH PPS final rule (76 FR 51641 through 
51643), the FY 2013 IPPS/LTCH PPS final rule (77 FR 53537 through 
53538), and the FY 2014 IPPS/LTCH PPS final rule (78 FR 50819 through 
50820) for details on previously-adopted HCAHPS submission 
requirements. We also refer hospitals and HCAHPS Survey vendors to the 
official HCAHPS website at http://www.hcahpsonline.org for new 
information and program updates regarding the HCAHPS Survey, its 
administration, oversight, and data adjustments. We did not propose any 
changes to these policies in the proposed rule.
i. Data Submission Requirements for Structural Measures
    We refer readers to the FY 2012 IPPS/LTCH PPS final rule (76 FR 
51643 through 51644) and the FY 2013 IPPS/LTCH PPS final rule (77 FR 
53538 through 53539) for details on the data submission requirements 
for structural measures. Hospitals are required to submit information 
for structural measures once annually via a CMS-approved web-based data 
collection tool available via the QualityNet Secure Portal (also 
referred to as the Hospital Quality Reporting system secure portal). 
The data submission period for structural measures begins in April 
until the same submission deadline as for the fourth calendar quarter 
of the chart-abstracted measures with respect to the reporting period 
for the previous calendar year. For example, for the FY 2024 payment 
determination, hospitals would be required to submit the required 
information between April 1, 2023 and May 15, 2023, with respect to the 
time period of January 1, 2022 through December 31, 2022.
    We refer readers to section VIII.C.5.a. of the preamble of this 
final rule, where we are finalizing the adoption of the Maternal 
Morbidity Structural Measure. For the Maternal Morbidity Structural 
Measure and the CY 2021 reporting period/FY 2023 payment determination 
only, we proposed and are finalizing a shortened reporting period from 
October 1, 2021 through December 31, 2021, while retaining the standard 
data submission period. Specifically, for the shortened reporting 
period hospitals will be required to submit the data between April 1, 
2022 and May 16, 2022 (we note that May 15, 2022 falls on a weekend and 
therefore the close of this data submission period is moved to May 16, 
2022).
    Thereafter, as described in section VIII.C.5.a. of the preamble of 
this final rule, the reporting period for the Maternal Morbidity 
Structural Measure will run from: January 1 through December 31 on an 
annual basis, and that the data submission period will continue to be 
consistent with our current policy (beginning in April until the same 
submission deadline as for the fourth calendar quarter of the chart-
abstracted measures with respect to the reporting period for the 
previous calendar year).
j. Data Submission and Reporting Requirements for CDC NHSN Measures
    For details on the data submission and reporting requirements for 
measures reported via the CDC's National Healthcare Safety Network 
(NHSN), we refer readers to the FY 2012 IPPS/LTCH PPS final rule (76 FR 
51629 through 51633; 51644 through 51645), the FY 2013 IPPS/LTCH PPS 
final rule (77 FR 53539), the FY 2014 IPPS/LTCH PPS final rule (78 FR 
50821 through 50822), and the FY 2015 IPPS/LTCH PPS final rule (79 FR 
50259 through 50262). The data submission deadlines are posted on the 
QualityNet website.
    In addition, we refer readers to section VIII.C.5.c. of the 
preamble of this final rule for more detail on our finalized proposal 
to adopt the COVID-19 Vaccination Coverage Among HCP measure, which 
requires facilities to report data on the number of HCP who have 
received the full regimen of a COVID-19 vaccine through the CDC's NHSN. 
Specific details on data submission for this measure can be found in 
the CDC's Overview of the Healthcare Safety Component, available at 
https://www.cdc.gov/nhsn/PDFs/slides/NHSN-Overview-HPS_Aug2012.pdf. For 
this measure, we will require reporting a single vaccination count for 
each healthcare facility by each individual facility's CMS 
Certification Number (CCN). For each CMS CCN, a percentage of the HCP 
who received a complete course of the COVID-19 vaccination will be 
calculated and publicly reported on the Care Compare website, so that 
the public will know what percentage of the HCP have been vaccinated in 
each hospital.
    Consistent with our adopted policies for CDC NHSN measures in the 
Hospital IQR Program, hospitals will report the measure through the 
NHSN web-based surveillance system.\1232\ Specifically, hospitals will 
use the COVID-19 vaccination data reporting modules in the NHSN 
Healthcare Personnel Safety (HPS) Component to report the number of HCP 
eligible to have worked at the facility during the self-selected week 
(denominator) and the number of those HCP who have received COVID-19 
vaccination (numerator).
---------------------------------------------------------------------------

    \1232\ Centers for Disease Control and Prevention. Surveillance 
for Weekly HCP COVID-19 Vaccination. Accessed at: https://www.cdc.gov/nhsn/hps/weekly-covid-vac/index.html on February 10, 
2021.
---------------------------------------------------------------------------

    For the COVID-19 HCP Vaccination measure, we proposed that 
hospitals would collect the numerator and denominator for the COVID-19 
HCP vaccination measure for at least one self-

[[Page 45423]]

selected week during each month of the reporting quarter and submit the 
data to the NHSN Healthcare Personal Safety (HPS) Component before the 
quarterly deadline to meet Hospital IQR Program requirements, beginning 
in October 2021 for the October 1, 2021 through December 31, 2021 
reporting period affecting FY 2023 payment determination and continuing 
for each quarter in subsequent years. If a hospital submits more than 
one week of data in a month, the most recent week's data would be used 
to calculate the measure. For example, if first and third week data are 
submitted, third week data would be used. If first, second, and fourth 
week data are submitted, fourth week data would be used. We proposed 
that for each quarter, the CDC would calculate a single quarterly 
COVID-19 HCP vaccination coverage rate for each hospital by taking the 
average of the data from the three weekly rates submitted by the 
hospital for that quarter. CMS will publicly report each quarterly 
COVID-19 HCP vaccination coverage rate as calculated by the CDC.
    We invited public comment on this proposal.
    Comment: Many commenters expressed concern about reporting using 
the NHSN and noted that hospitals may be required to report COVID-19 
vaccination data in multiple reporting systems. Some commenters 
requested CMS align with other HHS reporting systems, including HHS 
TeleTracking, and state reporting requirements to reduce burdensome 
duplicative reporting.
    Response: We recognize that this measure may lead to duplicative 
reporting if hospitals voluntarily report COVID-19 HCP vaccination 
information to other data reporting systems in addition to the NHSN per 
Hospital IQR Program requirements. We are collaborating with other HHS 
agencies, including the CDC, to minimize reporting burden to the extent 
feasible.
    Comment: Many commenters asserted that the frequency of reporting 
for the measure is overly burdensome. Some commenters recommended that 
hospitals report data once per quarter instead of one week per month.
    Response: We appreciate commenters' concerns regarding reporting 
frequency; however, we respectfully disagree that the frequency is 
overly burdensome or that hospitals should report once per quarter 
instead of one week per month, because we believe that important public 
health initiatives currently outweigh the burden. We proposed that 
hospitals report at least one self-selected week during each month of 
the reporting quarter and submit the data to the NHSN Healthcare 
Personal Safety (HPS) Component before the quarterly deadline. We 
proposed that for each quarter, the CDC would calculate a single 
quarterly COVID-19 HCP vaccination coverage rate for each hospital by 
taking the average of the data from the three weekly rates submitted by 
the hospital for that quarter. We believe that, given the public health 
importance of vaccination in addressing the COVID-19 PHE, the benefits 
of requiring reporting outweigh the burden. We believe that reporting 
these data on a frequent interval would increase their value by 
allowing the CDC to better track these important public health data 
while also being a valuable quality measure that supports consumer 
choice and hospital improvement initiatives. Because the CDC requests 
data reported on a monthly basis for one week per month, we believe 
this is an appropriate reporting frequency for our quality measure to 
ensure that hospitals do not have duplicative reporting requirements to 
meet the CDC's need for public health data and CMS' quality measure 
reporting requirements.
    Comment: A few commenters suggested that because the measure will 
provide information for a single point in time, it will quickly become 
outdated in the rapidly changing COVID-19 landscape, and thus would not 
be meaningful, nor would it reflect safety or quality of care. A 
commenter requested that CMS reconsider how the measure is calculated 
for public reporting. The commenter supported the concept of reporting 
one quarter of data. They recommend that after the first refresh, 
rather than calculating a summary measure of the COVID-19 vaccination 
coverage from the 3 monthly modules of data reported for the quarter 
during each refresh and adding one additional quarter of data to the 
measure calculation during each advancing refresh, until the point that 
four full quarters of data is reached, to use an alternate approach. 
They recommend updating the information monthly with only the most 
recent data, such that the measure would be consumed as the most recent 
quarter of data refreshed quarterly. They caution that averaging over 
12 months would result in the dilution of the most recent, and 
potentially more meaningful information, and may actually discourage 
higher provider vaccine uptake rates since it would be harder to change 
performance on this measure.
    Response: We refer readers to section IX.C.5.c. of this final rule 
for more details, where we are finalizing a modified version of our 
proposal. Based on public comment, we are not finalizing our proposal 
to add one additional quarter of data during each advancing refresh, 
until the point that four full quarters of data is reached and then 
report the measure using four rolling quarters of data. Instead, we 
will only report the most recent quarter of data. This would result in 
more meaningful information that is up to date and not diluted with 
older data.
    Comment: A few commenters suggested that CMS permit reporting of 
measure data in other systems or programs, including state-level 
reporting systems. These commenters supported data collection through 
the NHSN, but recommended it would be more appropriately captured 
through reporting programs other than the Hospital IQR Program.
    Response: We thank the commenters for their recommendation. We 
believe that it is appropriate to report measure data through the NHSN 
for use in the Hospital IQR Program as hospitals have regular 
experience with NHSN to currently report HAIs and previously used the 
NHSN to report the Influenza Vaccination Coverage Among HCP (NQF #0431) 
measure, and that this measure is an appropriate addition to the 
program given the vulnerability of patients receiving care in inpatient 
hospitals and the importance of reducing transmission of COVID-19 among 
HCP and between HCP and patients. We note that this measure is also 
being finalized in a number of other quality programs based in 
different healthcare settings and aligned for reporting via NHSN, 
including the Inpatient Psychiatric Facility (IPF) Quality Reporting 
Program (FY 2022 IPF PPS final rule) as well as the PPS-Exempt Cancer 
Hospital (PCH) Quality Reporting Program and LTCH Quality Reporting 
Program discussed in section IX.D.5.a and IX.E.4.a, respectively, in 
this FY 2022 IPPS/LTCH PPS final rule.
    As discussed in section IX.C.5.c. of this final rule, we are 
finalizing this measure with one modification to public reporting. We 
are not finalizing our plan to add one additional quarter of data 
during each advancing refresh, until the point that four full quarters 
of data is reached and then report the measure using four rolling 
quarters of data. Instead, we will only report the most recent quarter 
of data.
10. Validation of Hospital IQR Program Data
    In the FY 2022 IPPS/LTCH PPS proposed rule (86 FR 25598 through 
25600), we proposed changes to our Educational Review Process to extend 
the effects of the educational review

[[Page 45424]]

policy beginning with validations affecting the FY 2024 payment 
determination and for subsequent years. Previously we could only 
correct scores for the first 3 quarters of validation due to the 
inability to calculate the confidence interval in a timely manner for 
the 4th quarter of validation. We now believe it is feasible to 
calculate the confidence interval and use the corrected scores 
identified through an educational review for all 4 quarters of 
validation for chart-abstracted measures. This finalized update is 
described in detail in this section.
a. Background
    We refer readers to the FY 2013 IPPS/LTCH PPS final rule (77 FR 
53539 through 53553), the FY 2014 IPPS/LTCH PPS final rule (78 FR 50822 
through 50835), the FY 2015 IPPS/LTCH PPS final rule (79 FR 50262 
through 50273), the FY 2016 IPPS/LTCH PPS final rule (80 FR 49710 
through 49712), the FY 2017 IPPS/LTCH PPS final rule (81 FR 57173 
through 57181), the FY 2018 IPPS/LTCH PPS final rule (82 FR 38398 
through 38403), the FY 2019 IPPS/LTCH PPS final rule (83 FR 41607 
through 41608), and the FY 2021 IPPS/LTCH PPS final rule (85 FR 58942 
through 58953) for detailed information on chart-abstracted and eCQM 
validation processes and previous updates to these processes for the 
Hospital IQR Program.
    We refer readers to the FY 2021 IPPS/LTCH PPS final rule (85 FR 
58952) where we summarized our validation policies in the following 
table:
[GRAPHIC] [TIFF OMITTED] TR13AU21.286

b. Educational Review Process
(1) Chart-Abstracted Measures
(a) Background
    In the FY 2015 IPPS/LTCH PPS final rule (79 FR 50260), we 
established an educational review process for validation of chart-
abstracted measures. The process was subsequently updated in the FY 
2018 IPPS/LTCH PPS final rule (82 FR 38402 through 38403). Under our 
educational review process, hospitals may request an educational review 
if they believe they have been scored incorrectly or if they have 
questions about their validation results. Approximately 4 months after 
each quarter's validation submission deadline, validation results for 
chart-abstracted measures for the quarter are posted on the QualityNet 
Secure Portal (also referred to as the Hospital Quality Reporting (HQR) 
System). Hospitals have 30 calendar days following the date validation 
results are posted to identify any potential CDAC or CMS errors for the 
first three quarters of validation results and contact the Validation 
Support Contractor (VSC) to request an educational review. Upon receipt 
of an educational review request, we review the data elements 
identified in the request, as well as the written justifications 
provided by the hospital. We provide the results of an educational 
review, outlining the findings of whether the scores were correct or 
incorrect, to the requesting hospital through a CMS-approved secure 
file transmission process (82 FR 38402).
    If an educational review yields incorrect validation results for 
chart-abstracted measures, we use the corrected quarterly score, as 
recalculated during the educational review process to compute the final 
confidence interval (82 FR 38402). We use the revised score identified 
through an educational review when determining whether or not a 
hospital failed validation (82 FR 38402). Corrected scores, however, 
are only used if they indicate that the hospital performed more 
favorably than previously determined (82 FR 38402). We note that 
corrections only occur to calculations, not to the underlying measure 
data (82 FR 38402). Under the current policy, for the last quarter of 
validation for chart-abstracted measures, because of the need to 
calculate the confidence interval in a timely manner and the 
insufficient time available to conduct educational reviews, no 
educational reviews are available (82 FR 38403). The existing 
reconsideration process would be used to dispute an unsatisfactory 
validation result.
    In the FY 2021 IPPS/LTCH PPS final rule, we finalized several 
policies to incrementally align the validation processes for chart-
abstracted measure data and eCQM data in a stepwise process in the 
Hospital IQR Program (85 FR 58942 through 58952). As part of this 
policy, we updated the quarters of data required for validation for 
both chart-abstracted measures and eCQMs as summarized in these charts:

[[Page 45425]]

[GRAPHIC] [TIFF OMITTED] TR13AU21.287

[GRAPHIC] [TIFF OMITTED] TR13AU21.288

[GRAPHIC] [TIFF OMITTED] TR13AU21.289

(b) Extending the Effects of the Educational Review Policy Beginning 
With Validations Affecting the FY 2024 Payment Determination and 
Subsequent Years
    In light of the most recently finalized quarters included in 
validation, we proposed to extend the effects of the educational review 
policy beginning with validations affecting the FY 2024 payment 
determination and for subsequent years. As previously noted, in the 
past we could only correct scores for the first three quarters of 
validation due to the inability to calculate the confidence interval in 
a timely manner for the 4th quarter of validation. We now believe it is 
feasible to calculate the confidence interval and use the corrected 
scores identified through an educational review for all four quarters 
of validation for chart-abstracted measures, because the quarters used 
for validation are now early enough to calculate the confidence 
interval for the fourth quarter of validation in a timely manner. 
Specifically, under our previous policy, the quarters used for 
validation for the FY 2024 payment determination would have been 3Q 
2021, 4Q 2021, 1Q 2022 and 2Q 2022. Under the most recently finalized 
policy, the quarters used for validation for the FY 2024 payment 
determination are 1Q 2021, 2Q 2021, 3Q 2021, and 4Q 2021. Therefore, we 
proposed to extend the effects of educational reviews for 4th quarter 
data such that if an error is identified during the education review 
process for 4th quarter data, we would use the corrected quarterly 
score to compute the final confidence interval used for payment 
determination.
    All previously finalized policies with respect to education reviews 
would apply, such that approximately four months after each quarter's 
validation submission deadline, validation results for chart-abstracted 
measures for the quarter are posted on the QualityNet Secure Portal 
(also referred to as the Hospital Quality Reporting (HQR) System). 
Hospitals have 30 calendar days following the date validation results 
are posted to identify any potential CDAC or CMS errors for the first 
three quarters of validation results and contact the Validation Support 
Contractor (VSC) to request an educational review. Upon receipt of an 
educational review request, we review the data elements identified in 
the request, as well as the written justifications provided by the 
hospital. We provide the results of an educational review, outlining 
the findings of whether the scores were correct or incorrect, to the 
requesting hospital through a CMS-approved secure file transmission 
process (82 FR 38402). If an educational review yields incorrect 
validation results for chart-abstracted measures, we use the corrected 
quarterly score, as recalculated during the educational review process 
to compute the final confidence interval (82 FR 38402). We use the 
revised score identified through an educational review when determining 
whether or not a hospital failed validation (82 FR 38402). Corrected 
scores, however, are only used if they indicate that the hospital 
performed more favorably than previously determined (82 FR 38402). We 
note that corrections only occur to calculations, not to the underlying 
measure data (82 FR 38402). We also note that under our proposal, as is 
currently the process, the quarterly validation reports for the chart-
abstracted measures validation issued to hospitals would not be changed 
to reflect the updated score due to the burden associated with 
reissuing corrected reports (82 FR 38402).
    In addition, our proposal did not apply to the educational review 
process for eCQMs, which is discussed in the next section.
    We invited public comment on our proposal.
    Comment: A commenter supported our proposal because it believes 
that the changes will help ensure accurate reporting.
    Response: We thank the commenter for its support.
    After consideration of the public comment we received, we are 
finalizing our proposal as proposed.

[[Page 45426]]

(2) Educational Review Process for eCQMs for Validation Affecting the 
FY 2023 Payment Determination and Subsequent Years
    We refer readers to the FY 2021 IPPS/LTCH PPS (85 FR 58953) final 
rule where we finalized an educational review process for eCQM 
validation beginning with validations affecting the FY 2023 payment 
determination and for subsequent years (that is, starting with data 
from CY 2020). Under that process, hospitals receive eCQM validation 
results on an annual basis, and have the opportunity to request an 
educational review once annually following receipt of their results (85 
FR 58953). We did not propose any changes to these policies in the 
proposed rule.
11. Data Accuracy and Completeness Acknowledgement (DACA) Requirements
    We refer readers to the FY 2013 IPPS/LTCH PPS final rule (77 FR 
53554) for previously adopted details on DACA requirements. We did not 
propose any changes to the policy in the proposed rule.
12. Public Display Requirements
a. Background
    Section 1886(b)(3)(B)(viii)(VII) of the Act requires the Secretary 
to report quality measures of process, structure, outcome, patients' 
perspectives on care, efficiency, and costs of care that relate to 
services furnished in inpatient settings in hospitals on the internet 
website of CMS. Section 1886(b)(3)(B)(viii)(VII) of the Act also 
requires that the Secretary establish procedures for making information 
regarding measures available to the public after ensuring that a 
hospital has the opportunity to review its data before they are made 
public. Our current policy is to report data from the Hospital IQR 
Program as soon as it is feasible on CMS websites such as the Care 
Compare website, or its successor website, after a 30-day preview 
period (78 FR 50776 through 50778). We refer readers to the FY 2008 
IPPS/LTCH PPS final rule (72 FR 47364), the FY 2011 IPPS/LTCH PPS final 
rule (75 FR 50230), the FY 2012 IPPS/LTCH PPS final rule (76 FR 51650), 
the FY 2013 IPPS/LTCH PPS final rule (77 FR 53554), the FY 2014 IPPS/
LTCH PPS final rule (78 FR 50836), the FY 2015 IPPS/LTCH PPS final rule 
(79 FR 50277), the FY 2016 IPPS/LTCH PPS final rule (80 FR 49712 
through 49713), the FY 2018 IPPS/LTCH PPS final rule (82 FR 38403 
through 38409), the FY 2019 IPPS/LTCH PPS final rule (83 FR 41538 
through 41539), and the FY 2021 IPPS/LTCH PPS final rule (85 FR 58953) 
for details on public display requirements. The Hospital IQR Program 
quality measures are typically reported on the Care Compare website at 
https://www.medicare.gov/care-compare, or on other CMS websites such 
as: medicare.gov/care-compare. We did not propose any changes to these 
policies in the proposed rule. However, we refer readers to section 
IX.9.j., where we are finalizing a modified version of our proposed 
public reporting policy for the COVID-19 Vaccination Among HCP measure.
b. Public Reporting of eCQM Data
    We direct readers to the FY 2021 IPPS/LTCH PPS final rule (85 FR 
58954 through 58959) where we finalized public reporting requirements 
of eCQM data reported by hospitals for the CY 2021 reporting period/FY 
2023 payment determination and for subsequent years. We note that this 
policy incrementally increases the eCQM data publicly reported to four 
quarters of data for the CY 2023 reporting period/FY 2025 payment 
determination and subsequent years. We did not propose any changes to 
these policies in the proposed rule.
c. Overall Hospital Star Ratings
    In the CY 2021 OPPS/ASC final rule with comment period and interim 
final rule with comment period (85 FR 86193 through 86236), we 
finalized a methodology to calculate the Overall Hospital Quality Star 
Rating (Overall Star Ratings). The Overall Star Ratings will utilize 
data collected on hospital inpatient and outpatient measures that are 
publicly reported on a CMS website, including data from the Hospital 
IQR Program. We refer readers to section XVI. of the CY 2021 OPPS/ASC 
final rule with comment period for details. We did not propose any 
changes to these policies in the proposed rule.
13. Reconsideration and Appeal Procedures
    We refer readers to the FY 2012 IPPS/LTCH PPS final rule (76 FR 
51650 through 51651), the FY 2014 IPPS/LTCH PPS final rule (78 FR 
50836), and 42 CFR 412.140(e) for details on reconsideration and appeal 
procedures for the FY 2017 payment determination and subsequent years. 
We did not propose any changes to these policies in the proposed rule.
14. Hospital IQR Program Extraordinary Circumstances Exceptions (ECE) 
Policy
    We refer readers to the FY 2012 IPPS/LTCH PPS final rule (76 FR 
51651 through 51652), the FY 2014 IPPS/LTCH PPS final rule (78 FR 50836 
through 50837), the FY 2015 IPPS/LTCH PPS final rule (79 FR 50277), the 
FY 2016 IPPS/LTCH PPS final rule (80 FR 49713), the FY 2017 IPPS/LTCH 
PPS final rule (81 FR 57181 through 57182), the FY 2018 IPPS/LTCH PPS 
final rule (82 FR 38409 through 38411), and 42 CFR 412.140(c)(2) for 
details on the current Hospital IQR Program ECE policy. We also refer 
readers to the QualityNet website at: http://www.QualityNet.cms.gov for 
our current requirements for submission of a request for an exception. 
We did not propose any changes to the policies in the proposed rule.

D. Updates to the PPS-Exempt Cancer Hospital Quality Reporting (PCHQR) 
Program

1. Background
    The PPS-Exempt Cancer Hospital Quality Reporting (PCHQR) Program is 
authorized by section 1866(k) of the Act and applies to hospitals 
described in section 1886(d)(1)(B)(v) (referred to as ``PPS-Exempt 
Cancer Hospitals'' or ``PCHs''). For additional background information, 
including previously finalized measures and other policies for the 
PCHQR Program, we refer readers to all of the following final rules:
     The FY 2013 IPPS/LTCH PPS final rule (77 FR 53555 through 
53567).
     The FY 2014 IPPS/LTCH PPS final rule (78 FR 50837 through 
50853).
     The FY 2015 IPPS/LTCH PPS final rule (79 FR 50277 through 
50286).
     The FY 2016 IPPS/LTCH PPS final rule (80 FR 49713 through 
49723).
     The FY 2017 IPPS/LTCH PPS final rule (81 FR 57182 through 
57193).
     The FY 2018 IPPS/LTCH PPS final rule (82 FR 38411 through 
38425).
     The FY 2019 IPPS/LTCH PPS final rule (83 FR 41609 through 
41624).
     The CY 2019 OPPS/ASC final rule with comment period (83 FR 
59149 through 59154).
     The FY 2020 IPPS/LTCH PPS final rule (84 FR 42509 through 
42524).
     The FY 2021 IPPS/LTCH PPS final rule (85 FR 58959 through 
58966).
2. Overview of Proposed Updates to the PCHQR Program and Requests for 
Information
    In section IX.D.4. of the proposed rule, we proposed to remove the 
Oncology: Plan of Care for Pain--Medical Oncology and Radiation 
Oncology (NQF #0383) (PCH-15) measure beginning with the FY 2024 
program year (86 FR 25602). In section IX.D.5. of the preamble of the 
proposed rule, we proposed to adopt the COVID-19 Vaccination Coverage 
Among

[[Page 45427]]

Healthcare Personnel measure, beginning with the FY 2023 program year 
and for subsequent years (86 FR 25602 through 25605). In section 
I.X.D.9. of the preamble of the proposed rule, we proposed to update 
our terminology for this program by replacing the term ``QualityNet 
Administrator'' with ``QualityNet security official'' (86 FR 25607). In 
section IX.D.11. of the proposed rule, we proposed to codify existing 
PCHQR Program policies at 42 CFR 412.23(f)(3) and 42 CFR 412.24 (86 FR 
25607 through 25608).
    In section IX.D.2. of the preamble of the proposed rule, we also 
referred readers to section IX.B. of the preamble of the proposed rule 
(86 FR 25554 through 25561), Closing the Health Equity Gap in CMS 
Quality Programs--A Request for Information, where we requested 
information on our Equity Plan for Improving Quality in Medicare, which 
outlines our commitment to closing the health equity gap through 
improved data collection in order to better measure and analyze 
disparities across programs and policies. The request for information 
asked for public comment regarding the potential stratification of 
quality measure results by race and ethnicity and the potential 
creation of a hospital equity score in CMS quality reporting and value-
based purchasing programs, including the PCHQR Program.
    In section IX.D.2. of the preamble of the proposed rule, we also 
referred readers to section IX.A. of the preamble of the proposed rule 
(86 FR 25549 through 25554), where we requested information on 
potential actions we can take to expand the use of the FHIR standard 
(as described in that section) in furtherance of our goal to move fully 
to digital quality measurement in CMS quality reporting programs, 
including the PCHQR Program, and value-based purchasing programs by 
2025.
3. Measure Retention and Removal Factors for the PCHQR Program
    For a detailed discussion regarding our retention and removal 
factors, we refer readers to the FY 2017 IPPS/LTCH PPS final rule (81 
FR 57182 through 57183), where we adopted policies for measure 
retention and removal, and the FY 2019 IPPS/LTCH PPS final rule (83 FR 
41609 through 41611), where we updated our measure removal factors. We 
did not propose any changes to these policies in the proposed rule.
4. Removal of the Oncology: Plan of Care for Pain--Medical Oncology and 
Radiation Oncology (NQF #0383) (PCH-15) Measure From the PCHQR Program 
Beginning With the FY 2024 Program Year
    We proposed to remove the Oncology: Plan of Care for Pain--Medical 
Oncology and Radiation Oncology (NQF #0383) (PCH-15) (``Oncology: Plan 
of Care for Pain'') measure from the PCHQR Program beginning with the 
FY 2024 program year based on Factor-7: It is not feasible to implement 
the measure specifications (86 FR 25602). We first adopted the 
Oncology: Plan of Care for Pain measure for the FY 2016 program year in 
the FY 2014 IPPS/LTCH PPS final rule (78 FR 50842 through 50843) and we 
refer readers to this rule for a detailed discussion of the measure. We 
stated in the proposed rule that although we continue to believe the 
Oncology: Plan of Care for Pain measure provides important data for 
patients and hospitals in making decisions about care and informing 
quality improvement efforts, the measure steward has decided to revert 
to a previous version of the measure that requires a plan of care to 
address any, rather than just moderate-severe, pain and will no longer 
maintain the specifications for this measure as it is currently used in 
the PCHQR Program. In addition, the version of the measure that the 
measure steward has decided to revert to is designed to be paired with 
the Medical and Radiation--Pain Intensity Quantified (PCH-16/NQF #0384) 
measure (78 FR 50843), meaning they were developed to be used together 
(77 FR 53649). The Medical and Radiation--Pain Intensity Quantified 
(PCH-16/NQF #0384) measure was removed from the PCHQR Program's measure 
set beginning with the FY 2021 program year in the FY 2019 IPPS/LTCH 
PPS final rule because it was topped-out (83 FR 41611 through 41613).
    We stated in the proposed rule that through our Meaningful Measures 
Framework, we continue to focus on proposing quality measures that will 
reduce reporting and regulatory burden on providers and accelerate the 
move to fully digital measures.\1233\ In the FY 2014 IPPSLTCH PPS final 
rule, we stated our intention to simplify measure collection and 
submission, and to reduce the reporting burden of chart-abstracted 
measures (78 FR 50810). PCH-15 requires manual chart-abstraction, and 
we stated that we believed this proposal to remove it is aligned with 
the goals of the Meaningful Measures Initiative and a shift toward the 
use of digital quality measures. Further, the PCH-15 measure's mean and 
median for the past four years, including FY 2020, demonstrate very 
high performance with little variation among the 11 PCHs. Accordingly, 
because the version of the Oncology: Plan of Care for Pain measure that 
is currently used in the PCHQR Program will no longer be maintained by 
the measure steward, data show high performance on the measure with 
little variation, the updated version of the measure is designed to be 
used with the PCH-16 measure that we previously removed because it was 
topped-out, and the removal of chart-abstracted measures aligns with 
CMS goals to move to digital quality measures, we proposed to remove 
the Oncology: Plan of Care for Pain measure from the PCHQR measure set.
---------------------------------------------------------------------------

    \1233\ CMS List of Measures under Consideration for December 21, 
2020. Accessed March 12, 2021. https://www.cms.gov/files/document/measures-under-consideration-list-2020-report.pdf.
---------------------------------------------------------------------------

    We invited public comment on our proposal to remove the Oncology: 
Plan of Care for Pain--Medical Oncology and Radiation Oncology (NQF 
#0383) (PCH-15) measure from the PCHQR Program beginning with the FY 
2024 program year.
    Comment: A commenter supported the removal of the PCH-15 measure 
from the PCHQR measure set. The commenter further encouraged CMS to 
develop and include meaningful pain measures in the PCHQR Program in 
the future.
    Response: We thank the commenter for its support of our proposal. 
We agree that actionable pain measures can provide important data for 
patients and hospitals in making decisions about care and informing 
quality improvement efforts and will consider their inclusion in the 
program in the future.
    Comment: A few commenters opposed the removal of the Oncology: Plan 
of Care for Pain (PCH-15) Measure. Those commenters stated that the 
measure steward's decision to revert to an older version of the measure 
was appropriate because a care plan for any pain is necessary, not just 
moderate to severe pain, and that measuring pain is important to 
managing quality of life for cancer patients and the commenters 
believed that the measure should be updated and retained in the PCHQR 
Program. A commenter was concerned that the removal of the measure 
would undermine pain care and result in worse outcomes.
    Response: We appreciate commenters' concerns and agree that 
appropriate pain management is important for patients receiving care in 
PCHs. As we noted in the proposed rule, the PCH-15

[[Page 45428]]

measure has shown consistently high performance across the 11 PCHs. We 
believe the consistency across all PCHs demonstrates their commitment 
to appropriate pain management for cancer patients and we believe this 
work will continue in the absence of this measure. We do not believe 
that removing the measure will result in worse patient outcomes.
    Comment: A few commenters recommended that CMS retain the PCH-15 
measure and reintroduce the Oncology: Medical and Radiation--Pain 
Intensity Quantified (PCH-16/NQF #0384) Measure, noting that these 
measures were intended to be reported together. A commenter stated that 
the PCH-16 measure was removed from the PCHQR measure set because it 
was topped-out but asserted that this is only the case when the measure 
is manually reported instead of extracted from electronic health 
records or claims. A few commenters noted that both the PCH-15 and PCH-
16 measures are currently reported in the Merit-based Incentive Payment 
System (MIPS), the Oncology Care Model (OCM), and the Radiation 
Oncology (RO) Model and suggested that retaining these measures in the 
PCHQR measure set would promote program alignment. Another commenter 
stated that both measures have been used since the Physician Quality 
Reporting System (PQRS) was introduced. A commenter noted that the NQF 
has endorsed both the PCH-15 and PCH-16 measures within the past year.
    Response: We appreciate commenters' suggestions to reintroduce the 
PCH-16 measure. We also recognize that the measure, along with the PCH-
15 measure, continues to be used in other quality reporting programs 
and was recently re-endorsed by the NQF. We considered retaining the 
PCH-15 measure and reintroducing the PCH-16 measure. However, as we 
noted in the FY 2019 IPPS/LTCH final rule, we removed the PCH-16 
measure because it did not align with our policy goal to focus on 
outcome measures and did not support efforts to develop electronic 
clinical quality measure (eCQM) reporting for PCHs as part of our 
Meaningful Measures Framework \1234\ (83 FR 41612). While we 
acknowledge that both measures are included in other quality reporting 
programs and that the measures are intended to be reported together, we 
note that the measure steward has reverted to a previous version of the 
measure and will no longer maintain the specifications for this measure 
as it is currently used in the PCHQR Program. We proposed to remove the 
PCH-15 measure because the benefits of retaining it have lessened and 
the measure steward has decided to revert to a previous version of the 
measure that requires a plan of care to address any, rather than just 
moderate-severe, pain and will no longer maintain the specifications 
for this measure as it is currently used in the PCHQR Program.
---------------------------------------------------------------------------

    \1234\ https://www.cms.gov/meaningful-measures-20-moving-measure-reduction-modernization.
---------------------------------------------------------------------------

    We acknowledge the comment that reporting the PCH-16 measure 
manually versus electronically or via claims would impact whether the 
measure is topped-out and will consider this information in the 
development of new measures for the PCHQR Program. We did not propose 
reintroducing the PCH-16 measure and retaining the PCH-15 measure in 
the proposed rule, and we believe the removal is justified given the 
high performance of PCHs on the measure in the PCHQR Program and the 
burden of reporting chart-abstracted measures.
    After consideration of the public comments we received, we are 
finalizing the removal of the Oncology: Plan of Care for Pain--Medical 
Oncology and Radiation Oncology (NQF #0383) (PCH-15) measure from the 
PCHQR Program beginning with the FY 2024 program year, without 
modification.
5. Adoption of the COVID-19 Vaccination Coverage Among Health Care 
Personnel (HCP) Measure Beginning With the FY 2023 Program Year
a. Background
    On January 31, 2020, the Secretary declared a public health 
emergency (PHE) for the United States in response to the global 
outbreak of SARS-CoV-2, a novel (new) coronavirus that causes a disease 
named ``coronavirus disease 2019'' (COVID-19).\1235\ COVID-19 is a 
contagious respiratory illness \1236\ that can cause serious illness 
and death. Older individuals, racial and ethnic minorities, and those 
with underlying medical conditions are considered to be at higher risk 
for more serious complications from COVID-19.1237 1238
---------------------------------------------------------------------------

    \1235\ U.S. Dept of Health and Human Services, Office of the 
Assistant Secretary for Preparedness and Response. (2020). 
Determination that a Public Health Emergency Exists. Available at: 
https://www.phe.gov/emergency/news/healthactions/phe/Pages/2019-nCoV.aspx.
    \1236\ Centers for Disease Control and Prevention. (2020). Your 
Health: Symptoms of Coronavirus. Available at: https://www.cdc.gov/coronavirus/2019-ncov/symptoms-testing/symptoms.html.
    \1237\ Centers for Disease Control and Prevention. (2020). Your 
Health: Symptoms of Coronavirus. Available at https://www.cdc.gov/coronavirus/2019-ncov/symptoms-testing/symptoms.html.
    \1238\ Centers for Disease Control and Prevention. (2020). 
Health Equity Considerations and Racial and Ethnic Minority Groups. 
Available at: https://www.cdc.gov/coronavirus/2019-ncov/community/health-equity/race-ethnicity.html.
---------------------------------------------------------------------------

    As stated in the proposed rule, as of April 2, the U.S. had 
reported over 30 million cases of COVID-19 and over 550,000 COVID-19 
deaths. As of July 21, 2021, the U.S. has reported over 34 million 
cases of COVID 19 and over 607,000 COVID-19 deaths.\1239\ Hospitals and 
health systems saw significant surges of COVID-19 patients as community 
infection levels increased.\1240\ From December 2, 2020 to January 30, 
2021, more than 100,000 Americans were in the hospital with COVID-19 at 
the same time.\1241\
---------------------------------------------------------------------------

    \1239\ Centers for Disease Control and Prevention. (2021). CDC 
COVID Data Tracker: COVID-19 Vaccinations in the United States. 
Available at: https://covid.cdc.gov/covid-data-tracker/#vaccinations.
    \1240\ Associated Press. Tired to the Bone. Hospitals 
Overwhelmed with Virus Cases. November 18, 2020. Accessed on 
December 16, 2020, at https://apnews.com/article/hospitals-overwhelmed-coronavirus-cases-74a1f0dc3634917a5dc13408455cd895. Also 
see: New York Times. Just how full are U.S. intensive care units? 
New data paints an alarming picture. November 18, 2020. Accessed on 
December 16, 2020, at: https://www.nytimes.com/2020/12/09/world/just-how-full-are-us-intensive-care-units-new-data-paints-an-alarming-picture.html.
    \1241\ US Currently Hospitalized [verbar] The COVID Tracking 
Project. Accessed January 31, 2021 at: https://covidtracking.com/data/charts/us-currently-hospitalized.
---------------------------------------------------------------------------

    Evidence indicates that COVID-19 primarily spreads when individuals 
are in close contact with one another.\1242\ The virus is typically 
transmitted through respiratory droplets or small particles created 
when someone who is infected with the virus coughs, sneezes, sings, 
talks or breathes.\1243\ Thus, the CDC advises that infections mainly 
occur through exposure to respiratory droplets when a person is in 
close contact with someone who has COVID-19.1244 1245 
Experts believe that COVID-19 spreads less commonly through contact 
with a contaminated surface.\1246\ Subsequent to the publication of the

[[Page 45429]]

proposed rule, the CDC has confirmed that the three main ways that 
COVID-19 is spread are: (1) Breathing in air when close to an infected 
person who is exhaling small droplets and particles that contain the 
virus; (2) Having these small droplets and particles that contain virus 
land on the eyes, nose, or mouth, especially through splashes and 
sprays like a cough or sneeze; and (3) Touching eyes, nose, or mouth 
with hands that have the virus on them.\1247\ According to the CDC, 
those at greatest risk of infection are persons who have had prolonged, 
unprotected close contact (that is, within 6 feet for 15 minutes or 
longer) with an individual with confirmed COVID-19 infection, 
regardless of whether the individual has symptoms.\1248\ Although 
infections through inhalation at distances greater than six feet from 
an infectious source are less likely than at closer distances, the 
phenomenon has been repeatedly documented under certain preventable 
circumstances. These transmission events have involved the presence of 
an infectious person exhaling virus indoors for an extended time (more 
than 15 minutes and in some cases hours) leading to virus 
concentrations in the air space sufficient to transmit infections to 
people more than 6 feet away, and in some cases to people who have 
passed through that space soon after the infectious person left. 
Personal protective equipment (PPE) and other infection control 
precautions can reduce the likelihood of transmission in health care 
settings, but COVID-19 can still spread between health care personnel 
(HCP) and patients given the close contact that may occur during the 
provision of care.\1249\ The CDC has emphasized that health care 
settings, including long-term care settings, can be high-risk places 
for COVID-19 exposure and transmission.\1250\
---------------------------------------------------------------------------

    \1242\ Centers for Disease Control and Prevention. (2021). How 
COVID-19 Spreads. Accessed on April 3, 2021 at: https://www.cdc.gov/coronavirus/2019-ncov/prevent-getting-sick/how-covid-spreads.html.
    \1243\ Centers for Disease Control and Prevention. (2021). How 
COVID-19 Spreads. Accessed on April 3, 2021 at: https://www.cdc.gov/coronavirus/2019-ncov/prevent-getting-sick/how-covid-spreads.html.
    \1244\ Centers for Disease Control and Prevention (2021). How 
COVID-19 Spreads. Accessed on April 3, 2021 at: https://www.cdc.gov/coronavirus/2019-ncov/prevent-getting-sick/how-covid-spreads.html.
    \1245\ Centers for Disease Control and Prevention (2021). How 
COVID-19 Spreads. Accessed on April 3, 2021 at: https://www.cdc.gov/coronavirus/2019-ncov/prevent-getting-sick/how-covid-spreads.html.
    \1246\ Centers for Disease Control and Prevention. (2021). How 
COVID-19 Spreads. Accessed on April 3, 2021 at: https://www.cdc.gov/coronavirus/2019-ncov/prevent-getting-sick/how-covid-spreads.html.
    \1247\ Centers for Disease Control and Prevention. (2021). How 
COVID-19 Spreads. Accessed on July 15, 2021 at: https://www.cdc.gov/coronavirus/2019-ncov/prevent-getting-sick/how-covid-spreads.html.
    \1248\ Centers for Disease Control and Prevention. (2021). When 
to Quarantine. Accessed on April 2, 2021 at: https://www.cdc.gov/coronavirus/2019-ncov/if-you-are-sick/quarantine.html.
    \1249\ Centers for Disease Control and Prevention. (2020). 
Interim U.S. Guidance for Risk Assessment and Work Restrictions for 
Healthcare Personnel with Potential Exposure to COVID-19. Accessed 
on April 2 at: https://www.cdc.gov/coronavirus/2019-ncov/hcp/faq.html#Transmission.
    \1250\ Dooling, K, McClung, M, et al. ``The Advisory Committee 
on Immunization Practices' Interim Recommendations for Allocating 
Initial Supplies of COVID-19 Vaccine--United States, 2020.'' Morb 
Mortal Wkly Rep. 2020; 69(49): 1857-1859.
---------------------------------------------------------------------------

    Vaccination is a critical part of the nation's strategy to 
effectively counter the spread of COVID-19 and ultimately help restore 
societal functioning.\1251\ On December 11, 2020, the FDA issued the 
first Emergency Use Authorization (EUA) for a COVID-19 vaccine in the 
U.S.\1252\ Subsequently, the FDA issued EUAs for additional COVID-19 
vaccines.1253 1254
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    \1251\ Centers for Disease Control and Prevention. (2020). 
COVID-19 Vaccination Program Interim Playbook for Jurisdiction 
Operations. Accessed on December 18 at: https://www.cdc.gov/vaccines/imz-managers/downloads/COVID-19-Vaccination-Program-Interim_Playbook.pdf.
    \1252\ U.S. Food and Drug Administration. (2021). Pfizer-
BioNTech COVID-19 Vaccine. Available at https://www.fda.gov/emergency-preparedness-and-response/coronavirus-disease-2019-covid-19/pfizer-biontech-covid-19-vaccine. U.S. Food and Drug 
Administration. (2021). Pfizer-BioNTech COVID-19 Vaccine EUA Letter 
of Authorization. Available at https://www.fda.gov/media/150386/download.
    \1253\ U.S. Food and Drug Administration. (2021). Moderna COVID-
19 Vaccine EUA Letter of Authorization. Available at https://www.fda.gov/media/144636/download.
    \1254\ U.S. Food and Drug Administration. (2021). Janssen COVID-
19 Vaccine EUA Letter of Authorization. Available at https://www.fda.gov/media/146303/download.
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    As part of its national strategy to address COVID-19, the Biden 
Administration stated that it would work with states and the private 
sector to execute an aggressive vaccination strategy and outlined a 
goal of administering 200 million shots in 100 days.\1255\ After 
achieving this goal,\1256\ the Biden Administration announced a new 
goal to administer at least one COVID-19 vaccine shot to 70 percent of 
the U.S. adult population by July 4, 2021.\1257\ Although the goal of 
the U.S. government is to ensure that every American who wants to 
receive a COVID-19 vaccine can receive one, Federal agencies 
recommended that early vaccination efforts focus on those critical to 
the PHE response, including HCP providing direct care to patients with 
COVID-19, and individuals at highest risk for developing severe illness 
from COVID-19.\1258\ For example, the CDC's Advisory Committee on 
Immunization Practices (ACIP) recommended that HCP should be among 
those individuals prioritized to receive the initial, limited supply of 
the COVID-19 vaccine, given the potential for transmission in health 
care settings and the need to preserve health care system 
capacity.\1259\ Research suggests most states followed this 
recommendation,\1260\ and HCP began receiving the vaccine in mid-
December of 2020.\1261\
---------------------------------------------------------------------------

    \1255\ The White House. Remarks by President Biden on the COVID-
19 Response and the State of Vaccinations. Accessed on April 3, 2021 
at: https://www.whitehouse.gov/briefing-room/speeches-remarks/2021/03/29/remarks-by-president-biden-on-the-covid-19-response-and-the-state-of-vaccinations/.
    \1256\ The White House. Remarks by President Biden on the COVID-
19 Response and the State of Vaccinations. Accessed on June 2, 2021 
at: https://www.whitehouse.gov/briefing-room/speeches-remarks/2021/04/21/remarks-by-president-biden-on-the-covid-19-response-and-the-state-of-vaccinations-2/.
    \1257\ The White House. Remarks by President Biden on the COVID-
19 Response and the State of Vaccinations. Accessed on June 4, 2021, 
at: https://www.whitehouse.gov/briefing-room/statements-releases/2021/05/04/fact-sheet-president-biden-to-announce-goal-to-administer-at-least-one-vaccine-shot-to-70-of-the-u-s-adult-population-by-july-4th/.
    \1258\ Health and Human Services, Department of Defense. (2020) 
From the Factory to the Frontlines: The Operation Warp Speed 
Strategy for Distributing a COVID-19 Vaccine. Accessed December 18 
at: https://www.hhs.gov/sites/default/files/strategy-for-distributing-covid-19-vaccine.pdf; Centers for Disease Control 
(2020). COVID-19 Vaccination Program Interim Playbook for 
Jurisdiction Operations. Accessed December 18 at: https://www.cdc.gov/vaccines/imz-managers/downloads/COVID-19-Vaccination-Program-Interim_Playbook.pdf.
    \1259\ Dooling, K, McClung, M, et al. ``The Advisory Committee 
on Immunization Practices' Interim Recommendations for Allocating 
Initial Supplies of COVID-19 Vaccine--United States, 2020.'' Morb. 
Mortal Wkly Rep. 2020; 69(49): 1857-1859. ACIP also recommended that 
long-term care residents be prioritized to receive the vaccine, 
given their age, high levels of underlying medical conditions, and 
congregate living situations make them high risk for severe illness 
from COVID-19.
    \1260\ Kates, J, Michaud, J, Tolbert, J. ``How Are States 
Prioritizing Who Will Get the COVID-19 Vaccine First?'' Kaiser 
Family Foundation. December 14, 2020. Accessed on December 16 at 
https://www.kff.org/policy-watch/how-are-states-prioritizing-who-will-get-the-covid-19-vaccine-first/.
    \1261\ Associated Press. `Healing is Coming:' US Health Workers 
Start Getting Vaccine. December 15, 2020. Accessed on December 16 
at: https://apnews.com/article/us-health-workers-coronavirus-vaccine-56df745388a9fc12ae93c6f9a0d0e81f.
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    Frontline healthcare workers, such as those employed in PCHs, are 
being prioritized for vaccination in most locations. There are 
approximately 18 million healthcare workers in the United States.\1262\ 
As stated in the proposed rule, as of April 2, 2021, the CDC reported 
that over 162 million doses of COVID-19 vaccine had been administered, 
and approximately 60 million people had received full doses. As of July 
2, 2021, over 328 million doses of COVID-19 vaccine had been 
administered, and approximately 155.9 million people had received a 
complete vaccination course.\1263\ Subsequent to the publication of the 
proposed rule, on June 3, 2021 the White House confirmed that there was 
sufficient vaccine supply for all Americans.\1264\ We stated in the

[[Page 45430]]

proposed rule that we believe it is important to require that PCHs 
report their rates of HCP vaccination in order to assess whether they 
are taking steps to limit the spread of COVID-19 among their HCP, and 
to help sustain the ability of U.S. hospitals to continue serving their 
communities throughout the PHE and beyond. Therefore, we proposed a new 
measure, COVID-19 Vaccination Coverage Among HCP (COVID-19 vaccination 
measure), beginning with the FY 2023 program year. For that program 
year, PCHs would be required to report data on the measure for the 
fourth quarter of CY 2021 (that is, from October 2021 through December 
2021). For more information about the proposed reporting period, we 
referred readers to section IX.D.5.c. of the preamble of the proposed 
rule. We also proposed that the measure would assess the proportion of 
a PCH's HCP that has been vaccinated against COVID-19.
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    \1262\ Centers for Disease Control and Prevention. Healthcare 
Workers. (2017) Accessed February 18, 2021 at: https://www.cdc.gov/niosh/topics/healthcare/default.html.
    \1263\ Centers for Disease Control and Prevention. COVID Data 
Tracker. COVID-19 Vaccinations in the United States. (2021) Accessed 
on July 2, 2021. Available at: https://covid.cdc.gov/covid-data-tracker/#vaccinations.
    \1264\ Press Briefing by White House COVID-19 Response Team and 
Public Health Officials [verbar] The White House. Accessed on July 
21, 2021 at https://www.whitehouse.gov/briefing-room/press-briefings/2021/06/03/press-briefing-by-white-house-covid-19-response-team-and-public-health-officials-40/.
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    Although data showing the effectiveness of COVID-19 vaccines to 
prevent asymptomatic infection or transmission of SARS-CoV-2 are 
limited at this time, we stated in the proposed rule that we believe 
PCHs should report their rates of vaccination among their HCP as part 
of their efforts to assess and reduce the risk of transmission of 
COVID-19. HCP vaccination can potentially reduce illness that leads to 
work absence and limit disruptions to care.\1265\ Data from influenza 
vaccination demonstrates that provider uptake of the vaccine is also 
associated with that provider recommending vaccination to 
patients,\1266\ and we stated that we believe HCP COVID-19 vaccination 
in PCHs could similarly increase uptake among that patient population. 
We also stated that publishing the HCP vaccination rates will be 
helpful to many patients, including those who are at high-risk for 
developing serious complications from COVID-19, as they choose PCHs 
from which to seek treatment. We further stated that under CMS' 
Meaningful Measures Framework, the COVID-19 HCP vaccination measure 
addresses the quality priority of ``Promote Effective Prevention and 
Treatment of Chronic Disease'' through the Meaningful Measures Area of 
``Preventive Care.''
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    \1265\ Centers for Disease Control and Prevention. Overview of 
Influenza Vaccination among Health Care Personnel. October 2020. 
(2020) Accessed March 16, 2021 at: https://www.cdc.gov/flu/toolkit/long-term-care/why.htm.
    \1266\ Measure Application Committee Coordinating Committee 
Meeting Presentation. March 15, 2021. (2021) Accessed March 16, 2021 
at: http://www.qualityforum.org/Project_Pages/MAP_Coordinating_Committee.aspx.
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b. Overview of Measure
    The COVID-19 Vaccination Coverage Among HCP measure (``COVID-19 HCP 
vaccination measure'') is a process measure developed by the CDC to 
track COVID-19 vaccination coverage among HCP in non-long-term care 
facilities such as PCHs.
(1) Measure Specifications
    The denominator is the number of HCP eligible to work in the PCH 
for at least one day during the reporting period (as described in 
section IX.D.5.c.), excluding persons with contraindications to COVID-
19 vaccination that are described by the CDC.\1267\
---------------------------------------------------------------------------

    \1267\ Centers for Disease Control and Prevention. 
Contraindications and precautions. (2021) Accessed March 15, 2021 
at: https://www.cdc.gov/vaccines/covid-19/info-by-product/clinical-considerations.html#Contraindications.
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    The numerator is the cumulative number of HCP eligible to work in 
the PCH for at least one day during the reporting period (as described 
in section IX.D.5.c. of the preamble of the proposed rule) and who 
received a complete vaccination course against COVID-19 using an FDA-
authorized vaccine for COVID-19 (whether the FDA issued an approval or 
EUA). A complete vaccination course is defined under the specific FDA 
authorization (either the EUA or the approval) and may require multiple 
doses or regular revaccination.\1268\ Vaccination coverage is defined, 
for purposes of this measure, as the percentage of HCP eligible to work 
at the PCH for at least one day who received a complete vaccination 
course against COVID-19. The proposed specifications for this measure 
are available at https://www.cdc.gov/nhsn/nqf/index.html.
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    \1268\ Measure Applications Partnership Coordinating Committee 
Meeting Presentation. March 15, 2021. (2021) Accessed March 16, 2021 
at: http://www.qualityforum.org/Project_Pages/MAP_Coordinating_Committee.aspx.
---------------------------------------------------------------------------

(2) Review by the Measure Applications Partnership (MAP)
    The COVID-19 HCP vaccination measure was included on the publicly 
available ``List of Measures under Consideration for December 21, 
2020,'' \1269\ a list of measures under consideration for use in 
various Medicare programs. When the Measure Applications Partnership 
(MAP) Hospital Workgroup convened on January 11, 2021, it reviewed the 
measures on the MUC List, including the COVID-19 HCP vaccination 
measure. The MAP Hospital Workgroup recognized that the proposed 
measure represents a promising effort to advance measurement for an 
evolving national pandemic and that it would bring value to the PCHQR 
Program measure set by providing transparency about an important COVID-
19 intervention to help prevent infections in HCP and patients.\1270\ 
The MAP Hospital Workgroup also stated that collecting information on 
COVID-19 vaccination coverage among HCP and providing feedback to PCHs 
will allow PCHs to benchmark vaccine coverage rates and improve their 
vaccine coverage rates, and that reducing rates of COVID-19 in 
healthcare personnel may reduce transmission among patients and reduce 
instances of staff shortages due to illness.\1271\
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    \1269\ The National Quality Forum. (2021) Accessed March 14, 
2021 at: https://www.qualityforum.org/WorkArea/linkit.aspx?LinkIdentifier=id&ItemID=94212.
    \1270\ Measure Applications Partnership. MAP Preliminary 
Recommendations 2020-2021. Accessed on January 24, 2021 at: http://www.qualityforum.org/Project_Pages/MAP_Hospital_Workgroup.aspx.
    \1271\ Ibid.
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    In its preliminary recommendations, the MAP Hospital Workgroup did 
not support this measure for rulemaking, subject to potential for 
mitigation.\1272\ To mitigate its concerns, the MAP Hospital Workgroup 
believed that the measure needed well-documented evidence, finalized 
specifications, testing, and NQF endorsement prior to 
implementation.\1273\ Subsequently, the MAP Coordinating Committee met 
on January 25, 2021 and reviewed the COVID-19 Vaccination Coverage 
Among HCP measure. In the 2020-2021 MAP Final Recommendations issued 
March 11, 2021, the MAP offered conditional support for rulemaking 
contingent on CMS bringing the measure back to the MAP once the 
specifications are further refined, specifically saying that ``the 
incomplete specifications require immediate mitigation and further 
development should continue.'' \1274\ In its final report, the MAP 
noted that the measure would add value to the program measure set by 
providing visibility into an important intervention to limit COVID-19 
infections in healthcare personnel and

[[Page 45431]]

the patients for whom they provide care.\1275\
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    \1272\ Ibid.
    \1273\ Ibid.
    \1274\ Measure Applications Partnership. 2020-2021 
Considerations for Implementing Measures Final Report--Clinicians, 
Hospitals, and PAC-LTC. Accessed on March 12, 2021 at: https://www.qualityforum.org/Publications/2021/03/MAP_2020-2021_Considerations_for_Implementing_Measures_Final_Report_-_Clinicians,_Hospitals,_and_PAC-LTC.aspx.
    \1275\ Measure Applications Partnership. 2020-2021 Measures 
Final Report--Clinicians, Hospitals, and PAC-LTC. Accessed on March 
12, 2021 at: https://www.qualityforum.org/Publications/2021/03/MAP_2020-2021_Considerations_for_Implementing_Measures_Final_Report_-_Clinicians,_Hospitals,_and_PAC-LTC.aspx.
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    In response to the MAP final recommendation request that CMS bring 
the measure back to the MAP once the specifications are further 
refined, CMS and the CDC met with the MAP Coordinating Committee on 
March 15th. CMS and the CDC provided additional information to the MAP 
Coordinating Committee at that meeting that addressed vaccine 
availability, the alignment of the COVID-19 vaccination measure 
specifications as closely as possible with the Influenza HCP 
vaccination measure (NQF #0431) specifications, and the definition of 
HCP used in the measure. At this meeting, CMS and the CDC also 
presented preliminary findings from the testing of the numerator of 
COVID-19 Vaccination Coverage Among HCP, which is currently in process. 
These preliminary findings showed that the numerator data should be 
feasible and reliable. Testing of the numerator of the number of 
healthcare personnel vaccinated involves a comparison of vaccination 
data collected by the CDC directly from long-term care facilities 
(LTCs) through NHSN with vaccination data independently reported to the 
CDC through the Federal pharmacy partnership program. These are two 
completely independent data collection systems. In initial analyses of 
the first month of vaccination from December 2020 to January 2021 of 
HCP vaccination in approximately 1,200 facilities which reported to 
both systems, the number of healthcare personnel vaccinated was highly 
correlated between these 2 systems with a correlation coefficient of 
nearly 90 percent in the second two weeks of reporting.\1276\ Because 
of the high correlation across a large number of facilities and high 
number of HCP within those facilities receiving at least one dose of 
the COVID-19 vaccine, we stated in the proposed rule that we believe 
these data indicate the measure is feasible and reliable for use in 
PCHs (86 FR 25605).
---------------------------------------------------------------------------

    \1276\ For more information on testing results and other measure 
updates, please see the Meeting Materials (including Agenda, 
Recording, Presentation Slides, Summary, and Transcript) of the 
March 15, 2021 meeting available at: https://www.qualityforum.org/ProjectMaterials.aspx?projectID=75367; Gharpure R, Guo A, Bishnoi 
CK, et al. Early COVID-19 First-Dose Vaccination Coverage Among 
Residents and Staff Members of Skilled Nursing Facilities 
Participating in the Pharmacy Partnership for Long-Term Care 
Program--United States, December 2020-January 2021. MMWR Morb Mortal 
Wkly Rep 2021;70:178-182. DOI: http://dx.doi.org/10.15585/mmwr.mm7005e2.
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    We stated in the proposed rule that we value the recommendations of 
the MAP and considered these recommendations carefully. Section 
1890A(a)(4) of the Act requires the Secretary to take into 
consideration input from multi-stakeholder groups in selecting quality 
and efficiency measures. While we value input from the MAP, we also 
stated in the proposed rule that believe it is important to propose the 
measure as quickly as possible to address the urgency of the COVID-19 
PHE and its impact on PCHs and the vulnerable populations they serve. 
We continue to engage with the MAP to mitigate its concerns and 
appreciate the MAP's conditional support for the measure.
(3) NQF Endorsement
    Section 1866(k)(3)(A) of the Act states that subject to 
subparagraph (B), any measure specified by the Secretary for the PCHQR 
Program must have been endorsed by the entity with a contract under 
section 1890(a) of the Act. The National Quality Forum (NQF) currently 
holds this contract. Under section 1866(k)(3)(B), in the case of a 
specified area or medical topic determined appropriate by the Secretary 
for which a feasible and practical measure has not been endorsed by the 
entity with a contract under section 1890(a) of the Act, the Secretary 
may specify a measure that is not so endorsed as long as due 
consideration is given to measures that have been endorsed or adopted 
by a consensus organization identified by the Secretary.
    The proposed COVID-19 Vaccination Coverage Among HCP measure is not 
NQF endorsed and has not been submitted to NQF for endorsement 
consideration. The CDC, in collaboration with CMS, is planning to 
submit the measure for consideration in the NQF Fall 2021 measure 
cycle.
    Because this measure is not NQF-endorsed, we considered whether 
there are other available measures that assess COVID-19 vaccination 
rates among HCP. We found no other feasible and practical measures on 
the topic of COVID-19 vaccination among HCP, therefore the exception in 
section 1866(k)(3)(B) of the Act applies.
c. Data Collection, Submission and Reporting
    Given the time sensitive nature of this measure considering the 
current PHE, we proposed that for the FY 2023 program year, the 
reporting period for the proposed COVID-19 Vaccination Coverage Among 
HCP measure would be from October 1, 2021 through December 31, 2021. 
Thereafter, we proposed quarterly reporting deadlines for the PCHQR 
Program. PCHs would report the measure through the NHSN web-based 
surveillance system.\1277\ PCHs currently use the NHSN web-based system 
to report five HAI measures for the PCHQR Program, as well as the 
Influenza Vaccination Coverage Among HCP (NQF #0431).
---------------------------------------------------------------------------

    \1277\ Centers for Disease Control and Prevention. Surveillance 
for Weekly HCP COVID-19 Vaccination. Accessed at: https://www.cdc.gov/nhsn/hps/weekly-covid-vac/index.html on February 10, 
2021.
---------------------------------------------------------------------------

    To report this measure, we proposed that PCHs would collect the 
numerator and denominator for the COVID-19 HCP vaccination measure for 
at least one self-selected week during each month of the reporting 
quarter and submit the data to the NHSN Healthcare Personal Safety 
(HPS) Component before the quarterly deadline to meet PCHQR Program 
requirements. While we stated in the proposed rule that it would be 
ideal to have HCP vaccination data for every week of each month, we are 
mindful of the time and resources that PCHs would need to report the 
data. Thus, in collaboration with the CDC, we determined that data from 
at least one week of each month would be sufficient to obtain a 
reliable snapshot of vaccination levels among a PCH's healthcare 
personnel while balancing the costs of reporting. If a PCH submits more 
than one week of data in a month, the most recent week's data would be 
used to calculate the measure. For example, if first and third week 
data are submitted, third week data would be used. If first, second, 
and fourth week data are submitted, fourth week data would be used. 
Each quarter, we proposed that the CDC would calculate a single 
quarterly COVID-19 HCP vaccination coverage rate for each PCH, which 
would be calculated by taking the average of the data from the three 
weekly rates submitted by the PCH for that quarter. CMS would publicly 
report each quarterly COVID-19 HCP vaccination coverage rate as 
calculated by the CDC.
    As described in section IX.D.5.b.(1). of the preamble of the 
proposed rule (86 FR 25605), PCHs would report the number of HCP 
eligible to have worked at the facility during the self-selected week 
that the PCH reports data for in NHSN (denominator) and the number of 
those HCP who have received a complete course of a COVID-19 vaccination 
(numerator) during the same self-selected week.

[[Page 45432]]

    We invited public comment on our proposal to add a new measure, 
COVID-19 Vaccination Coverage Among HCP, to the PCHQR Program beginning 
with the FY 2023 program year, with an October 1, 2021 through December 
31, 2021 reporting period for that program year, and continuing with 
quarterly reporting deadlines for subsequent PCHQR Program years.
    Comment: Many commenters expressed their support for our proposal 
to adopt the COVID-19 Vaccination Coverage Among HCP Measure. A few 
commenters stated their belief that the measure supports PCHs, 
healthcare personnel, and the communities they serve. A few commenters 
recommended that CMS continue to work with stakeholders as the PHE 
evolves to ensure the measure remains appropriate and timely.
    Response: We thank commenters for their support of the measure and 
agree that COVID-19 vaccination remains important. We intend to 
continue working with stakeholders as the commenters suggested.
    Comment: A commenter expressed support for the measure 
specifications, noting that the entire radiation oncology team, not 
just physicians, have daily contact with patients over the course of 
their treatment and capturing vaccination status protects patients and 
staff.
    Response: We thank the commenter for its support and agree that it 
is important to measure vaccination status throughout the PCH in order 
to protect patients and staff.
    Comment: A few commenters were supportive of reporting the measure 
through the CDC NHSN. A commenter encouraged CMS to use the NHSN over 
other systems, including the HHS TeleTracking system, to promote 
consistency and reduce burden from duplicative reporting. Another 
commenter expressed support for NHSN and its ability to ensure 
transparency and accountability in reporting.
    Response: We thank these commenters for their support.
    Comment: A few commenters recommended that CMS consider 
incorporating reporting for other vaccines as part of the COVID-19 
Vaccination Coverage Among HCP Measure. A commenter suggested that the 
measure include HCP coverage for pertussis vaccines. Another commenter 
encouraged CMS to retain the Influenza Vaccination Coverage Among HCP 
Measure (PCH-28/NQF #0431) in the PCHQR measure set.
    Response: We thank commenters for their feedback and note that the 
Influenza Vaccination Coverage Among HCP Measure remains in the PCHQR 
Program. We will consider whether to incorporate reporting for 
additional vaccines in the future.
    Comment: A few commenters recommended that CMS delay the proposal 
to adopt the COVID-19 Vaccination Coverage Among HCP measure until more 
information on the long-term efficacy of the vaccines is clear. These 
commenters expressed concern regarding whether a booster vaccination 
will be required and whether the current measure may be premature given 
unknowns about the future of the PHE. Other commenters expressed 
concerns about potential unintended consequences of adding the measure 
into the program too quickly given the rapidly changing circumstances 
in which vaccines are being developed and deployed. Some commenters 
also asserted that tracking HCP vaccination will be complicated until 
information on boosters becomes available.
    Response: We appreciate commenters' concerns about the duration of 
vaccine efficacy and the potential need for boosters. The COVID-19 
Vaccination Coverage Among HCP measure is a measure of a completed 
vaccination course (as defined in the measure specifications \1278\) 
and does not address booster shots. Currently, the need for COVID-19 
booster doses has not been established, and no additional doses are 
currently recommended for HCP.\1279\ However, we believe that the 
numerator is sufficiently broad to include potential future boosters as 
part of a ``complete vaccination course'' and therefore the measure is 
sufficiently specified to address boosters. While we recognize 
commenters' concerns that the measure has been proposed quickly, the 
COVID-19 PHE has significantly impacted PCHs and their patients and we 
do not agree that adoption is premature. The intent of adopting the 
COVID-19 Vaccination Coverage Among HCP measure is to collect and 
report data that will support public health tracking and provide 
beneficiaries and their caregivers information to support informed 
decision making. For these reasons, we believe that it is appropriate 
to collect and report this data as soon as possible.
---------------------------------------------------------------------------

    \1278\ CDC. Measure Specification: NHSN COVID-19 Vaccination 
Coverage. Available at: https://www.cdc.gov/nhsn/pdfs/nqf/covid-vax-hcpcoverage-508.pdf.
    \1279\ Centers for Disease Control and Prevention. Vaccine 
Administration. Available at https://www.cdc.gov/vaccines/covid-19/clinical-considerations/covid-19-vaccines-us.html. Accessed June 25, 
2021.
---------------------------------------------------------------------------

    Comment: A few commenters noted that, presently, all COVID-19 
vaccines are authorized through an EUA and that some individuals remain 
hesitant to receive vaccination while the vaccine is authorized by an 
EUA. These commenters stated that the measure is premature until such 
time that a vaccine has received full FDA approval. A few commenters 
recommended that, if a delay is not possible, reporting for the measure 
should be voluntary for at least the first year.
    Response: While we support widespread vaccination coverage, we also 
understand that some HCP may be concerned about receiving the COVID-19 
vaccine prior to the vaccine receiving full FDA approval. Although we 
recognize there are differences between EUA authorization and full FDA 
approval, we note that the process for each is scientifically rigorous. 
Each vaccine manufacturer that received EUA authorization enrolled tens 
of thousands of participants in randomized clinical trials, which is 
similar to what is required for full FDA approval.\1280\ Manufacturers 
submit the same robust and rigorous data for both an EUA authorization 
and full FDA approval, and more than 330 million doses of COVID-19 
vaccines authorized by EUAs have been administered.\1281\ We believe 
these vaccines have been proven to be safe and effective. The COVID-19 
Vaccination Coverage Among HCP measure is also a process measure that 
assesses HCP vaccination coverage rates, not an outcome measure for 
which PCHs are held directly accountable for a particular outcome. As 
stated previously, the intent of adopting the COVID-19 Vaccination 
Coverage Among HCP measure is to collect and report data that will 
support public health tracking and provide beneficiaries and their 
caregivers information to support informed decision making. For these 
reasons, we believe that it is appropriate to collect and report this 
data as soon as possible.
---------------------------------------------------------------------------

    \1280\ Harvard Law Petrie-Flom Center. ``What's the Difference 
Between Vaccine Approval (BLA) and Authorization (EUA)?'' June 15, 
2021. Available at: https://blog.petrieflom.law.harvard.edu/2021/06/15/whats-the-difference-between-vaccine-approval-bla-and-authorization-eua/.
    \1281\ Centers for Disease Control and Prevention. (2021). CDC 
COVID Data Tracker: COVID-19 Vaccinations in the United States. 
Available at: https://covid.cdc.gov/covid-data-tracker/#vaccinations 
(Accessed on July 19, 2021).
---------------------------------------------------------------------------

    Comment: A few commenters expressed concerns about the measure's 
numerator and denominator. A commenter noted that the measure numerator 
differs from the Influenza Vaccination Coverage Among HCP (NQF #0431) 
measure. The commenter noted several differences in data elements 
reported in NHSN, including the

[[Page 45433]]

possibility for one or two doses, the potential for future boosters, 
variance in vaccine supply, and the option to select ``offered but 
declined vaccine'' or ``adverse event following vaccination.''
    A commenter asserted that the denominator, which defines HCP to 
include all HCP who receive a direct paycheck from the hospital 
regardless of clinical responsibility or patient contact, is too broad 
of a population and is problematic. The commenter further stated that 
significant resources would be required to document the vaccination 
status of all employees, many of whom received vaccines from third 
parties. A commenter argued that it will be challenging to collect the 
full and accurate count of adult students, trainees, and volunteers as 
these individuals are not always captured or identified as such in 
human resources or hospital databases.
    A few commenters expressed concerns about the potential impact of 
state legislation or regulation that may limit ability to require 
vaccination or request vaccine status from HCP.
    Response: We appreciate commenters' concerns regarding the 
differences in the numerator specifications for the Influenza 
Vaccination Coverage Among HCP measure (NQF #0431). While we have 
sought to align this measure with the Influenza Vaccination Coverage 
Among HCP measure (NQF #0431), each measure addresses different public 
health initiatives and different vaccines, and therefore the measure 
specifications cannot be in complete alignment. For example, influenza 
is seasonal and influenza vaccines are therefore only delivered during 
influenza season (October 1 through March 31). We believe that, given 
the public health importance of vaccination in addressing the COVID-19 
PHE, the benefits of requiring additional reporting outweigh the 
burden. We also note that although this information is not captured in 
the numerator or denominator, the CDC's NHSN tool allows hospitals to 
indicate that HCP were offered a vaccination but declined.\1282\
---------------------------------------------------------------------------

    \1282\ https://www.cdc.gov/nhsn/forms/instr/57.220-toi-508.pdf.
---------------------------------------------------------------------------

    We recognize that some PCHs may still be obtaining vaccination 
records from their employees and other personnel that work within their 
hospitals. With respect to the concern that some PCHs may have 
incomplete data to report, we acknowledge the logistical challenges of 
collecting vaccination status for all HCPs within a PCH. However, given 
the highly contagious nature of COVID-19, we believe the information is 
important for patients, including particularly vulnerable individuals 
such as cancer patients.
    With regard to concerns about state-level legislation that may 
limit a PCH's ability to require vaccination or request vaccine status 
from HCP, we reiterate that the COVID-19 Vaccination Coverage Among HCP 
measure does not require HCP to receive the vaccination and is a 
process measure that assesses HCP vaccination coverage rates, not an 
outcome measure for which PCHs are held directly accountable for a 
particular outcome. While we are aware that at least one state has 
enacted legislation that prohibits employers from requiring employees 
to disclose immunization status,\1283\ we are not aware of any state 
legislation that prohibits employers from requesting voluntary 
reporting of immunization status. Additionally, the Equal Employment 
Opportunity Commission (EEOC) released updated and expanded technical 
assistance on May 28, 2021,\1284\ stating that Federal equal employment 
opportunity (EEO) laws do not prevent an employer from requiring all 
employees physically entering the workplace to be vaccinated for COVID-
19, so long as the employer complies with the reasonable accommodation 
provisions of the Americans with Disabilities Act (ADA) and Title VII 
of the Civil Rights Act of 1964 and other EEO considerations. We again 
note that this measure does not require HCP to receive a COVID-19 
vaccine and it does not require HCP to report their vaccination status. 
Therefore, we do not believe that this measure conflicts with any 
Federal or state-level requirements and believe that it is appropriate 
to require PCHs to report these data.
---------------------------------------------------------------------------

    \1283\ Montana House Bill 0702 (enacted May 7, 2021). Bill text 
available at: https://leg.mt.gov/bills/2021/billpdf/HB0702.pdf. Bill 
status including enactment available at: http://laws.leg.mt.gov/
legprd/
LAW0203W$BSRV.ActionQuery?P_SESS=20211&P_BLTP_BILL_TYP_CD=HB&P_BILL_N
O=0702&P_BILL_DFT_NO=&P_CHPT_NO=&Z_ACTION=Find&P_ENTY_ID_SEQ2=&P_SBJT
_SBJ_CD=&P_ENTY_ID_SEQ=.
    \1284\ U.S. Equal Employment Opportunity Commission. What You 
Should Know About COVID-19 and the ADA, the Rehabilitation Act, and 
Other EEO Laws. Available at https://www.eeoc.gov/wysk/what-you-should-know-about-covid-19-and-ada-rehabilitation-act-and-other-eeo-laws. Accessed June 25, 2021.
---------------------------------------------------------------------------

    Comment: Several commenters expressed concerns about the exclusion 
of HCP with contraindications to COVID-19 vaccination in the 
denominator of the measure specifications. These commenters noted that 
data on HCP medical contraindications are not captured in hospital 
human resources databases or employee electronic health records, and 
therefore, hospitals are unable to exclude those individuals from the 
denominator of the measure, which may lead to inaccurate reporting and 
data collection burden. A commenter stated that this problem is 
compounded by the fact that indications and contraindications for the 
COVID-19 vaccines have changed and may continue to evolve as the 
disease is better understood. A commenter recommended CMS update the 
denominator to include all HCP with a clear explanation in public 
reporting that the denominator did not exclude HCP with 
contraindications, asserting that this change would allow for 
consistent cross-provider reporting and more accurate measurement and 
comparisons.
    A commenter stated that the exclusion of HCP with contraindications 
alone is too narrow, noting that the Equal Employment Opportunity 
Commission (EEOC) requires employers to provide reasonable 
accommodations for employees with religious beliefs, practices or 
observances that prevent them from receiving vaccination and stating 
that HCP with such religious beliefs should be excluded as well.
    Response: Regarding the difficulty in capturing contraindication 
information in order to exclude such HCP from the denominator of the 
measure specifications, we note that PCHs must report HCP who have 
contraindications as part of the influenza vaccine measure,\1285\ and 
therefore we believe collecting contraindication information from HCP 
is feasible.
---------------------------------------------------------------------------

    \1285\ CDC. Monitor Influenza Vaccination Coverage among your 
Health Care Personnel. Available at https://www.cdc.gov/flu/toolkit/long-term-care/reporting.htm.
---------------------------------------------------------------------------

    Regarding the comment that only excluded HCP with contraindications 
is too narrow and that HCP who refuse the vaccine for other reasons 
should also be excluded, we recognize that there are many reasons, 
including religious objections, that may lead individual HCP to decline 
vaccination. We note that the intent of the measure is to capture the 
vaccination rate within PCHs so that patients have information 
available on HCP vaccination to inform their health care decisions. 
Additionally, because the measure does not require vaccination, we do 
not believe this proposal conflicts with the reasonable accommodation 
requirements of the EEOC.
    Comment: Some commenters expressed concern that the measure lacks 
NQF endorsement and stated that the measure requires refinement. A few 
commenters noted that lack of NQF

[[Page 45434]]

endorsement is especially concerning for vaccines approved under EUAs. 
A commenter stated that, while it supports the measure, it has concerns 
about the use of the vaccination in certain populations (that is, 
pregnant women, immunocompromised individuals) without further study 
and encouraged CMS to pursue NQF endorsement in the future.
    Response: We believe that in the context of the current COVID-19 
PHE and continued monitoring and surveillance following the PHE, it is 
important to adopt this measure as quickly as possible to allow 
tracking and reporting of COVID-19 Vaccination Coverage Among HCP. This 
tracking would allow PCHs to identify the appropriateness and 
effectiveness of their initiatives to improve vaccination coverage and 
would provide patients and consumers with important information. We, 
therefore, believe it is appropriate to use the exception provided in 
section 1886(k)(3)(A) of the Act to adopt this measure because we 
assessed there is no NQF endorsed measure on the topic of COVID-19 
vaccination coverage among healthcare personnel. The CDC, in 
collaboration with CMS, is planning to submit the measure for 
consideration in the NQF Fall 2021 measure cycle.
    Comment: Several commenters opposed our proposal to adopt the 
COVID-19 Vaccination Coverage Among HCP Measure. A commenter noted that 
PCHs may be required to report COVID-19 vaccination information in 
multiple systems and recommended a single point of reporting. A 
commenter stated that it supports COVID-19 vaccination efforts but 
believes that CMS should not adopt the measure and instead focus on 
supporting vaccination efforts in provider settings.
    Response: We agree that it is important to support vaccination 
efforts in provider settings. We believe that it is appropriate to use 
quality reporting program measures to encourage such efforts by 
collecting data on vaccination coverage among HCP. We do recognize that 
this measure may lead to duplicative reporting requirements if PCHs 
voluntarily report COVID-19 HCP vaccination information to data 
reporting systems other than NHSN, and we are collaborating with other 
HHS agencies, including the CDC, to ensure minimal reporting burden and 
to eliminate duplicative requirements to the extent feasible.
    Comment: Several commenters opposed mandatory data submission via 
NHSN for the measure beginning October 1, 2021. A commenter noted that 
vaccination is progressing differently in each state and hospitals may 
not have tracking programs in place at that time. A commenter expressed 
concern about the impact that multiple state and Federal reporting 
requirements may have on hospitals. A few commenters recommended CMS 
delay implementation of the measure for at least one full calendar year 
until the FY 2024 program year when hospitals are fully capable of 
reporting and data will be more representative of fully vaccinated HCP. 
Some commenters suggested voluntary reporting for the first year.
    Response: We believe that in the context of the current COVID-19 
PHE and continued monitoring and surveillance following the PHE, it is 
important to adopt this measure as quickly as possible to allow 
tracking and reporting of COVID-19 Vaccination Coverage Among HCP. 
While we recognize that the data may not fully represent all activities 
to prevent and control infections, we do believe that the ongoing 
nature of the PHE demonstrates the importance of reporting HCP 
vaccination rates in PCHs as quickly as possible.
    Comment: Several commenters opposed publicly reporting PCH 
performance on the proposed COVID-19 vaccination measure. A commenter 
asserted that the country is still in the early phases of deploying 
vaccines and changes to supply, strategy, or disease course could lead 
to unreliable data for the public. Another commenter expressed concern 
that publicly reporting measure data that may be skewed due to 
insufficient response time, refusal to receive the vaccine, or refusal 
from HCP to provide vaccination status, and that such skewed data may 
further fuel vaccine hesitancy. A few commenters believed measure data 
should not be publicly reported until vaccines receive full FDA 
approval.
    Response: We believe that HCP vaccination is important to prevent 
the spread of COVID-19 and encourage HCP to disclose their vaccination 
status. While we recognize that HCP may decline to provide their 
vaccination status to PCHs, we disagree that such declinations would 
result in unreliable data. We also respectfully disagree that public 
reporting of vaccination data will discourage HCP vaccine uptake. We 
note that the national average of HCP who had received the influenza 
vaccination, as reported on the then Hospital Compare website, was 85 
percent, 80 percent, and 82 percent respectively for FY 2017, 2018, and 
2019 PCHQR Program years. The average of HCP within PCHs who had 
received the influenza vaccine in FY 2020 was even higher at 89 
percent.\1286\ We do not believe that this represents performance that 
suggests a negative relationship between public reporting and vaccine 
uptake among HCP and we believe that publicly reporting the data will 
be useful to consumers in choosing healthcare providers, including by 
making comparisons between PCHs.
---------------------------------------------------------------------------

    \1286\ CMS Provider Data Catalog. Cancer Treatment Measures--
PPS-Exempt Cancer Hospital. Available at: https://data.cms.gov/provider-data/dataset/k653-4ka8.
---------------------------------------------------------------------------

    However, with regard to concerns that data may be skewed by 
insufficient response time or hesitancies among HCP to receive the 
vaccine or report that they have received the vaccine, we believe it is 
important to make the most up-to-date and accurate data available to 
beneficiaries, which will support them in making essential decisions 
about health care. Based on these concerns, we will update the public 
reporting to use quarterly reporting, as opposed to averaging over four 
rolling quarters, which allows the most recent quarter data to be 
displayed without combining it with older quarters of data. This would 
result in information that is more up to date than it would be if it 
was diluted with older data. This update does not affect the data 
collection schedule established for submitting data to NHSN for the 
COVID-19 vaccination measure. This would simply update the data that 
are displayed for the public reporting purposes.
    After consideration of the public comments we received, we are 
finalizing the proposal to adopt the COVID-19 Vaccination Coverage 
Among HCP, to the PCHQR Program beginning with the FY 2023 program 
year, with an October 1, 2021 through December 31, 2021 reporting 
period for that program year, and continuing with quarterly reporting 
deadlines for subsequent PCHQR program years. However, based on public 
comment, we will not finalize our plan to publicly report data averaged 
over four rolling quarters. We will instead only report the most recent 
quarter of data. This would result in more meaningful information that 
is up to date and not diluted with older data.
6. Summary of PCHQR Program Measures for the FY 2023 Program Year and 
Subsequent Years
    This table summarizes the PCHQR Program measure set for the FY 2023 
program year and subsequent years including the adoption of the COVID-
19

[[Page 45435]]

Vaccination Coverage Among HCP measure as finalized in this final rule.
BILLING CODE 4120-01-P
[GRAPHIC] [TIFF OMITTED] TR13AU21.290

7. Maintenance of Technical Specifications for Quality Measures
    We maintain and periodically update technical specifications for 
the PCHQR Program measures. The specifications may be found on the 
QualityNet website at: https://qualitynet.cms.gov/pch. We also refer 
readers to the FY 2015 IPPS/LTCH PPS final rule (79 FR 50281), where we 
adopted a policy to use a subregulatory process to make nonsubstantive 
updates to measures used for the PCHQR Program. We did not propose any 
changes to our processes for maintaining technical specifications for 
PCHQR Program measures.
8. Public Display Requirements
    Under section 1866(k)(4) of the Act, we are required to establish 
procedures for making the data submitted under the PCHQR Program 
available to the public. For additional information regarding 
previously finalized public display requirements and policies, we refer 
readers to previous final rules.
    In the table that follows, we summarize our current public display 
requirements for the PCHQR Program measures. The PCHQR measures' 
performance data is made publicly available on a CMS website, which is 
currently the Provider Data Catalog, available at: https://data.cms.gov/provider-data/. We did not propose any changes to these 
public display requirements.

[[Page 45436]]

[GRAPHIC] [TIFF OMITTED] TR13AU21.291

BILLING CODE 4120-01-C
9. Form, Manner, and Timing of Data Submissions
a. Procedural Requirements
    We refer readers to the FY 2013 IPPS/LTCH PPS final rule (77 FR 
53563 through 53567) for our previously finalized procedural 
requirements for the PCHQR Program. Data submission requirements and 
deadlines for the PCHQR Program are posted on the QualityNet website.
b. Update of the Reference to QualityNet Administrator
    In section IX.D.9. of the proposed rule, we stated that under our 
current procedural requirements, each PCH that participates in the 
PCHQR Program must identify one or more QualityNet Administrators who 
will follow the registration process located on the QualityNet website 
(https://qualitynet.cms.gov) (77 FR 53563).
    In the proposed rule, we proposed to use the term ``QualityNet 
security official'' instead of ``QualityNet Administrator'' to align 
with the terminology we use or proposed to use in other quality 
reporting programs. We stated that this proposed update in terminology 
would not change the individual's responsibilities or add burden.
    Additionally, we clarified that failing to maintain an active 
QualityNet security official once a PCH has successfully registered to 
participate in the PCHQR Program will not result in a finding that the 
PCH did not successfully participate in the PCHQR Program.
    We invited public comment on our proposal to replace the term 
``QualityNet administrator'' with ``QualityNet security official.''
    Comment: A commenter supported CMS' proposal to replace the term 
``QualityNet administrator'' with ``QualityNet security official'' and 
appreciated the clarification regarding maintaining an active 
QualityNet security official.
    Response: We thank the commenter for its support.
    After consideration of the public comments we received, we are 
finalizing the proposal to replace the term ``QualityNet 
administrator'' with ``QualityNet security official'' and are codifying 
this update at 42 CFR 412.24(b)(1), without modification.
10. Extraordinary Circumstances Exceptions (ECE) Policy Under the PCHQR 
Program
    We refer readers to the FY 2019 IPPS/LTCH PPS final rule (83 FR 
41623 through 41624), for a discussion of the Extraordinary 
Circumstances Exceptions (ECE) policy under the PCHQR Program. We did 
not propose any changes to this policy.
11. Codification of PCHQR Program Requirements at New 42 CFR 412.23(f) 
and New 42 CFR 412.24 of Our Regulations
    There are currently no codified PCHQR Program requirements in our 
regulations. Accordingly, as we have done with a number of other CMS 
quality reporting programs, we proposed to add a new section at 42 CFR 
412.24 entitled, ``Requirements under the PPS-Exempt Cancer Hospital 
Quality Reporting (PCHQR) Program'' that codifies the program 
requirements listed in this proposed rule and a new paragraph (3) to 42 
CFR 412.23(f) that requires cancer hospitals that participate in the 
PCHQR Program to follow all such program requirements (86 FR 25607 
through 25608). We stated that we believe that the codification of 
these requirements will make it easier for stakeholders to find these 
requirements.
    Specifically, we proposed to amend 42 CFR 412.23(f) by adding a new 
paragraph (3) that requires cancer hospitals, as classified under that 
paragraph, participating in the PCHQR Program to follow all 
requirements listed in the new section 42 CFR 412.24. We also proposed 
to add a new section at 42 CFR 412.24 that contains the regulations 
that govern the PCHQR Program--
     Program participation requirements (adopted in the FY 2013 
IPPS/LTCH PPS final rule (77 FR 53563)) including the PCHQR Program 
registration process;
     Data submission requirements for quality measures (adopted 
in the FY 2013 IPPS/LTCH PPS final rule (77 FR 53563)) that are 
selected by CMS under section 1866(k) of the Act and must be submitted 
in a form and manner, and at a time, specified by CMS;
     Quality measure removal and retention factors (adopted in 
the FY 2017 IPPS/LTCH PPS final rule (81 FR

[[Page 45437]]

57182 through 57183) and expanded in FY 2019 IPPS/LTCH PPS final rule 
(83 FR 41609 through 41611));
     Public reporting requirements for quality measure data 
reported by PCHs, with measure information displayed on the CMS website 
(adopted in the FY 2017 IPPS/LTCH PPS final rule (81 FR 57191)); and
     Our extraordinary circumstances exception policy (adopted 
in the FY 2014 IPPS/LTCH PPS final rule (78 FR 50848) and updated in 
the FY 2018 IPPS/LTCH PPS final rule (82 FR 38424 through 38425)) 
detailing the process for CMS to grant an extension or exception to 
quality measure reporting requirements under the PCHQR Program.
    We welcomed public comment on the proposed codification of these 
existing PCHQR Program policies.
    Comment: A few commenters supported the proposal to codify exiting 
PCHQR program requirements, but a commenter suggested that CMS codify 
them in the regulations under 42 CFR part 489, which the commenter 
believed implements section 1866(k) of the Act, the statutory basis of 
the program.
    Response: We thank the commenters for their feedback. We believe 
that Part 412 is the appropriate placement for the PCHQR Program 
requirements because that Part includes regulations that govern the 
quality reporting programs for other providers excluded from IPPS, 
including long-term care hospitals, inpatient rehabilitation hospitals, 
and inpatient psychiatric hospitals.
    After consideration of the public comments we received, we are 
finalizing the proposal to codify existing PCHQR Program policies at 
Sec.  412.24. We are also codifying at Sec.  412.1(a)(7) that the 42 
CFR part 412 includes the implementation of section 1866(k), which 
directs hospitals described in section 1886(d)(1)(B)(v) of the Act to 
submit data on quality measures to the Secretary, and at revised Sec.  
412.1(b)(2) that Subpart B includes requirements for the PCHQR Program.

E. Long-Term Care Hospital Quality Reporting Program (LTCH QRP)

1. Background and Statutory Authority
    The Long-Term Care Hospital Quality Reporting Program (LTCH QRP) is 
authorized by section 1886(m)(5) of the Act, and it applies to all 
hospitals certified by Medicare as Long-Term Care Hospitals (LTCHs). 
Section 1886(m)(5)(C) of the Act requires LTCHs to submit to the 
Secretary quality measure data specified under section 1886(m)(5)(D) in 
a form and manner, and at a time, specified by the Secretary. In 
addition, section 1886(m)(5)(F) of the Act requires LTCHs to submit 
data on quality measures under section 1899B(c)(1) of the Act, resource 
use or other measures under section 1899B(d)(1) of the Act, and 
standardized patient assessment data required under section 1899B(b)(1) 
of the Act. LTCHs must submit the data required under section 
1886(m)(5)(F) of the Act in the form and manner, and at the time, 
specified by the Secretary. Under the LTCH QRP, the Secretary must 
reduce by 2 percentage points the annual update to the LTCH PPS 
standard Federal rate for discharges for an LTCH during a fiscal year 
if the LTCH has not complied with the LTCH QRP requirements specified 
for that fiscal year. For more information on the background for the 
LTCH QRP, we refer readers to the FY 2012 IPPS/LTCH PPS final rule (76 
FR 51743 through 51744), the FY 2013 IPPS/LTCH PPS final rule (77 FR 
53614), the FY 2014 IPPS/LTCH PPS final rule (78 FR 50853), the FY 2015 
IPPS/LTCH PPS final rule (79 FR 50286), the FY 2016 IPPS/LTCH PPS final 
rule (80 FR 49723 through 49725), the FY 2017 IPPS/LTCH PPS final rule 
(81 FR 57193), the FY 2018 IPPS/LTCH PPS final rule (82 FR 38425 
through 38426), the FY 2019 IPPS/LTCH PPS final rule (83 FR 41624 
through 41634), and the FY 2020 IPPS/LTCH PPS final rule (84 FR 42524 
through 42591). For more information on the requirements under the LTCH 
QRP, we refer readers to 42 CFR 412.560.
2. General Considerations Used for the Selection of Quality Measures 
for the LTCH QRP
    For a detailed discussion of the considerations we historically use 
for the selection of LTCH QRP quality, resource use, and other 
measures, we refer readers to the FY 2016 IPPS/LTCH PPS final rule (80 
FR 49728).
3. Quality Measures Currently Adopted for the FY 2022 LTCH QRP
    The LTCH QRP currently has 17 measures for the FY 2022 LTCH QRP, 
which are set out in the following Table FF1. For a discussion of the 
factors used to evaluate whether a measure should be removed from the 
LTCH QRP, we refer readers to FY 2019 IPPS/LTCH PPS final rule (83 FR 
41624 through 41634) and to the regulations at 42 CFR 412.560(b)(3).

[[Page 45438]]

[GRAPHIC] [TIFF OMITTED] TR13AU21.292

4. LTCH QRP Quality Measure Beginning with the FY 2023 LTCH QRP
    Section 1899B(h)(1) of the Act permits the Secretary to remove, 
suspend, or add quality measures or resource use or other measures 
described in sections 1899B(c)(1) or (d)(1) of the Act respectively, so 
long as the Secretary publishes in the Federal Register (with a notice 
and comment period) a justification for such removal, suspension, or 
addition. We proposed to adopt one new measure, the COVID-19 
Vaccination Coverage among Healthcare Personnel (HCP) \1287\ measure as 
an ``other'' measure under section 1899B(d)(1) of the Act beginning 
with the FY 2023 LTCH QRP. In accordance with section 1899B(a)(1)(B) of 
the Act, the data used to calculate this measure are standardized and 
interoperable. The proposed measure supports the Meaningful Measures 
domain of Promote Effective Prevention and Treatment of Chronic 
Disease. CMS identified the measure concept as a priority in response 
to the current public health crisis. This process measure was developed 
with the Centers for Disease Control and Prevention (CDC) to track 
COVID-19 vaccination coverage among HCP in the LTCH setting. This 
measure is described in more detail later in this section.
---------------------------------------------------------------------------

    \1287\ The measure steward changed the name of the measure from 
SARS-CoV-2 Vaccination Coverage among Healthcare Personnel to COVID-
19 Vaccination Coverage among Healthcare Personnel. There were no 
changes to the measure itself, other than the name change.
---------------------------------------------------------------------------

    In addition, we proposed to update the denominator for one measure, 
the Transfer of Health (TOH) Information to the Patient-Post-Acute Care 
(PAC) measure to exclude patients discharged home under the care of an 
organized home health service or hospice. a. COVID-19 Vaccination 
Coverage among Healthcare Personnel (HCP) Measure Beginning with the FY 
2023 LTCH QRP.
(1) Background
    On January 31, 2020, the Secretary of the U.S. Department of Health 
and Human Services (HHS) declared a public health emergency (PHE) for 
the United States in response to the global outbreak of SARS-CoV-2, a 
novel (new)

[[Page 45439]]

coronavirus that causes a disease named ``coronavirus disease 2019'' 
(COVID-19).\1288\ COVID-19 is a contagious respiratory infection\1289\ 
that can cause serious illness and death. Older individuals, racial and 
ethnic minorities,\1290\ and those with underlying medical conditions 
are considered to be at higher risk for more serious complications from 
COVID-19.\1291\ As of April 10, 2021, the U.S. reported over 30 million 
cases of COVID-19 and over 558,000 COVID-19 deaths.\1292\ Hospitals and 
health systems saw significant surges of COVID-19 patients as community 
infection levels increased. \1293\ In December 2020 and January 2021, 
media outlets reported that more than 100,000 Americans were in the 
hospital with COVID-19.\1294\
---------------------------------------------------------------------------

    \1288\ U.S. Dept. of Health and Human Services, Office of the 
Assistant Secretary for Preparedness and Response. (2020). 
Determination that a Public Health Emergency Exists. Available at: 
https://www.phe.gov/emergency/news/healthactions/phe/Pages/2019-nCoV.aspx.
    \1289\ Centers for Disease Control and Prevention. (2020). Your 
Health: Symptoms of Coronavirus. Available at: https://www.cdc.gov/coronavirus/2019-ncov/symptoms-testing/symptoms.html.
    \1290\ Centers for Disease Control and Prevention. (2020). 
Health Equity Considerations and Racial and Ethnic Minority Groups. 
Available at: https://www.cdc.gov/coronavirus/2019-ncov/community/health-equity/race-ethnicity.html.
    \1291\ Centers for Disease Control and Prevention. (2020). Your 
Health: Symptoms of Coronavirus. Available at https://www.cdc.gov/coronavirus/2019-ncov/symptoms-testing/symptoms.html.
    \1292\ Centers for Disease Control and Prevention. (2020). CDC 
COVID Data Tracker. Available at: https://covid.cdc.gov/covid-data-tracker/#cases_casesper100klast7days.
    \1293\ Associated Press. Tired to the Bone. Hospitals 
Overwhelmed with Virus Cases. November 18, 2020. Accessed on 
December 16, 2020, at https://apnews.com/article/hospitals-overwhelmed-coronavirus-cases-74a1f0dc3634917a5dc13408455cd895. Also 
see: New York Times. Just how full are U.S. intensive care units? 
New data paints an alarming picture. November 18, 2020. Accessed on 
December 16, 2020, at: https://www.nytimes.com/2020/12/09/world/just-how-full-are-us-intensive-care-units-new-data-paints-an-alarming-picture.html.
    \1294\ NPR. U.S. Hits 100,000 COVID-19 Hospitalizations, Breaks 
Daily Death Record. Dec. 2, 2020. Accessed on December 17, 2020 at 
https://www.npr.org/sections/coronavirus-live-updates/2020/12/02/941902471/u-s-hits-100-000-covid-19-hospitalizations-breaks-daily-death-record; The Wall Street Journal. Coronavirus Live Updates: 
U.S. Hospitalizations, Newly Reported Cases, Deaths Edge Downward. 
Accessed on January 11 at https://www.wsj.com/livecoverage/covid-2021-01-11.
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    Evidence indicates that COVID-19 primarily spreads when individuals 
are in close contact with one another.\1295\ The virus is typically 
transmitted through respiratory droplets or small particles created 
when someone who is infected with the virus coughs, sneezes, sings, 
talks or breathes.\1296\ Experts believe that COVID-19 spreads less 
commonly through contact with a contaminated surface \1297\ and is not 
thought to be a common way that COVID-19 spreads, and that in certain 
circumstances, infection can occur through airborne transmission.\1298\
---------------------------------------------------------------------------

    \1295\ Centers for Disease Control and Prevention. (2021). 
COVID-19. Your Health. Frequently Asked Questions. Accessed on 
January 11, 2021 at: https://www.cdc.gov/coronavirus/2019-ncov/faq.html.
    \1296\ Centers for Disease Control and Prevention (2021). COVID-
19. Your Health. Frequently Asked Questions. Accessed on January 11, 
2021 at: https://www.cdc.gov/coronavirus/2019-ncov/faq.html.
    \1297\ Centers for Disease Control and Prevention (2021). COVID-
19. Your Health. Frequently Asked Questions. Accessed on January 11, 
2021 at: https://www.cdc.gov/coronavirus/2019-ncov/faq.html.
    \1298\ Centers for Disease Control and Prevention. (2020). 
Centers for Disease Control Scientific Brief: SARS-CoV-2 and 
Potential Airborne Transmission. Available at: https://www.cdc.gov/coronavirus/2019-ncov/more/scientific-brief-sars-cov-2.html.
---------------------------------------------------------------------------

    According to the CDC, those at greatest risk of infection are 
persons who have had prolonged, unprotected close contact (that is, 
within 6 feet for 15 minutes or longer) with an individual with 
confirmed SARS-CoV-2 infection, regardless of whether the individual 
has symptoms.\1299\ Subsequent to the publication of the proposed rule, 
the CDC has confirmed that the three main ways that COVID-19 is spread 
are: (1) Breathing in air when close to an infected person who is 
exhaling small droplets and particles that contain the virus; (2) 
Having these small droplets and particles that contain virus land on 
the eyes, nose, or mouth, especially through splashes and sprays like a 
cough or sneeze; and (3) Touching eyes, nose, or mouth with hands that 
have the virus on them.\1300\ Personal protective equipment (PPE) and 
other infection-control precautions can reduce the likelihood of 
transmission in healthcare settings, COVID-19 can spread between 
healthcare personnel (HCP) and patients given the close contact that 
may occur during the provision of care.\1301\ The CDC has emphasized 
that healthcare settings, including LTCHs, can be high-risk places for 
COVID-19 exposure and transmission.\1302\ Vaccination is a critical 
part of the nation's strategy to effectively counter the spread of 
COVID-19 and ultimately help restore societal functioning.\1303\
---------------------------------------------------------------------------

    \1299\ Centers for Disease Control and Prevention. (2020). 
Clinical Questions about COVID-19: Questions and Answers. Accessed 
on December 2, 2020 at: https://www.cdc.gov/coronavirus/2019-ncov/hcp/faq.html.
    \1300\ Centers for Disease Control and Prevention. (2021). How 
COVID-19 Spreads. Accessed on July 15, 2021 at: https://www.cdc.gov/coronavirus/2019-ncov/prevent-getting-sick/how-covid-spreads.html.
    \1301\ Centers for Disease Control and Prevention. (2020). 
Interim U.S. Guidance for Risk Assessment and Work Restrictions for 
Healthcare Personnel with Potential Exposure to COVID-19. Accessed 
on December 2 at: https://www.cdc.gov/coronavirus/2019-ncov/hcp/guidance-risk-assesment-hcp.html.
    \1302\ Dooling, K, McClung, M, et al. ``The Advisory Committee 
on Immunization Practices' Interim Recommendations for Allocating 
Initial Supplies of COVID-19 Vaccine--United States, 2020.'' Morb 
Mortal Wkly Rep. 2020; 69(49): 1857-1859.
    \1303\ Centers for Disease Control and Prevention. (2020). 
COVID-19 Vaccination Program Interim Playbook for Jurisdiction 
Operations. Accessed on December 18 at: https://www.cdc.gov/vaccines/imz-managers/downloads/COVID-19-Vaccination-Program-Interim_Playbook.pdf.
---------------------------------------------------------------------------

    On December 11, 2020, the Food and Drug Administration (FDA) issued 
the first Emergency Use Authorization (EUA) for a COVID-19 vaccine in 
the U.S.\1304\ Subsequently the FDA issued EUAs for additional COVID-19 
vaccines. In issuing these EUAs, the FDA determined that it was 
reasonable to conclude that the known and potential benefits of each 
vaccine, when used as authorized to prevent COVID-19, outweighed its 
known and potential risks.1305 1306 1307
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    \1304\ U.S. Food and Drug Administration. (2020). Pfizer-
BioNTech COVID-19 Vaccine EUA Letter of Authorization. Available at 
https://www.fda.gov/media/144412/download.
    \1305\ Ibid.
    \1306\ U.S. Food and Drug Administration. (2021). ModernaTX, 
Inc. COVID-19 Vaccine EUA Letter of Authorization. Available at 
https://www.fda.gov/media/144636/download.
    \1307\ U.S. Food and Drug Administration (2020). Janssen 
Biotech, Inc. COVID-19 Vaccine EUA Letter of Authorization. 
Available at https://www.fda.gov/media/146303/download.
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    As part of its national strategy to address COVID-19, the Biden-
Harris administration stated that it would work with states and the 
private sector to execute an aggressive vaccination strategy and has 
outlined a goal of administering 200 million shots in 100 days.\1308\ 
After achieve this goal,\1309\ the Biden-Harris Administration 
announced a new goal to administer at least one COVID-19 vaccine shot 
to 70 percent of the U.S. adult population by July 4, 2021.\1310\ 
Although the goal of the U.S. government is to ensure that every 
American who wants to receive a COVID-19 vaccine can receive one, 
Federal agencies recommended that early vaccination efforts focus on 
those critical to the PHE response, including healthcare personnel 
(HCP), and

[[Page 45440]]

individuals at highest risk for developing severe illness from COVID-
19.\1311\ For example, the CDC's Advisory Committee on Immunization 
Practices (ACIP) recommended that HCP should be among those individuals 
prioritized to receive the initial, limited supply of the COVID-19 
vaccination, given the potential for transmission in healthcare 
settings and the need to preserve healthcare system capacity.\1312\ 
Research suggests most states followed this recommendation,\1313\ and 
HCP began receiving the vaccine in mid-December of 2020.\1314\ 
Subsequent to the publication of the SNF PPS proposed rule, on April 8, 
2021, the White House confirmed that there was sufficient vaccine 
supply for all Americans.\1315\
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    \1308\ The White House. Remarks by President Biden on the COVID-
19 Response and the State of Vaccinations. March 29, 2021. Accessed 
at: https://www.whitehouse.gov/briefing-room/speeches-remarks/2021/03/29/remarks-by-president-biden-on-the-covid-19-response-and-the-state-of-vaccinations/.
    \1309\ U.S. Food and Drug Administration. (2021). Janssen COVID-
19 Vaccine EUA Letter of Authorization. Available at https://www.fda.gov/media/146303/download.
    \1310\ The White House. Remarks by President Biden on the COVID-
19 Response and the State of Vaccinations. Accessed on June 4, 2021, 
at: https://www.whitehouse.gov/briefing-room/statements-releases/2021/05/04/fact-sheet-president-biden-to-announce-goal-to-administer-at-least-one-vaccine-shot-to-70-of-the-u-s-adult-population-by-july-4th/.
    \1311\ Health and Human Services, Department of Defense. (2020) 
From the Factory to the Frontlines: The Operation Warp Speed 
Strategy for Distributing a COVID-19 Vaccine. Accessed December 18 
at: https://www.hhs.gov/sites/default/files/strategy-for-distributing-covid-19-vaccine.pdf; Centers for Disease Control 
(2020). COVID-19 Vaccination Program Interim Playbook for 
Jurisdiction Operations. Accessed December 18 at: https://www.cdc.gov/vaccines/imz-managers/downloads/COVID-19-Vaccination-Program-Interim_Playbook.pdf.
    \1312\ Dooling, K, McClung, M, et al. ``The Advisory Committee 
on Immunization Practices' Interim Recommendations for Allocating 
Initial Supplies of COVID-19 Vaccine--United States, 2020.'' Morb. 
Mortal Wkly Rep. 2020; 69(49): 1857-1859. ACIP also recommended that 
long-term care residents be prioritized to receive the vaccine, 
given their age, high levels of underlying medical conditions, and 
congregate living situations make them high risk for severe illness 
from COVID-19.
    \1313\ Kates, J, Michaud, J, Tolbert, J. ``How Are States 
Prioritizing Who Will Get the COVID-19 Vaccine First?'' Kaiser 
Family Foundation. December 14, 2020. Accessed on December 16 at 
https://www.kff.org/policy-watch/how-are-states-prioritizing-who-will-get-the-covid-19-vaccine-first/.
    \1314\ Associated Press. `Healing is Coming:' US Health Workers 
Start Getting Vaccine. December 15, 2020. Accessed on December 16 
at: https://apnews.com/article/us-health-workers-coronavirus-vaccine-56df745388a9fc12ae93c6f9a0d0e81f.
    \1315\ Press Briefing by White House COVID-19 Response Team and 
Public Health Officials [verbar] The White House.
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    HCP are at risk of carrying COVID-19 infection to patients, 
experiencing illness or death as a result of COVID-19 themselves, and 
transmitting it to their families, friends, and the general public. We 
believe it is important to require that LTCHs report COVID-19 HCP 
vaccination in order to assess whether they are taking steps to limit 
the spread of COVID-19 among their HCP, reduce the risk of transmission 
of COVID-19 within their facilities, and to help sustain the ability of 
LTCHs to continue serving their communities throughout the PHE and 
beyond.
    We also believe that publishing facility-level COVID-19 HCP 
vaccination rates on Care Compare would be helpful to many patients, 
including those who are at high-risk for developing serious 
complications from COVID-19, as they choose facilities from which to 
seek treatment. Under the Meaningful Measures framework, the COVID-19 
Vaccination Coverage among Healthcare Personnel measure addresses the 
quality priority of ``Promote Effective Prevention & Treatment of 
Chronic Disease'' through the Meaningful Measures Area of ``Preventive 
Care.''
    Therefore, we proposed a new measure, COVID-19 Vaccination Coverage 
among HCP to assess the proportion of an LTCH's healthcare workforce 
that has been vaccinated against COVID-19.
(2) Stakeholder Input
    In our development and specification of the measure, a transparent 
process was employed to seek input from stakeholders and national 
experts and engage in a process that allows for pre-rulemaking input on 
each measure, under section 1890A of the Act.\1316\ To meet this 
requirement, the following opportunity was provided for stakeholder 
input.
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    \1316\ Centers for Medicare & Medicaid Services. Pre-rulemaking. 
Accessed at https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/QualityMeasures/Pre-Rulemaking.
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    The pre-rule making process includes making publicly available a 
list of quality and efficiency measures, called the Measures Under 
Consideration (MUC) List that the Secretary is considering adopting, 
through Federal rulemaking process, for use in Medicare program(s). 
This allows multi-stakeholder groups to provide recommendations to the 
Secretary on the measures included on the list. The COVID-19 
Vaccination Coverage among Healthcare Personnel measure was included on 
the publicly available ``List of Measures under Consideration for 
December 21, 2020'' (MUC List).\1317\ Five comments were received from 
industry stakeholders during the pre-rulemaking process on the COVID-19 
Vaccination Coverage among HCP measure, and support was mixed. 
Commenters generally supported the concept of the measure. However, 
there was concern about the availability of the vaccine and measure 
definition for HCP, and some commenters encouraged CMS to continue to 
update the measure as new evidence comes in.
---------------------------------------------------------------------------

    \1317\ National Quality Forum. List of Measures Under 
Consideration for December 21, 2020. Accessed at: https://www.cms.gov/files/document/measures-under-consideration-list-2020-report.pdf on January 12, 2021.
---------------------------------------------------------------------------

(3) Measure Applications Partnership (MAP) Review
    When the Measure Applications Partnership (MAP) Post-Acute Care/
Long-Term Care (PAC-LTC) Workgroup convened on January 11, 2021, it 
reviewed the MUC List and the COVID-19 Vaccination Coverage among HCP 
measure. The MAP recognized that the proposed measure represents a 
promising effort to advance measurement for an evolving national 
pandemic and that it would bring value to the LTCH QRP measure set by 
providing transparency about an important COVID-19 intervention to help 
limit COVID-19 infections.\1318\ The MAP also stated that collecting 
information on COVID-19 vaccination coverage among healthcare personnel 
and providing feedback to facilities would allow facilities to 
benchmark coverage rates and improve coverage in their facility, and 
that reducing rates of COVID-19 in healthcare personnel may reduce 
transmission among patients and reduce instances of staff shortages due 
to illness.\1319\
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    \1318\ Measure Applications Partnership. MAP Preliminary 
Recommendations 2020-2021. Accessed on February 3, 2021 at: https://www.qualityforum.org/WorkArea/linkit.aspx?LinkIdentifier=id&ItemID=94650.
    \1319\ Ibid.
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    In its preliminary recommendations, the MAP PAC-LTC Workgroup did 
not support this measure for rulemaking, subject to potential for 
mitigation.\1320\ To mitigate its concerns, the MAP believed that the 
measure needed well-documented evidence, finalized specifications, 
testing, and NQF endorsement prior to implementation.\1321\ 
Subsequently, the MAP Coordinating Committee met on January 25, 2021, 
and reviewed the COVID-19 Vaccination Coverage among Healthcare 
Personnel measure. In the 2020-2021 MAP Final Recommendations, the MAP 
offered conditional support for rulemaking contingent on CMS bringing 
the measures back to MAP once the specifications are further clarified. 
The final MAP report is available at http://www.qualityforum.org/Publications/2021/03/MAP_2020-2021_Considerations_for_Implementing_Measures_Final_Report_-_Clinicians,_Hospitals,_and_PAC-LTC.aspx.
---------------------------------------------------------------------------

    \1320\ Ibid.
    \1321\ Ibid.
---------------------------------------------------------------------------

    In response to the MAP request for CMS to bring the measure back 
once the specifications were further clarified, CMS met with the MAP 
Coordinating Committee on March 15, 2021. First, CMS and CDC clarified 
the alignment of

[[Page 45441]]

the COVID-19 Vaccination Coverage among HCP with the Influenza 
Vaccination Coverage among HCP (NQF #0431), an NQF-endorsed measure 
since 2012. The COVID-19 Vaccination Coverage among HCP measure is 
calculated using the same approach as the Influenza Vaccination 
Coverage among HCP measure.\1322\ The approach to identifying HCPs 
eligible for the COVID-19 vaccination is analogous to those used in the 
NQF endorsed flu measure which underwent rigorous review from technical 
experts about the validity of that approach and for which ultimately 
received NQF endorsement. More recently, prospective cohorts of health 
care personnel, first responders, and other essential and frontline 
workers over 13 weeks in eight U.S. locations confirmed that authorized 
COVID-19 vaccines are highly effective in real-world conditions. 
Vaccine effectiveness of full immunization with two doses of vaccines 
was 90 percent.\1323\
---------------------------------------------------------------------------

    \1322\ The Influenza Vaccination Coverage among Healthcare 
Personnel (NQF #0431) measure which is NQF endorsed and was adopted 
in the IRF QRP in the FY 2014 IRF PPS Final Rule (78 FR 47905 
through 47906), and in the LTCH QRP in the FY 2013 IPPS/LTCH PPS 
Final Rule (77 FR 53630 through 53631).
    \1323\ Centers for Disease Control and Preventions. Morbidity 
and Mortality Weekly Report. March 29, 2021. Available at: https://www.cdc.gov/mmwr/volumes/70/wr/mm7013e3.htm?s_cid=mm7013e3_w.
---------------------------------------------------------------------------

    Additionally, to support the measure's data element validity, the 
CDC conducted testing of the COVID-19 vaccination numerator using data 
collected through the NHSN and independently reported through the 
Federal Pharmacy Partnership for Long-term Care Program for delivering 
vaccines to long-term care facilities. These are two completely 
independent data collection systems. In initial analyses of the first 
month of vaccination for approximately 1,200 facilities that had data 
from both systems, the number of HCP vaccinated was highly correlated 
between these two systems with a correlation coefficient of nearly 90 
percent in the second two weeks of reporting. Of note, assessment of 
data element reliability may not be required by NQF if data element 
validity is demonstrated.\1324\ To assess the validity of new 
performance measure score (in the case, percentage of COVID-19 
vaccination coverage), NQF allows assessment by face validity (that is, 
subjective determination by experts that the measure appears to reflect 
quality of care, done through a systematic and transparent 
process),\1325\ and the MAP concurred with the face validity of the 
COVID-19 Vaccination Coverage among HCP measure. Materials from the 
March 15, 2021 MAP Coordinating Committee meeting can be found on the 
NQF website here: https://www.qualityforum.org/ProjectMaterials.aspx?projectID=75367.
---------------------------------------------------------------------------

    \1324\ National Quality Form. Key Points for Evaluating 
Scientific Acceptability. Revised January 3, 2020. https://
www.qualityforum.org/Measuring_Performance/Scientific_Methods_Panel/
Docs/
Evaluation_Guidance.aspx#:~:text=NQF%20is%20not%20prescriptive%20abou
t,reliability%20or%20validity%20testing%20results.&text=Reliability%2
0and%20validity%20must%20be,source%20and%20level%20of%20analysis)
    \1325\ Ibid.
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    This measure is not NQF endorsed, but the CDC, in collaboration 
with CMS, plans to submit the measure for consideration in the Fall NQF 
2021 measure cycle.
(4) Competing and Related Measures
    Section 1886(m)(5)(D)(i) of the Act requires that absent an 
exception under section 1886(m)(5)(D)(ii) of the Act, measures 
specified under section 1886(m)(5)(D) of the Act be endorsed by the 
entity with a contract under section 1890(a) of the Act, currently the 
National Quality Forum (NQF). In the case of a specified area or 
medical topic determined appropriate by the Secretary for which a 
feasible and practical measure has not been endorsed, section 
1886(m)(5)(D)(ii) of the Act permits the Secretary to specify a measure 
that is not so endorsed, as long as due consideration is given to the 
measures that have been endorsed or adopted by a consensus organization 
identified by the Secretary. Section 1899B(e)(2)(A) of the Act requires 
that, subject to section 1899B(e)(2)(B) of the Act, each measure 
specified by the Secretary under section 1899B of the Act be endorsed 
by the entity with a contract under section 1890(a) of the Act. 
However, in the case of a specified area or medical topic determined 
appropriate by the Secretary for which a feasible and practical measure 
has not been endorsed by the entity with a contract under section 
1890(a) of the Act, the Secretary may specify a measure that is not so 
endorsed as long as due consideration is given to measures that have 
been endorsed or adopted by a consensus organization identified by the 
Secretary. The proposed COVID-19 Vaccination Coverage among HCP measure 
is not currently NQF endorsed and has not been submitted to the NQF for 
consideration, so we considered whether there are other available 
measures that assess COVID-19 vaccinations among HCP. After review of 
the NQF's consensus-endorsed measures, we were unable to identify any 
NQF-endorsed measures for LTCHs focused on capturing COVID-19 
vaccination coverage among HCP, and we found no other feasible and 
practical measure on the topic of COVID-19 vaccination coverage among 
HCP. The only other vaccination coverage of HCP measure we found was 
the Influenza Vaccination Coverage among Healthcare Personnel (NQF 
#0431) measure which is NQF endorsed and was adopted in the LTCH QRP in 
the FY 2013 IPPS/LTCH PPS Final Rule (77 FR 53630 through 53631).
    Given the novel nature of the SARS-CoV-2 virus, and the significant 
and immediate risk it poses in LTCHs, we believe it is necessary to 
finalize the measure as soon as possible. Therefore, after 
consideration of other available measures that assess COVID-19 
vaccination rates among HCP, we believe the exception under section 
1899B(e)(2)(B) of the Act applies. This measure has the potential to 
generate actionable data on vaccination rates that can be used to 
target quality improvement among LTCH providers.
(5) Quality Measure Calculation
    The COVID-19 Vaccination Coverage among Healthcare Personnel (HCP) 
measure is a process measure developed by the CDC to track COVID-19 
vaccination coverage among HCP in facilities such as LTCHs. Since this 
measure is a process measure, rather than an outcome measure, it does 
not require risk-adjustment.
    The denominator would be the number of HCP eligible to work in the 
LTCH for at least one day during the reporting period, excluding 
persons with contraindications to COVID-19 vaccination described by the 
CDC.\1326\
---------------------------------------------------------------------------

    \1326\ Centers for Disease Control and Prevention. Interim 
Clinical Considerations for Use of COVID-19 Vaccines Currently 
Authorized in the United Sates. Accessed at: https://www.cdc.gov/vaccines/covid-19/info-by-product/clinical-considerations.html.
---------------------------------------------------------------------------

    The numerator would be the cumulative number of HCP eligible to 
work in the LTCH for at least 1 day during the reporting period and who 
received a complete vaccination course against SARS-CoV-2. A complete 
vaccination course may require one or more doses depending on the 
specific vaccine used. The finalized measure specifications can be 
found on the CDC website here: https://www.cdc.gov/nhsn/nqf/index.html.
    We proposed that LTCHs would submit data for the measure through 
the CDC/NHSN data collection and submission framework.\1327\ This

[[Page 45442]]

framework is currently used for reporting the CAUTI (NQF #0318) and 
Influenza Vaccination Coverage among Healthcare Personnel (NQF #0431) 
measures. LTCHs would use the COVID-19 vaccination data reporting 
module in the NHSN Healthcare Personnel Safety (HPS) Component to 
report the number of HCP eligible who have worked at the facility that 
week (denominator) and the number of those HCP who have received a 
completed COVID-19 vaccination course (numerator). LTCHs would submit 
COVID-19 vaccination data for at least one week each month. If LTCHs 
submit more than 1 week of data in a month, the most recent week's data 
would be used for measure calculation purposes. Each quarter, the CDC 
would calculate a summary measure of COVID-19 vaccination coverage from 
the 3 monthly modules reported for the quarter. This quarterly rate 
would be publicly reported on the Care Compare website. Subsequent to 
the first refresh, one additional quarter of data would be added to the 
measure calculation during each advancing refresh, until the point four 
full quarters of data is reached. Thereafter, the measure would be 
reported using four rolling quarters of data on Care Compare.
---------------------------------------------------------------------------

    \1327\ Centers for Disease Control and Prevention. Surveillance 
for Weekly HCP COVID-19 Vaccination. Accessed at: https://www.cdc.gov/nhsn/hps/weekly-covid-vac/index.html on February 10, 
2021.
---------------------------------------------------------------------------

    For purposes of submitting data to CMS for the FY 2023 LTCH QRP, 
LTCHs would be required to submit data for the period October 1, 2021 
through December 31, 2021. Following the initial data submission 
quarter for the FY 2023 LTCH QRP, subsequent compliance for the LTCH 
QRP would be based on a full calendar year of data submission. For more 
information on the measure's proposed public reporting period, we refer 
readers to section IX.E.9.d. of this final rule.
    We invited public comments on our proposal to add a new measure, 
COVID-19 Vaccination Coverage among Healthcare Personnel, to the LTCH 
QRP beginning with the FY 2023 LTCH QRP.
    Comment: A number of commenters support the proposal to adopt the 
COVID-19 Vaccination Coverage among HCP measure for the LTCH QRP. A 
commenter mentioned that the COVID-19 pandemic had a disproportionate 
and devastating impact on older adults living in congregate care 
settings and expressed that this measure is vitally important to 
protect the health and wellbeing of the community, particularly older 
adults. Commenters agree that the measure would help assess the degree 
to which LTCHs are taking steps to limit the spread of COVID-19 and 
reduce the risk of transmission within their facilities. Commenters 
pointed out that public reporting of COVID-19 vaccination among HCP on 
Care Compare would provide consumers with important information with 
which to make informed decisions about the safety of an LTCH. 
Commenters also believe the information would provide greater 
transparency to stakeholders seeking to effectively target vaccine 
hesitancy.
    Response: We thank the commenters for their support. We agree that 
the COVID-19 pandemic has had a disproportionate and devastating impact 
on older adults living in congregate care settings and that the COVID-
19 Vaccination among HCP measure will help assess the degree to which 
LTCHs are taking steps to limit the spread of COVID-19 and reduce the 
risk of transmission within their facilities. Consistent with 
information published by the CDC and others, LTCHs can be high-risk 
places for COVID-19 exposure and transmission, and COVID-19 can spread 
among HCP and residents given the close contact that may occur during 
the provision of care.\1328\ Additionally, Medscape Medical News 
reported on June 28, 2021,\1329\ that Federal data show one in four 
hospital workers across the United States are still unvaccinated, and 
only one in every three hospital workers are vaccinated in the nation's 
50 largest health systems. We agree with commenters that public 
reporting of COVID-19 Vaccination Coverage among HCP on Care Compare 
would provide consumers with important information with which to make 
informed decisions about the safety of an LTCH, and would provide 
greater transparency to Federal officials and other stakeholders 
seeking to effectively target vaccine hesitancy.
---------------------------------------------------------------------------

    \1328\ Chen MK, Chevalier JA, Long EF. Nursing home staff 
networks and COVID-19. Proceedings of the National Academy of 
Sciences of the United States of America (PNAS). Available at: 
https://www.pnas.org/content/118/1/e2015455118. Accessed June 29, 
2021.
    \1329\ Medscape. Disturbing Number of Hospital Workers Still 
Unvaccinated. Available at: https://www.medscape.com/viewarticle/953871. Accessed July 13, 2021.
---------------------------------------------------------------------------

    Comment: We received numerous comments requesting that CMS delay 
the adoption of the COVID-19 Vaccination Coverage among HCP measure 
until it has received NQF endorsement. Commenters were concerned that 
since the measure has not been fully specified, tested, or endorsed by 
the NQF, then it may not be thoroughly tested and vetted, and may 
impact patients' certainty that the data they rely on are reliable. 
Other commenters included language from the Post-Acute Care/Long-term 
Care Workgroup (Workgroup) of the Measures Application Partnership 
(MAP) meeting transcript to support their position. They urged the 
agency, in addition to seeking NQF endorsement, to fully develop and 
test the measure for reliability and accuracy before implementing it in 
the LTCH QRP.
    Response: Given the novel nature of the SARS-CoV-2 virus, and the 
significant and immediate health risk it poses in LTCHs, we believe it 
is necessary to adopt this measure as soon as possible. Additionally, 
given the results from CDC's preliminary validity testing of the data 
elements required for the measure numerator (described in Section 
IX.E.4.a.(3) of the FY 2022 IPPS/LTCH PPS proposed rule (86 FR 25070), 
the alignment between the denominator of this measure and the 
denominator of the Influenza Vaccination among HCP (NQF #0431) measure, 
and the MAP's determination that the COVID-19 Vaccination Coverage 
among HCP measure has face validity, CMS proposes the COVID-19 
Vaccination Coverage among HCP measure beginning with the FY 2023 QRP. 
As discussed in Section #.E.4.a(4) of this final rule, CMS proposed to 
adopt this measure without NQF endorsement, as we were unable to 
identify any NQF-endorsed measures for LTCHs focused on capturing 
COVID-19 vaccination coverage among HCP, and we found no other feasible 
and practical measure on the topic of COVID-19 vaccination coverage 
among HCP. The CDC as the measure steward, in collaboration with CMS, 
plans to submit the measure for consideration in the Fall NQF 2021 
measure cycle.
    Comment: In the context of raising concerns about unanswered 
questions related to COVID-19 vaccines and their potential to affect 
the appropriateness of this measure, some commenters questioned whether 
there would be COVID-19 seasons similar to how there are flu seasons. 
Another commenter stated it is not clear how the COVID-19 ``season'' is 
defined, or whether it would be associated with the initial vaccination 
process or potential boosters in the future.
    Response: CMS appreciates that there are unanswered questions 
related to the SARS-CoV-2 virus and COVID-19 vaccinations, including 
whether COVID-19 seasons may develop similar to the way other human 
coronaviruses and influenza have seasons. In the event that seasonal 
COVID-19 patterns emerge, CMS will collaborate with the CDC to 
determine whether specification

[[Page 45443]]

and reporting changes for the COVID-19 Vaccination Coverage among HCP 
measure are appropriate. In the meantime, CMS believes the current 
measure specifications appropriately reflect current COVID-19 vaccine 
recommendations.
    Comment: In reaction to CMS' characterization of the alignment 
between the Influenza Vaccination Coverage among HCP (NQF #0431) 
measure and the COVID-19 Vaccination Coverage among HCP measure, some 
commenters raised concerns about specification differences. They 
believe there are key differences between the two measures, such as how 
the vaccines are administered and data are collected. Specifically, 
some commenters pointed out that the Influenza Vaccination Coverage 
among HCP (NQF #0431) measure utilizes HCP working in the facility for 
the denominator whereas the proposed COVID-19 metric utilizes HCP 
eligible to work in the facility.
    Response: We acknowledge that there are implementation differences 
between the two measures, even though the CDC modeled the COVID-19 
Vaccination Coverage among HCP measure after the Influenza Vaccination 
Coverage among HCP (NQF #0413) measure. Nevertheless, the measures are 
aligned with respect to the reporting mechanism used to report data 
(that is, NHSN) and key components of the measure specifications (for 
example, the types of personnel included in the denominator), but still 
allow for important differences. These differences are necessary to 
ensure the validity of the COVID-19 Vaccination Coverage among HCP 
measure, as the administration of the influenza vaccine and the COVID-
19 vaccine differ in multiple ways.
    The intent of the COVID-19 Vaccination among HCP measure is to 
include HCP who work regularly in the LTCH. However, many HCP who 
regularly work in a LTCH may be temporarily absent due to illness, 
injury, or vacation/leave. Because the measurement period covered by 
the Influenza Vaccination Coverage among HCP (NQF #0431) measure is 
quite long (the entire 6 month influenza season), such absences will 
not impact the Influenza Vaccination Coverage among HCP (NQF #0431) 
measure denominator. However, the measurement period of the COVID-19 
Vaccination among HCP measure is only one week, considerably shorter 
than the time period covered by the Influenza Vaccination Coverage 
among HCP (NQF #0431) measure, so a number of regularly working HCP may 
be absent during this shortened period. Therefore, HCP who regularly 
work in the LTCH, but may be temporarily absent for up to 2 weeks, are 
still to be included in the COVID-19 Vaccination among HCP measure. We 
refer readers to section ##.E.4.a.(5) of this final rule and to the 
Instructions for Completion of the Weekly Healthcare Personnel COVID-19 
Vaccination Cumulative Summary Form for Non-Long-Term Care Facilities 
(57.220, Rev 3) at https://www.cdc.gov/nhsn/forms/instr/57.220-toi-508.pdf which explains how to determine eligible HCP for the measure.
    Comment: A commenter questioned whether the COVID-19 Vaccination 
among HCP measure aligned with the Merit-based Incentive Payment System 
(MIPS) measure that was reviewed by the MAP and assesses patients who 
received at least one dose (in addition to a complete course).
    Response: We understand the commenter to be inquiring as to whether 
this measure is similar to the measure considered for another quality 
reporting program, the Merit-based Incentive Payment System (MIPS) for 
clinicians. If so, MUC--0045, the SARS-Co-V-2 Vaccination by Clinician 
measure differs from the COVID-19 Vaccination among HCP measure. Most 
notably, the SARS-CoV-2 Vaccination by Clinician measure assesses the 
proportion of patients who received at least one SARS-CoV-2 vaccination 
while the COVID-19 Vaccination among HCP measure assesses the 
proportion of HCP who complete a SARS-CoV-2 vaccination course.
    Comment: Some commenters submitted comments stating they believe it 
is premature to begin tracking COVID-19 vaccinations because the COVID-
19 vaccines are authorized through an EUA and do not have full FDA 
approval at this time. Several commenters stated the measure should not 
be adopted until all existing vaccines authorized under an EUA have 
received full approval by FDA. Another commenter stated that until FDA 
approves the vaccines, they do not have control over the vaccination 
status of their employees.
    Response: We disagree with the comment that tracking COVID-19 
vaccinations is premature because the vaccines are authorized through 
an EUA. We believe that due to the continued COVID-19 PHE and the 
ongoing risk of infection transmission in the LTCH population, the 
benefits of finalizing this measure in this year's final rule are 
essential for patient safety. The COVID-19 vaccines are authorized by 
FDA for widespread use through EUAs. We refer readers to the FDA 
website for additional information related to FDA's process for 
evaluating an EUA request at https://www.fda.gov/vaccines-blood-biologics/vaccines/emergency-use-authorization-vaccines-explained. 
Additionally, two of the three vaccines authorized for emergency use 
are shown to be 90 to 95% effective in preventing COVID-19 in persons 
without prior infection, and are equally effective across a variety of 
characteristics, including age, gender, race, ethnicity, and body mass 
index or presence of other medical conditions.1330 1331 In 
clinical trials, the Pfizer vaccine was 100% effective at preventing 
severe disease. The third vaccine authorized for emergency use 
demonstrates it is 93.1% effective at preventing COVID-19 
hospitalization and 75% effective against all-cause death.\1332\
---------------------------------------------------------------------------

    \1330\ Effectiveness of Pfizer--.
    \1331\ Effectiveness of Pfizer-BioNTech and Moderna Vaccines 
Against COVID-19 Among Hospitalized Adults Aged >=65 Years--United 
States, January-March 2021. Morbidity and Mortality Weekly Report 
(MMWR). May 7, 2021. Available at: https://www.cdc.gov/mmwr/volumes/70/wr/mm7018e1.htm?s_cid=mm7018e1_w. Accessed July 19, 2021.
    \1332\ The Advisory Committee on Immunization Practices' Interim 
Recommendation for Use of Janssen COVID-19 Vaccine--United States, 
February 2021. Morbidity and Mortality Weekly Report (MMWR). March 
5, 2021. Available at: https://www.cdc.gov/mmwr/volumes/70/wr/mm7009e4.htm. Accessed July 19, 2021.
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    The U.S. Equal Employment Opportunity Commission (EEOC) released 
updated and expanded technical assistance on May 28, 2021.\1333\ 
Specifically, the EEOC stated the Federal equal employment opportunity 
(EEO) laws do not prevent an employer from requiring all employees 
physically entering the workplace to be vaccinated for COVID-19, so 
long as the employer complies with the reasonable accommodation 
provisions of the Americans with Disabilities Act (ADA) and Title VII 
of the Civil Rights Act of 1964 and other EEO considerations. However, 
the adoption of this measure does not require that HCP complete a 
COVID-19 vaccination course. In addition, FDA is closely monitoring the 
safety of the COVID-19 vaccines authorized for emergency use. 
Additionally, even if LTCHs have limited control over the vaccination 
status of their employees, the information collected by this measure is 
vitally important and useful to stakeholders.
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    \1333\ U.S. Equal Employment Opportunity Commission. What You 
Should Know About COVID-19 and the ADA, the Rehabilitation Act, and 
Other EEO Laws. Available at: https://www.eeoc.gov/wysk/what-you-should-know-about-covid-19-and-ada-rehabilitation-act-and-other-eeo-laws. Accessed June 25, 2021.
---------------------------------------------------------------------------

    Comment: A commenter stated that if CMS proceeded with finalizing 
the

[[Page 45444]]

measure, they strongly encourage the agency to consider including all 
HCP in the denominator, at least for an initial reporting period, to 
allow for consistent cross-provider reporting and accurate measurement 
and comparisons. The commenter also stated that if CMS publicly reports 
this measure, there should be a clear explanation that the measure 
includes HCP with contraindications.
    Response: We interpret the commenter to be stating that the 
denominator should include HCP with and without contraindication to the 
vaccination. We believe that excluding HCP with contraindications from 
the measure strikes an appropriate balance between obtaining accurate 
estimates of vaccine rates among HCP within LTCHs and not holding an 
LTCH accountable for HCP with a COVID-19 vaccination contraindication, 
as the number of HCP with contraindications or exclusions from 
vaccination is expected to be low.
    Comment: Several commenters requested CMS provide clarification 
about how evolving vaccine recommendations will be accounted for in the 
COVID-19 Vaccination among HCP measure proposed for the LTCH QRP. A 
commenter noted that CMS proposed a COVID-19 Vaccination Coverage among 
HCP measure for the Inpatient Quality Reporting (IQR) program in the FY 
2022 Inpatient Prospective Payment System (IPPS)/LTCH proposed rule (86 
FR 25573) and stated the numerator would be calculated based on HCP who 
received a completed vaccination course ``since the vaccine was first 
available or on a repeated interval if revaccination is recommended.'' 
They requested CMS provide clarification how evolving vaccine 
recommendations will be accounted for in the COVID-19 Vaccination among 
HCP measure proposed for the LTCH QRP. Several commenters specifically 
questioned how vaccination boosters would factor into reporting 
requirements. Several commenters believe it would be premature for CMS 
to adopt the measure because it is unknown how long the COVID-19 
vaccination would be effective as well as whether and how often booster 
shots may be required. Commenters noted that these were important 
unanswered questions they thought would affect both the design and 
feasibility of any HCP vaccination measure and would likely result in a 
change to the measure definition. Several commenters suggested CMS wait 
until expectations are clarified about maintaining employees' COVID-19 
vaccinations.
    Response: The COVID-19 Vaccination Coverage among HCP measure is a 
measure of a completed vaccination course (as defined in Section 
IX.E.4.a(5) of the FY 2022 IPPS/LTCH PPS proposed rule (86 FR 25070)). 
A complete vaccination course may require one or more doses depending 
on the specific vaccine used. Currently, the need for COVID-19 booster 
doses has not been established, and no additional doses are currently 
recommended for HCP.\1334\ However, we believe that the numerator is 
sufficiently broad to include potential future boosters as part of a 
``complete vaccination course'' and therefore the measure is 
sufficiently specified to address boosters.
---------------------------------------------------------------------------

    \1334\ Centers for Disease Control and Prevention. Vaccine 
Administration. Available at: https://www.cdc.gov/vaccines/covid-19/clinical-considerations/covid-19-vaccines-us.html. Accessed June 25, 
2021.
---------------------------------------------------------------------------

    Comment: A couple of commenters expressed concern about unintended 
consequences and legal risks to their organization if HCP experience an 
adverse event related to vaccination, and therefore oppose adoption of 
the COVID-19 Vaccination Coverage among HCP measure into the LTCH QRP.
    Response: It is unclear what unintended consequences and legal 
risks the commenters are referring to. The LTCH QRP is a pay-for-
reporting program, and LTCHs are assessed under the program based on 
whether they have met the LTCH QRP's reporting requirements. The 
COVID19 Vaccination among HCP measure would not require LTCH HCP to 
receive the vaccine in order for LTCHs to successfully report the 
measure. We proposed the COVID-19 Vaccination Coverage among HCP to 
capture the number of HCP who have received a completed vaccine course.
    Comment: A commenter raised concerns that this measure may compel 
facilities to ensure their employees are vaccinated, and that mandates 
could be beneficial to measure performance. The commenter pointed out 
that the decision to implement a mandate in some cases may be beyond 
providers' control, as multiple states have introduced or passed 
legislation prohibiting discrimination on COVID-19 vaccination status; 
other existing state laws might also prohibit mandatory vaccine 
policies. In practical terms, this could mean that facilities that are 
unable to mandate COVID-19 vaccines could be at a systematic 
performance disadvantage on the measure. Another commenter states it 
would be difficult for providers in some states to accurately collect 
and report data on vaccination coverage due to new state laws 
restricting an employer's ability to obtain information regarding an 
employee's vaccination status. They claim that by adding this measure, 
CMS would be mandating providers to report data that may be limited due 
to state restrictions.
    Response: Adoption of the COVID-19 Vaccination Coverage among HCP 
measure into the LTCH QRP would not mandate or require LTCH HCP to 
complete a COVID-19 vaccination course. It could be the case that LTCHs 
that do not require their HCP to be vaccinated could have lower 
vaccination rates than LTCHs that do. However, an LTCH's ability to 
require vaccines does not make the information provided by this measure 
any less valuable or important to stakeholders. We believe it is 
important that LTCHs report the COVID-19 Vaccination Coverage among HCP 
measure as soon as possible to assess the potential spread of COVID-19 
among their HCP and reduce the risk of transmission of COVID-19 within 
their facilities, and to help sustain the ability of LTCHs to continue 
serving their communities throughout the PHE and beyond.
    Comment: Several commenters raised concerns about factors affecting 
COVID-19 vaccination rates that they feel are out of their control. For 
example, some commenters expressed concern over future availability of 
vaccines, including a commenter who specifically expressed concern over 
the potential for supply chain disruptions that could impact measure 
performance through no fault of their own. Another commenter described 
challenges related to vaccine availability where the LTCH is located 
and the personal preferences of a facility's staff.
    Response: We proposed this measure to provide information to 
stakeholders about the extent to which HCP have completed a COVID-19 
vaccination course during a defined period of time. Factors such as 
vaccine availability, geographic location, and personal staff 
preferences ultimately do not make the information captured by this 
measure any less valuable to stakeholders. However, if an LTCH believes 
they were disproportionately affected by the PHE, they have the 
opportunity to apply for an individual exception or extension within 90 
days of the date that the extraordinary circumstances occurred as set 
forth in our regulations at 42 CFR 412.560(c). Instructions for 
requesting an extraordinary circumstances exemption (ECE) may be found 
on the LTCH QRP Reconsideration and Exception and Extension web page at 
https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-

[[Page 45445]]

Instruments/LTCH-Quality-Reporting/LTCH-Quality-Reporting-
Reconsideration-and-Exception-and-Extension. Additionally, subsequent 
to the publication of the FY 2022 IPPS/LTCH PPS proposed rule, on April 
27, 2021, the White House confirmed that there was sufficient vaccine 
supply for all Americans.\1335\
---------------------------------------------------------------------------

    \1335\ Press Briefing by White House COVID-19 Response Team and 
Public Health Officials [verbar] The White House
---------------------------------------------------------------------------

    Comment: Multiple commenters responded about challenges related to 
collecting information required for measure reporting. A commenter 
expressed that their employees' medical records are not kept in the 
primary electronic health record (EHR), as this is an Occupational 
Safety and Health Administration (OSHA) violation. They go on to 
explain that this means they will need to build their own reports to 
abstract these data. Another commenter noted that some personnel may 
have received their vaccine outside the facility at mass vaccination 
sites, and collecting these data across personnel could prove 
burdensome. Another commenter explained that existing systems do not 
capture information pertaining to the measure's inclusion criteria, 
listing COVID-19 vaccine contraindications as an example. The same 
commenter also has concerns related to challenges providers may have 
accounting for adult/student trainees and volunteers.
    Response: LTCHs have experience tracking information and collecting 
data to inform their care approaches and business practices. CMS 
acknowledges there will be initial burden in collecting the information 
and this is accounted for in Section #.B.7 of this final rule. The data 
sources for the number of HCP who have received COVID-19 vaccines may 
include HCP health records and paper and/or electronic documentation of 
vaccination given at the healthcare facility, pharmacy, or elsewhere. 
Further, HCP receiving vaccination elsewhere may provide documentation 
of vaccination. We are confident in LTCHs' abilities to track the 
COVID-19 vaccination information of their HCP. In addition, as more 
people become vaccinated, the burden of tracking who has had one or 
more doses should decline.
    Comment: A commenter expressed that a hospital or a person should 
not be penalized because some people cannot receive vaccines for 
various reasons, and expressed that it is discrimination to separate 
the vaccinated from the unvaccinated. The commenter goes on to explain 
that people need to have choices and do what is best for their health.
    Response: The LTCH QRP is a pay-for-reporting program, meaning that 
penalties are tied to measure reporting and not performance. 
Additionally, this measure does not separate the vaccinated from the 
unvaccinated, but rather reports on the proportion of HCP who have 
completed a COVID-19 vaccination course at a given LTCH during a 
defined time period. Finally, this measure does not mandate the receipt 
of COVID-19 vaccines.
    Comment: A commenter had a concern with the measure specifications 
because their healthcare system has some employees that work at three 
different hospitals within the health care system during any one week 
period. They requested clarification on how these employees would be 
reported for purposes of the COVID-19 Vaccination among HCP measure.
    Response: The LTCH QRP is distinct and separate from other CMS 
Quality Reporting Programs, and therefore any HCP that is eligible to 
work one day during the reporting period in the LTCH is counted for 
purposes of the COVID-19 Vaccination Coverage among HCP measure, 
regardless of whether they work in another facility who is also 
reporting the same measure. Section 1886(m)(5)(F) of the Act requires 
each LTCH to submit data on resource use and other measures under 
section 1899(d)(1) of the Act to the Secretary.
    Comment: A commenter questioned adopting the measure since they 
assert that there are remaining unanswered questions they believe 
affect both the design and feasibility of any HCP vaccination measure, 
such as how long the vaccines confer immunity.
    Response: We acknowledge the science around the SARS-CoV-2 virus 
continues to evolve. It is another reason the COVID-19 Vaccination 
Coverage among HCP measure is so important. Population immunity means 
that enough people in a community are protected from getting a disease 
because they have already had the disease or because they have been 
vaccinated. Population immunity makes it hard for the disease to spread 
from person to person.\1336\
---------------------------------------------------------------------------

    \1336\ Centers for Disease Control and Prevention. Population 
Immunity. Available at: https://www.cdc.gov/coronavirus/2019-ncov/vaccines/keythingstoknow.html. Accessed June 25, 2021.
---------------------------------------------------------------------------

    We are still learning how effective the vaccines are against new 
variants of the virus that cause COVID-19. Current evidence suggests 
that the COVID-19 vaccines authorized for use in the United States 
offer protection against most variants currently spreading in the 
United States.\1337\ The CDC will continue to monitor how vaccines are 
working to see if variants have any impact on how well COVID-19 
vaccines work in real-world conditions.
---------------------------------------------------------------------------

    \1337\ Centers for Disease Control and Prevention. COVID-19 
vaccines and new variants. Available at: https://www.cdc.gov/
coronavirus/2019-ncov/vaccines/effectiveness/
work.html#:~:text=COVID%2D19%20vaccines%20and%20new%20variants%20of%2
0the%20virus&text=Current%20data%20suggest%20that%20COVID,after%20the
y%20are%20fully%20vaccinated. Accessed June 25, 2021.
---------------------------------------------------------------------------

    Comment: A commenter is concerned that the proposed measure will 
create significant implementation challenges and that it may not be 
feasible for many providers to accurately report on. One reason given 
for this was that the indications and contraindications for the COVID-
19 vaccination have changed at a relatively high frequency, and they 
are concerned they may continue to change.
    Response: The contraindications have not changed. Contraindications 
are listed in the FDA Fact Sheets 1338 1339 1340 and in the 
Interim Clinical Considerations for Use of COVID-19 Vaccines Currently 
Authorized in the United States at https://www.cdc.gov/vaccines/covid-19/clinical-considerations/covid-19-vaccines-us.html. Information may 
be updated based on data from safety monitoring systems at any time. 
Contraindications and other clinical considerations are accounted for 
in the COVID-19 Vaccination Coverage among HCP measure.
---------------------------------------------------------------------------

    \1338\ See, e.g., U.S. Food and Drug Administration. (2021). 
Fact Sheet for Healthcare Providers Administering Vaccine, Emergency 
Use Authorization (EUA) of the Pfizer-BioNTech COVID-19 Vaccine to 
Prevent Coronavirus Disease 2019 (COVID-19). Available at: https://www.fda.gov/media/144413/download.
    \1339\ See, e.g., U.S. Food and Drug Administration. (2021). 
Fact Sheet for Healthcare Providers Administering Vaccine, Emergency 
Use Authorization (EUA) of the Moderna COVID-19 Vaccine to Prevent 
Coronavirus Disease 2019 (COVID-19). Available at: https://www.fda.gov/media/144637/download.
    \1340\ See, e.g., U.S. Food and Drug Administration. (2021). 
Fact Sheet for Healthcare Providers Administering Vaccine, Emergency 
Use Authorization (EUA) of the Janssen COVID-19 Vaccine to Prevent 
Coronavirus Disease 2019 (COVID-19). Available at: https://www.fda.gov/media/146304/download.
---------------------------------------------------------------------------

    Comment: A commenter believes the reporting burden of the COVID-19 
Vaccination Coverage among HCP measure to be unreasonable for several 
reasons, including training and revisions to QRP reporting processes, 
as well as updating IT systems that LTCHs will have to undertake. They 
state that tracking the Influenza Vaccination Coverage of HCP (NQF 
#0431) measure

[[Page 45446]]

across all employees, licensed independent practitioners, adult 
students and trainees, and volunteers over the age of 18 has been 
challenging and burdensome, and requiring LTCHs to track COVID-19 
vaccination coverage among these same groups is an unreasonable burden 
when the COVID-19 pandemic is still ongoing.
    Response: LTCHs are currently required to submit data for the 
Influenza Vaccination among HCP measure (NQF #0431) to the CDC's NHSN 
Healthcare Personnel Safety Component (HPS) annually. While LTCHs will 
not have the burden of registering and learning how to use the NHSN, we 
acknowledge there will be burden with collecting the required 
information. However, we believe it will be minimal because LTCHs 
already have experience successfully reporting information using the 
NHSN reporting modules. We refer readers to Section #.B.7. of this 
final rule for an estimate of burden related to the COVID-19 
Vaccination Coverage among HCP measure.
    We believe it is important that LTCHs report COVID-19 HCP 
vaccination rates as soon as possible to assess the potential spread of 
COVID-19 among their HCP and the risk of transmission of COVID-19 
within their facilities, and to help sustain the ability of LTCHs to 
continue serving their communities throughout the PHE and beyond. 
Additionally, consistent vaccination reporting by LTCHs via the NHSN 
will help CMS to identify additional resources and tools LTCHs may need 
to address the challenges of the PHE.
    Comment: A commenter disagreed with the proposal of adopting the 
COVID-19 Vaccination Coverage among HCP measure to the LTCH QRP, citing 
the fact that any new measure added to the LTCH QRP creates another 
basis for CMS to financially penalize LTCHs for even the smallest 
infractions of the multitudinous guidance documents concerning not only 
the reporting of the quality data itself, but the many technical 
elements that need to be perfectly executed in the CDC's NHSN system 
for that quality data to be processed and transferred to CMS. They feel 
that providers should never be financially penalized if they report all 
their quality data by the reporting deadlines, but especially when the 
quality measure concerns an ongoing global pandemic.
    Response: Section 1886(m)(5)(A)(i) of the Act requires the 
Secretary to apply the 2 percent payment reduction under the LTCH QRP 
to LTCHs that fail to meet the LTCH QRP reporting requirements during a 
fiscal year. LTCHs are not financially penalized if they report all 
their LTCH QRP data by the reporting deadlines.
    There are reports available in the Analysis Reports section of NHSN 
which LTCHs can run to verify their data are complete.\1341\ 
Additionally, CMS' contractor sends informational messages to LTCHs 
that are not meeting Annual Payment Update (APU) thresholds on a 
quarterly basis ahead of each submission deadline. Information about 
how to sign up for these alerts can be found on the LTCH QRP Help web 
page at https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/LTCH-Quality-Reporting/LTCH-Quality-Reporting-Help.
---------------------------------------------------------------------------

    \1341\ Detailed guidance can be found at: https://www.cdc.gov/nhsn/cms/index.html. If you have questions regarding these reports 
within NHSN, please contact the NHSN Help Desk at cdc.gov">NHSN@cdc.gov.
---------------------------------------------------------------------------

    Comment: A commenter did not support the proposed COVID-19 
Vaccination Coverage among HCP measure because it only excludes 
patients who do not get a COVID-19 vaccine due to medical 
contraindications. They state that since the EEOC requires employers to 
provide a reasonable accommodation if an employee's sincerely held 
religious belief, practice or observance prevents them from receiving 
the vaccination, the EEOC policy conflicts with the specifications of 
the proposed measure.
    Response: We believe the commenter is referring to the updated and 
expanded technical assistance the EEOC issued on May 28, 2021.\1342\ 
CMS disagrees that the proposal conflicts with the EEOC's guidance. 
Specifically the EEOC stated the EEO laws do not prevent an employer 
from requiring all employees physically entering the workplace to be 
vaccinated for COVID-19, so long as the employer complies with the 
reasonable accommodation provisions of the Americans with Disabilities 
Act (ADA) and Title VII of the Civil Rights Act of 1964 and other EEO 
considerations. This measure would report the number of HCP who have 
received a COVID-19 vaccination, but it does not require LTCH HCP to 
receive a COVID-19 vaccination.
---------------------------------------------------------------------------

    \1342\ U.S. Equal Employment Opportunity Commission. What You 
Should Know About COVID-19 and the ADA, the Rehabilitation Act, and 
Other EEO Laws. Available at: https://www.eeoc.gov/wysk/what-you-should-know-about-covid-19-and-ada-rehabilitation-act-and-other-eeo-laws. Accessed June 25, 2021.
---------------------------------------------------------------------------

    Final Decision: After careful consideration of the public comments, 
we are finalizing our proposal as proposed to adopt the COVID-19 
Vaccination Coverage among HCP measure to the LTCH QRP beginning with 
the FY 2023 LTCH QRP.
b. Update to the Transfer of Health (TOH) Information to the Patient--
Post-Acute Care (PAC) Measure Beginning With the FY 2023 LTCH QRP
    We proposed to update the Transfer of Health Information to the 
Patient--Post-Acute Care (PAC) measure denominator to exclude patients 
discharged home under the care of an organized home health service or 
hospice. This measure assesses for and reports on the timely transfer 
of health information, specifically transfer of a medication list. We 
adopted this measure in the FY 2020 IPPS/LTCH PPS final rule (84 FR 
42525 through 42535) beginning with the FY 2022 LTCH QRP. It is a 
process measure that evaluates the transfer of information when a 
patient is discharged from his or her current PAC setting to a private 
home/apartment, board and care home, assisted living, group home, 
transitional living, or home under the care of an organized home health 
service organization or hospice.
    This measure, adopted under section 1899B(c)(1)(E) of the Act, was 
developed to be a standardized measure for the IRF QRP, LTCH QRP, SNF 
QRP and Home Health (HH) QRP. The measure is calculated by one 
standardized data element that asks, ``At the time of discharge, did 
the facility provide the patient's current reconciled medication list 
to the patient, family, and/or caregiver?'' The discharge location is 
captured by items on the Long-Term Care Hospital (LTCH) Continuity 
Assessment Record and Evaluation (CARE) Data Set (LCDS).
    Specifically, we are proposed to update the measure denominator. 
Currently, the measure denominators for both the TOH-Patient measure 
and the TOH-Provider measure assess the number of patients discharged 
home under the care of an organized home health service organization or 
hospice. In order to align the measure with the SNF QRP, IRF QRP, and 
HH QRP, and avoid counting the patient in both TOH measures in the LTCH 
QRP, we proposed the removal of this location from the definition of 
the denominator for the TOH-Patient measure. Therefore, we proposed to 
update to the denominator for the TOH-Patient measure to only 
discharges to a private home/apartment, board and care home, assisted 
living, group home, or transitional living. For additional technical 
information regarding the TOH-Patient measure, we refer readers to the 
document titled ``Final Specifications for LTCH QRP Quality Measures 
and Standardized Patient Assessment Data Elements available at https://
www.cms.gov/Medicare/Quality-

[[Page 45447]]

Initiatives-Patient-Assessment-Instruments/LTCH-Quality-Reporting/
Downloads/Final-Specifications-for-LTCH-QRP-Quality-Measures-and-
SPADEs.pdf.
    We invited public comments on our proposal to update the 
denominator of the Transfer of Health (TOH) Information to the 
Patient--Post-Acute Care (PAC) measure beginning with the FY 2023 LTCH 
QRP.
    Comment: We received overwhelming support for our proposal to 
update the TOH-Patient-PAC measure's denominator to remove the 
inclusion of ``home under care of an organized home health service 
organization or hospice.'' Commenters agreed that the update will 
reduce denominator redundancy in the two TOH Information--PAC measures. 
A commenter mentioned that this update will increase the usefulness of 
both the TOH-Patient-PAC and TOH-Provider-PAC measures because the same 
patients will not be counted in both measures. Another commenter noted 
their appreciation of CMS' continued review of measures used in its 
various Medicare QRPs to make changes that mitigate unnecessary 
provider burden.
    Response: We appreciate the commenters' support, and agree that 
this update removes redundancy between the TOH-Patient-PAC and TOH-
Provider-PAC measures, and reduces burden.
    Comment: A commenter noted their support for our proposal to update 
the TOH-Patient-PAC measure, but also recommended that CMS remove short 
stays (for example less than 5 days) from all LTCH QRP measures.
    Response: While this comment is out of scope, we would like to 
clarify that CMS carefully considers length of stay when developing 
quality measures. For example, stays less than three days long are 
excluded from the Change in Mobility Among Long-Term Care Hospital 
Patients Requiring Ventilation Support measure (NQF #2632) because it 
would typically not allow sufficient time to collect all of the items 
or for a patient to demonstrate a meaningful change. We agree that it 
may be more challenging to acquire and transfer medication information 
for patients with shorter lengths of stay, but maintain our believe 
that this is critically important for all patients regardless of stay 
length, and especially important for patients who are discharged for 
emergent reasons.
    Final Decision: After careful consideration of the public comments 
we received, we are finalizing our proposal as proposed to update the 
denominator for the Transfer of Health (TOH) Information to the 
Patient--Post-Acute Care (PAC) measure beginning with the FY 2023 LTCH 
QRP.
5. LTCH QRP Quality Measures Under Consideration for Future Years: 
Request for Information
    We sought input on the importance, relevance, appropriateness, and 
applicability of each of the measures and concepts under consideration 
listed in Table FF2 for future years in the LTCH QRP.
[GRAPHIC] [TIFF OMITTED] TR13AU21.293

    We received several comments on this RFI, which are summarized 
below:
    Comment: Several commenters supported the inclusion of most of the 
proposed measures listed in Table FF2. A commenter said they were 
concerned that most of these metrics are not valid for LTCHs, and 
believes they should first be initiated in the short stay hospital 
where baseline information can be obtained and then LTCHs could add to 
the patient's continuing care record. This commenter also questioned 
whether an LTCH has any ability to impact these metrics during a 
patient's LTCH stay.
    A commenter thought the most significant opportunity from the 
proposed list was the concept of measuring malnutrition, and said there 
should be significant efforts to identify patients that have clinical 
diagnoses associated with being malnourished. Another commenter said 
that while malnutrition and frailty, are important factors in patient 
clinical and utilization outcomes, they did not think LTCHs were likely 
to reverse patient malnutrition or frailty as a clinical outcome within 
the timespan of one admission. Several commenters thought frailty would 
be more appropriate as a risk-adjustment variable or used in stratified 
reporting of measure results, and recommended that CMS not implement it 
as a process of care measure.
    A few commenters stated that the concept of shared decision-making 
may be more appropriately assessed at the clinician-level than the 
hospital level.
    We appreciate the input provided by commenters. While we will not 
be responding to specific comments submitted in response to this 
Request for Information in this final rule, we intend to use this input 
to inform our future measure development efforts.
6. Fast Healthcare Interoperability Resources (FHIR) in Support of 
Digital Quality Measurement in Quality Programs--Request for 
Information (RFI)
a. Solicitation of Comments
    We sought input on the following steps that would enable 
transformation of CMS' quality measurement enterprise to be fully 
digital:
    i. What EHR/IT systems do you use and do you participate in a 
health information exchange (HIE)?
    ii. How do you currently share information with other providers?

[[Page 45448]]

    iii. In what ways could we incentivize or reward innovative uses of 
health information technology (IT) that could reduce burden for post-
acute care settings, including but not limited to LTCHs?
    iv. What additional resources or tools would post-acute care 
settings, including but not limited to LTCHs, and health IT vendors 
find helpful to support the testing, implementation, collection, and 
reporting of all measures using FHIR standards via secure APIs to 
reinforce the sharing of patient health information between care 
settings?
    v. Would vendors, including those that service post-acute care 
settings, such as LTCHs, be interested in or willing to participate in 
pilots or models of alternative approaches to quality measurement that 
would align standards for quality measure data collection across care 
settings to improve care coordination, such as sharing patient data via 
secure FHIR API as the basis for calculating and reporting digital 
measures?
    We received a number of comments and appreciate the time commenters 
took to respond. We plan to continue working with other agencies and 
stakeholders to coordinate and to inform our transformation to dQMs 
leveraging health IT standards. We will consider all input as we 
develop future LTCH QRP proposals and future subregulatory policy 
guidance. Any updates to specific program requirements related to 
quality measurement and reporting provisions would be addressed through 
separate and future notice-and-comment rulemaking, as necessary.
7. Closing the Health Equity Gap in Post-Acute Care Quality Reporting 
Programs--Request for Information (RFI)
a. Solicitation of Public Comment
    Under the authority of the IMPACT Act and section 1886(m)(5) of the 
Act, we sought comment on the possibility of revising measure 
development, and the collection of other Standardized Patient 
Assessment Data Elements that address gaps in health equity in the LTCH 
QRP. Any potential data collection or measure reporting related to 
health equity within a CMS program, including the LTCH QRP that might 
result from public comments received in response to this solicitation 
would be addressed through a separate notice-and-comment rulemaking in 
the future.
    Specifically, we are invited public comment on the following:
     Recommendations for quality measures, or measurement 
domains that address health equity, for use in the LTCH QRP.
     As finalized in the FY 2020 IPPS/LTCH PPS final rule (84 
FR 42577 through 42588), LTCHs must report certain Standardized Patient 
Assessment Data Elements on SDOH, including race, ethnicity, preferred 
language, interpreter services, health literacy, transportation and 
social isolation.\1343\ CMS sought guidance on any additional 
Standardized Patient Assessment Data Elements that could be used to 
assess health equity in the care of LTCH patients, for use in the LTCH 
QRP.
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    \1343\ In response to the COVID-19 PHE, CMS released an Interim 
Final Rule (85 FR 27595 through 27597) which delayed the compliance 
date for the collection and reporting of the SDOH for at least one 
full fiscal year after the end of the PHE.
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     Recommendations for how CMS can promote health equity in 
outcomes among LTCH patients. For example, we are interested in 
feedback regarding whether including facility-level quality measure 
results stratified by social risk factors and social determinants of 
health (for example, dual eligibility for Medicare and Medicaid, race) 
in confidential feedback reports could allow facilities to identify 
gaps in the quality of care they provide. (For example, methods similar 
or analogous to the CMS Disparity Methods \1344\ which provide 
hospital-level confidential results stratified by dual eligibility for 
condition-specific readmission measures, which are currently included 
in the Hospital Readmission Reduction Program (see 84 FR 42496 through 
42500)).
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    \1344\ https://qualitynet.cms.gov/inpatient/measures/disparity-methods/methodology.
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     Methods that commenters or their organizations use in 
employing data to reduce disparities and improve patient outcomes, 
including the source(s) of data used, as appropriate.
     Given the importance of structured data and health IT 
standards for the capture, use, and exchange of relevant health data 
for improving health equity, the existing challenges LTCHs encounter 
for effective capture, use, and exchange of health information, 
including data on race, ethnicity, and other social determinants of 
health, to support care delivery and decision making.
    While we will not be responding to specific comments submitted in 
response to this Health Equity RFI in this final rule, we appreciate 
all of the comments and interest in this topic. We will continue to 
take all concerns, comments, and suggestions into account as we 
continue work to address and develop policies on this important topic. 
It is our hope to provide additional stratified information to 
providers related to race and ethnicity if feasible. The provision of 
stratified measure results will allow PAC providers to understand how 
they are performing with respect to certain patient risk groups, to 
support these providers in their efforts to ensure equity for all of 
their patients and to identify opportunities for improvements in health 
outcomes.
8. Form, Manner, and Timing of Data Submission Under the LTCH QRP
a. Background
    We refer readers to the regulatory text at 42 CFR 412.560(b) for 
information regarding the current policies for reporting LTCH QRP data.
b. Schedule for Data Submission of the COVID-19 Vaccination Coverage 
Among Healthcare Personnel Measure Beginning With the FY 2023 LTCH QRP
    As discussed in section IX.E.4.a. of this final rule, we proposed 
to adopt the COVID-19 Vaccination Coverage among HCP measure beginning 
with the FY 2023 LTCH QRP. Given the time-sensitive nature of this 
measure in light of the PHE, we proposed an initial data submission 
period from October 1, 2021 through December 31, 2021. Starting in CY 
2022, LTCHs would be required to submit data for the entire calendar 
year beginning with the FY 2024 LTCH QRP.
    LTCHs would submit data for the measure through the CDC/NHSN web-
based surveillance system. LTCHs currently utilize the NHSN for 
purposes of meeting other LTCH QRP requirements.\1345\ LTCHs would use 
the COVID-19 vaccination data collection module in the NHSN Healthcare 
Personnel Safety (HPS) Component to report the cumulative number of HCP 
eligible to work in the LTCH for at least 1 day during the reporting 
period, excluding persons with contraindications to COVID-19 
vaccination (denominator) and the cumulative number of HCP eligible to 
work in the LTCH for at least 1 day during the reporting period and who 
have received a complete vaccination course against COVID-19 
(numerator). LTCHs would submit COVID-19 vaccination data through the 
NHSN for at least 1 week each month and the CDC would report to CMS 
quarterly.
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    \1345\ Centers for Disease Control and Prevention. Surveillance 
for Weekly HCP COVID-19 Vaccination. Accessed at: https://www.cdc.gov/nhsn/hps/weekly-covid-vac/index.html on February 10, 
2021.
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    We invited public comments on this proposal.
    Comment: Several commenters expressed concerns about the

[[Page 45449]]

administrative burden associated with reporting of the COVID-19 
Vaccination Coverage among Healthcare Personnel measure through NHSN as 
well as other systems, referring to the Department of Health and Human 
Services TeleTracking system, and various state agencies and databases. 
They stated that having to utilize these systems in addition to the 
NHSN is redundant and burdensome, and requires additional staff to meet 
the current demands for reporting COVID-19 information. They urged CMS 
to use data from these other systems without requiring additional data 
collection in the NHSN.
    Response: The TeleTracking system was one system used by the 
Federal Government to manage the critical first months of the COVID-19 
PHE, as it was critical that the Federal Government receive data to 
facilitate planning, monitoring, and resource allocation during the 
COVID-19 PHE. The TeleTracking system collects a number of data points, 
such as ventilators in the facility, ventilators in use, ICU beds 
available and ICU beds occupied, but providers, including LTCHs, are 
not required to report data to the TeleTracking system for the LTCH 
QRP. We have proposed to use the NHSN COVID-19 Modules for tracking 
COVID-19 vaccination coverage among HCP across all sites of service, 
including for the LTCH QRP because the Tele-Tracking system does not 
collect the information needed to calculate the COVID-19 Vaccination 
coverage among HCP, and because LTCHs currently utilize the NHSN for 
reporting data on the NHSN Catheter-Associated Urinary Tract Infection 
(CAUTI) Outcome Measure (NQF #0138), the NHSN Central Line-Associated 
Bloodstream Infection (CLABSI) Outcome Measure (NQF #0139), the NHSN 
Facility-Wide Inpatient Hospital-onset Clostridium difficile Infection 
(CDI) Outcome Measure (NQF #1717), and the Influenza Vaccination 
Coverage Among Healthcare Personnel (NQF #0431) measure.
    However, we do recognize that this measure may lead to duplicative 
reporting requirements if LTCHs voluntarily report COVID-19 HCP 
vaccination information to data reporting systems other than the NHSN, 
and we are collaborating with other HHS agencies, including the CDC, to 
ensure minimal reporting burden and to eliminate duplicative 
requirements to the extent feasible.
    Comment: Several comments were submitted questioning CMS' statement 
that the COVID-19 Vaccination Coverage among HCP measure was modeled 
after the Influenza vaccination among HCP (NQF #0431) measure. A 
commenter stated it was not clear why there would be multiple time 
frames associated with the COVID-19 Vaccination Coverage among HCP 
measure, rather than the submission frequency for the Influenza 
Vaccination among HCP (NQF #0431) measure which is only one time per 
year. This commenter suggested that if CMS were to adopt this COVID-19 
Vaccination Coverage among HCP measure, that an organization submit its 
compliance one time for the identified period.
    Response: We are interpreting the commenter's reference to multiple 
time frames to refer to the one week per month proposed data submission 
frequency. We agree that there are key differences between the 
Influenza Vaccination among HCP measure and the COVID-19 Vaccination 
Coverage among HCP measure. We acknowledge that even though the CDC 
modeled the COVID-19 Vaccination Coverage among HCP measure after the 
Influenza Vaccination among HCP measure, the influenza vaccine and the 
COVID-19 vaccine are not identical. The measures are aligned with 
respect to the reporting mechanism used to report data (the NHSN) and 
key components of the measure specifications (for example, the 
definition of the denominator), but the measures allow for important 
differences to reflect the reality that the circumstances around 
vaccine administration are not identical. We proposed a reporting 
schedule for the COVID-19 Vaccination Coverage among HCP measure of 1 
week per month to provide vaccination coverage data on a more timely 
basis than the Influenza Vaccination Coverage among HCP measure (NQF 
#0431), while also reducing the burden on LTCHs that weekly reporting 
of this information would have created.
    Comment: Several commenters disagreed with the measure submission 
frequency, stating that CMS should revise the methodology associated 
with the frequency of data collection for this measure because they 
believe data from one day each month is a sufficient snapshot of COVID-
19 vaccination rates for a LTCH's HCP. They went on to say that the 
time and resources required by LTCHs to report the data one week a 
month creates an undue burden on LTCHs during the PHE.
    Response: We developed the COVID-19 Vaccination Coverage among HCP 
measure to align with the Influenza Vaccination among HCP (NQF #0431) 
measure. However, we proposed that LTCHs report the measure one week 
per month to provide vaccination coverage data on a more timely basis 
than the Influenza Vaccination among HCP (NQF #0431) measure while also 
reducing burden on LTCHs. Additionally a weekly reporting period has 
been the reporting cycle for many COVID-19-related metrics during the 
pandemic.
    Final Decision: After careful consideration of the public comments 
we received, we are finalizing as proposed the schedule for data 
submission of the COVID-19 Vaccination Coverage among Healthcare 
Personnel measure beginning with the FY 2023 SNF QRP.
9. Policies Regarding Public Display of Measure Data for the LTCH QRP
a. Background
    Section 1886(m)(5)(E) of the Act requires the Secretary to 
establish procedures for making the LTCH QRP data available to the 
public, including the performance of individual LTCHs, after ensuring 
that LTCHs have the opportunity to review their data prior to public 
display. LTCH QRP measure data are currently displayed on the Long-term 
care hospitals website within Care Compare and the Provider Data 
Catalog, which are CMS websites. Both Care Compare and the Provider 
Data Catalog replaced LTCH Compare and Data.Medicare.gov, which were 
retired in December 2020. For a more detailed discussion about our 
policies regarding public display of LTCH QRP measure data and 
procedures for the opportunity to review and correct data and 
information, we refer readers to the FY 2017 IPPS/LTCH PPS final rule 
(81 FR 57231 through 57236).
b. Publicly Report the Compliance With Spontaneous Breathing Trial 
(SBT) by Day 2 of the LTCH Stay Measure Beginning With the FY 2023 LTCH 
QRP
    We proposed public reporting for the Compliance with Spontaneous 
Breathing Trial (SBT) by Day 2 of the LTCH Stay measure beginning with 
the March 2022 Care Compare refresh or as soon as technically feasible 
using four rolling quarters of discharge data collected in Q3 2020 
through Q2 2021 (July 1, 2020 through June 30, 2021) for the inaugural 
display of this measure. We proposed publicly reporting the Compliance 
with SBT by Day 2 of the LTCH Stay measure for data collected from July 
1, 2018 through December 31, 2019 on CMS' Provider Data Catalog (PDC) 
web page. We adopted the Compliance with SBT by Day 2 of the LTCH Stay 
measure in the FY 2018 IPPS/LTCH PPS final rule (82 FR 38439 through 
38446). Data collection for this assessment-based measure began with 
patients admitted and discharged on or

[[Page 45450]]

after July 1, 2018. To ensure the statistical reliability of the data, 
we proposed not to publicly report an LTCH's performance on the measure 
if the LTCH had fewer than 20 eligible cases \1346\ during each 
performance period. LTCHs that have fewer than 20 eligible cases would 
be distinguished with a footnote that states: ``The number of cases/
patient stays is too small to publicly report.''
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    \1346\ We define an ``eligible case'' as a case that meets all 
of the criteria under the measure's denominator, which can be found 
In the LTCH QRP Measure Calculations and Reporting Manual found on 
the LTCH QRP Measures Information web page here: https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/LTCH-Quality-Reporting/LTCH-Quality-Reporting-Measures-Information.
---------------------------------------------------------------------------

    LTCHs were required to collect and submit data for the Compliance 
with Spontaneous Breathing Trial (SBT) by Day 2 of the LTCH Stay 
measure beginning on July 1, 2018 (Q3 2018), six calendar year quarters 
prior to the data proposed for the inaugural display of the measure on 
Care Compare. The first quarter of data collected and submitted by 
LTCHs (that is, Q3 2018) will be nearly 3.5 years old at that time. 
Therefore, CMS believes it is in the best interest of providers and the 
public to use the most recent available four quarters of data (that is, 
July 1, 2020 through June 30, 2021) for the inaugural public display of 
the Compliance with Spontaneous Breathing Trial (SBT) by Day 2 of the 
LTCH Stay measure on Care Compare and to post provider performance on 
the Compliance with Spontaneous Breathing Trial (SBT) by Day 2 of the 
LTCH Stay measure using the older data (that is, July 1, 2018 through 
December 31, 2019) on CMS' Provider Data Catalog (PDC) web page 
(https://data.cms.gov/provider-data/).
    We invited public comments on the proposal to publicly display the 
measure, Compliance with Spontaneous Breathing Trial (SBT) by Day 2 of 
the LTCH Stay measure on Care Compare and PDC.
    Comment: We received two comments supporting the proposed public 
reporting of the SBT by Day 2 of the LTCH Stay measure. A commenter 
stated that because LTCHs have been measuring these data since 2018, 
and some even longer than that, it would not be onerous to use 4 
quarters of the most recent data for public reporting in the March 2022 
Care Compare refresh.
    Response: We thank the commenters for their support, and agree that 
because the SBT by Day 2 of the LTCH Stay measure is not new, and LTCHs 
have the ability to access their QM feedback reports, they have had 
information to help them improve their SBT strategies, and better 
understand their own LTCH's SBT rate compared to other LTCHs and the 
national average.
    Comment: We received a comment raising several concerns about the 
SBT by Day 2 of the LTCH Stay measure specifications, including the 
timeframe for the measure, administrative burden and the multi-
component structure of the measure. Additionally, the commenter stated 
the measure might have the unintended consequence of pressuring 
clinicians to make a judgment without enough information, and 
encouraged the agency to perform a meta-analysis of the SBT by Day 2 of 
the LTCH Stay measure if it had not yet done so.
    Response: The SBT by Day 2 of the LTCH Stay measure was finalized 
in the FY 2018 IPPS/LTCH PPS Final Rule (82 FR 38443), and CMS did not 
propose changes to the measure specifications in the 2022 IPPS/LTCH PPS 
(86 FR 25070) proposed rule. Therefore, we will not be responding to 
those comments here, but will take these comments into consideration 
for potential refinements in the future.
    Regarding unintended consequences, we interpret the commenter to 
mean that publicly reporting the SBT by Day 2 of the LTCH Stay measure 
might pressure clinicians to make a judgment without enough 
information, which could negatively impact patient outcomes. We 
appreciate the commenters' concerns pertaining to patient safety, and 
would like to emphasize that patient safety is a top priority. We 
encourage LTCHs to use best patient care practices when assessing 
patients for readiness for ventilator liberation. In addition, we note 
that while the measure assesses LTCHs on completing an assessment of 
the patient to determine whether patient is medically ready to be 
liberated from mechanical ventilation, it does not require providers to 
make any particular assessment, and we encourage providers to classify 
patients as ``weaning'' or ``non-weaning'' as clinically appropriate. 
Of note, evidence-based guidelines emphasize that after a commonsense 
clinical assessment, the best approach to determining readiness for 
ventilator discontinuation is an SBT,\1347\ and that the most effective 
method of liberation follows a systematic approach that includes a 
daily assessment of weaning readiness, in conjunction with spontaneous 
breathing trials.\1348\ If a clinician deems a patient medically 
unready to perform SBT, then the decision should documented and LTCHs 
should code this item appropriately.
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    \1347\ Hess DR, et al. Ventilator Discontinuation: Why Are We 
Still Weaning? American Journal of Respiratory and Critical Care 
Medicine, 184(4), pp. 392-394.
    \1348\ Haas CF, Loik PS. Ventilator discontinuation protocols. 
Respir Care. 2012 Oct;57(10):1649-63. Accessed July 1, 2021.
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    Finally, CMS regularly monitors the performance for all measures 
submitted for purposes of the LTCH QRP to identify unintended 
consequences, and should they arise makes measure modifications as 
appropriate.
    Comment: Several commenters stated they do not support CMS' 
proposal to publicly report LTCH QRP data that was collected by LTCHs 
during the COVID-19 PHE. They noted that even after July 1, 2020, many 
parts of the country were experiencing their highest rates of COVID-19 
infections rather than during Q1 and Q2 of 2020 when the QRP reporting 
exception was in effect.
    Response: We interpret the commenters to be referring to both the 
SBT by Day 2 of the LTCH Stay measure and the VLR measure, and will 
respond to the comment for both measures here.
    We believe that the unprecedented risks associated with the COVID-
19 PHE warrant direct attention. COVID-19 caused severe respiratory 
symptoms including acute respiratory distress syndrome (ARDS), which 
can progress to acute respiratory failure (ARF). A recent study found 
an increase of approximately 3% annually in the last five years of 
mortality due to respiratory failure. Additionally the number of deaths 
from ARDS, which had been declining in the U.S., is now stagnant. The 
incidence of mortality due to acute respiratory failure (ARF) and ARDS 
is also higher in rural areas and among non-Hispanic black 
persons.\1349\ Data also shows that eight out of every 10 deaths 
related to COVID-19 have been in adults 65 years of age and older. When 
compared to 18- to 29-year-olds, adults over 65 have five to eight 
times higher risk of being hospitalized from COVID-19 and those older 
than 75 have 220 times higher risk of dying.\1350\ Moreover, many 
common chronic conditions raise the risks associated with contracting 
COVID-19, including hypertension, obesity, chronic obstructive 
pulmonary disease, heart disease, diabetes, and chronic kidney

[[Page 45451]]

disease.\1351\ The COVID-19 pandemic was expected to result in an 
increased utilization of mechanical ventilation, and in recently 
conducted routine monitoring of its measures, CMS found evidence 
consistent with this expectation where the number of patients who were 
admitted to a LTCH on mechanical ventilation increased 7.5% since Q3 of 
2019.
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    \1349\ Parcha V, Kalra R, Bhatt, SP, et al. Trends and 
Geographic Variation in Acute Respiratory Failure and ARDS Mortality 
in the United States.
    \1350\ National Institute for Health Care Management (NIHCM). 
Aging & COVID-19: Vaccination, Mental and Physical Health, and 
Isolation. Updated February 17, 2021. Available at: https://nihcm.org/publications/aging-covid-19-vaccination-mental-and-physical-health-and-isolation. Accessed June 26, 2021.
    \1351\ Centers for Disease Control and Prevention. Science 
Brief: Evidence used to update the list of underlying medical 
conditions that increase a person's risk of severe illness from 
COVID-19. Available at: https://www.cdc.gov/coronavirus/2019-ncov/science/science-briefs/underlying-evidence-table.html. Accessed June 
26, 2021.
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    Therefore we do not believe delaying the public reporting of the 
SBT by Day 2 of the LTCH Stay measure and the VLR measure is in the 
public's best interest. We believe that publicly reporting the SBT by 
Day 2 of the LTCH Stay and VLR measures on Care Compare can assist 
consumers by providing more recent quality data as well as more 
actionable data for LTCH providers.
    Final Decision: After careful consideration of the public comments, 
we are finalizing our proposal to publicly report the Spontaneous 
Breathing Trial (SBT) by Day 2 of the LTCH Stay Measure on Care Compare 
and PDC.
c. Publicly Report the Ventilator Liberation Rate for the PAC LTCH QRP 
Measure Beginning With the FY 2023 LTCH QRP
    We proposed public reporting for the Ventilator Liberation Rate for 
the PAC LTCH QRP measure, beginning with the March 2022 Care Compare 
refresh or as soon as technically feasible using four rolling quarters 
of discharge data collected in Q3 2020 through Q2 2021 (July 1, 2020 
through June 30, 2021) for the inaugural display of this measure. We 
proposed publicly reporting the Ventilator Liberation rate for the PAC 
LTCH QRP measure for data collected from July 1, 208 through December 
31, 2019 on CMS' Provider Data Catalog (PDC) web page. We adopted the 
Ventilator Liberation Rate measure in the FY 2018 IPPS/LTCH PPS final 
rule (82 FR 38439 through 38446). Data collection for this assessment-
based measure began with patients admitted and discharged on or after 
July 1, 2018. To ensure the statistical reliability of the data, we 
proposed not to publicly report an LTCH's performance on the measure if 
the LTCH had fewer than 20 eligible cases during each performance 
period. LTCHs that have fewer than 20 eligible cases would be 
distinguished with a footnote that states: ``The number of cases/
patient stays is too small to publicly report.''
    LTCHs were required to collect and submit data for the Ventilator 
Liberation Rate for the PAC LTCH QRP measure beginning on July 1, 2018 
(Q3 2018), 6 calendar year quarters prior to the data proposed for the 
inaugural display of the measure on Care Compare. The first quarter of 
data collected and submitted by LTCHs (that is, Q3 2018) will be nearly 
3.5 years old at that time. Therefore, CMS believes it is in the best 
interest of providers and the public to use the most recent available 
four quarters of data (that is July 1, 2020 through June 30, 2021) for 
the inaugural public display of the Ventilator Liberation Rate for the 
PAC LTCH QRP measure on Care Compare and to post provider performance 
on the Ventilator Liberation Rate for the PAC LTCH QRP measure using 
the older data (that is, July 1, 2018 through December 31, 2019) on 
CMS' Provider Data Catalog (PDC) web page (https://data.cms.gov/provider-data/).
    We invited public comments on the proposal to publicly display the 
measure, Ventilator Liberation Rate for the PAC LTCH QRP on Care 
Compare and PDC.
    Comment: We received two comments in support of the proposed public 
reporting of the Ventilator Liberation Rate (VLR) for the PAC LTCH QRP 
measure. A commenter stated that because LTCHs have been reporting this 
data to CMS since 2018, and some even longer than that, it would not be 
onerous to use 4 quarters of the most recent data for public reporting 
in the March 2022 Care Compare refresh.
    Response: We thank the commenters for their support, and agree that 
the VLR measure is not new. LTCHs have the ability to access their QM 
feedback reports, so they have had information to help them improve 
their care approaches to achieve higher VLRs, and better understand 
their own LTCH's VLR rate compared to other LTCHs and the national 
average.
    Comment: Several commenters stated they do not support CMS' 
proposal to publicly report LTCH QRP data that was collected by LTCHs 
during the COVID-19 PHE. They noted that even after July 1, 2020, many 
parts of the country were experiencing their highest rates of COVID-19 
infections rather than during Q1 and Q2 of 2020 when the QRP reporting 
exception was in effect.
    Response: We interpret the commenters to be referring to both the 
SBT by Day 2 of the LTCH Stay measure and the VLR measure. We disagree 
with the commenter and believe that the unprecedented risks associated 
with the COVID-19 PHE warrant direct attention, especially given the 
evidence CMS found in recently conducted routine monitoring of its 
measures where the number of patients who were admitted to a LTCH on 
mechanical ventilation increased 7.5% since Q3 of 2019. While we 
understand that there are concerns related to the use of Q3 and Q4 2020 
data and subsequent quarters, we do not believe that further exempting 
providers from LTCH QRP reporting requirements, nor the continued 
suspension of public reporting, are actionable solutions. We granted a 
6-month exception to LTCH QRP reporting requirements due to the PHE 
under 42 CFR 412.560(c)(4)(i) of our regulations for Q1 and Q2 of 2020, 
a sufficient timeframe for LTCHs to adjust to the change in care 
patterns associated with the pandemic. We further believe that the 
public display of quality data is extremely important so patients and 
caregivers can continue to make informed healthcare choices. More 
details can be found in section ##.E.9.b of this final rule.
    Final Decision: After careful consideration of the public comments, 
we are finalizing our proposal as proposed to publicly report the 
Ventilator Liberation Rate for the PAC LTCH QRP on Care Compare and 
PDC.
d. Publicly Report the COVID-19 Vaccination Coverage Among Healthcare 
Personnel (HCP) Measure Beginning With the FY 2023 LTCH QRP
    We proposed to publicly report the COVID-19 Vaccination Coverage 
among Healthcare Personnel (HCP) measure beginning with the September 
2022 Care Compare refresh or as soon as technically feasible using data 
collected for Quarter 4 2021 (October 1, 2021 through December 31, 
2021). If finalized as proposed, a LTCH's HCP COVID-19 vaccination 
coverage rate would be displayed based on one quarter of data. Provider 
preview reports would be distributed in June 2022. Subsequent to the 
September 2022 Care Compare refresh, one additional quarter of data 
would be added to the measure calculation during each advancing 
refresh, until the point four quarters of data is reached. Thereafter, 
the measure would be publicly reported using four rolling quarters of 
data.
    We invited public comments on this proposal for the public display 
of the measure, COVID-19 Vaccination Coverage among HCP on Care 
Compare.
    Comment: A commenter supported the proposed adoption of the COVID-
19 Vaccination Coverage among HCP measure to monitor vaccination rates 
among HCP in LTCHs because requiring facilities to report COVID-19

[[Page 45452]]

Vaccination Coverage among HCP rates would provide greater transparency 
to Federal officials and other stakeholders seeking to effectively 
target vaccine hesitancy and resources related to the COVID-19 
vaccines. They also believe that publishing facility-level data on HCP 
vaccination rates would provide additional information about 
facilities' pandemic response and readiness efforts.
    Response: We thank the commenter for their support and agree that 
vaccinations are a critical part of the nation's strategy to 
effectively counter the spread of COVID-19 and ultimately help restore 
societal functioning.\1352\ The CDC has emphasized that health care 
settings, including LTCHs, can be high-risk places for COVID-19 
exposure and transmission.\1353\
---------------------------------------------------------------------------

    \1352\ Centers for Disease Control and Prevention. (2020). 
COVID-19 Vaccination Program Interim Playbook for Jurisdiction 
Operations. Accessed on December 18 at https://www.cdc.gov/vaccines/imz-managers/downloads/COVID-19-Vaccination-Program-Interim_Playbook.pdf.
    \1353\ Dooling, K, McClung, M, et al. ``The Advisory Committee 
on Immunization Practices' Interim Recommendations for Allocating 
Initial Supplies of COVID-19 Vaccine--United States, 2020.'' Morb 
Mortal Wkly Rep. 2020; 69(49): 1857-1859.
---------------------------------------------------------------------------

    Comment: Several commenters voiced their concern about publicly 
reporting the COVID-19 Vaccination Coverage among HCP measure. While 
many of them voiced their support of the right of consumers to access 
real-time meaningful data to help inform healthcare decision-making, 
they believe the use of a single, dated measure is not a true 
reflection of the safety or quality of care delivered at an LTCH since 
vaccines are just one tactic for preventing and controlling COVID-19 
infections.
    Response: CMS believes it is important to make the most up-to-date 
data available to beneficiaries, which will support them in making 
essential decisions about health care. Based on these concerns, we will 
revise the public reporting policy for this measure to use quarterly 
reporting, as opposed to averaging over four rolling quarters, which 
allows the most recent quarter of data to be displayed. This revision 
would result in publishing information that is more up to date and 
would not affect the data collection schedule established for 
submitting data to NHSN for the COVID-19 Vaccination Coverage among HCP 
measure. This revision would simply update the way the measure's data 
are displayed for public reporting purposes.
    Comment: Commenters were concerned that if CMS adopted the COVID-19 
Vaccination among HCP measure, then the data will be publicly displayed 
on Care Compare without proper context, and they are concerned the 
public will not understand the information concerning the FDA's EUA 
process as well as the legal questions LTCHs faced about whether they 
could impose vaccination requirements as a condition of employment.
    Response: It is unclear what legal questions the commenters are 
referring to, but we assume they are related to requiring vaccination. 
As discussed in section #.E.4.a.(5) of this final rule, the COVID-19 
Vaccination among HCP measure does not require LTCHs to vaccinate their 
HCP. In addition, we believe staff vaccination rates are essential 
information for consumers that are activity making decisions about 
where to seek care. While we understand there are concerns related to 
the vaccine's FDA authorization and the inability to require their HCP 
to receive a COVID-19 vaccination, the COVID-19 vaccinations are 
authorized by the FDA for widespread use through EUAs.
    Comment: Commenters supportive of using the TeleTracking system to 
report vaccination information in lieu of the NHSN also urged CMS to 
direct consumers to use the TeleTracking system to find LTCH's 
performance on the COVID-19 Vaccination Coverage among HCP measure, 
instead of Care Compare.
    Response: We disagree. The Care Compare tool provides a user-
friendly interface that patients and caregivers can use to make 
informed decisions about healthcare based on cost, quality of care, 
volume of services, and other data, while also giving patients and 
caregivers the option to compare LTCHs using this information. The data 
found in the TeleTracking system does not have these features.
    Comment: Several commenters did not support the proposal to use a 
shortened reporting timeframe of October 2021-December 2021 to meet the 
APU reporting requirements for the FY 2023.
    Response: We interpret the comment to be about the LTCH QRP 
reporting requirements to meet the compliance threshold for the FY 2023 
Annual Payment Update (APU). Our proposal to use of one quarter of data 
for the initial year of quality reporting for a new measure is 
consistent with the approach finalized in the FY 2016 IPPS/LTCH PPS 
final rule (80 FR 49326 to 49843) for all new measures in their first 
year of data reporting.
    Final Decision: After careful consideration of the public comments, 
we are finalizing our proposal to publicly report the COVID-19 
Vaccination Coverage among Healthcare Personnel (HCP) measure beginning 
with the September 2022 Care Compare refresh or as soon as technically 
feasible based on data collected for Q4 2021 (October 1, 2021 through 
December 31, 2021). However, in response to public comment, we will not 
finalize our plan to add one additional quarter of data during each 
advancing refresh, until the point that four full quarters of data is 
reached and then report the measure using four rolling quarters of 
data. We will instead only report the most recent quarter of data.
e. Public Reporting of Quality Measures in the LTCH QRP With Fewer 
Quarters Due to COVID-19 Public Health Emergency (PHE) Exemption
(1) COVID-19 Public Health Emergency Temporary Exemptions
    Under the authority of section 319 of the Public Health Service 
Act, the Secretary declared a public health emergency (PHE) effective 
as of January 27, 2020. On March 13, 2020, subsequent to a presidential 
declaration of national emergency under the Stafford Act, the Secretary 
invoked Section 1135(b) of the Act (42 U.S.C. 1320b-5) to waive or 
modify the requirements of titles XVIII, XIX, and XXI of the Act and 
regulations related to the PHE for COVID-19 effective as of March 1, 
2020.\1354\ On March 27, 2020, we sent a guidance memorandum under the 
subject title, ``Exceptions and Extensions for Quality Reporting 
Requirements for Acute Care Hospitals, PPS-Exempt Cancer Hospitals, 
Inpatient Psychiatric Facilities, Skilled Nursing Facilities, Home 
Health Agencies, Hospices, Inpatient Rehabilitation Facilities, Long-
Term Care Hospitals, Ambulatory Surgical Centers, Renal Dialysis 
Facilities, and MIPS Eligible Clinicians Affected by COVID-19'' to the 
Medicare Learning Network (MLN) Connects Newsletter and Other Program-
Specific Listserv Recipients,\1355\ hereafter referred to as the March 
27, 2020 CMS Guidance Memo. In that memo we granted an exception to the 
LTCH QRP reporting requirements from Q4 2019 (October 1, 2019-December 
31, 2019) Q1 2020 (January 1, 2020-March 31, 2020) and Q2 2020 (April 
1, 2020-June 30, 2020). We also stated that we would not publicly 
report any LTCH QRP data that might be greatly impacted by the

[[Page 45453]]

exceptions from Q1 and Q2 of 2020. This exception impacted the schedule 
for public reporting that would have included those two quarters of 
data.
---------------------------------------------------------------------------

    \1354\ https://www.phe.gov/emergency/news/healthactions/section1135/Pages/covid19-13March20.aspx.
    \1355\ https://www.cms.gov/files/document/guidance-memo-exceptions-and-extensions-quality-reporting-and-value-based-purchasing-programs.pdf.
---------------------------------------------------------------------------

    LTCH QRP measures are publicly reported on Care Compare. Care 
Compare uses four quarters of data for LCDS assessment-based measures, 
with the exception of the Functional Outcome Measure: Change in 
Mobility Among Long-Term Care Hospital Patients requiring Ventilator 
Support (NQF #2632) which uses eight quarters of data. Care Compare 
uses eight quarters of data for claims based measures. Table FF3 
displays the original schedule for public reporting of LTCH QRP 
measures.\1356\
---------------------------------------------------------------------------

    \1356\ More information about the LTCH QRP Public Reporting 
schedule can be found on the LTCH QRP Public Reporting website at: 
https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/LTCH-Quality-Reporting/LTCH-Quality-Public-Reporting.
---------------------------------------------------------------------------

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    During 2020, we conducted testing to inform decisions about 
publicly reporting data for those refreshes which include partially 
and/or fully exempt data (discussed later in this section). The testing 
helped us develop a plan for posting data that are as up-to-date as 
possible and that also meet acceptable standards for public reporting. 
We believe that the plan allows us to provide consumers with helpful 
information on the quality of LTCH care, while also making the 
necessary adjustments to accommodate the exemption provided LTCHs. The 
following sections provide the results of our testing, and explains how 
we used

[[Page 45455]]

the results to develop plans for accommodating exempt and partially-
exempt data in public reporting.
(2) Exempted Quarters
    In the March 27, 2020 Medicare Learning Network (MLN) Newsletter on 
Exceptions and Extensions for Quality Reporting Program (QRP) 
Requirements, we stated that we would not report any PAC quality data 
that might be greatly impacted by the exemptions granted for Quarter 1 
and Quarter 2 of 2020. Given the timing of the PHE onset, we determined 
that we would not use LCDS assessments or LTCH claims from Quarter 1 
and Quarter 2 of 2020 for public reporting, but that we would assess 
the COVID-19 PHE impact on data from Quarter 4 2019. Before proceeding 
with the December 2020 refresh, we conducted testing to ensure that, 
despite the voluntary nature of reporting for that quarter, public 
reporting would still meet our public reporting standards. We found the 
level of reporting, measured in the number of eligible stays and 
providers, and the reported outcomes, to be in line with levels and 
trends observed in FY 2018 and FY 2019. We note that Quarter 4 2019 
ended before the onset of the COVID-19 pandemic in the United States. 
Thus, we proceeded with including these data in LTCH QRP measure 
calculations for the December 2020 refresh.
(3) Update on Data Freeze for December 2021 Public Reporting 
Methodology for LTCH Claims-Based and LCDS Assessment-Based Measures
    In addition to the March 2021 refresh, there are several other 
forthcoming refreshes for which the original public reporting schedules 
included exempted quarters of LTCH QRP data. The impacted refreshes for 
LCDS assessment and claims based measures are outlined in Table FF3. We 
determined that freezing the data displayed on the website with the 
December 2020 refresh values--that is, hold the data constant after the 
December 2020 refresh data on the website without subsequent update--
would be the most straightforward, efficient, and equitable approach 
for LTCHs. Thus, we decided that, for as many refreshes as necessary, 
we would hold data constant on the website with the December 2020 data, 
and communicate this decision to the public.
    Because December 2020 refresh data will become increasingly out-of-
date and thus less useful for consumers, we analyzed whether it would 
be possible to use fewer quarters of data for one or more refreshes and 
thus reduce the number of refreshes that continue to display December 
2020 data. Using fewer quarters of more up-to-date data requires that: 
(1) A sufficient percentage of LTCHs would still likely have enough 
assessment data to report quality measures (reportability); and (2) 
fewer quarters would likely produce similar measure scores for 
providers, with similar reliability, and thus not unfairly represent 
the quality of care LTCHs provide during the period reported in a given 
refresh (reliability).
    To assess these criteria, we conducted reportability and 
reliability analysis using 3 quarters of data in a refresh, instead of 
the standard 4 quarters of data for reporting assessment-based measures 
and using 6 quarters instead of 8 for the Functional Outcome Measure: 
Change in Mobility Among Long-Term Care Hospital Patients requiring 
Ventilator Support (NQF #2632) measure; and using 6 quarters instead of 
8 for claims-based measures. Specifically, we used historical data to 
calculate LCDS assessment based and LTCH claims based measures under 
two scenarios:
     Standard Public Reporting (SPR) Base Scenario: We used 
four quarters of CY 2019 data as a proxy alternative for the exempted 
quarters in CY 2020 in order to compare results. For assessment-based 
measures, the quarters used in this scenario are Q1 through Q4 2019. 
For the Functional Outcome Measure: Change in Mobility Among Long-Term 
Care Hospital Patients requiring Ventilator Support (NQF #2632) 
measure, the quarters used in this scenario are Q1 2018 through Q4 
2019. For claims-based measures, the quarters used in this scenario are 
Q1 2018 through Q4 2019.
     COVID-19 Affected Reporting (CAR) Scenario: We calculated 
LTCH QRP measures using 3 quarters (Q2 2019 through Q4 2019) of LTCH 
QRP data for assessment-based measures, 6 quarters (Q1 2018 through Q4 
2018 and Q3 2019 through Q4 2019) for the Functional Outcome Measure: 
Change in Mobility Among Long-Term Care Hospital Patients requiring 
Ventilator Support (NQF #2632) measure, and 6 quarters (Q1 2018 through 
Q4 2018 and Q3 2019 through Q4 2019) for claims-based measures. The CAR 
scenario uses the most recently available data to simulate the public 
health emergency reality where quarters 1 and 2 of a calendar year must 
be excluded from calculation. Quarterly trends in LCDS assessment-based 
and LTCH claims-based measures indicate that these measures do not 
exhibit substantial seasonal variation.
    To assess performance in these scenarios, we calculated the 
reportability as the percent of LTCHs meeting the case minimum for 
public reporting (the public reporting threshold). To test the 
reliability of restricting the LTCHs included in the SPR Base Scenario 
to those included in the CAR Scenario, we performed three tests on the 
set of LTCHs included in both scenarios. First, we evaluated measure 
correlation using the Pearson and Spearman correlation coefficients, 
which assess the alignment of LTCHs' provider scores. Second, for each 
scenario, we conducted a split-half reliability analysis and estimated 
intraclass correlation (ICC) scores, where higher scores imply better 
internal reliability. Modest differences in ICC scores between 
scenarios would suggest that using fewer quarters of data does not 
impact the internal reliability of the results. Third, we estimated 
reliability scores where a higher value indicates that measure scores 
are relatively consistent for patients admitted to the same LTCH and 
variation in the measure reflects true differences across providers. To 
calculate the reliability results, we restricted the LTCHs included in 
the SPR scenario to those included in the CAR scenario. Our testing 
indicated that the expected impact of using fewer quarters of data on 
reportability and reliability of LCDS assessment-based and claims-based 
measures is acceptable.
    We proposed to use the CAR scenario as the approach for the 
following affected refreshes: For LCDS assessment-based measures, the 
affected refresh is the December 2021 refresh; for claims-based 
measures, the affected refreshes occur from December 2021 through June 
2023. For the earlier three affected refreshes (March, June and 
September 2021), we decided to hold constant the Care Compare website 
with December 2020 data. We communicated this decision in a Public 
Reporting Tip Sheet, which is located at: https://www.cms.gov/files/document/LTCHqrp-covid19prtipsheet-october-2020.pdf.
    Our proposed CAR approach for the affected refreshes would allow us 
to begin displaying more recent data in December 2021, rather than 
continue displaying December 2020 data (Q1 2019 through Q4 2019 and Q1 
2018 through Q4 2019 for assessment-based measures, Q4 2017 through Q3 
2019 for claims-based measures). We believe resuming public reporting 
starting in December 2021 with fewer quarters of data can assist 
consumers by providing more recent quality data as well as more 
actionable data for LTCH providers. Our testing results indicate we can 
achieve these positive impacts with acceptable

[[Page 45456]]

changes in reportability and reliability. Table FF4 summarizes the 
revised schedule (that is, frozen data) and the proposed schedule (that 
is, using fewer quarters in the affected refreshes) for assessment-
based measures. Table FF5 summarizes the revised schedule (that is, 
frozen data) and the proposed schedule (that is, using fewer quarters 
in the affected refreshes) for claims-based measures.
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    We invited public comments on the proposal to use the CAR scenario 
to publicly report LTCH measures for the December 2021-June 2023 
refreshes. A summary of those comments and our responses follow.
    Comment: Commenters generally did not support CMSs' proposal to 
utilize fewer than the standard number of quarters for public reporting 
of quality measures on Care Compare, stating that in many parts of the 
country, the highest rates of COVID-19 infections occurred after July 
1, 2020 when LTCH QRP reporting requirements resumed, rather than in Q1 
and Q2 of 2020 when LTCHs were exempted from LTCH QRP reporting 
requirements. They believe the Q3 2020 data collected were equally 
``impacted,'' due to patients admitted with COVID-19 or recovering from 
COVID-19. They instead recommend that CMS should not resume the public 
display of new LTCH QRP data until the COVID-19 PHE is over.
    Response: While we understand that there are concerns related to 
the use of Q3 and Q4 2020 data and beyond, we do not believe that 
further exempting providers from LTCH QRP reporting requirements, nor 
the continued suspension of public reporting, are actionable solutions. 
We granted a six-month exception to LTCH QRP reporting requirements due 
to the PHE under 42 CFR 412.560(c)(4)(i) of our regulations for Q1 and 
Q2 of 2020, a sufficient timeframe for LTCHs to adjust to the change in 
care patterns associated with the pandemic. We further believe that the 
public display of quality data is extremely important so patients and 
caregivers can continue to make informed healthcare choices. The 
continued need for access to LTCH QRP data on Care Compare by CMS 
beneficiaries outweighs potential LTCH impacts.
    As described above, we conducted testing to inform our decisions 
about publicly reporting data for refreshes using Q3 and Q4 2020. As 
discussed in section IX.E.8.c.3. of the FY 2022 IPPS/LTCH PPS proposed 
rule (86 FR 25621 through 25622), the testing helped us develop a plan 
that we believe meets acceptable standards for public reporting. LTCHs 
that believe they were disproportionately affected by the PHE may apply 
for an individual exception or extension to the LTCH QRP Q3 and/or Q4 
2020 data submissions. Instructions for requesting an extraordinary 
circumstances exemption (ECE) may be found on the LTCH QRP 
Reconsideration and Exception and Extension web page at https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/LTCH-Quality-Reporting/LTCH-Quality-Reporting-Reconsideration-and-Exception-and-Extension.
    Comment: A commenter requested that CMS include disclaimers on Care 
Compare to explain the potential impacts the PHE may have had on LTCH 
performance scores.
    Response: We do not believe that posting additional messaging 
alluding to how LTCH measure scores may or may not be affected by the 
ongoing PHE would be helpful to consumers. Such messages would give the 
impression that the data posted on Care Compare are inaccurate or 
cannot be used when making informed healthcare decisions, which is not 
the case given the extensive testing CMS conducts.
    Comment: A commenter stated that if CMS does decide to proceed with 
the public display of LTCH QRP data collected during the pandemic, they 
must notify LTCHs before the data is displayed.
    Response: Historically, we have provided the following types of 
confidential provider feedback reports that give providers opportunity 
to review and correct data: (1) Review and Correct, which allows 
providers to review and correct their data for any given CY quarter, as 
early as one day following the end of the given quarter, but prior to 
the data submission deadline for that quarter, which falls 
approximately 4.5 months after the end of the quarter; and (2) Provider 
Preview Report, the purpose of which is to allow providers to preview 
their quality measure scores that will be publicly posted for the 
upcoming refresh of Care Compare, and also allows providers to

[[Page 45458]]

request a formal review of the data contained within, should the 
provider disagree with the reported measure results.
    CMS also provides Quality Measure Reports (Facility and Patient-
Level), the purpose of which is to allow providers to improve quality 
based on the most up-to-date data they have entered and/or modified 
within our systems. This report type is not related to public 
reporting, and is produced solely for the benefit of quality 
improvement. Quality measure Reports are not related to public 
reporting and do not observe the quarterly data submission deadlines of 
assessment-based data, and will continue to capture and include any and 
all data entered and/or modified beyond any data submission deadline. 
CMS provides Quality Measure Reports in order to give providers, 
including LTCHs, the most accurate picture of quality within their 
facility, allowing for the improvement of quality. While CMS has 
historically added new measures to the Quality Measure Reports prior to 
public reporting, the QM reports are not related to public reporting. 
Because we believe it is in the best interest of our beneficiaries that 
LTCHs publicly report the results of the COVID-19 Vaccination HCP 
measures as soon as it is feasible, in this instance, we are not able 
to add this measure to the QM reports prior to public reporting. 
Instead, we plan to add this new measure to the QM reports in fall 
2022, at the earliest, but maintain that while this may be out of 
sequence compared to our actions historically, a delay will in no way 
affect a providers ability to review and/or correct their data for this 
measure, nor will it affect a LTCH's ability to preview the COVID-19 
Vaccination HCP data prior to the public posting of this data.
    The COVID-19 Vaccination HCP measure is stewarded by the CDC NHSN. 
To date, CMS has never added any of the CDC NHSN measures to the Review 
and Correct report, as the data for these measures are at the CDC. In 
lieu of this, the CDC makes accessible to PAC providers, including 
LTCHs, reports that are similar to the Review and Correct reports that 
allow for real-time review of data submissions for all CDC NHSN 
measures adopted for use in the CMS PAC QRPs, including the LTCH QRP. 
These reports are referred to as the ``CMS Reports'' within the 
Analysis Reports page in the NHSN Application. Such a report exists for 
each CDC/NHSN measure within the LTCH QRP, and each report is intended 
to mimic the data that will be sent to CMS on their behalf. This report 
will exist to serve the same ``review and correct'' purposes for the 
COVID-19 Vaccination HCP measure. The CDC publishes reference guides 
for each facility type (including LTCH) and each NHSN measure, which 
explain how to run and interpret the reports.
    We will provide LTCHs with a preview of LTCH performance on the 
COVID-19 Vaccination HCP measure, as it will be available on the LTCH 
Provider Preview Report, which will be issued approximately 3 months 
prior to displaying the measure on Care Compare. As always, LTCHs will 
have a full 30 days to preview their data. Should a LTCH disagree with 
their measure results, they can request a formal review of their data 
by CMS. Instruction for submitting such a request are available on the 
LTCH QRP Reconsideration and Exception & Extension web page at https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/LTCH-Quality-Reporting/LTCH-Quality-Reporting-Reconsideration-and-Exception-and-Extension.
    Final Decision: After careful consideration of the public comments, 
we are finalizing our proposal as proposed to use the CAR scenario to 
publicly report LTCH measures for the December 2021-June 2023 
refreshes.
(4) Update on Data Freeze for December 2021 Public Reporting 
Methodology for NHSN-Based Measures
    CDC recommends using the four most recent non-contiguous non-
exempted quarters of data for NHSN reporting in the LTCH QRP. This non-
contiguous compilation of quarterly reporting would continue until the 
time when four contiguous quarters of reporting resumes (based on CDC's 
review, this would occur in July 2022). Tables FF6 and FF7 display the 
original schedules for public reporting of LTCH CDI, CAUTI and CLABSI 
measures and the HCP Influenza measure, respectively. Tables FF8 and 
FF9 summarize the revised schedule and finalized schedule for LTCH CDI, 
CAUTI, and CLABSI measures and the HCP Influenza measure, respectively.
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F. Changes to the Medicare Promoting Interoperability Program

1. Background
a. Statutory Authority for the Medicare Promoting Interoperability 
Program
    The HITECH Act (Title IV of Division B of the ARRA, together with 
Title XIII of Division A of the ARRA) authorized incentive payments 
under Medicare and Medicaid for the adoption and meaningful use of 
certified electronic health record technology (CEHRT). Incentive 
payments under Medicare were available to eligible hospitals and 
critical access hospitals (CAHs) for certain payment years (as 
authorized under sections 1886(n) and 1814(l) of the Act, respectively) 
if they successfully demonstrated meaningful use of certified 
electronic health record technology (CEHRT), which included reporting 
on clinical quality measures using CEHRT. Incentive payments were 
available to Medicare Advantage (MA) organizations under section 
1853(m)(3) of the Act for certain affiliated hospitals that 
successfully demonstrated meaningful use of CEHRT. In accordance with 
the timeframe set forth in the statute, these incentive payments under 
Medicare generally are no longer available, except for Puerto Rico 
eligible hospitals. For more information on the Medicare incentive 
payments available to Puerto Rico eligible hospitals, we refer readers 
to the FY 2021 IPPS/LTCH PPS final rule (85 FR 58976 and 58977) and the 
FY 2019 IPPS/LTCH PPS final rule (83 FR 41672 through 41675).
    Sections 1886(b)(3)(B)(ix) and 1814(l)(4) of the Act also 
established downward payment adjustments under Medicare, beginning with 
fiscal year (FY) 2015, for eligible hospitals and CAHs that did not 
successfully demonstrate meaningful use of CEHRT for certain associated 
electronic health record (EHR) reporting periods. Section 1853(m)(4) of 
the Act established a negative payment adjustment to the monthly 
prospective payments for a qualifying MA organization if its affiliated 
eligible hospitals are not meaningful users of CEHRT, beginning in 
2015.
    Section 1903(a)(3)(F)(i) of the Act established 100 percent Federal 
financial participation (FFP) to States for providing incentive 
payments to eligible Medicaid providers (described in section 
1903(t)(2) of the Act) to adopt, implement, upgrade, and meaningfully 
use CEHRT. We previously established, however, that in accordance with 
section 1903(t)(5)(D) of the Act, in no case may any Medicaid eligible 
hospital receive an incentive after calendar year (CY) 2021 (42 CFR 
495.310(f), 75 FR 44319). Therefore, December 31, 2021 is the last date 
that States could make Medicaid Promoting Interoperability Program 
payments to Medicaid eligible hospitals (other than pursuant to a 
successful appeal related to CY 2021 or a prior year) (84 FR 42591 
through 42592). For additional discussion or context around the 
discontinuation of the Medicaid Promoting Interoperability Program, we 
refer readers to the FY 2019 IPPS/LTCH PPS final rule (83 FR 41676 
through 41677).
2. EHR Reporting Period
a. Background
    Under the definition of ``EHR reporting period for a payment 
adjustment year'' at 42 CFR 495.4, the EHR reporting period in CY 2022 
is a minimum of any continuous 90-day period in CY 2022 for new and 
returning participants in the Medicare Promoting Interoperability 
Program. Eligible hospitals and CAHs may select an EHR reporting period 
of a minimum of any continuous 90-day period in CY 2022 (from January 
1, 2022 through December 31, 2022) (85 FR 58966 through 58967). Since 
the EHR reporting period in CY 2015 (see 80 FR 62777 through 62781, and 
the definitions of EHR reporting period and EHR reporting period for a 
payment adjustment year at 495.4), we have consistently established an 
EHR reporting period of a minimum of any continuous 90-day period for 
eligible hospitals and CAHs for the Medicare Promoting Interoperability 
Program in order to provide maximum flexibility to providers and their 
health IT vendors.
b. EHR Reporting Period in CY 2023 and CY 2024 for Eligible Hospitals 
and CAHs
    For CY 2023, in the FY 2022 IPPS/LTCH proposed rule (86 FR 25628 
through 25629), we proposed to continue the EHR reporting period of a 
minimum of any continuous 90-day period for new and returning 
participants (eligible hospitals and CAHs) in the Medicare Promoting 
Interoperability Program.

[[Page 45461]]

    For CY 2024, in the FY 2022 IPPS/LTCH proposed rule (86 FR 25628 
through 25629), we proposed an EHR reporting period of a minimum of any 
continuous 180-day period for new and returning participants (eligible 
hospitals and CAHs) in the Medicare Promoting Interoperability Program.
    We also proposed to amend the definition of ``EHR reporting period 
for a payment adjustment year'' at 42 CFR 495.4, to include these 
proposed EHR reporting periods in CYs 2023 and 2024.
    The CY 2024 proposal would minimally increase the information 
collection burden on data submitters, and having additional data 
available to further improve our program is beneficial. In increasing 
the EHR reporting period in CY 2024, this would allow eligible 
hospitals, CAHs, and vendors time to plan in advance, build upon, and 
utilize investments already made within their infrastructure. Reporting 
on additional data would also provide eligible hospitals and CAHs the 
opportunity to continuously monitor their performance and identify 
areas that may require investigation and corrective action. Increasing 
the EHR reporting period in CY 2024 is important for the continued 
improvement of interoperability and health information exchange by 
producing more comprehensive and reliable data for patients and 
providers, which are key goals of the Medicare Promoting 
Interoperability Program.
    We sought comments on the proposed EHR reporting periods in CYs 
2023 and 2024, and proposed changes to the regulation text at 42 CFR 
495.4.
    Comment: Many commenters supported the EHR reporting period 
proposal to maintain the current policy of a minimum of any continuous 
90-day period for CY 2023. Commenters emphasized that this consistency 
will allow eligible hospitals and CAHs ample time to implement the 2015 
Edition Cures Update and to complete required testing allowing 
continued flexibility for planned system downtimes, and routine system 
upgrade cycles.
    Response: We thank commenters for their support of the CY 2023 EHR 
reporting period proposal. We agree that for CY 2023, keeping the EHR 
reporting period at a minimum of any continuous 90-days will afford 
eligible hospitals and CAHs the individual site-specific flexibility 
they might need while implementing the 2015 Edition Cures Update and 
preparing for a lengthening of the EHR reporting period of a minimum of 
any continuous 180-days for CY 2024.
    Comment: Some commenters were supportive of the proposed increase 
to the EHR reporting period to a minimum of any continuous 180-days in 
CY 2024, but shared concerns related to the 2015 Edition Cures Update 
implementation deadlines. Specifically, commenters expressed concerns 
that the 2015 Edition Cures Update may require extended testing periods 
until the updates have been fully implemented. Commenters are concerned 
that extended testing will result in scheduled and unscheduled 
downtime, limiting their ability to report on a minimum of a 
continuous, but unaffected, 180-day period. A few commenters also had 
concerns surrounding routine system upgrades and scheduled downtimes 
limiting their ability to report on a minimum of a continuous 180-day 
period.
    Response: We thank commenters for supporting the lengthening of the 
EHR reporting period and sharing their implementation concerns. We 
believe that an EHR reporting period for CY 2024 of 180 days will not 
impact eligible hospitals and CAHs efforts to update, implement, and 
test their EHR systems to maintain compliance with the 2015 Edition 
Cures Update. Eligible hospitals and CAHs must use certified EHR 
technology updated to the 2015 Edition Cures Update during an EHR 
reporting period in 2023 of their choosing; therefore, they should have 
completed implementation by 2024 (86 FR 25628 through 25629). We also 
believe that by proposing and finalizing this increase in the FY 2022 
IPPS/LTCH PPS proposed and final rules, eligible hospitals and CAHs 
will have more than two years of planning with their respective vendor 
to meet site-specific needs for implementation and future planning for 
a longer EHR reporting period. For information on the timelines 
associated with the 2015 Edition Cures Update and associated final 
policies for the Medicare Promoting Interoperability Program, we refer 
commenters to the Office of the National Coordinator for Health 
Information Technology's (ONC) 21st Century Cures Act final rule (85 FR 
25642 through 25961), and the CY 2021 PFS final rule (85 FR 84815 
through 84825). For commenters concerned with limited flexibility in 
choosing a 180-day reporting period when considering general updates to 
health IT systems or transitions between health IT systems, we suggest 
early planning with vendors on the timing of routine system updates and 
downtimes to allow for maximum flexibility in choosing their 180-day 
reporting period.
    Comment: Some commenters supported our proposal to increase the 
length of the EHR reporting period, but have asked that we delay 
implementation until CY 2025. Commenters expressed that the additional 
year will ensure that eligible hospitals and CAHs have had enough time 
to recover from the COVID-19 PHE.
    Response: We thank commenters for their feedback. We understand the 
continued efforts required of eligible hospitals and CAHs throughout 
the COVID-19 PHE. We believe that the COVID-19 PHE has highlighted 
areas where we can focus our efforts to include allowing eligible 
hospitals and CAHs the opportunity to monitor their performance over a 
longer EHR reporting period, and to identify areas that may require 
investigation and corrective action. This is important for the 
continued improvement of interoperability and health information 
exchange, which are key goals of the Medicare Promoting 
Interoperability Program.
    Comment: A few commenters supported lengthening the EHR reporting 
period, but suggest permanently adopting an exception which allows for 
a 90-day EHR reporting period for eligible hospitals and CAHs that 
undergo EHR vendor transitions or system upgrades in any given year.
    Response: We would like to thank these commenters for their 
suggestions, and will take this feedback under consideration for future 
program years. We would like to note that through CY 2023, the 90-day 
EHR reporting period has been finalized as a minimum requirement, and 
that eligible hospitals and CAHs are continuously encouraged to use 
longer reporting periods, up to and including the full calendar year. 
Additionally, we would like to remind commenters that the Medicare 
Promoting Interoperability Program allows hardship exception 
applications for extreme and uncontrollable circumstances, including 
vendor issues. Additional information on this process is available at: 
https://www.cms.gov/Regulations-and-Guidance/Legislation/EHRIncentivePrograms/PaymentAdj_Hardship.
    Comment: Several commenters did not support the proposed 
lengthening the EHR reporting period in CY 2024, and instead suggest 
maintaining the policy at 90-days for CY 2023 and all subsequent years. 
Commenters were concerned that the additional reporting requirements 
lend themselves to increased reporting burden, and could contribute to 
clinical burnout due to non-clinical work.

[[Page 45462]]

    Response: We would like to thank commenters for their suggestions. 
The EHR reporting period was first established in the Stage 1 final 
rule (75 FR 44320) as a minimum of any continuous 90-day period 
beginning with the first payment year, and each successive year. We 
disagree that in lengthening the EHR reporting period from 90-days to 
180-days will cause clinicians additional burden due to non-clinical 
requirements, and would like to reiterate that we have maintained the 
90-day reporting period policy since 2011. With electronic reporting, 
there is no additional requirement or action needed by clinical staff 
to account for the longer EHR reporting period. As continue to strive 
towards promoting greater use of interoperable health IT, balanced 
against systemic requirements and limitations, and will continue to 
take commenters' feedback and concerns under consideration with our 
policies.
    After consideration of the public comments we received, we are 
finalizing our proposal that for CY 2023, the EHR reporting period is a 
minimum of any continuous 90-day period in CY 2023 for new and 
returning participants (eligible hospitals and CAHs) in the Medicare 
Promoting Interoperability Program. We are finalizing our proposal that 
for CY 2024 the EHR reporting period is a minimum of any continuous 
180-day period in CY 2024 for new and returning participants (eligible 
hospitals and CAHs) in the Medicare Promoting Interoperability Program. 
We are also finalizing the corresponding changes to the definition of 
``EHR reporting period for a payment adjustment year'' at 42 CFR 495.4 
as proposed.
3. Changes to the Query of Prescription Drug Monitoring Program Measure 
Under the Electronic Prescribing Objective
a. Measure Background
    We have adopted a Query of Prescription Drug Monitoring Program 
(PDMP) measure under the Electronic Prescribing objective. For 
background on this measure, we refer readers to the FY 2019 IPPS/LTCH 
PPS final rule (83 FR 41648 through 41656), the FY 2020 IPPS/LTCH PPS 
final rule (84 FR 42593 through 42596), and the FY 2021 IPPS/LTCH PPS 
final rule (85 FR 58967 through 58969). In the FY 2021 IPPS/LTCH PPS 
final rule (85 FR 58967 through 58969), we finalized that the Query of 
PDMP measure will remain optional and eligible for 5 bonus points in CY 
2021.
b. State PDMPs' Progress and Previous Stakeholder Feedback
    In the FY 2020 and FY 2021 IPPS/LTCH PPS final rules (84 FR 42593 
through 42596 and 85 FR 58967 through 58969), we described the concern 
expressed by stakeholders that they believed it was premature for the 
Medicare Promoting Interoperability Program to require the Query of 
PDMP measure and score it based on performance. Feedback received from 
health IT vendors and hospitals expressed that flexibility in the 
measure presents unintended challenges such as significant burden 
associated with IT system design and additional development needed to 
accommodate the measure and any future changes to it.
    We understand that there is wide variation across the country in 
how health care providers are implementing and integrating PDMP queries 
into health IT and clinical workflows, and that it could be burdensome 
for health care providers if we were to narrow the measure to specify a 
single approach to PDMP-EHR integration at this time. At the same time, 
we have heard extensive feedback from EHR developers that effectively 
incorporating the ability to count the number of PDMP queries in the 
EHR would require more robust measurement specifications. These 
stakeholders stated that health IT developers may face significant cost 
burdens if they fully develop numerator and denominator calculations 
for all the potential use cases and are required to change the 
specification at a later date. Stakeholders have stated that the costs 
of additional development will likely be passed on to health care 
providers without additional benefit as this development would be 
solely for the purpose of calculating the measure rather than 
furthering the clinical goal of the measure (for public comments 
discussed in last year's final rule, we refer readers to 85 FR 58967 
through 58969).
    In support of efforts to expand the use of PDMPs, there are 
currently a number of federally supported activities underway aimed at 
developing a more robust and standardized approach to EHR-PDMP 
integration. Federal partners, including the Centers for Disease 
Control and Prevention (CDC) and the Office of the National Coordinator 
for Health Information Technology (ONC), and private sector 
stakeholders, are focused on developing and refining standard-based 
approaches to enable effective integration into clinical workflows, 
exploring emerging technical solutions to enhance access and use of 
PDMP data, and providing technical resources to a variety of 
stakeholders to advance and scale the interoperability of health IT 
systems and PDMPs. Moreover, a number of enhancements to PDMPs are 
occurring across the country, including enhancements to RxCheck, which 
is a federally supported interstate exchange hub for PDMP data.\1357\ 
The ONC Interoperability Standards Advisory describes current and 
emerging standards related to PDMP and opioid use disorder (OUD) data 
capture and exchange that would allow a provider to request a patient's 
medication history from a State PMDP and for PDMP data to be exchanged 
between systems and states.\1358\ We believe these standards and 
technical approaches are likely to rapidly reach maturity to support 
exchange across health care system stakeholders.
---------------------------------------------------------------------------

    \1357\ https://www.pdmpassist.org/RxCheck.
    \1358\ https://www.healthit.gov/isa/allows-a-provider-request-a-patients-medication-history-a-state-prescription-drug-monitoring.
---------------------------------------------------------------------------

    The SUPPORT for Patients and Communities Act (Pub. L. 115-271), 
enacted in 2018, is an important investment in combating the opioid 
epidemic. Several of the provisions of the SUPPORT for Patients and 
Communities Act address opioid use disorder prevention, recovery, and 
treatment, including legislative changes specific to the Medicare and 
Medicaid programs intended to increase access to evidence-based 
treatment and follow-up care. However, with respect to PDMPs, the 
SUPPORT for Patients and Communities Act included new requirements and 
Federal funding for PDMP enhancement, integration, and 
interoperability, and established mandatory use of PDMPs by certain 
Medicaid providers to help reduce opioid misuse and overprescribing and 
to help promote the overall effective prevention and treatment of 
opioid use disorder beginning in October of 2021.
c. Measure Changes
    Given current efforts to improve the technical foundation for EHR-
PDMP integration, the continued implementation of the SUPPORT for 
Patients and Communities Act (in particular, its provisions specific to 
Medicaid providers and qualified PDMPs), our ongoing review of 
alternative measure approaches, and stakeholder concerns about the 
current readiness across states for implementation of the existing 
measure, we believe that at least one more year is needed prior to 
potentially requiring the Query of PDMP measure.

[[Page 45463]]

    While we appreciate the concerns that stakeholders have shared, we 
continue to believe that this measure can play an important role in 
helping to address the opioid crisis. By integrating PDMP data into the 
health record, health care providers can improve clinical decision 
making by utilizing this information to identify potential opioid use 
disorders, inform the development of care plans, and develop effective 
interventions. Maintaining it as an optional measure with bonus points 
signals to the hospital and vendor community that this is an important 
measure which addresses a current gap that can help spur development 
and innovation in order to reduce barriers and challenges.
    Therefore, in the FY 2022 IPPS/LTCH proposed rule (86 FR 25629 
through 25630), we proposed for the EHR reporting period in CY 2022 to 
maintain the Electronic Prescribing Objective's Query of PDMP measure 
as optional while increasing its associated bonus points from 5 points 
to 10 points, as well as proposed corresponding changes to the 
regulation at Sec.  495.24(e)(5)(iii)(B). As a result of this proposal, 
the maximum total points available for the Electronic Prescribing 
Objective would increase to 20 points for CY 2022, and we proposed to 
revise Sec.  495.24(e)(5)(ii)(B) to reflect this increase. This 
proposed increase of the measure's associated bonus points to 10 points 
is consistent with the policy finalized for MIPS eligible clinicians in 
the CY 2021 PFS final rule (85 FR 84887 through 84888) and would be in 
alignment with the MIPS Promoting Interoperability performance 
category.
d. Health IT Updates and Measure Direction
    Given recent progress in a variety of areas, we believe that there 
is now a clearer trajectory forward to potentially requiring the Query 
of PDMP measure. These developments include updated requirements for 
certified health IT, standards development activities around PDMPs, and 
other projects that can more tangibly inform future policy changes. For 
example, under final policies recently adopted in the CY 2021 Physician 
Fee Schedule final rule (85 FR 84815 through 84828), participants in 
the Medicare Promoting Interoperability Program and the MIPS Promoting 
Interoperability performance category will begin using certified EHR 
technology incorporating application programming interfaces (APIs) 
based on HL7[supreg] FHIR[supreg] standard version Release 4 in CY 2023 
consistent with updates to certified health IT which were finalized in 
the ``21st Century Cures Act: Interoperability, Information Blocking, 
and the ONC Health IT Certification Program'' final rule (hereinafter 
referred to as the ``ONC 21st Century Cures Act final rule''), 
published in the May 1, 2020 Federal Register (85 FR 25642 through 
25961 and 25740).\1359\ Updates to 2015 Edition health IT certification 
criteria in the ONC 21st Century Cures Act final rule also incorporated 
NCPDP SCRIPT standard version 2017071 for electronic prescribing. The 
availability of both standardized APIs and updated standards for e-
prescribing within certified health IT could serve as a stepping stone 
to future technical approaches that enable more seamless exchange of 
data between CEHRT and PDMP systems.
---------------------------------------------------------------------------

    \1359\ HL7[supreg] and FHIR[supreg] are registered trademarks of 
Health Level Seven International.
---------------------------------------------------------------------------

    ONC also began work in partnership with the CDC, the Department of 
Justice's Bureau of Justice Assistance, and the eHealth Exchange to 
develop a prototype to pilot an innovative technical solution for the 
delivery of patient medication histories across State lines via 
HL7[supreg] FHIR[supreg]. The eHealth Exchange is a network of networks 
that is active in all 50 states connecting Federal and non-Federal 
healthcare organizations to improve patient care and public health. To 
date, the prototype has been successfully tested in several states. 
Early prototype testing used synthetic data to evaluate system capacity 
to send and receive a patient's medication history request and 
response. The goal of the project is to allow any provider who is live 
on the eHealth Exchange to use that existing connection to query a 
patient's record on the RxCheck Hub, which routes the query to 
individual State PDMPs who are also live on RxCheck. This solution will 
enable providers to query PDMPs via existing connections to health 
information exchange networks as a way to: (1) Leverage existing 
technology, (2) reduce burden associated with multiple, disparate 
system interfaces and workflows, and (3) allow for the exchange and 
full integration of data within allowable law from the point of 
exchange for medication reconciliation, allergy checks, and other forms 
of clinical decision support.
    Based upon these developments, which are advancing enhanced 
certified functionality, effective functional data exchange, and the 
use of open, mature standards, we believe there is a much better 
informed roadmap for achieving better integration between PDMPs and 
EHRs with enhanced interoperability of controlled prescription data 
across states and systems. We believe that as these activities develop, 
they can help to address some of the previous concerns raised by 
stakeholders around this measure, and we will continue to work with ONC 
to monitor these activities.
    We sought comments on our proposal to maintain the Query of PDMP 
measure in the EHR reporting period in CY 2022 as optional and to 
increase the bonus points associated with the measure to 10 bonus 
points.
    Comment: The vast majority of commenters agreed with the proposal 
to maintain the Electronic Prescribing Objective's Query of PDMP 
measure in the CY 2022 EHR reporting period as optional and to increase 
the bonus points associated with the measure to 10 bonus points. Many 
of the commenters who supported the proposal referenced how the 
implementation methods under each state still vary greatly due to the 
uniqueness of local laws for each particular PDMP's jurisdiction. The 
same commenters also appreciated that the increase in available bonus 
points to 10 points is consistent with a similar policy finalized by 
the Merit-based Incentive Payment System (MIPS) eligible clinicians in 
the CY 2021 PFS final rule, therefore maintaining an aspect of 
alignment with the MIPS Promoting Interoperability performance 
category.
    Response: We thank commenters for their support for the proposal as 
we recognize that additional time before requiring the Query of PDMP 
measure would enable further progress to be made around integration 
between PDMPs and EHR systems. We acknowledge that there is some 
complexity for how various state programs are maturing their systems 
toward the development of effective PDMP-EHR integration and we 
continue to collaborate with our various partners (including but not 
limited to the Office of the National Coordinator for Health 
Information Technology, ONC) to increase access and promote further use 
of standards to support exchange of information with PDMPs. This 
ongoing partnership to develop more consistent and interoperable 
approaches to sharing data with PDMPs will inform continued progress in 
this area of health information exchange, while our proposal would 
provide for an additional year for states and other stakeholders to 
make greater progress toward improving interoperability across systems.
    Comment: Some commenters who supported the proposal also suggested 
that CMS should continue to maintain the Query of PDMP measure as 
optional beyond CY 2022 in order to help lift undue burden off the 
facilities which

[[Page 45464]]

are still struggling to seamlessly integrate EHR systems with PDMPs. 
Similarly, some commenters supported the intent of the measure and 
support the role it plays in improving patient care by potentially 
protecting vulnerable populations from opioid overdoses, but suggested 
that the measure should not be required until PDMPs are able to give 
providers a full, real-time accounting of patients' prescription drug 
history.
    Response: We thank commenters for expressing their concerns 
regarding requiring the Query of PDMP measure in the future. However, 
we continue to believe the Query of PDMP measure will be a useful and 
informative measure as more state PDMPs and hospital EHR systems are 
effectively integrated. We refer readers to section IX.F. of the 
proposed rule and this final rule for an overview of the key efforts 
which have been underway and highlighted aims of improving the 
technical approaches to EHR-PDMP integration, including the 
implementation of key provisions from the SUPPORT for Patients and 
Communities Act. The proposal was only for the CY 2022 EHR reporting 
period. We will take commenters' feedback into consideration in 
proposals for future years of the program.
    After consideration of the public comments received, we are 
finalizing our proposal to maintain the Query of PDMP measure as 
optional while increasing its associated bonus points from 5 points to 
10 points for the EHR reporting period in CY 2022. As a result, the 
maximum total points available for the Electronic Prescribing Objective 
will increase to 20 points for the EHR reporting period in CY 2022. We 
are also finalizing the corresponding changes to the regulation at 
Sec. Sec.  495.24(e)(5)(ii)(B) and 495.24(e)(5)(iii)(B) as proposed.
4. Changes to the Provide Patients Electronic Access to Their Health 
Information Measure Under the Provider to Patient Exchange Objective
a. Background
    In the FY 2019 IPPS/LTCH PPS final rule (83 FR 41636 through 
41668), we renamed the Patient Electronic Access Objective to the 
Provider to Patient Exchange Objective. This objective includes the 
Provide Patients Electronic Access to Their Health Information measure.
b. Data Availability Requirement for Eligible Hospitals and CAHs
    In the FY 2022 IPPS/LTCH proposed rule (86 FR 25631), we proposed 
to modify the Provide Patients Electronic Access to Their Health 
Information measure by requiring eligible hospitals and CAHs to ensure 
that patient health information remains available to the patient (or 
patient-authorized representative) to access indefinitely, using any 
application of their choice that is configured to meet the technical 
specifications of the API in the eligible hospital or CAH's CEHRT, as 
described under 495.24(e)(7)(ii)(B). Eligible hospitals and CAHs would 
be required to ensure this information remain available indefinitely 
(that is, not merely for a defined period of time). As proposed, this 
requirement would apply beginning with the EHR reporting period in CY 
2022, and would include all patient health information from encounters 
on or after January 1, 2016. We also proposed to add corresponding 
regulatory text at 495.24(e)(7)(ii)(C), as well as restructuring some 
of the existing text under 495.24(e)(7) to improve clarity and 
readability.
    In the Patient Access and Interoperability final rule (85 FR 25510, 
25527 through 25528), we finalized that beginning on January 1, 2021, 
MA organizations, Medicaid FFS programs, Medicaid managed care plans, 
CHIP FFS programs, CHIP managed care entities, and QHP issuers on the 
FFEs must make available to beneficiaries and enrollees through a 
Patient Access API, certain claims and clinical data that they maintain 
with a date of service on or after January 1, 2016. Recognizing the 
challenges faced by payers during the COVID-19, we announced we will 
exercise enforcement discretion and not enforce these new requirements 
until July 1, 2021.\1360\ The look-back period finalized in the Patient 
Access and Interoperability final rule aimed to align with the required 
policy for payer-to-payer data exchange finalized in the same rule, 
providing patients with the same timeframe of information as payers to 
ensure consistent implementation, while minimizing cost and burden and 
maximizing patient benefit (85 FR 25542). The finalized look-back 
period for payers also required that data be available for 5 years 
after disenrollment (Sec.  422.119(f)).
---------------------------------------------------------------------------

    \1360\ https://www.cms.gov/Regulations-and-Guidance/Guidance/Interoperability/index.
---------------------------------------------------------------------------

    Currently, the Provide Patients Electronic Access to Their Health 
Information measure does not specify how long eligible hospitals and 
CAHs are required to make patient data available or ensure that patient 
data remain available to patients in the event that an eligible 
hospital or CAH switches EHR vendors. In an effort to minimize 
stakeholder burden, we wanted to align the date under our proposal for 
making information about encounters available, with the date of service 
start date (January 1, 2016) as finalized in the Patient Access and 
Interoperability final rule. As an alternative to our proposal, we 
considered different encounter start dates, such as encounters on or 
after January 1, 2012, or encounters on or after January 1, 2019. We 
believe, however, that a requirement for hospitals to ensure patient 
health information remains available indefinitely, as well as an 
encounter start date of January 1, 2016 would provide the most benefit 
to patients when accessing their health information as compared to the 
burden and costs to eligible hospitals and CAHs implementing these 
proposed requirements.
    We sought public comments on our proposals to modify the Provide 
Patients Electronic Access to Their Health Information measure, as well 
as the alternatives we considered and discussed above.
    Comment: A commenter expressed support for our proposal, stating 
that aligning requirements across the healthcare sector would minimize 
confusion and burden for hospitals.
    Response: We would like to thank this commenter for their support, 
and agree that as we continue to align requirements across program 
areas, this will minimize reporting burden and redundancies.
    Comment: Many commenters support the principle that patients should 
have prompt access to their data with minimal effort, but did not 
support our proposal as proposed. Several commenters stated that the 
lack of clarity around key terminology was a main concern. 
Specifically, commenters requested additional clarification on how we 
are defining an ``indefinite'' timeline, what specific data would be 
included in ``all patient health information,'' and how we will address 
software platform changes regarding non-transferable data given those 
terms.
    Response: We thank commenters for their feedback, and agree that 
patients should have access to their data with minimal effort. For 
commenters requesting additional clarification on the terms used in the 
proposal, including ``indefinite'' and ``all patient health 
information,'' thank you for these requests. We agree with commenters 
that we need to more clearly define what an ``indefinite'' timeline 
entails, as well as to more clearly define what specific data should be 
included in ``all patient health information.'' We agree with 
commenters that we need to consider defining and allowing for

[[Page 45465]]

exceptions as well. We agree that as proposed, this modification needs 
additional clarification, and for these reasons, we are not finalizing 
this proposal at this time. In the future, we will be seeking 
additional feedback from eligible hospitals and CAHs, in the event that 
we decide to propose changes to the measure in future rulemaking.
    Regarding software platform changes and non-transferable data, we 
would like to note that the ONC 21st Century Cures Act final rule 
established a new criterion, ``electronic health information export'' 
at Sec.  [thinsp]170.315(b)(10), which requires a certified health IT 
module to electronically export all electronic health information 
(EHI), as defined in Sec.  [thinsp]171.102, that can be stored at the 
time of certification by the product of which the health IT module is a 
part (85 FR 25690-25693). A health IT developer of certified health IT 
products, which, at the time presented for certification electronically 
stores EHI, must certify such products to this new criterion and make 
these products available to their customers by December 31, 2023. We 
believe this certified functionality will further support the 
capability to seamlessly transfer electronic health information between 
systems. Although we are not finalizing this proposal at this time, we 
will consider these suggestions in the event we decide to propose 
changes to the measure in future rulemaking.
    Comment: Several commenters shared concerns regarding potential 
conflict between state laws and our proposed data availability 
requirement, and also between state laws and our proposed requirement 
to make available ``all patient health information.'' One example 
shared by a few commenters is that different states have different 
timeline requirements for data retention (mentioned were 7 and 10 
years), as opposed to our proposal for an ``indefinite'' availability 
period. Another commenter shared that some states have laws requiring 
that physicians withhold certain patient health information from being 
released (specifically, California protected health information laws 
were shared), where our proposal included ``all patient health 
information,'' non-specific of any exclusions.
    Response: We thank commenters for sharing this feedback and their 
concerns. We agree with commenters that we need to continue our 
collaborative efforts with the CMSPatient Access and Interoperability 
team and ONC as we consider how we might address this issue in future 
rulemaking. We also agree with commenters that we need to address 
varying data availability requirements between individual states, and 
ensure that we also account for state protected personal health 
information. For these reasons, we are not finalizing our proposal at 
this time. Instead, CMS may hold a listening session in the future 
where we welcome feedback as we continue to consider potential 
revisions to this measure amidst the feedback we have received.
    Comment: Many commenters were not supportive of our proposal, but 
offered suggestions for us to consider. A few commenters suggested that 
CMS consider setting expectations on a forward-looking basis rather 
than taking a retrospective approach. Some commenters suggested that we 
consider working more closely with ONC to clearly distinguish between 
USCDI and the larger set of electronic health information as defined in 
the ONC Information Blocking rules. Another commenter asked that we 
ensure this policy is aligned with ONC's requirements for certified 
health IT. A commenter suggested that we consider postponing this 
policy until the Patient Access and Interoperability final rule has 
been fully implemented before expanding into the Medicare Promoting 
Interoperability Program. A commenter suggested that we consider 
requiring hospitals to support any API of the patient's choosing, then 
follow with the data retention requirement over time.
    Response: Again, we thank commenters for sharing their suggestions 
for improvement. We agree with the commenters' suggestions, and will 
continue to collaborate with the CMS Patient Access and 
Interoperability team and ONC, especially regarding the feedback 
commenters shared above. We agree with commenters that CMS and ONC need 
to clearly distinguish between the USCDI requirements against the 
larger set of electronic health information, especially in light of 
this proposed modification. We agree with commenters that additional 
work is essential on this proposal, and will not be finalizing at this 
time. We will take into consideration the suggestion to consider 
postponing this policy until the Patient Access and Interoperability 
final rule has been fully implemented, and as mentioned previously, CMS 
may hold a listening session in the future where we welcome additional 
feedback as we consider this measure for future rulemaking.
    After consideration of the public comments we received, we are not 
finalizing our proposal to modify the Provide Patients Electronic 
Access to Their Health Information measure by requiring eligible 
hospitals and CAHs to ensure that patient health information remains 
available to the patient (or patient-authorized representative) to 
access indefinitely and using any application of their choice that is 
configured to meet the technical specifications of the API in the 
eligible hospital or CAH's CEHRT, as described under 
495.24(e)(7)(ii)(B). We are also not finalizing our proposals to add 
and restructure corresponding regulatory text at Sec.  
495.24(e)(7)(ii)(C) and Sec.  495.24(e)(7). We wish to emphasize that 
CMS and HHS strongly believe that a patient's health information remain 
available to the patient (or patient-authorized representative) through 
available technology tools, including the technology capabilities 
specified to successfully report on the Provide Patient Access to the 
Health Information measure. We will take commenters' suggestions under 
consideration and will seek further input as we consider whether to 
propose changes to the measure in future rulemaking.
5. Health Information Exchange Objective: Engagement in Bi-Directional 
Exchange Through Health Information Exchange (HIE)
a. Background
    Organizations that provide health information exchange services 
(HIEs) allow for the sharing of health information among clinicians, 
hospitals, care coordinators, labs, radiology centers, and other health 
care providers through secure, electronic means so that health care 
providers can have the benefit of the most recent information available 
from other health care providers. HIEs allow for broader 
interoperability beyond one health system or point-to-point connections 
among payers, patients, and health care providers. By enabling bi-
directional exchange of information between health care providers and 
aggregating data across providers with disparate systems, HIEs can 
bring together the information needed to create a true longitudinal 
care record and support improved care coordination by facilitating 
timely access to robust health information across care settings. In the 
FY 2022 IPPS/LTCH proposed rule (86 FR 25631 through 25634), we stated 
that for the purposes of this proposal, bi-directional exchange means 
that the hospital's EHR enables querying and sharing data by sending, 
receiving, and incorporating data via an HIE for all unique patients 
treated in place of service inpatient hospital or emergency department 
(POS 21 and 23 respectively). Healthcare quality and public health 
outcomes have been shown in multiple studies to experience a beneficial 
effect from

[[Page 45466]]

health information exchanges with improved medication reconciliation, 
improved immunization and health record completeness, and improved 
population level immunization rates,\1361\ while other research has 
shown a decrease in emergency department utilization and improved care 
process when using an HIE.\1362\
---------------------------------------------------------------------------

    \1361\ https://academic.oup.com/jamia/article/25/9/1259/4990601: 
ibid.
    \1362\ https://pubmed.ncbi.nlm.nih.gov/27521368/: Journal of the 
American Medical Informatics Association. 2017 Apr 1;24(e1):e103-
e110. doi: 10.1093/jamia/ocw116. ``Health Information Exchange 
Associated With Improved Emergency Department Care Through Faster 
Accessing of Patient Information From Outside Organizations''.
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    HIE services are available from many organizations today, which may 
be referred to as HIEs, health information networks, health information 
organizations (HIOs), or other terms. State and regional HIEs have a 
long history of connecting health care providers caring for a common 
patient population across a specified geographic area. These HIEs 
represent a significant public investment, with $564 million in Federal 
funding provided as part of the 2009 HITECH Act, ongoing State funding 
and support from CMS under both 42 CFR 495.322 and 42 CFR 433 Subpart 
C.\1363\ These State and regional HIEs typically obtain not just EHR-
generated data, but a broader array of ADT (admit, discharge, transfer) 
feeds and lab feeds as they build on local relationships. These HIEs 
may have similar but not identical capabilities, employing different 
models of data storage and a variety of business models. Regional and 
State-based exchanges have also begun to address national-level 
exchange, with efforts designed to link State and regional networks so 
that health care providers can obtain information on individual 
patients wherever they receive care throughout the United States. In 
addition to these initiatives, many EHR vendors are participating in 
the development of national-level networks designed to ensure their 
customers can share information with customers of other vendors. For 
data on HIE availability and adoption, we refer readers to 86 FR 25632.
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    \1363\ https://protect2.fireeye.com/url?k=d8978709-84c28e1a-d897b636-0cc47adb5650-e634c1ba410d0153&u=https://www.healthit.gov/sites/default/files/reports/finalsummativereportmarch_2016.pdf.
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b. New Health Information Exchange (HIE) Bi-Directional Exchange 
Measure
    We believe that incentivizing participation in HIEs that support 
bi-directional exchange will contribute to a longitudinal care record 
for the patient and facilitate enhanced care coordination across 
settings. The use of an HIE means that essential health information is 
available for care team members even in the case of referrals the 
clinician may not be aware of, or for instances where the eligible 
hospital or CAH is contributing to the patient's record, but may not be 
the health care provider making the referral. In these instances, such 
transitions may or may not be able to be automatically identified by an 
EHR for inclusion in the denominators of the two existing measures 
associated with the HIE objective for the Promoting Interoperability 
Program (42 CFR 495.24(e)(6)).
    Under the existing measures for the HIE objective (42 CFR 
495.24(e)(6)), only the known transition of care from primary care 
physician to specialist would be included in the denominator. However, 
under the alternative measure for bi-directional exchange through a HIE 
that we proposed, we would incentivize the eligible hospital or CAH to 
engage in health information exchange for care coordination that 
includes these additional transitions and referrals as well as other 
potential scenarios: Where the recipient of the transition of care may 
be unknown; where the eligible hospital or CAH may not be the referring 
health care provider; where the transition of care may happen outside 
the scope of the EHR reporting period. In this way, the eligible 
hospital or CAH's action to engage in bi-directional exchange through 
an HIE would allow each health care provider to contribute to the 
longitudinal care record in a manner that supports a wide range of 
transitions and referrals beyond those currently reflected in the 
measure denominators. This engagement supports robust health 
information exchange without placing burden on the hospital or the 
patient to be individually accountable to facilitate exchange via 
multiple (and potentially unknown) point-to-point connections.
    The COVID-19 public health emergency (PHE) has further highlighted 
the need to encourage interoperable HIE infrastructure and bi-
directional exchange across the country that can ensure patients, 
health care providers, and public health authorities have the data they 
need to support quality care. In addition to supporting general care 
coordination, HIEs can specifically support the PHE response by 
facilitating enhanced use of telehealth and telemedicine through 
obtaining and aggregating patient information including when the 
patient's health care provider(s) may not be known.
    In the CY 2021 PFS final rule (85 FR 84888 through 84893), we added 
an alternative measure for bi-directional exchange through a HIE under 
the Health Information Exchange objective for the MIPS Promoting 
Interoperability performance category beginning with the performance 
period in 2021. In the FY 2022 IPPS/LTCH PPS proposed rule, we proposed 
to add a similar measure for eligible hospitals and CAHs participating 
in the Medicare Promoting Interoperability Program beginning with the 
EHR reporting period in CY 2022 (86 FR 25631-25634).
    We proposed at 86 FR 25631 through 25634 to add the following new 
measure for inclusion in the Health Information Exchange objective at 
42 CFR 495.24(e)(6)(ii)(C): Health Information Exchange (HIE) Bi-
Directional Exchange measure. We proposed to add this new HIE Bi-
Directional Exchange measure to the HIE objective as an optional 
alternative to the two existing measures: The Support Electronic 
Referral Loops by Sending Health Information measure 42 CFR 
495.24(e)(6)(ii)(A) and the Support Electronic Referral Loops by 
Receiving and Reconciling Health Information measure 42 CFR 
495.24(e)(6)(ii)(B). We proposed that eligible hospitals and CAHs may 
either report the two existing measures and associated exclusions OR 
may choose to report the new measure and are proposing to revise 42 CFR 
495.24(e)(6)(ii) to reflect this change. We proposed that the HIE Bi-
Directional Exchange measure would be worth 40 points. In no case could 
more than 40 points total be earned for the HIE objective. We proposed 
the HIE Bi-Directional Exchange measure would be reported by 
attestation and would require a yes/no response. As we believe that 
fulfillment of this measure is an extremely high value action, a 
``yes'' response would enable eligible hospitals and CAHs to earn the 
40 points allotted to the HIE objective. We proposed that eligible 
hospitals and CAHs would attest to the following:
     Participating in an HIE in order to enable secure, bi-
directional exchange of information to occur for all unique patients 
admitted to or discharged from the eligible hospital or CAH inpatient 
or emergency department (POS 21 or 23), and all unique patient records 
stored or maintained in the EHR for these departments, during the EHR 
reporting period in accordance with applicable law and policy.
     Participating in an HIE that is capable of exchanging 
information across a broad network of unaffiliated exchange partners 
including those using disparate EHRs, and not engaging in

[[Page 45467]]

exclusionary behavior when determining exchange partners.
     Using the functions of CEHRT to support bi-directional 
exchange with an HIE.
    We believe it is appropriate for the new optional measure to serve 
as an alternative measure of performance on health information exchange 
since, in order to successfully meet the measure, an eligible hospital 
or CAH would be required to meet an overall standard of performance on 
health information exchange that is broader than the denominators and 
numerators of the current measures. To successfully attest to the new 
measure the eligible hospital or CAH must establish the technical 
capacity and workflows to engage in bi-directional exchange of 
information via an HIE for to occur for all unique patients admitted to 
or discharged from the eligible hospital or CAH inpatient or emergency 
department (POS 21 or 23) and all unique patient records stored or 
maintained in the EHR for these departments during the EHR reporting 
period. This includes enabling the ability to query for or receive 
health information to occur for all unique patients admitted to or 
discharged from the eligible hospital or CAH inpatient or emergency 
department (POS 21 or 23) and all unique patient records stored or 
maintained in the EHR, as well as enabling sending or sharing 
information for these patients regardless of known referral or 
transition status, or the timing of any potential transition or 
referral. The proposed requirement to enable querying for or receiving 
health information for all unique patients admitted to or discharged 
from the eligible hospital or CAH inpatient or emergency department 
(POS 21 or 23) and all unique patient records stored or maintained in 
the EHR for these departments is broader than the current Support 
Electronic Referral Loops by Receiving and Reconciling Health 
Information measure, which includes only new patients and known 
transitions or referrals received that occur during the EHR reporting 
period. Similarly, the proposed requirement to enable sending or 
sharing information for all unique patients admitted to or discharged 
from the eligible hospital or CAH inpatient or emergency department 
(POS 21 or 23) and all unique patient records stored or maintained in 
the EHR for these departments represents a broader scope than the 
current Support Electronic Referral Loops by Sending Health Information 
measure which includes only known transitions of care or referrals made 
that occur during the EHR reporting period. This proposed requirement 
is likewise more expansive than the denominators of either measure.
    Relative to the numerators for the current measures, the new 
optional measure would require that bi-directional engagement be 
enabled for all unique patients admitted to or discharged from the 
eligible hospital or CAH inpatient or emergency department (POS 21 or 
23) and all unique patient records stored or maintained in the EHR for 
these departments during the EHR reporting without exclusion, 
exception, or allowances made for partial credit. This is similar to 
achieving a score of 100 percent on both the Support Electronic 
Referral Loops by Sending Health Information measure and the Support 
Electronic Referral Loops by Receiving and Reconciling Health 
Information measure, while additionally completing required actions for 
additional exchange cases not included in the existing denominators. 
Finally, while we believe this optional measure would establish a high-
performance standard with respect to information sharing, we also 
believe that availability of this optional measure would reduce current 
reporting burden associated with the program, as eligible hospitals or 
CAHs choosing to report on the measure would not be required to report 
on the two existing numerator/denominator measures.
    To successfully attest to this measure, the eligible hospital or 
CAH must use the capabilities defined for CEHRT to engage in bi-
directional exchange via the HIE, which includes capabilities which 
support exchanging the clinical data within the Common Clinical Data 
Set (CCDS) or the United States Core Data for Interoperability (USCDI). 
This is consistent with the existing measures under the Health 
Information Exchange objective, which require the use of CEHRT to 
create a Consolidated Clinical Document Architecture (C-CDA) document, 
and support the exchange of the clinical data within the CCDS or the 
USCDI. We believe there are numerous certified health IT capabilities 
which can support bi-directional exchange with a qualifying HIE. For 
instance, participants may interact with an HIE by using technology 
certified to the criterion at Sec.  170.315(b)(1) to transmit C-CDAs to 
the HIE. Participants could also utilize API technology certified to 
either the criterion at Sec.  170.315(g)(8) or (g)(10), as finalized in 
the ONC 21st Century Cures Act final rule (85 FR 25742), to enable an 
HIE to obtain data in the CCDS or USCDI from a participant's EHR. 
Additional certified health IT modules may also support exchange of 
information with an HIE for transitions of care, including modules 
certified to certification criteria at Sec.  [thinsp]170.315(g)(7), 
``Design and performance--Application access--patient selection,'' and 
(g)(9), ``Design and performance--Application access--all data 
request,'' which support information exchange via API; the 
certification criterion at Sec.  [thinsp]170.315(e)(1) ``View, 
download, and transmit to 3rd party'' which supports patient access to 
their information; and the certification criterion at Sec.  
[thinsp]170.315(g)(6) ``Consolidated CDA creation performance'' which 
supports creation of a summary of care record. We recognize that HIEs 
are currently interacting with health care providers using certified 
health IT in a variety of ways, and believe that we should allow for 
substantial flexibility in how health care providers use certified 
health IT to exchange data using an HIE.
    Furthermore, an eligible hospital or CAH attesting to these three 
statements would not be required to use all of the relevant certified 
health IT modules, as previously described, to support their connection 
with an HIE, nor must a connection with an HIE be solely based on 
certified health IT modules. For instance, a provider's EHR could 
generate a C-CDA using a certified health IT module, and subsequently 
transmit that document to an HIE using technology that is not part of a 
certified health IT module. Such an approach would be acceptable for 
attesting to the third proposed attestation statement requiring the use 
of CEHRT to support the measure.
    We note that none of the actions required to attest to this measure 
are intended to conflict with a patient's rights or covered entities' 
(for example, health care providers) requirements/responsibilities 
under the HIPAA Privacy Rule, as set out at 45 CFR parts 160 and 164. 
We also understand that different HIEs that enable exchange in the 
manner described may have different policies related to confidentiality 
of patient information based on local circumstances and requirements. 
Nothing in the attestation statements for this measure are intended to 
conflict with individual HIE policies that may exist in these areas, or 
prevent eligible hospitals or CAHs from complying with these policies 
as a condition of their participation in the HIE.
    We invited comments on our proposal, and whether commenters believe 
such an optional measure would incentivize eligible hospitals and CAHs 
to participate in HIEs while establishing a high-performance standard 
for sharing information with other health care providers.

[[Page 45468]]

    Finally, while our proposed attestation statements for this measure 
do not explicitly refer to participation in a health information 
network, or partnering with a health information network that 
participates in the Trusted Exchange Framework and Common Agreement 
(TEFCA) described in section 4003 of the 21st Century Cures Act, we 
recognize that this is likely to be an important way for eligible 
hospitals and CAHs to enable bi-directional health information exchange 
in the future. We will continue to explore ways to provide further 
guidance and/or update this measure to align with the use of health 
information networks that participate in the TEFCA in the future. For 
more information on current developments related to the TEFCA, we refer 
readers to www.HealthIT.gov/TEFCA.
    Comment: The majority of comments supported the addition of the HIE 
Bi-directional exchange measure. One stated that the ongoing capability 
for bi-directional exchange, and use of such a capability, are critical 
to advancing effective interoperability. Several commenters supported 
that this measure would be reported via attestation and were encouraged 
to see CMS' acknowledgement that this measure could align with the ONC 
efforts on the Trusted Exchange Framework and Common Agreement (TEFCA). 
Other commenters agreed that this measure will encourage bi-directional 
exchange of health information with community partners to promote care 
coordination for patients with chronic conditions and complex care 
needs. Several commenters concurred with our rationale that the new 
measure can support robust health information exchange while minimizing 
the burden on hospitals and patients to be individually accountable to 
facilitate exchange via multiple connections.
    Response: We appreciate the support from commenters on the addition 
of this measure.
    Comment: Some commenters suggested that CMS should take into 
consideration the fact that there are care settings that may lack 
certain technical capabilities and struggle with bi-directional 
exchange of patients' electronic health information compared to 
Promoting Interoperability Program participants.
    Response: We understand that not all eligible hospitals and CAHs 
may be able to report this measure in CY 2022 which is why we proposed 
to make this an alternative measure to the two existing HIE measure. We 
encourage bi-directional exchange and will be monitoring the uptake of 
this measure to determine future policies surrounding this measure.
    Comment: A commenter asked that we clarify that, while HIE 
participation must ``enable secure, bi-directional exchange of 
information to occur for all unique patients . . . and all unique 
patient records stored or maintained in the EHR . . .'', that exchange 
of patient summaries or other patient data need not occur for all such 
patients, only that it can occur as needed or requested. Another 
commenter expressed concern that the proposed bi-directional engagement 
measure would have to be enabled for all unique patients admitted to or 
discharged from the eligible hospital or CAH inpatient or emergency 
department and all unique patient records stored or maintained in the 
EHR for those departments during the EHR reporting period. The 
commenter asked if there would be no exclusions, exceptions or 
allowances made for partial credit.
    Response: The first attestation statement, as proposed, would 
require an eligible hospital or CAH to enable bi-directional exchange 
for all of an eligible hospital's or CAHs patient records. Enabling bi-
directional exchange does not mean that an eligible hospital or CAH 
would be required to conduct information transactions that are not 
clinically necessary. Rather, it means that an eligible hospital or CAH 
has established the capabilities necessary to complete exchanges of 
information for their patients at the appropriate time. We also decline 
to provide partial credit for this measure as partial performance would 
not meet the goals of the measure. Our goal in proposing this measure 
is to incentivize the high standard of performance on health 
information exchange which can be achieved by establishing robust, bi-
directional exchange capabilities facilitated by an HIE. We do not 
believe that allowing an eligible hospital or CAH to satisfy the 
measure based on a partial threshold would be consistent with 
incentivizing a high performance standard for the exchange of health 
information.
    Comment: A commenter asked that we clarify that, if such a provider 
or vendor-specific network connects with a regional or national 
exchange framework that enables connection across ``a broad network of 
unaffiliated exchange partners,'' whether such a connection would 
satisfy the attestation.
    Response: For purposes of this measure and its attestation 
statements, the term ``HIE'' broadly refers to arrangements that 
facilitate the exchange of health information, and may include 
arrangements commonly denoted as exchange ``frameworks,'' ``networks,'' 
or using other terms. We understand that under some arrangements, HIEs 
or networks may partner with other network entities in order to extend 
their reach. Such arrangements would qualify to meet the intent of the 
second statement regarding sharing across unaffiliated providers.
    Comment: A commenter stated that in their hospital C-CDAs come in 
and count as received, and then they generate responses and send out 
for follow-up post discharge. The bi-directional HIE which they are a 
part of currently is a pull and not a push exchange for all 
organizations. The commenter requested more detail on this measure to 
assist in understanding if this measure is a feasible option for 
providers using an EHR-specific vendor network for some connections, 
and a Health Information Service Provider (HISP) to connect with 
organizations that use different vendors.
    Response: We stated in the proposed rule (86 FR 25633) that in 
order to attest successfully to the new measure the eligible hospital 
or CAH must establish the technical capacity and workflows to engage in 
bi-directional exchange of information for all unique patients admitted 
to or discharged from the eligible hospital or CAH inpatient or 
emergency department (POS 21 or 23) and all unique patient records 
stored or maintained in the EHR for these departments during the EHR 
reporting period. This includes enabling the ability to query or 
receive health information on all unique patients admitted to or 
discharged from the eligible hospital or CAH inpatient or emergency 
department (POS 21 or 23) and all unique patient records stored or 
maintained in the EHR for these departments, as well as enabling 
sending or sharing information for these patients regardless of known 
referral or transition status, or the timing of any potential 
transition or referral. Furthermore, we clarified in the preamble of 
the FY 2022 IPPS/LTCH proposed rule (86 FR 25631 through 25634) that an 
eligible hospital or CAH attesting to these three statements would not 
be required to use all relevant certified health IT modules to support 
their connection with an HIE, nor must a connection with an HIE be 
solely based on certified health IT modules. For instance, a provider's 
EHR could generate a C-CDA using a certified health IT module, and 
subsequently transmit that document to an HIE using technology that is 
not part of a certified health IT module.
    Regarding the commenter's example, provided the eligible hospital 
or CAH

[[Page 45469]]

successfully attested to the first attestation statement regarding bi-
directional exchange for patients, and that the use of the HISP allowed 
the eligible hospital or CAH to successfully attest to the elements in 
the second attestation statement regarding sharing information across a 
broad network of unaffiliated exchange partners, including those using 
disparate EHRs, the participant would be able to successfully attest to 
the measure. The measure does not limit eligible hospitals or CAHs to 
the use of a single solution for all instances of bi-directional 
exchange.
    Comment: A commenter stated that we should specifically limit any 
interoperability incentives to non-profit state or local HIEs which 
have state or locality-based governance, are non-profit, and which have 
shown that these HIEs are available to any healthcare provider of any 
type, including schools, jails, group homes, and shelters serving the 
underserved or mentally ill. These HIEs should be required to have a 
physical presence in each state. The commenter stated that the HIEs 
should not be preferentially affiliated with any EHR vendor and CMS 
should encourage these HIEs to serve as public health data utilities.
    Response: We appreciate the commenter's focus on these types of 
HIEs. However, we decline to add additional restrictions on the types 
of HIEs that can qualify for the measure as our goal is broad inclusion 
of HIE arrangements that facilitate robust exchange of health 
information in alignment with the existing HIE measures. We believe the 
second attestation statement requiring HIEs to support exchange across 
a ``broad network of unaffiliated exchange partners, including those 
using disparate EHRs, and not engaging in exclusionary behavior when 
determining exchange partners,'' addresses concerns that the measure 
would incentivize use of HIEs that exclude certain providers.
    Comment: A commenter suggested that it would be helpful if we 
provide examples of the types of transactions we see as pertinent to 
this measure.
    Response: We take a broad view of the types of transactions 
applicable to this measure. As stated in the preamble of the FY 2022 
IPPS/LTCH proposed rule (86 FR 25631 through 25634), we believe there 
are numerous certified health IT capabilities which can support bi-
directional exchange with a qualifying HIE.
    Comment: Several commenters asked that we clarify what types of 
audit evidence are expected for this measure.
    Response: Suggested documentation would include the following: A 
dated report or screenshot that documents successful receipt and 
transmission of patient data via the entity providing health 
information exchange services. Any such documentation should include 
evidence to support that it was generated for that eligible hospital or 
CAH's system (for example, identified by National Provider Identifier 
(NPI), CMS certification identification number, hospital name, etc.) 
and/or letter, email, or other documentation from the entity providing 
health information exchange services that confirm participation of the 
eligible hospital or CAH, the date of on-boarding, a description of 
services provided, and a description of exchange network participants 
(for example, number/type of participating providers). Other types of 
documentation could also include letter, email, or other documentation 
from the eligible hospital or CAH's CEHRT vendor confirming a 
connection between the hospital's CEHRT and an entity providing health 
information exchange services, the date of on-boarding, a description 
of services provided, and a description of exchange network 
participants (for example, number/type of participating providers) for 
the duration of the EHR reporting period.
    Comment: Many commenters requested that CMS define ``HIE''. One 
stated that the undefined term could exclude organizational models that 
might not be self-identified or otherwise identified as HIEs. The 
commenter believes that the measure should be expanded to ``HIEs, 
exchange frameworks, or other organizations focused on bidirectional 
health information exchange''. In defining HIEs, commenters also 
suggested that CMS consider cross-referencing the definition of HIEs 
and HINs established by ONC in 45 CFR 171.102.
    Response: We appreciate the commenters' request for clarification. 
The term ``HIE'' is intended to refer broadly to arrangements that 
facilitate the exchange of health information, and may include 
arrangements commonly denoted as exchange ``frameworks,'' ``networks,'' 
or using other terms. To satisfy the measure, an HIE or other exchange 
network must support eligible hospitals and CAHs by fulfilling the 
requirements of the attestation statements, to include providing the 
capabilities specified under attestation statement 1 to allow an 
eligible hospital or CAH to enable bi-directional exchange for all of 
an eligible hospital's or CAHs patient records, and meeting the 
standard specified under attestation statement 2 related to 
facilitating non-exclusionary exchange. The attestation statements 
proposed for the purposes of this bi-directional exchange measure are 
intended to reward providers for engaging in robust information 
exchange through HIEs with measure-specific characteristics, which we 
believe are beyond the minimum necessary for an individual or entity to 
meet the functional definition of HIN/HIE established by ONC in 45 CFR 
171.102. Thus, the attestations simply refer to the provider's 
participation in the HIE and a measure-specific set of capabilities 
from the HIE.
    Comment: A commenter requested that CMS clarify if ``HIE'' includes 
exchange frameworks and networks as defined in ONC's information 
blocking regulations and/or if ``HIE'' includes other organizations 
focused on bi-directional health information exchange. The commenter 
suggested that we need to work with ONC to ensure that CEHRT 
requirements for EHRs are aligned with the proposed new measure.
    Response: As stated previously, for purposes of this measure and 
its attestation statements, the term ``HIE'' broadly refers to 
arrangements that facilitate the exchange of health information, and 
may include arrangements commonly denoted as exchange ``frameworks,'' 
``networks,'' or using other terms. The attestation statements proposed 
for the purposes of this bi-directional exchange measure are intended 
to reward providers for engaging in robust information exchange through 
HIEs with measure-specific characteristics, which we believe are beyond 
the minimum necessary for an individual or entity to meet the 
functional definition of HIN/HIE established by ONC in 45 CFR 171.102. 
Thus, the attestations simply refer to the provider's participation in 
the HIE and a measure-specific set of capabilities from the HIE. 
Regarding alignment with ONC's Health IT Certification Program, as 
discussed in the proposed rule we believe that health IT certified to a 
number of certification criteria specified under the CEHRT definition 
could support exchange with an HIE under this measure (86 FR 25633).
    Comment: A commenter requested confirmation that the term ``all 
unique patient records stored or maintained in the EHR for these 
departments'' does not include a technical requirement to support 
receipt of a query for a C-CDA from an HIE. The commenter indicated 
there is no ONC certification requirement to support this type of 
query, so requiring it of health care providers before the technology 
is

[[Page 45470]]

widespread across the software development industry will create a very 
significant issue and threaten the ability of those providers to 
comply.
    Response: The first attestation statement, regarding enabling 
secure, bi-directional exchange, does not prescribe that query 
functionality must be used among HIE participants. The ability for 
CEHRT to send a C-CDA to an HIE for every patient encounter, transition 
or referral, and the ability to retrieve a C-CDA from an HIE when a 
patient arrives for an encounter, referral or transition, using CEHRT, 
would satisfy the functional requirements described in the 
attestations.
    Comment: A commenter encouraged CMS to continue to offer eligible 
hospitals and CAHs additional options and flexibility in meeting 
interoperability objectives. The commenter recommended that CMS work 
closely with ONC to ensure forward movement toward establishing the 
TEFCA. The commenter also recommended that the measure ``Engagement in 
Bi-directional Exchange Through Health Information Exchange (HIE)'' 
remain optional and that in addition to the measure's base 40 points, 
CMS consider bonus points for this measure.
    Response: We appreciate the suggestions and may consider them in 
future rulemaking.
    After consideration of the comments that we received, we are 
finalizing our proposal to add the HIE Bi-Directional Exchange Measure 
to the Medicare Promoting Interoperability Program as optional and 
worth 40 points beginning with the EHR reporting period in CY 2022. 
This measure will be an alternative to reporting on two existing HIE 
objective measures: The Support Electronic Referral Loops by Sending 
Health Information measure (42 CFR 495.24(e)(6)(ii)(A)) and the Support 
Electronic Referral Loops by Receiving and Reconciling Health 
Information measure (42 CFR 495.24(e)(6)(ii)(B)). Eligible hospitals 
and CAHs may either report the two existing measures and associated 
exclusions OR may choose to report the new measure. The HIE Bi-
Directional Exchange measure will be worth 40 points. In no case will 
more than 40 points total be earned for the HIE objective. The HIE Bi-
Directional Exchange measure will be reported by attestation and 
require a yes/no response. Eligible hospitals and CAHs will attest to 
the following:
     Participating in an HIE in order to enable secure, bi-
directional exchange of information to occur for all unique patients 
admitted to or discharged from the eligible hospital or CAH inpatient 
or emergency department (POS 21 or 23), and all unique patient records 
stored or maintained in the EHR for these departments, during the EHR 
reporting period in accordance with applicable law and policy.
     Participating in an HIE that is capable of exchanging 
information across a broad network of unaffiliated exchange partners 
including those using disparate EHRs, and not engaging in exclusionary 
behavior when determining exchange partners.
     Using the functions of CEHRT to support bi-directional 
exchange with an HIE.
    We are finalizing the corresponding changes to the regulation at 42 
CFR 495.24(e)(6)(ii)(C).
6. Modifications to the Public Health and Clinical Data Exchange 
Objective
a. Background
    In the FY 2019 IPPS/LTCH PPS final rule (83 FR 41637 through 41645, 
41665 through 41667), for the Public Health and Clinical Data Exchange 
Objective, we finalized that eligible hospitals and CAHs must report on 
any two measures of their choice from the following 6 measures: 
Syndromic Surveillance Reporting; Immunization Registry Reporting; 
Clinical Data Registry Reporting; Electronic Case Reporting; Public 
Health Registry Reporting; and Electronic Reportable Laboratory Result 
Reporting. We also finalized that an eligible hospital or CAH must 
submit a yes/no response for any two measures to earn 10 points for the 
objective. Failure to report on two measures or submitting a ``no'' 
response for a measure will earn a score of zero. In addition, there 
are exclusions available for each of the measures. If an exclusion is 
claimed for one measure, but the eligible hospital or CAH submits a 
``yes'' response for another measure, they would earn the 10 points for 
the Public Health and Clinical Data Exchange objective. If an eligible 
hospital or CAH claims exclusions for both measures they select to 
report on, the 10 points would be redistributed to the Provide Patients 
Electronic Access to Their Health Information measure under the 
Provider to Patient Exchange objective.
    The Medicare Promoting Interoperability Program for eligible 
hospitals and CAHs has been an important mechanism for encouraging 
healthcare data exchange for public health purposes through the Public 
Health and Clinical Data Exchange Objective. But in an attempt to 
reduce burden, we previously stated our intention to propose in future 
rulemaking to remove the Public Health and Clinical Data Exchange 
objective and measures no later than CY 2022 (83 FR 41665). Many 
commenters strongly opposed this potential policy change noting that 
the inclusion of this objective incentivizes health care providers to 
share data with public health agencies (83 FR 41666). In response to 
these comments, we stated that we would continue to monitor the data we 
compile specific to the public health reporting requirements and take 
the commenters' concerns into consideration related to future actions 
(83 FR 41667). Effective responses to public health events, such as the 
COVID-19 PHE, require fast, accurate exchange of data between health 
care providers and Federal, State, and local public health agencies 
(PHAs). Health care providers collect these data for patient care and 
PHAs need them to protect the public, whether to track an outbreak, 
initiate contact tracing, find gaps in vaccine coverage, or pinpoint 
the source of a foodborne outbreak.
    While our current approach has encouraged healthcare systems to 
stand up some of these capabilities, significant gaps remain, and in 
the absence of stronger incentives, it will be difficult to stand up 
the comprehensive data exchange needed for future public health 
response. Thus, we believe that a more assertive approach is needed.
b. Modifications to the Reporting Requirements for the Public Health 
and Clinical Data Exchange Objective
    At 86 FR 25634 through 25638 we proposed to require four of the 
measures associated with the Public Health and Clinical Data Exchange 
Objective, beginning with the EHR reporting period in CY 2022: 
Syndromic Surveillance Reporting; Immunization Registry Reporting; 
Electronic Case Reporting; and Electronic Reportable Laboratory Result 
Reporting. We proposed corresponding changes to the regulation text at 
42 CFR 495.24(e)(8)(ii). These four measures would put PHAs on better 
footing for future health threats and a long-term COVID-19 pandemic 
recovery by strengthening three important public health functions: (1) 
Early warning surveillance, (2) case surveillance, and (3) vaccine 
uptake. Requiring these measures would enable nationwide syndromic 
surveillance for early warning of emerging outbreaks and threats; 
automated case and laboratory reporting for fast public health 
response; and local and national visibility on immunization uptake so 
PHAs can tailor vaccine distribution strategies.
    Comment: Many commenters supported the proposed modifications

[[Page 45471]]

of this objective and concurred that the proposed modifications to the 
objective could better prepare the healthcare system for future health 
threats and long-term pandemic recovery by strengthening critical 
public health functions. Several commenters strongly supported raising 
the bar for Public Health reporting and updating the Public Health and 
Clinical Data Exchange Objective with regard to participating hospitals 
implementing Electronic Case Reporting, Electronic Reportable 
Laboratory Result Reporting, Syndromic Surveillance Reporting and 
Immunization Registry Reporting. These four measures all have mature 
and well-adopted standards and should represent the floor for all 
Public Health reporting.
    Response: We thank commenters for their support.
    Comment: Many commenters did not support requiring four measures in 
CY 2022. One stated that it is infeasible to require four measures for 
CY 2022 and does not accurately reflect current PHA data systems 
capabilities and the corresponding reporting landscape for hospitals 
and CAHs. Several commenters recommended that CMS use a flexible, 
staged approach to scoring the four measures it proposes to require. 
Many commenters supported an alternative approach that would require 
three of the four measures for CY 2022 and all four measures required 
in CY 2023. A few commenters encouraged CMS to provide sufficient lead 
time for implementation. A commenter stated that the proposed timeline 
is extremely burdensome. Several commenters mentioned the lack of 
public health reporting infrastructure with one stating that hospitals 
should not be penalized for the lack of critical public health 
reporting infrastructure, and those who make a good faith effort to 
report despite these challenges should be eligible to achieve 
meaningful use of EHR technology. Another commenter stated that 
hospitals and other healthcare facilities have been under tremendous 
stress from responding to the COVID-19 PHE, and this would divert 
resources to handle the increased reporting requirements so the 
commenter suggested delaying the requirement to add two additional 
measures until at least CY 2023. A few commenters indicated that many 
states are not ready to support this proposal because they rely on 
local networks instead of statewide registries.
    Response: Currently, PHAs in all 50 states accept electronic case 
report data, syndromic surveillance data, immunization registry data, 
and electronic lab report data. We understand that infrastructure gaps 
may exist and that different public health jurisdictions have different 
capabilities to process and use this data. The CDC is supporting PHAs 
to rapidly advance their capabilities through the Epidemiology and 
Laboratory Capacity cooperative agreement,\1364\ and through the Data 
Modernization Initiative.\1365\ Importantly, the measures themselves 
have exclusions that account for this varied landscape. Eligible 
hospitals and CAHs that could report to a PHA that has not declared 
readiness can still earn points towards the Public Health and Clinical 
Data Exchange Objective, if they are at option one of active engagement 
(completed registration to complete data), and ready to implement 
option two of active engagement (testing and validation) as soon as the 
PHA does declare readiness The three options are Active Engagement 
Option 1 includes completing registration to submit data, Active 
Engagement Option 2 includes testing and validation, and Active 
Engagement Option 3 includes production (80 FR 62818). Thus, eligible 
hospitals and CAHs will not be penalized for the lack of public health 
infrastructure. While hospitals and healthcare facilities are currently 
challenged by COVID-19, each of these reporting requirements provides 
public health with information that is essential to the public health 
response to COVID-19 and that will be essential for managing and 
responding to current and future health threats.
---------------------------------------------------------------------------

    \1364\ CDC--ELC Cooperative Agreement--DPEI--NCEZID.
    \1365\ Data Modernization Initiative [bond] CDC.
---------------------------------------------------------------------------

    Comment: A commenter encouraged CMS to update the specifications 
for each of the required registries to allow a provider to claim an 
exclusion if their state does not have, or cannot support, one or more 
of the four required registries: Electronic Case Reporting, Electronic 
Reportable Laboratory Result Reporting, Syndromic Surveillance 
Reporting, or Immunization Registry Reporting.
    Response: All four of the required measures include exclusions that 
address jurisdictions in which the PHA does not support the reporting 
type: Electronic Case Reporting, Electronic Reportable Laboratory 
Result Reporting, Syndromic Surveillance Reporting and Immunization 
Registry Reporting.
    Comment: A commenter urged CMS to work more closely with its 
Federal partners, including CDC and ONC, to align requirements for 
public health data collection and reporting and the requisite health 
information technology capabilities. Further the commenter stated that 
given the federated approach to public health in the U.S., CMS needs to 
consider the disparate state-level public health data collection and 
reporting requirements.
    Response: We thank the commenter for their support and agree that 
CMS, CDC, and ONC should work together closely to align the 
requirements for public health data collection and the requisite health 
information technology capabilities. The three agencies are already 
collaborating closely on these critical issues. We recognize that the 
CDC Data Modernization Initiative has efforts towards streamlining 
requirements as much as possible within the federated approach to 
public health.
    Comment: A commenter encouraged CMS to define ``active engagement'' 
in these measures to reflect that data sharing must be occurring rather 
than the hospital solely having the intent of sharing data or still 
conducting onboarding processes with public health authorities. This 
approach will also help replace inefficient paper-based mechanisms to 
give authorities, clinicians, and patients more complete, timely data.
    Response: We thank the commenter for their suggestion and may 
consider revising our active engagement definitions that we finalized 
in the EHR Incentive Program Stage 3 final rule (80 FR 62862 through 
62864) in future rulemaking.
    Comment: Some commenters stated that they will have to submit a 
hardship exception application for 2022 reporting because they cannot 
satisfy the proposed requirements.
    Response: We remind readers of the availability of exclusions for 
all of the required measures: Electronic Case Reporting, Electronic 
Reportable Laboratory Result Reporting, Syndromic Surveillance 
Reporting and Immunization Registry Reporting. In addition, eligible 
hospitals and CAHs may submit a hardship exception application. For 
more information, go to https://www.cms.gov/Regulations-and-Guidance/Legislation/EHRIncentivePrograms/PaymentAdj_Hardship.
    After consideration of the public comments we received, and as 
discussed in greater detail in the following sections of the preamble, 
we are finalizing our proposal to require four of the measures 
associated with the Public Health and Clinical Data Exchange Objective, 
beginning with the EHR reporting period in CY 2022: Syndromic 
Surveillance Reporting; Immunization Registry Reporting; Electronic 
Case Reporting; and Electronic Reportable Laboratory Result Reporting. 
We are also finalizing

[[Page 45472]]

corresponding changes to the regulation text at 42 CFR 
495.24(e)(8)(ii), as proposed.
(1) Syndromic Surveillance Reporting Measure
    Syndromic surveillance provides PHAs with a timely way to detect, 
understand, and monitor health events using data from EHRs in emergency 
departments (EDs) and urgent care centers. By tracking patient symptoms 
and discharge diagnoses, PHAs have a strong early warning system that 
allows them to identify, monitor, characterize, and respond to novel 
and continuing health events (for example, influenza, drug overdoses, 
vaping associated lung injuries, natural disasters, bioterrorism 
threats, and COVID-19) in near real time. Syndromic surveillance also 
provides real-time information for health events that are not supported 
by case reporting or laboratory reporting, such as injuries, suicidal 
ideation, non-reportable infectious diseases, and subtle health changes 
that are undiagnosed but can be detected by automated monitoring of 
chief complaint narratives and population-level trends. Syndromic 
surveillance relies on the secondary use of EHR data that supports 
delivery of care, enabling an efficient and cost-effective way to 
identify and characterize public health threats. The provision of these 
data requires no action from a health care provider, with data exchange 
automated from the EHR.
    Syndromic surveillance has been critical for responding to the 
COVID-19 PHE, enabling situational awareness for decision makers at 
local, state, and national levels. The National Syndromic Surveillance 
Program (NSSP) is the primary mechanism for national-level syndromic 
surveillance in the United States. State and local stakeholders are 
critical end users and facilitate onboarding of hospitals, 
administering access to data, and monitoring data quality. CDC provides 
tools and assistance to facilitate these functions (for example, 
message mapping guides, standards, onboarding assistance, and data 
quality resources). As of July 13, 2021, nearly 6,000 healthcare 
facilities covering 50 states and the District of Columbia contribute 
data to NSSP, representing approximately 70% of all U.S. nonfederal 
EDs.\1366\ With approximately 3 in 10 nonfederal hospitals not 
participating in NSSP, there remain major gaps in syndromic 
surveillance coverage, leaving blind spots in the ability of local, 
state, and Federal PHAs to adequately prepare for, and respond to, 
emerging local and regional public health events.
---------------------------------------------------------------------------

    \1366\ Overview of the National Syndromic Surveillance Program 
(NSSP), https://www.cdc.gov/nssp/overview.
---------------------------------------------------------------------------

    We proposed to make Syndromic Surveillance Reporting a required 
measure under the Public Health and Clinical Data Exchange Objective in 
the Medicare Promoting Interoperability Program (86 FR 25634 through 
25635) beginning with the EHR reporting period in CY 2022 to expand the 
coverage of syndromic surveillance to every region in the United 
States, help healthcare facilities and PHAs better prepare for emerging 
health events, and provide critical national early warning capabilities 
necessary for swift response and control of outbreaks, such as COVID-
19. Requiring eligible hospitals and CAHs to report on participation in 
syndromic surveillance is anticipated to significantly increase 
hospital engagement with a PHA to submit syndromic data, particularly 
from the ED. The public health benefit of syndromic surveillance would 
be strengthened as the proportion of participating hospitals increases, 
that is, as more hospitals participate, there are more comprehensive 
and timely data with fewer gaps and the capability itself becomes 
better at detecting emerging threats. ED data are often among the 
earliest indicators of emerging health threats. As demonstrated with 
the COVID-19 pandemic, surveillance data from EDs often foreshadow a 
rise in the percent of persons testing positive, case incidence and 
deaths, and can focus assessments on relevant populations, such as age 
groups, racial or ethnic groups, persons experiencing homelessness, 
persons with recent travel history, or recently vaccinated patients. 
Increased coverage would also improve coordination with PHAs, providing 
hospitals with the ability to respond to the emergence of new health 
threats and modify their treatments, preparedness planning, and 
facility staffing accordingly. Converting the Syndromic Surveillance 
Reporting measure from optional to required would not pose a 
significant burden on hospitals; as hospitals in all 50 states already 
participate in NSSP, the necessary infrastructure for wider adoption is 
already in place. More than two-thirds of nonfederal EDs participate in 
NSSP, demonstrating the feasibility of participation for a broad range 
of facilities and systems. Many nonparticipating facilities are part of 
larger health networks that have facilities already participating in 
NSSP.\1367\ CDC's robust technical assistance program through NSSP and 
the network of State and local stakeholders would provide direct 
assistance to address technical challenges. While setting up the 
syndromic surveillance capability requires some initial implementation 
effort from the hospital, there is no significant ongoing burden, as 
the EHR vendor sets up and maintains the data feed.
---------------------------------------------------------------------------

    \1367\ Overview of the National Syndromic Surveillance Program 
(NSSP), https://www.cdc.gov/nssp/overview.html.
---------------------------------------------------------------------------

    In addition, upon further review of the current description for the 
Syndromic Surveillance Reporting measure, we believe the reporting 
requirement should include ED data only. Data from the ED setting are 
the most important based on clinical severity and there is existing 
infrastructure among hospitals and PHAs to make this a feasible policy 
to implement. While urgent care data are valuable, adding a requirement 
for reporting in that setting at this time could impose unnecessary 
burden on some healthcare facilities and PHAs; however, the reporting 
of urgent care data remains an option and could be required at the 
discretion of the PHA.
    The current description of this measure is as follows: The eligible 
hospital or CAH is in active engagement with a public health agency to 
submit syndromic surveillance data from an urgent care setting. We 
proposed to change the setting for which data is required to be 
submitted from urgent care to the emergency department, place of 
service code 23, beginning with the EHR reporting period in CY 2022. We 
proposed to codify this change at 42 CFR 495.24(e)(8)(ii)(A). We also 
proposed that the first exclusion for this measure be modified to 
remove the reference to urgent care. The other two exclusions are 
unchanged. We proposed to modify the first exclusion at 42 CFR 
495.24(e)(8)(iii)(A)(1).
    Comment: Some commenters stated that there are major gaps in 
syndromic surveillance coverage such as inadequate state health 
information technology infrastructure and states being unable to 
receive electronic data and objected to making the measure required in 
2022.
    Response: While syndromic surveillance reporting is well-
established, gaps in coverage remain and are a key consideration for 
strengthening public health reporting requirements. In the context of 
the current COVID-19 pandemic response, a timely reduction of these 
coverage

[[Page 45473]]

gaps serves to enhance PHAs capacity to perform surveillance and guide 
response. Further, we remind readers of the availability of 3 
exclusions for this measure, two of which address gaps resulting from 
PHAs declaring that they are not yet capable of receiving syndromic 
surveillance data.
    Gaps in coverage for syndromic reporting can be due to hospitals 
not reporting to PHAs that are able to receive syndromic data, and gaps 
can also be created when PHAs are unable to receive syndromic data. 
Requiring this measure is expected to improve coverage in areas where 
PHAs attest readiness to receive syndromic data. Eligible hospitals and 
CAHs that would report to a PHA that has not declared readiness can 
still get credit towards the Medicare Promoting Interoperability 
Program as long as they are using active engagement option one and have 
registered with the PHA, but they must be ready move through the 
options for active engagement as soon as the PHA does declare 
readiness. Thus, eligible hospitals and CAHs will not be penalized for 
the lack of public health infrastructure.
    Comment: A commenter stated that they disagreed with CMS' statement 
that the proposed public health reporting requirements would not pose a 
significant burden on hospitals because, at the time, 49 states were 
participating in the National Syndromic Surveillance Program (NSSP). To 
the contrary the commenter believed that state participation in NSSP is 
not an indicator of providers' burdens and does not reflect the degree 
to which EHRs are capable of meeting CMS' public health reporting 
measures. The commenter asserted that given the federated approach to 
public health in the U.S., CMS needs to consider the disparate state-
level public health data collection and reporting requirements. The 
commenter stated that they are concerned about the proposal to not 
require syndromic reporting from urgent care given the importance of 
syndromic surveillance across settings. For example, many patients 
turned to alternative sites of care during the PHE out of concern for 
possible exposure to COVID-19 in emergency departments and other 
hospital settings. Finally, the commenter stated that public health 
surveillance was previously expected to improve due to increased use of 
EHRs and electronic exchange of health information; however, additional 
health information technology capabilities and applications are needed 
to further ensure syndromic surveillance data collection across 
multiple settings of care, reporting and exchange. The nation needs 
real-time data for syndromic surveillance, providing an upstream 
alternative to identifying cases before tests can detect them or 
patients are hospitalized. This includes collecting data across 
multiple settings of care, such as urgent care, clinics, physicians' 
offices, and telehealth visits.
    Response: Syndromic surveillance reporting is a well-established 
activity and the standardized message is well supported by EHR systems, 
with more than 266 Certified Health IT Modules offering the capability 
certified to the ``Transmission to public health agencies--syndromic 
surveillance'' certification criterion at 45 CFR 170.315(f)(2).
    With more than 3,000 non-Federal emergency departments in the 
United States already participating in the National Syndromic 
Surveillance Program and 45 states with more than 50% of their 
emergency department facilities already providing syndromic 
surveillance data in accordance with well-established data standards, 
adoption of this activity is strong. However, the remaining gaps in 
coverage limit public health's ability to detect and monitor health 
events in the community. This was particularly evident during the 
COVID-19 pandemic, when syndromic surveillance data from emergency 
departments provided an important early indicator of population-level 
COVID-19 activity. Long-term, the goal is to expand syndromic 
surveillance capabilities toward a broad array of clinical settings, 
and some PHAs already incorporate urgent care data into their 
surveillance. However, hospital emergency departments remain a core 
focus and offer broad representation of patients with acute or severe 
illness presenting to urgent care facilities. This revision to this 
measure does not reduce the ability of PHAs to receive syndromic data 
from urgent care facilities.
    Comment: A commenter stated that the Syndromic Surveillance 
Reporting measure should include more than just the emergency 
department setting. In doing so, public health data would be more 
comprehensive, as most of the population would use a primary care or 
urgent care setting to address the potential spread of communicable 
diseases. Another disagreed with the removal of urgent care settings 
from Syndromic Surveillance reporting as this setting is a data 
critical source and should continue to be included.
    Response: Long term, NSSP intends to expand syndromic surveillance 
capabilities toward a broader array of clinical care settings, and some 
PHAs have begun to accept data from settings such as urgent care and 
primary care. However, with limited public health resources, hospital 
emergency department data offers broad representation and national 
coverage, and remains a core focus for syndromic surveillance. As 
finalized, this measure does not reduce the ability of PHAs to receive, 
nor require, data from urgent care facilities, primary care facilities, 
or other clinical settings.
    After consideration of the public comments we received, we are 
finalizing our proposal to make Syndromic Surveillance Reporting a 
required measure under the Public Health and Clinical Data Exchange 
Objective in the Medicare Promoting Interoperability Program beginning 
with the EHR reporting period in CY 2022. We are finalizing our 
proposal to change the setting for which data is required to be 
submitted from urgent care to the emergency department, place of 
service code 23, beginning with the EHR reporting period in CY 2022. We 
are codifying this change as proposed at 42 CFR 495.24(e)(8)(ii)(A). We 
are also finalizing that the first exclusion for this measure is 
modified to remove the reference to urgent care. The other two 
exclusions are unchanged. We are modifying the first exclusion as 
proposed at 42 CFR 495.24(e)(8)(iii)(A)(1).
(2) Immunization Registry Reporting Measure
    Immunizations are considered one of the ten great public health 
achievements and have resulted in declines in cases, hospitalizations, 
deaths, and health care costs associated with vaccine preventable 
diseases.\1368\ The benefits and value of immunizations are realized 
when public policy, health systems, and community-based intervention 
efforts are working in coordination. Ensuring the coordination of these 
efforts can achieve high immunization coverage is dependent on the 
availability of timely, accurate, and complete information on 
vaccinations received by individuals in a population.
---------------------------------------------------------------------------

    \1368\ Ten Great Public Health Achievements-United States, 
2001--2010 (cdc.gov)
---------------------------------------------------------------------------

    Immunization registries (also called immunization information 
systems or IIS) are powerful tools that allow collaboration between 
vaccine providers and public health agencies and enable coordination of 
population-based interventions. Immunization registries are 
confidential, population-based, computerized systems that record all 
vaccination doses administered by participating health care providers 
for individuals residing within a particular

[[Page 45474]]

jurisdiction. At the point of clinical care, an immunization registry 
can provide consolidated immunization histories to assist vaccine 
providers in determining appropriate patient vaccinations. At the 
population level, immunization registries provide data on vaccination 
coverage assessment and program operations and in guiding public health 
action to improve vaccination rates.
    Currently, 50 states, the District of Columbia, 8 island 
territories, and 3 cities (New York City, Philadelphia, and San Diego) 
operate an immunization registry. CDC provides technical assistance and 
nationwide leadership to all State immunization registries to ensure 
the optimal use of immunization registries for determining vaccination 
coverage at local, State, and national levels. Immunization registries 
already have connections in place to capture administered doses in 
real-time for a substantial portion of the population, a process 
accelerated over the last eight years by the Promoting Interoperability 
Programs. According to data from the most recent CDC IIS Annual Report 
(2019) available, immunization registries currently hold demographics 
and immunization data on 95% of children 0-6 years, 82% of adolescents, 
and 60% of adults.\1369\ While each State Immunization registry 
currently coordinates with health care providers and EHR systems to 
achieve interoperability and facilitate immunization reporting, varying 
State reporting policies limit the completeness and timeliness of 
records in immunization registries and the optimal use of immunization 
registries for determining vaccination coverage.
---------------------------------------------------------------------------

    \1369\ https://www.cdc.gov/vaccines/programs/iis/annual-report-iisar/2019-data.html.
---------------------------------------------------------------------------

    We proposed to make the Immunization Registry Reporting measure a 
required measure under the Public Health and Clinical Data Exchange 
objective of the Medicare Promoting Interoperability Program beginning 
with the EHR reporting period in CY 2022 (86 FR 25635 through 25636) as 
it is critical for understanding vaccination coverage both at the 
jurisdiction level and nationwide and identifying where additional 
vaccination efforts are needed. Making standardized reporting to an 
immunization registry a required measure would provide an immediate 
benefit by increasing the COVID-19 vaccination records reported to 
these systems. Making the measure required would also improve the data 
quality of records in immunization registries and facilitate use of 
immunization registries for clinical decision support and tracking of 
vaccine administration and distribution.
    We believe that making the Immunization Registry Reporting measure 
required, compared to the current option that allows a provider to 
choose this measure as one of two among six measures, would increase 
the reporting of immunization data by health care providers to public 
health agencies. Making the measure required is also critical for the 
COVID-19 vaccination response because it would provide a better view of 
the vaccines administered and distributed at national, State and local 
levels. This is a function that immunization registries currently 
provide for all public vaccines, but would be particularly important 
for COVID-19 vaccines. In addition to the COVID-19 vaccination 
response, there is an equally important need for routine vaccination 
coverage to increase. More complete data in immunization registries as 
a result of the required measure would also optimize the use of 
immunization registries to determine who has not been vaccinated, 
pockets of under vaccination, and identifying where interventions 
should be focused for routine and emergency response vaccines. 
Requiring the measure would reduce the regulatory and administrative 
burden health care providers experience when exchanging information 
with immunization registries.
    We did not propose any changes to the description of the measure 
including any of the exclusions that we established at 42 CFR 
495.24(e)(8)(iii)(B).
    Comment: Many commenters supported the proposal to make the 
Immunization Registry Reporting measure required. Some commenters 
stated that vaccines are arguably the most critical tool to fight 
COVID-19 and any future pandemics. Others stated that knowledge of 
immunization status helps to inform diagnostic testing and diagnosis. 
With initial access to COVID-19 vaccination, many individuals received 
vaccine in non-traditional settings where their providers may not have 
access to the documentation. Several other commenters stated that 
routine immunizations have been deferred and/or missed altogether 
during the pandemic, and this shift to require the Immunization 
Registry Reporting measure would support stronger surveillance and 
awareness of immunization rates for all vaccines. Embedding 
immunization data exchange throughout public and private health care 
will help to ensure informed clinical decisions and data driven 
population health well into the future. The commenter stated that the 
broad availability of immunization data through real-time Electronic 
Health Record (EHR)-IIS query significantly lowers the burden (and 
cost) to providers in accessing immunization records and forecasts at 
the point of care. This functionality to query the IIS from within an 
EHR and receive back a consolidated record and forecast for 
immunizations due is currently available to health care providers in 
the vast majority of states across the country and is in the process of 
being developed in the remaining locations. This accelerated adoption 
of query functions across EHRs and IIS is due in large part to 
incentives provided through Meaningful Use/Promoting Interoperability 
Program. A commenter stated that immunization registries are critical 
for understanding the comprehensive view of a patient's immunization 
status, which is essential for health care providers to make 
recommendations for require vaccinations. Increasing use of 
immunization registries is one tactic to help increase immunization 
rates and improve population health.
    Response: We appreciate the support for requiring this measure.
    Comment: A commenter stated that immunization registries are 
critical for understanding the comprehensive view of a patient's 
immunization status, which is essential for providers to make 
recommendations for require vaccinations. Increasing use of 
immunization registries is one tactic to help increase immunization 
rates and improve population health.
    Response: We thank the commenters for their support.
    Comment: A commenter suggested that we should ensure there are 
exclusions available if there is not a state immunization registry 
available for a provider to report to. Additionally, CMS should survey 
the state immunization registries to determine if there is readiness at 
the state level to conduct this level of exchange.
    Response: The commenter is correct that the exclusions that we 
established at 42 CFR 495.24(e)(8)(iii)(B) remain available. As we have 
stated previously, currently, 50 states, the District of Columbia, 8 
island territories, and 3 cities (New York City, Philadelphia, and San 
Diego) operate an immunization registry.
    After consideration of the public comments we received, we are 
finalizing our proposal to make the Immunization Registry Reporting 
measure a required measure under the

[[Page 45475]]

Public Health and Clinical Data Exchange objective of the Medicare 
Promoting Interoperability Program beginning with the EHR reporting 
period in CY 2022.
(3) Electronic Case Reporting
    Healthcare providers are required by State law to report certain 
diseases and conditions, a process called case reporting, which 
provides PHAs with data on approximately 120 diseases and conditions of 
public health significance.\1370\ Case reporting is a vital and long-
standing tool that PHAs use to prevent the spread of infectious 
diseases. Case reporting serves as early notification to PHAs for 
potential outbreaks, and includes information that enables PHAs to 
start contact tracing and other prevention measures. Case reports also 
include critical clinical information that would not be included in 
syndromic surveillance or laboratory reporting, and can help to 
illuminate the impact of comorbidities, treatments, and variable access 
to care. Information from the case reports can be used to further work 
on social determinants of health and ensure equal access to 
preventative care across populations. Electronic case reporting is the 
automated, real-time, bi-directional exchange of case report 
information between EHRs and PHAs. Electronic case reporting uses 
standard codes to trigger the transfer of relevant clinical data to 
PHAs for case investigation and follow-up. As of March 2021, most 
states do not require electronic submission of case reports as part of 
their regulations and case reporting often occurs through outdated 
manual methods (for example, fax, email, or phone), which results in 
delays, underreporting, and incomplete or inaccurate case data. Manual 
case reporting also imposes burdens on health care providers, taking 
staff time away from patients to submit case reports and comply with 
State reporting requirements. Electronic case reporting allows health 
care providers to fulfill mandated public health reporting requirements 
without imposing additional burden and disrupting the clinical 
workflow. This automated data exchange facilitates faster and more 
efficient disease tracking, case management, and contact tracing. 
Electronic case reporting provides more timely and complete data than 
manual reporting, including data on demographics, comorbidities, 
immunizations, medications, occupation, and other treatments.
---------------------------------------------------------------------------

    \1370\ CSTE State Reportable Condition Assessment page: https://www.cste.org/page/SRCA.
---------------------------------------------------------------------------

    Recent efforts by the CDC have sought to significantly improve the 
effectiveness of electronic case reporting through eCR. Now, a 
strategic initiative that allows for rapid adoption and implementation 
of electronic case reporting for COVID-19 (https://www.cdc.gov/coronavirus/2019-ncov/hcp/electronic-case-reporting.html). As part of 
this initiative, CDC and its partners have developed an eCR Now 
FHIR[supreg] Application to establish electronic case reporting 
capability in EHR systems using an application programming interface 
(API). The initiative also supports an electronic case reporting 
infrastructure that is helping to advance interoperability. This 
infrastructure supports sending electronic case reports to a shared 
service platform managed by the Association of Public Health 
Laboratories (APHL (https://www.aphl.org/programs/informatics/pages/aims_platform.aspx), and not directly to a PHA, which means that any 
health care provider that has implemented the specifications for eCR 
Now and connected to the APHL system also has a connection with every 
State PHA, many large local health departments, and some territories 
that are also connected.
    This promotes nationwide interoperability and increases the 
availability of data for patients who may be traveling or spending time 
away from their home State. For example, if a patient is a resident of 
one State but seeks care in another State, this infrastructure will 
automatically route the case report to both states that would have 
jurisdiction over this report. This increases inter-jurisdictional 
reporting, allowing for more seamless case investigation at the 
national level.
    As a result of the CDC effort to scale up eCR Now for COVID-19, all 
50 states, the District of Columbia, Puerto Rico and 12 large local 
jurisdictions have connected to the eCR shared services platform and 
are currently receiving electronic case reports, with more than 8,800 
healthcare facilities on board and 8.9 million reports for COVID-19 
received by PHAs as of July 21, 2021.\1371\ The eCR infrastructure is 
designed to rapidly scale for PHEs, such as COVID-19, but it is also 
enabled to currently support data transmission for 108 reportable 
conditions. While these are significant advancements in the adoption of 
electronic case reporting by healthcare providers, an accompanying 
policy incentive is needed to encourage continued adoption of 
electronic case reporting by health care providers at a national level.
---------------------------------------------------------------------------

    \1371\ Healthcare Facilities in Production for COVID-19 
Electronic Case Reporting [verbar] CDC.
---------------------------------------------------------------------------

    We believe the uneven adoption of electronic case reporting creates 
a public health vulnerability. We proposed to make the Electronic Case 
Reporting measure a required measure under the Public Health and 
Clinical Data Exchange objective of the Medicare Promoting 
Interoperability Program beginning with the EHR reporting period in CY 
2022 (86 FR 25636 through 25637). We believe making this a required 
measure would accelerate development of electronic case reporting 
capabilities in EHR systems, reduce healthcare administrative burden of 
complying with State-mandated disease reporting requirements, provide 
regulatory clarity for EHR vendors, and improve the timeliness, 
completeness, and utility of case report data for PHAs.
    We believe that requiring the Electronic Case Reporting measure 
would be feasible and beneficial for eligible hospitals and CAHs. This 
change would encourage EHR vendors to make electronic case reporting 
available to their customers, which would make adoption of this 
capability relatively straightforward for eligible hospitals and CAH. 
As described in the EHR Incentive Program-Stage 3 and Modifications to 
Meaningful Use in 2015 through 2017 final rule (80 FR 62888), for 
purposes of this measure, eligible hospitals and CAHs must use a health 
IT module certified to the ``Transmission to public health agencies--
electronic case reporting'' certification criterion at 45 CFR 
170.315(f)(5). This certification criterion relates to how the health 
IT uses structured data within an EHR to trigger or indicate the 
generation of an electronic initial case report (eICR).\1372\ Eligible 
hospitals and CAHs may then transmit the report in the manner specified 
by the case reporting requirements of the entity to which they are 
transmitting a report. In addition, ONC clarified earlier this year 
that in order for a Certified Health IT Developer to be certified to 45 
CFR 170.315(f)(5), the developer may provide documentation of 
electronic case reporting implementation using the eCR Now FHIR 
application implementation guide to its ONC-Authorized Certification 
Body.
---------------------------------------------------------------------------

    \1372\ For more information about this certification criterion, 
please see the Certification Companion Guide at https://www.healthit.gov/test-method/transmission-public-health-agencies-electronic-case-reporting.
---------------------------------------------------------------------------

    We believe that requiring the Electronic Case Reporting measure

[[Page 45476]]

would provide certainty to Certified Health IT Developers and 
facilitate an organized and industry-wide rollout of electronic case 
reporting capabilities. This change would encourage EHR vendors to make 
electronic case reporting available to their customers, which would 
make adoption of this capability relatively straightforward for 
eligible hospitals and CAHs.
    We did not propose any changes to the description of the Electronic 
Case Reporting measure and the exclusions that we established at 42 CFR 
495.24(e)(8)(iii)(C) will remain available.
    Comment: Several commenters supported making the Electronic Case 
Reporting measure required for eligible hospitals and CAHs. The 
commenters believe this change has the potential to revolutionize the 
way local health departments investigate reportable communicable 
diseases. According to the commenter, under the current state, a 
significant amount of investigators' time is spent obtaining 
information already available in the patient's EHR, including critical 
data such as treatment information, hospitalization status, or race and 
ethnicity. Incentivizing electronic case reporting has the potential to 
eliminate these tedious and time-consuming tasks, both for 
investigators as well as hospital staff, such as infection 
preventionists, who typically supply this information. As a result, 
these skilled employees would be able to rededicate this time to 
actively preventing disease transmission, through activities such as 
contact tracing, thereby making our communities (and in the case of 
infection preventionists, health care facilities) safer places. Another 
commenter stated that Electronic Reportable Laboratory Result Reporting 
measure data is automatically processed into our disease surveillance 
system and is the primary method for all our notifiable conditions work 
and they supported making it a requirement. A commenter stated that the 
phenomenal success of the eCR Now program in the area of electronic 
Case Reporting has highlighted how focused support can rapidly expand 
electronic Public Health reporting. Additional programs with a similar 
approach focused on other Public Health programs could dramatically 
expand reporting in areas such as Newborn Screening, Vital Records and 
Birth Defect Reporting. As well, eCR Now is an excellent example of the 
role that systems can play in reducing the implementation burden for 
Public Health, healthcare organizations and HIT Vendors. The commenter 
strongly supported the development of additional infrastructure to 
promote interoperability in other Public Health program areas.
    Response: We appreciate the commenters support for this proposal.
    Comment: A commenter stated their belief that technology adoption 
for electronic case reporting to various agencies continues to mature, 
and recommended delaying a requirement to specifically participate in 
electronic case reporting for one more year. Another commenter stated 
that although their organization was one of the first adopters of 
electronic case reporting, they will need an extra year to implement 
certified health IT for electronic case reporting after the conclusion 
of the COVID-19 PHE. This commenter stated that the hardship lies 
disproportionately heavily on small, rural hospitals where technical 
staff are working under competing priorities. The commenter also stated 
the vendor-dependent coordination to local code mapping required for 
setting trigger codes, which takes coordination and time.
    Response: Currently, all 50 states, DC, Puerto Rico, and several 
local PHAs accept data from electronic case reporting for COVID-19. We 
recognize that different public health jurisdictions have different 
capabilities to process and use this data; CDC is supporting PHAs to 
rapidly advance their capabilities. We note that CMS has included 
Electronic Case Reporting as an optional measure for hospitals and CAHs 
since 2015. Additionally, ONC has supported certified functionality for 
electronic case reporting through the ONC Certification Program for the 
same period. More recently, ONC clarified that Certified Health IT 
Developers' can certify to the criterion, ``Transmission to public 
health agencies--electronic case reporting'' at 170.315(f)(5) by 
providing documentation of support for eCR Now implementation. Given 
the need for case data by PHAs and the clear technology pathways for 
Certified Health IT Developers to support their eligible hospital and 
CAH clients, the proposed timeline of CY22 for implementation is both 
needed and feasible.
    We reiterate that, public health has an urgent need for this data 
in order to respond to routine outbreaks and to be prepared for 
emergency response. We note that a number of developments in recent 
years have created opportunities to pursue electronic case reporting, 
such as the eICR CDA standard, which was first published in 2016, and 
the expanded architecture efforts for electronic case reporting 
implemented since 2018, giving EHR vendors and other stakeholders a 
variety of options for technology development.
    Comment: A commenter suggested that we need to ensure FHIR APIs and 
electronic case reporting is in place prior to requiring the Electronic 
Case Reporting measure. As a result, the commenter recommended delaying 
making this requirement mandatory until CY2023.
    Response: ONC's 21st Century Cures Act final rule updated 
certification criteria in the ONC Health IT Certification program 
related to the use of APIs. The API certification criteria at 45 CFR 
Sec.  170.315(g)(10), as finalized in the 21st Century Cures Act final 
rule, requires the use of Health Level 7 (HL7[supreg]) Fast Healthcare 
Interoperability Resources (FHIR[supreg]) standard Release 4. Health IT 
developers must make certified technology meeting the new certification 
criteria available to customers by December 31, 2022.
    Given the critical nature of getting to nationwide implementation 
of electronic case reporting, Certified Health IT Developers have 
options for how they support hospitals or CAHs to meet the 90-day EHR 
reporting period in 2022. For Certified Health IT Developers not 
already supporting electronic case reporting, these capabilities can be 
certified to the certification criterion for ``Transmission to public 
health agencies--electronic case reporting'' at Sec.  170.315(f)(5) by 
providing their ONC-Authorized Certification Body documentation that 
sufficiently describes how the Health IT Module meets the functional 
requirements of the criterion and/or documentation of electronic case 
reporting implementation using the eCR Now FHIR application and the 
ability to meet paragraph (i) of this criterion. Certified Health IT 
Developers are encouraged to visit the 2015 Edition Cures Update 
Certification Companion Guide page (https://www.healthit.gov/test-method/transmission-public-health-agencies-electronic-case-reporting) 
for more information. With appropriate prioritization by Health IT 
Developers, implementation of eCR capabilities is achievable.
    Comment: A commenter stated that based on discussions with their 
exchange partners, development of electronic case reporting is still in 
its infancy and more time is needed before this option should be 
required. The commenter respectfully requested the Electronic Case 
Reporting measure not be required for 2022.
    Response: The Electronic Case Reporting measure has been an 
optional measure in the program since 2015, with corresponding 
certification

[[Page 45477]]

requirements from ONC. In addition, the eICR CDA standard was first 
published in 2016, and the developments in architecture have been 
implemented since 2018. During COVID-19, there have been rapid advances 
in support for electronic case reporting from national exchange 
networks. We acknowledge the commenter's point that electronic case 
reporting does not have nationwide adoption, which further serves to 
indicate the importance of a updating program requirements to further 
incentivize the adoption and use of this capability. Electronic case 
reporting is a long-standing need for public health and rapid 
implementation by healthcare organizations will lead to a more prepared 
data infrastructure for routine and emergency public health 
surveillance. We are committed to improving data exchange between 
public health and healthcare, and this final policy will promote rapid 
adoption of electronic case reporting to ensure that there is a more 
scalable infrastructure in place prior to the next pandemic or 
emergency response. Given the urgencies of the need for case data by 
PHAs and the clear need for improved bi-directional information flow 
between public health and healthcare, a timeline of 2022 is necessary 
for implementation by hospitals and CAHs.
    Comment: An EHR vendor commented that all their products do not 
currently have the electronic case reporting functionality and 
suggested the following options: 1. Delay requiring the Electronic Case 
Reporting measure to the 2023 reporting year, 2. Add an exclusion for 
the 2022 reporting year for the clients of any EHR vendor that must 
complete software development work to provide the ONC certified 
Electronic Case Reporting functionality, OR 3. Make the Electronic Case 
Reporting requirement non-mandatory for 2022.
    Response: There are exclusions for the Electronic Case Reporting 
measure that are based on the capability of PHAs. The need for 
electronic case reporting capability in EHR products has been long 
standing, and the need for PHAs to receive critical data for public 
health investigations has never been more apparent than now. As shown 
by the COVID-19 pandemic, where PHAs received significant missing and 
incomplete data from health care providers, an interoperable and 
scalable data stream from health care providers to public health is 
necessary. Many healthcare organizations had increased costs and 
challenges manually reporting data to public health, and the 
variability of formats and completeness posed a significant challenge 
in the nation's ability to respond to COVID-19. Further delaying the 
implementation of electronic case reporting capabilities will hinder 
the nation's preparedness for future emergency response.
    After consideration of the public comments we received, we are 
finalizing our proposal to make the Electronic Case Reporting measure a 
required measure under the Public Health and Clinical Data Exchange 
objective of the Medicare Promoting Interoperability Program beginning 
with the EHR reporting period in CY 2022.
(4) Electronic Reportable Laboratory Result Reporting Measure
    State laws and regulations require laboratories to report certain 
diseases and conditions identified by testing to State and local PHAs. 
Electronic laboratory reporting (ELR) is the automated transmission of 
reports from laboratories to State and local PHAs. ELR produces faster 
and more complete information than manual reporting, reduces the burden 
of submission to PHAs, and eliminates opportunities for data entry 
error. ELR facilitates efficient case investigation, contact tracing, 
identification of hot spots, and other core public health functions. 
Because ELR requires essential fields, PHAs are less likely to request 
follow up information when receiving reports via ELR feeds, further 
reducing burden on laboratories.
    Prior to the COVID-19 pandemic, more than 90% of laboratory reports 
sent to PHAs were submitted via ELR; the bulk of this reporting came 
from commercial laboratories. Hospital laboratories were less likely to 
utilize ELR data feeds relative to commercial laboratories, relying on 
other means to report results. The COVID-19 pandemic posed a tremendous 
challenge to the nation's laboratory and testing infrastructure, and 
rates of ELR to PHAs declined as COVID-19 testing increased, a 
multitude of tests (for example, point-of-care tests) entered the 
market, and non-traditional testing sites (for example, drive thru 
testing sites) where ELR is not available were utilized. Throughout the 
pandemic, the subset of hospital laboratories, while still a relatively 
small portion of overall testing volume, continued to lag in ELR 
implementation relative to larger commercial and clinical laboratories. 
A CDC-Association of Public Health Laboratories (APHL) collaboration 
has enabled the reporting of COVID-19 laboratory data through the APHL 
Informatics Messaging Services (AIMS) platform. Using AIMS, PHAs can 
submit essential data to CDC for detailed analysis, visualization, and 
surveillance, providing a national snapshot of the testing landscape 
and informing Federal response efforts. Section 18115 of the 
Coronavirus Aid, Relief, and Economic Security (CARES) Act and HHS 
implementing guidance require all laboratories conducting testing for 
SARS-CoV-2 to report results to a State or local public health agency 
(which then report these data to CDC). The HHS implementing guidance 
allows for reporting using multiple potential methods, including ELR. 
All State PHAs are capable of and are receiving ELR for notifiable 
conditions.
    We proposed at 86 FR 25637 to make the Electronic Reportable 
Laboratory Result Reporting measure a required measure under the Public 
Health and Clinical Data Exchange objective of the Medicare Promoting 
Interoperability Program beginning with the EHR reporting period in CY 
2022. We believe that making this measure required would spur hospital 
laboratories to adopt this capability, increase the timeliness and 
completeness of laboratory reporting to PHAs, strengthen the 
effectiveness of prevention and control measures, reduce the burden of 
reporting by laboratory staff, and aid in laboratory compliance with 
the requirements of section 18115 of the CARES Act as well as future 
PHEs. Requiring the Electronic Reportable Laboratory Result Reporting 
measure would incentivize the minority of hospital laboratories that 
have not adopted ELR to upgrade to this essential capability. With the 
availability of the APHL AIMS platform, HIEs, and other mechanisms, 
there is a diversity of options for eligible hospitals and CAHs to 
establish an ELR channel with a PHA to feasibly implement this 
requirement. In addition, CDC-provided ELR technical assistance is also 
available, further reducing implementation barriers.
    We did not propose to change the description of the Electronic 
Reportable Laboratory Result Reporting measure and the exclusions that 
we established at 42 CFR 495.24(e)(8)(iii)(F) will remain available.
    Comment: A commenter stated that during the COVID-19 pandemic, 
hospital clinical laboratories have cited problems collecting required 
data elements for reporting electronically to public health agencies. 
Electronic submission of laboratory results to public health agencies 
is not currently mandated at the Federal level, and states vary on 
whether electronic submission is required and on the format of the 
electronic submission. The commenter stated each interface with an EHR 
or with an individual state's public

[[Page 45478]]

health agency is costly ($40,000 to $70,000 on average per interface), 
and each change made to an interface also has associated cost. Further 
complicating the matter is the variability by state as to who is 
required to do the reporting, and the commenter indicated this will 
also need to be clarified if it is going to be standardized at a 
national level. To alleviate reporting burdens on clinical laboratories 
and state public health agencies, the commenter recommended national 
standardized reporting requirements and formats in which clinical 
laboratories would be required to report only to the state in which the 
laboratory is located, and the same national standards could be used by 
state public health agencies to report data on out-of-state patients to 
the state public health agency of the patient's residency. The 
commenter believes there is too much variability and obstacles in the 
current reporting structure to make this a required measure for 2022.
    Response: We thank the commenter for their thoughts and we 
reiterate our position that making this measure required would spur 
hospital laboratories to adopt this capability, increase the timeliness 
and completeness of laboratory reporting to PHAs, strengthen the 
effectiveness of prevention and control measures, reduce the burden of 
reporting by laboratory staff, and aid in laboratory compliance with 
the requirements of section 18115 of the CARES Act as well as future 
PHEs. While we understand there are inconsistencies in reporting 
requirements depending on the jurisdiction, there are nearly 130 
Modules certified to 170.315(f)(3) using HL7 2.5.1. Implementation 
specifications (HL7 Version 2.5.1 Implementation Guide: Electronic 
Laboratory Reporting to Public Health, Release 1 (US Realm)). CMS will 
continue to work with both the CDC and ONC to refine standards and 
address barriers to reporting, including ways to report once and 
redirect the information more seamlessly where needed.
    After consideration of the public comments we received, we are 
finalizing our proposal to make the Electronic Reportable Laboratory 
Result Reporting measure a required measure under the Public Health and 
Clinical Data Exchange objective of the Medicare Promoting 
Interoperability Program beginning with the EHR reporting period in CY 
2022.
7. Scoring of the Public Health and Clinical Data Exchange Objective
    We proposed that, beginning with the EHR reporting period in CY 
2022, an eligible hospital or CAH would receive 10 points for the 
Public Health and Clinical Data Exchange objective if they report a 
``yes'' response for each of the following 4 required measures: 
Syndromic Surveillance Reporting; Immunization Registry Reporting; 
Electronic Case Reporting; and Electronic Reportable Laboratory Result 
Reporting (86 FR 25638). In the event an eligible hospital or CAH is 
able to claim an exclusion for three or fewer of these four required 
measures, we proposed they would receive 10 points for the objective if 
they report a ``yes'' response for one or more of these measures and 
claim applicable exclusions for which they qualify for the remaining 
measures. If the eligible hospital or CAH fails to report on any one of 
the four measures required for this objective or reports a ``no'' 
response for one or more of these measures, we proposed that the 
eligible hospital or CAH would receive a score of zero for the Public 
Health and Clinical Data Exchange objective, and a total score of zero 
for the Medicare Promoting Interoperability Program. If an eligible 
hospital or CAH claims applicable exclusions for which they qualify for 
all four required measures, we proposed to redistribute the points 
associated with the objective to the Provider to Patient Exchange 
objective. We proposed corresponding changes to 42 CFR 495.24(e)(8)(ii) 
and (iii) to reflect these proposals.
    We proposed to retain the Public Health Registry Reporting and 
Clinical Data Registry Reporting measures and to make them optional and 
available for bonus points beginning with the EHR reporting period in 
CY 2022. We proposed an eligible hospital or CAH may earn a maximum of 
5 bonus points if they report a ``yes'' response for either the Public 
Health Registry Reporting measure OR the Clinical Data Registry 
Reporting measure. We proposed to further modify 42 CFR 
495.24(e)(8)(ii) to add: Eligible hospitals and CAHs could receive a 
bonus of 5 points for this objective if they report the measures 
specified under 42 CFR 495.24(e)(8)(iii)(D) or (E).
    In connection with our proposals to make these measures optional, 
we proposed the three exclusions that we established for each measure 
would no longer be available beginning with the EHR reporting period in 
2022. For the Public Health Registry Reporting measure, we proposed to 
revise 42 CFR 495.24(e)(8)(iii)(D), and for the Clinical Data Registry 
Reporting measure we proposed to revise 42 CFR 495.24(e)(8)(iii)(E).
    Comment: Many commenters supported our proposal to allocate five 
bonus points to eligible hospitals and CAHs that report either the 
Public Health Registry Reporting or the Clinical Data Registry 
Reporting measures.
    Response: We appreciate the commenters support for this proposal.
    Comment: A commenter recommended keeping the public health registry 
as one of the required registry measures, or, allowing the public 
health registry measure to be an option in the same category as the 
four proposed required registries (syndromic surveillance, immunization 
registry, electronic case reporting, and electronic reportable 
laboratory result). This will help rural and critical access hospitals 
meet requirements under the public health and clinical data exchange 
objective. While the commenter agreed with CMS on the critical 
importance of reporting to public health agencies to assist with 
responding to or preventing public health emergencies, the commenter is 
concerned the proposed approach will relegate clinical registry 
reporting to one of secondary importance. Hospitals have limited 
capacity to respond to the various government reporting requirements, 
and we fear some facilities may forego or drop optional reporting to 
clinical registries to meet these new public health reporting mandate. 
Clinical registries serve as the backbone for quality improvement in 
many medical specialties, and are critical to addressing the most 
common and high cost chronic conditions from which Medicare 
beneficiaries suffer, both during public health emergencies and normal 
times. As such, it is imperative that CMS ensure robust clinical 
registry reporting. As an alternative to CMS' proposal, the commenter 
recommended adding Clinical Data Registry Reporting measure to the four 
other types of required registry reporting measures, and drop the 
optional Public Health Registry Reporting measure since the key aspects 
of addressing any public health emergency are already covered through 
syndromic surveillance, electronic case reporting, electronic lab 
result reporting and immunizations.
    Response: We do not agree that the public health registry and 
clinical data registry should be included in under the four required 
measures to be reported on. We considered the measures that were most 
likely to improve our readiness for future health threats. While we 
understand the concerns expressed by the commenters, we believe that 
awarding bonus points for the reporting of the Public Health Registry 
Reporting measure or the Clinical Data Registry Reporting measure will 
incentivize hospitals to

[[Page 45479]]

continue to submit data to these registries. Further we believe that 
once hospitals are actively reporting to clinical data registries that 
they will continue to do so even though it is not a requirement of the 
Medicare Promoting Interoperability Program. We will monitor hospitals' 
reporting of the four required measures to determine if we should 
modify the requirements in the future.
    After consideration of the public comments we received, we are 
finalizing our proposals that beginning with the EHR reporting period 
in CY 2022, an eligible hospital or CAH would receive 10 points for the 
Public Health and Clinical Data Exchange objective if they report a 
``yes'' response for each of the following 4 required measures: 
Syndromic Surveillance Reporting; Immunization Registry Reporting; 
Electronic Case Reporting; and Electronic Reportable Laboratory Result 
Reporting (86 FR 25638). Further, we are finalizing that in the event 
an eligible hospital or CAH is able to claim an exclusion for three or 
fewer of these four required measures, they would receive 10 points for 
the objective if they report a ``yes'' response for one or more of 
these measures and claim applicable exclusions for which they qualify 
for the remaining measures. If the eligible hospital or CAH fails to 
report on any one of the four measures required for this objective or 
reports a ``no'' response for one or more of these measures, we are 
finalizing that the eligible hospital or CAH would receive a score of 
zero for the Public Health and Clinical Data Exchange objective, and a 
total score of zero for the Medicare Promoting Interoperability 
Program. If an eligible hospital or CAH claims applicable exclusions 
for which they qualify for all four required measures, we are 
finalizing to redistribute the points associated with the objective to 
the Provider to Patient Exchange objective. We are modifying 42 CFR 
495.24(e)(8)(ii) as proposed to add: Eligible hospitals and CAHs could 
receive a bonus of 5 points for this objective if they report the 
measures specified under 42 CFR 495.24(e)(8)(iii)(D) or (E). The three 
exclusions that we established for each measure will no longer be 
available beginning with the EHR reporting period in 2022. For the 
Public Health Registry Reporting measure, we are revising 42 CFR 
495.24(e)(8)(iii)(D) as proposed, and for the Clinical Data Registry 
Reporting measure are revising 42 CFR 495.24(e)(8)(iii)(E), as 
proposed.
8. SAFER Guides
a. Background
    ONC developed and released the Safety Assurance Factors for EHR 
Resilience Guides (SAFER Guides) in 2014, and later updated them in 
2016. This series of nine user guides support hospitals' ability to 
address EHR safety.\1373\ Collectively, the SAFER Guides help 
healthcare organizations to conduct self-assessments to optimize the 
safety and safe use of EHRs in the three areas listed in this rule, in 
Table IX.F.-01. The SAFER Guides were intended to be utilized by EHR 
users, developers, patient safety organizations, and those who are 
concerned with optimizing the safe use of Health IT. By completing a 
self-assessment using the SAFER Guides, providers can help to develop a 
``culture of safety'' within their organizations and ensure they are 
responsible operators of technology tools, including certified health 
IT products, which they utilize in the delivery of care. The SAFER 
Guides are based on the best evidence available at the time of 
publication, including a literature review, expert opinion, and field-
testing at a wide range of healthcare organizations, from small 
ambulatory care practices to large health systems.
---------------------------------------------------------------------------

    \1373\ https://www.healthit.gov/topic/safety/safer-guides.
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    In the FY 2019 IPPS/LTCH final rule (83 FR 41663), commenters 
expressed concern with having the ability to maintain continuous 
electronic connectivity, and identified a need to account for planned 
and unplanned system outages or downtime. In response, we referred 
readers to the SAFER Guides, to utilize and incorporate as a part of 
their emergency planning processes. In the case of system disruption, 
failure, or natural disaster, the SAFER Guides provide recommended 
safety practices during planned or unplanned EHR unavailability, where 
end users are unable to access all or part of their EHR. Also included 
are back-up procedures to prevent the potential loss of clinical and 
administrative data, and how to utilize paper charting during such 
downtime (83 FR 41663). We believe that conducting annual self-
assessments based on the SAFER Guides' recommendations would satisfy 
stakeholder feedback received through the Annual Call for Measures and 
through public comment (83 FR 41663), supporting alternative and 
consistent safety practices for EHR users. We also believe requiring 
eligible hospitals and CAHs to conduct an annual self-assessment using 
the SAFER Guides would support the goals of improved EHR use and health 
care quality, as described in section 1886(n)(3)(A) of the Act.
BILLING CODE 4120-01-P
[GRAPHIC] [TIFF OMITTED] TR13AU21.301


[[Page 45480]]


BILLING CODE 4120-01-C
b. New SAFER Guides Measure
    We proposed in the FY 2022 IPPS/LTCH proposed rule (86 FR 25638), 
to add a new SAFER Guides measure to the Protect Patient Health 
Information objective beginning with the CY 2022 EHR reporting period. 
For this measure, we proposed that an eligible hospital or CAH must 
attest to having conducted an annual self-assessment of all nine SAFER 
Guides (available at https://www.healthit.gov/topic/safety/safer-guides), at any point during the calendar year in which the EHR 
reporting period occurs, with one ``yes/no'' attestation statement 
accounting for a complete self-assessment using all nine guides. We 
proposed that in CY 2022, this measure would be required, but it would 
not be scored, and that reporting ``yes'' or ``no'' will not affect the 
total score for the Medicare Promoting Interoperability Program. We 
also proposed to add corresponding regulatory text for this measure at 
Sec.  495.24(e)(4)(ii) and (iv).
    In order to complete a ``self-assessment'' of the SAFER Guides we 
would expect that each eligible hospital or CAH would complete the 
checklist of recommended practices included at the beginning of each 
SAFER Guide. Following the checklist, a practice worksheet provides the 
rationale for, and examples of, how to implement each recommended 
practice, likely sources of input into the assessment of each practice, 
and fillable fields to record follow-up actions.
    We understand that every organization faces unique circumstances, 
and will implement a particular safety practice differently. As a 
result, some of the specific examples in the SAFER Guides for 
recommended practices may not be applicable to every organization. We 
note that a ``self-assessment'' does not require an organization to 
confirm that it has implemented ``fully in all areas'' each practice 
described in a particular SAFER guide, nor will an organization be 
scored on how many of the practices the organization has fully 
implemented. Rather, the intent of this proposed requirement is for 
eligible hospitals and CAHs to regularly assess their progress and 
status on important facets of patient safety.
    The recommended practices in the SAFER Guides are intended to be 
useful for all EHR users and, we recognize that the individuals 
responsible for the proposed annual self-assessment may vary across 
organizations. An optimal team for completing an annual review of the 
SAFER Guides might include representatives from an eligible hospital or 
CAHs clinical leadership, nursing staff, pharmacy representatives, and 
the staff responsible for implementing and maintaining both internal 
technology systems as well as data connections with external partners, 
such as an HIE.
    Regarding the frequency of self-assessments using the SAFER Guides, 
we proposed that an eligible hospital or CAH must attest to completing 
their self-assessment using the SAFER Guides on an annual basis, 
following an initial completion of the self-assessment (some 
organizations may have already completed a self-assessment using the 
SAFER Guides prior to implementation of this requirement, if 
finalized). We would expect providers to revisit this assessment to 
determine whether any changes have occurred for their organization. We 
believe that requiring eligible hospitals and CAHs to periodically 
review this self-assessment as proposed would support a stronger 
culture of change management within organizations participating in the 
Medicare Promoting Interoperability Program, and would assist 
organizations in actively understanding and addressing potential safety 
vulnerabilities, which may significantly impact an organization's 
safety posture. We recognize that organizations may be at different 
stages in their progress towards assessing patient safety 
vulnerabilities and that hospitals vary in the resources that they 
could devote to annual self-assessment using the Guides. Gathering this 
information may be time consuming for small or rural hospitals that 
have contracted out some implementation services and may not have 
expertise available on staff to complete a full self-assessment using 
the SAFER Guides. For eligible hospitals and CAHs with less experience 
in these areas, we note that there are a number of resources available, 
which may be able to assist with completing a self-assessment.
    We invited public comments on these proposals.
    Comment: Many commenters supported our proposal to require a self-
assessment, annually, of all nine SAFER Guides. Commenters stated that 
this requirement will encourage program participants to regularly 
assess their progress on practices that optimize the safety and safe 
use of EHRs, and others agree that completion of the self-assessments 
will promote best practices for the safe use and maintenance of health 
IT by hospitals.
    Response: We would like to thank commenters for their support. We 
agree that given the opportunity to regularly assess progress, the 
SAFER Guides will help optimize the safety and safe use of EHRs, and 
allow eligible hospitals and CAHs the opportunity to make improvements 
as necessary over time.
    Comment: Several commenters supported our proposal to require a 
self-assessment of all nine SAFER Guides, but have instead recommended 
an incremental approach to its implementation. Specifically, a 
commenter suggested that we allow eligible hospitals and CAHs three 
years to complete their self-assessment, rather than requiring an 
assessment of all nine guides annually. Another commenter suggested a 
phased-in approach, incrementally increasing the number of self-
assessments that we would require annually.
    Response: We appreciate the commenters' support. We believe that in 
requiring the completion of this self-assessment annually, it would 
assist organizations in actively understanding and addressing potential 
safety vulnerabilities regularly, which may significantly impact an 
organization's safety posture in a timelier manner. As discussed above, 
the ``self-assessment'' does not require an organization to confirm 
that it has implemented ``fully in all areas'' each practice, nor will 
the organization be scored on how many of the practices the 
organization has fully implemented. The intent is for eligible 
hospitals and CAHs to regularly assess their progress and status on 
important facets of patient safety. Last, as indicated in the following 
comment and response, initial assessments using the SAFER Guides may 
remain unaffected unless an eligible hospital made significant system 
upgrades or a transition between systems, and an eligible hospital or 
CAH could briefly review this existing self-assessment in order to 
complete the measure.
    Comment: Several commenters supported of our proposal but have 
requested clarification and/or suggestions for improvement. A few 
commenters stated that many of the SAFER Guides represent one-time 
configuration or verification steps, which for many hospitals, would 
remain unchanged from year to year. These commenters further suggested 
that we clarify which guides hold a higher priority, so hospitals know 
how to better focus their efforts. A commenter suggested that CMS and 
ONC collaborate to ensure that the SAFER Guides be updated regularly to 
ensure the most current guidance is shared with eligible hospitals and 
CAHs. A commenter suggested that in lieu of requiring an annual self-
assessment, ONC and CMS increase efforts for education and outreach, to

[[Page 45481]]

disseminate this information to hospitals. A couple commenters 
requested clarification that this requirement will not be scored, and 
that an answer of ``yes'' and ``no'' are both acceptable without 
affecting their total scores.
    Response: We appreciate the commenters' support and suggestions. As 
discussed above, the completion of these self-assessments would assist 
organizations in actively understanding and addressing potential safety 
vulnerabilities regularly. The ``self-assessment'' does not require an 
organization to confirm that it has implemented ``fully in all areas'' 
each practice, nor will the organization be scored on how many of the 
practices the organization has fully implemented. As commenters have 
mentioned, several of the SAFER Guides will require an initial 
assessment that may not change significantly unless an eligible 
hospital made significant system upgrades or a transition between 
systems. Our larger focus is for eligible hospitals and CAHs to 
regularly assess their progress and status on important facets of 
patient safety. We would like to thank commenters for their suggestions 
that CMS and ONC coordinate efforts to regularly assess and update the 
SAFER Guides and to consider expanding on Education and Outreach 
efforts. We will continue to collaborate with ONC and take these 
suggestions under consideration. Last, we do confirm that for CY 2022, 
both ``yes'' and ``no'' are acceptable, an attestation of ``no'' will 
not alter final scores, and an attestation of ``no'' will not affect 
one's ability to be considered a Meaningful User.
    Comment: Few commenters did not support our proposal to require a 
self-assessment of all nine SAFER Guides, annually. A commenter 
expressed concern that the SAFER Guides do not improve 
interoperability, but instead create additional reporting burden on 
hospitals. Another commenter stated that the SAFER Guides self-
assessment would be out of scope for the Medicare Promoting 
Interoperability Program. A commenter stated that due to the reporting 
burden this requirement may cause, if we should finalize, we should 
consider postponing until the CY 2023 reporting period at a minimum.
    Response: We want to thank these commenters for sharing their 
feedback and concerns. With a central focus on patient safety, we 
disagree that the SAFER Guides self-assessments are out of scope for 
the Medicare Promoting Interoperability Program. We would like to 
remind commenters that the Protect Patient Health Information objective 
is essential to all aspects of Meaningful Use, and ensuring that 
Patient Health Information is protected and secure assists in 
addressing the unique risks and challenges that EHRs may present. Under 
the Protect Patient Health Information objective, the SAFER Guides 
measure is one way that we can proactively assess individual readiness. 
Therefore, we respectfully disagree that the SAFER Guides self-
assessment is out of scope for our Program. For the commenter who 
raised concerns about the additional reporting burdens this measure may 
present, we appreciate this feedback. We would like to reiterate that 
eligible hospitals and CAHs are not being scored on this measure, that 
an attestation of ``yes'' and ``no'' are both acceptable answers 
without penalty, and that eligible hospitals and CAHs will vary in 
their levels of implementation. Last, after an initial self-assessment, 
several of the SAFER Guides will not require the same type of annual 
assessments, absent vendor and/or system changes.
    After consideration of the public comments we received, we are 
finalizing our proposal to add a new SAFER Guides measure to the 
Protect Patient Health Information objective beginning with the CY 2022 
EHR reporting period. Eligible hospitals or CAHs must attest to having 
conducted an annual self-assessment of all nine SAFER Guides (available 
at https://www.healthit.gov/topic/safety/safer-guides), at any point 
during the calendar year in which the EHR reporting period occurs, with 
one ``yes/no'' attestation statement accounting for a complete self-
assessment using all nine guides. We are finalizing that in CY 2022, 
this measure will be required, eligible hospitals and CAHs are not 
being scored on this measure, and that an attestation of ``yes'' and 
``no'' are both acceptable answers without penalty. We are also 
finalizing our proposal to add corresponding regulatory text for this 
measure at Sec.  495.24(e)(4)(ii) and (iv).
9. Actions To Limit or Restrict the Compatibility or Interoperability 
of CEHRT
a. Background
    Section 106(b)(2) of the Medicare Access and CHIP Reauthorization 
Act of 2015 (MACRA) includes the heading ``Preventing Blocking The 
Sharing Of Information.'' Section 106(b)(2)(B) amended section 
1886(n)(3)(A)(ii) of the Act for eligible hospitals and, by extension, 
section 1814(l)(3) of the Act for CAHs to require that a hospital 
demonstrates (through a process specified by the Secretary, such as the 
use of an attestation) that the hospital has not knowingly and 
willfully taken action (such as to disable functionality) to limit or 
restrict the compatibility or interoperability of the certified EHR 
technology. To implement these provisions, we established and codified 
at 42 CFR 495.40(b)(2)(i)(I) attestation requirements for the Promoting 
Interoperability Programs to support the ``prevention of information 
blocking,'' which consist of three statements containing specific 
representations about a health care provider's implementation and use 
of CEHRT. For further discussion on these requirements, we refer 
readers to the CY 2017 Quality Payment Program final rule (81 FR 77028 
through 77035) and the Interoperability and patient access final rule 
(85 FR 25578 through 25580). The attestation statements finalized for 
eligible hospitals and CAHs at 42 CFR 495.40(b)(2)(i)(I) are:
     Statement 1: Did not knowingly and willfully take action 
(such as to disable functionality) to limit or restrict the 
compatibility or interoperability of certified EHR technology.
     Statement 2: Implemented technologies, standards, 
policies, practices, and agreements reasonably calculated to ensure, to 
the greatest extent practicable and permitted by law, that the 
certified EHR technology was, at all relevant times: (1) Connected in 
accordance with applicable law; (2) compliant with all standards 
applicable to the exchange of information, including the standards, 
implementation specifications, and certification criteria adopted at 45 
CFR part 170; (3) Implemented in a manner that allowed for timely 
access by patients to their electronic health information; and (4) 
Implemented in a manner that allowed for the timely, secure, and 
trusted bi-directional exchange of structured electronic health 
information with other health care providers (as defined by 42 U.S.C. 
300jj(3)), including unaffiliated providers, and with disparate 
certified EHR technology and vendors.
     Statement 3: Responded in good faith and in a timely 
manner to requests to retrieve or exchange electronic health 
information, including from patients, health care providers (as defined 
by 42 U.S.C. 300jj(3)), and other persons, regardless of the 
requestor's affiliation or technology vendor.
    Participants in the Medicare Promoting Interoperability Program 
that are required to attest to the three statements under 42 CFR 
495.40(b)(2)(i)(I) are also subject to public reporting as established 
in the Patient Access and Interoperability final rule (85 FR 25578 
through 25580).

[[Page 45482]]

Under this policy, we will post information on a CMS website available 
to the public for eligible hospitals and CAHs who have attested ``no'' 
to any of these three statements. Section 4004 of the 21st Century 
Cures Act added section 3022 to the Public Health Service Act (PHSA) 
(the ``PHSA information blocking provision''), which describes 
practices by health care providers, health IT developers, and health 
information exchanges and networks, that constitute information 
blocking, and provides for civil monetary penalties and other 
disincentives for those who engage in information blocking. In the ONC 
21st Century Cures Act final rule published in the Federal Register on 
May 1, 2020, ONC finalized a definition of information blocking and 
identified reasonable and necessary activities (``exceptions'') that do 
not constitute information blocking (85 FR 25642). For health care 
providers (as defined in 42 U.S.C. 300jj) ``information blocking means 
a practice that (1) Except as required by law or covered by an 
exception [. . .], is likely to interfere with access, exchange, or use 
of electronic health information; and if conducted by a health care 
provider, such provider knows that such practice is unreasonable and is 
likely to interfere with, prevent, or materially discourage access, 
exchange, or use of electronic health information'' (45 CFR 171.103).
    The Cures Act provides for civil monetary penalties for any 
individual or entity that is a developer, network, or exchange that has 
committed information blocking (see section 3022(b)(2)(A) of the PHSA). 
Regarding health care providers, the Cures Act provides that ``Any 
[health care provider] determined by the [HHS] Inspector General to 
have committed information blocking shall be referred to the 
appropriate agency to be subject to appropriate disincentives using 
authorities under applicable Federal law, as the Secretary sets forth 
through notice and comment rulemaking'' (section 3022(b)(2)(B) of the 
PHSA). For more information about the information blocking policies 
finalized in the ONC 21st Century Cures Act final rule, see https://www.healthit.gov/curesrule/final-rule-policy/information-blocking.
b. Changes to the Attestation Statements
    Although there could be some degree of overlap between conduct 
described in the attestation statements under 42 CFR 495.40(b)(2)(i)(I) 
and conduct that could be considered information blocking under section 
3022 of the PHSA and ONC's implementing regulations at 45 CFR 171.103, 
it is important to note these are separate and distinct authorities. 
For instance, the ONC 21st Century Cures Act final rule finalized a 
definition for what constitutes information blocking, and exceptions to 
information blocking that are not reflected in the previously finalized 
attestation statements under 42 CFR 495.40(b)(2)(i)(I). While we 
previously stated in the 2017 QPP final rule that these attestations 
statements did not impose ``unnecessary or unreasonable requirements'' 
on health care providers (81 FR 77029), after careful review of these 
statements in light of the information blocking regulations at 45 CFR 
part 171, we believe that statements 2 and 3 are no longer necessary. 
Thus, beginning with the CY 2022 EHR reporting period, we proposed at 
42 CFR 495.40(b)(2)(i)(I) and (J) to no longer require statements 2 and 
3. We believe that the similarities between practices described under 
statements 2 and 3, and the practices that could constitute information 
blocking under section 3022 of the PHSA and ONC's implementing 
regulations will create confusion for stakeholders. To this point, the 
practices that could constitute information blocking under 45 CFR part 
171 are much broader than those described in the attestation 
statements. We discuss specific instances of potential confusion in 
this final rule.
    Statement 2 requires attestation to a series of statements 
regarding the use of certified technology and a designated manner for 
implementing certified technology. For instance, attestations to the 
implementation of technology compliant with the standards for certified 
health IT at 45 CFR part 170, and use of functionality to support 
health information exchange with other providers. However, as 
previously stated, the definition of information blocking finalized in 
the ONC 21st Century Cures Act final rule is not specific to, nor 
limited to, the use of certified technology which is compliant with 
certain standards or the use of certain functionality. Under the ONC 
21st Century Cures Act final rule, a health care provider may still be 
determined to have engaged in practices likely to interfere with 
access, exchange, or use of electronic health information (information 
blocking) regardless of whether they are using certified technology.
    Regarding statement 3, we stated in the 2017 QPP final rule that 
``technical, legal, and other practical constraints may prevent a 
health care provider from responding to some requests to access, 
exchange, or use electronic health information in a health care 
provider's certified EHR technology'' (81 FR 77033). Subsequently, in 
the ONC 21st Century Cures Act final rule, ONC established a set of 
reasonable and necessary activities that are not considered information 
blocking when responding to a request for EHI. The reasonable and 
necessary activities established under the ONC 21st Century Cures Act 
final rule now provide more specific direction to providers when 
responding to a request for EHI than the general ``technical, legal, 
and other practical constraints'' which we described in the QPP 2017 
final rule with regards to statement 3. Accordingly, we believe that 
continuing to require statement 3 may introduce confusion for those 
health care providers who are obligated to comply with the regulations 
finalized in the ONC 21st Century Cures Act final rule when responding 
to a request for EHI.
    In order to distinguish the attestation required by section 
106(b)(2)(B) of MACRA from information blocking under section 3022 of 
the PHSA, we proposed in the FY 2022 IPPS/LTCH proposed rule (86 FR 
25639 through 25641), to modify the heading of the regulation text at 
42 CFR 495.40(b)(2)(i)(I) and the definition of ``meaningful EHR user'' 
under 495.4 from ``Support for health information exchange and the 
prevention of information blocking'' to ``Actions to limit or restrict 
the compatibility or interoperability of CEHRT,'' which reflects the 
language used in section 106(b)(2)(B) of MACRA.
    We invited public comments on our proposals.
    Comment: All commenters expressed support for our proposal to no 
longer require Statements 2 and 3 under 42 CFR 495.40(b)(2)(i)(I). 
Commenters shared appreciation for our efforts to eliminate duplicative 
reporting burden, eliminate redundancies, and our efforts towards 
streamlining our requirements.
    Response: We thank commenters for their support and positive 
feedback. We are continuing to make efforts towards alignment across 
programs and agencies, and reducing reporting burden among eligible 
hospitals and CAHs.
    After consideration of the public comments, we are finalizing our 
proposal without modification. That is, we will no longer require 
Statements 2 and 3 under 42 CFR 495.40(b)(2)(i)(I) and (J), beginning 
with the EHR reporting period in 2022. Additionally, we are finalizing 
our proposal to modify the heading of the regulation text at 42 CFR 
495.40(b)(2)(i)(I), and the definition of ``meaningful EHR user'' under 
495.4 from ``Support for health information exchange and the prevention 
of information blocking'' to ``Actions to

[[Page 45483]]

limit or restrict the compatibility or interoperability of CEHRT.''
10. Overview of Objectives and Measures for the Medicare Promoting 
Interoperability Program in 2022
    For ease of reference, Table IX.F.-02 lists the objectives and 
measures for the Medicare Promoting Interoperability Program for the 
EHR reporting period in CY 2022 as revised to reflect the final 
policies established in this final rule. Table IX.F.-03 lists the 2015 
Edition certification criteria required to meet the objectives and 
measures.
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10. Proposed Changes to the Scoring Methodology for the EHR Reporting 
Period in CY 2022
a. Proposed Performance-Based Scoring Threshold Increase
    In the FY 2019 IPPS/LTCH PPS final rule (83 FR 41636 through 
41645), we adopted a new performance-based scoring methodology for 
eligible hospitals and CAHs attesting under the Medicare Promoting 
Interoperability Program which included a minimum scoring threshold 
which eligible hospitals and CAHs must meet in order to satisfy the 
requirement to report on the objectives and measures of meaningful use 
under 42 CFR 495.24. We established at 42 CFR 495.24(e)(1)(i) that 
eligible hospitals and CAHs must earn a total score of at least 50 
points on the objectives and measures to be considered a meaningful EHR 
user.
    The Medicare Promoting Interoperability Program's performance 
results from CY 2019 (the first full year of programmatic data 
demonstrating the new performance-based scoring methodology) revealed 
that 3,776 of 3,828 participating eligible hospitals and CAHs that 
reported to the program successfully met the minimum threshold score of 
50 points.
    For CY 2022 and subsequent years, we proposed in the FY 2022 IPPS/
LTCH proposed rule (86 FR 25649) to increase the minimum scoring 
threshold from 50 points to 60 points, and proposed corresponding 
changes to the regulation text at 42 CFR 495.24(e)(1)(i)(C). Given the 
widespread success of participating hospitals in CY 2019, we believe 
that such program results signify the need for raising the minimum 
score for CY 2022. We note that eligible hospitals and CAHs will have 
gained two more years of experience in the Medicare Promoting 
Interoperability Program (CYs 2020 and 2021) at the 50-point minimum 
score threshold to improve performance. This increase from 50 points to 
60 points represents our intent to heighten the required standards for 
the Medicare Promoting Interoperability Program's performance levels 
and encourage higher levels of performance through the advanced usage 
of CEHRT in order to further incentivize eligible hospitals and CAHs to 
improve interoperability and health information exchange.
    We sought comments on our proposal to increase the minimum scoring 
threshold from 50 to 60 points.
    Comment: Generally, commenters supported our proposal for CY 2022 
and subsequent years to increase the minimum scoring threshold from 50 
to 60 points. Some commenters cited that the increase was of a 
reasonable amount and that the Medicare Promoting Interoperability 
Program's threshold had remained unchanged for several years, stating 
that the proposed increase to 60 points would be an opportunity to show 
continued growth in the program and reflect the success of its 
participants.
    Response: We thank the commenters for their support and agree that, 
based upon the success of the program, it is appropriate to increase 
the minimum scoring threshold. Data results from program year 2019 
showed that 98.6% of participating hospitals scored higher than the 
current 50 point minimum. As the 50-point threshold has been in place 
since CY 2019, we continue to believe that the program is prepared to 
adapt and evolve toward this increased standard of participation for 
consideration as a meaningful EHR user. We've stated that eligible 
hospitals and CAHs would have gained two additional years of experience 
in the program (CYs 2020 and 2021) with the current threshold of 50 
points, and this increase to 60 points represents our desire to 
encourage higher levels of program performance and to further 
incentivize eligible hospitals and CAHs to improve their advancement 
toward interoperability, promote greater health information exchange, 
and raise overall patient care quality.
    Comment: Some commenters, while agreeing in theory with a proposed 
increase to 60 points, indicated their desire to stress the importance 
of CMS taking a measured and staged approach in any future program 
changes (including adjustments made to the minimum scoring threshold). 
Several commenters expressed concerns over whether smaller, rural, or 
emerging hospitals would struggle to meet the 60-point threshold and 
fail to qualify as meaningful EHR users. The same commenters also 
highlighted the Public Health Emergency surrounding COVID-19 as a 
challenging time to improve overall performance for those eligible 
hospitals and CAHs participating in the Medicare Promoting 
Interoperability Program.
    Response: We thank the commenters for sharing their concerns 
surrounding the proposed rule's change to increase the program's 
minimum scoring threshold. While we admit to widespread difficulties 
experienced by eligible hospitals and CAHs during the Public Health 
Emergency, we believe that there has been sufficient time since CY 2019 
for programmatic stability in

[[Page 45492]]

the Medicare Promoting Interoperability Program's available objectives 
and measures to warrant such a nominal increase of 10 points. We would 
like to highlight that this final rule includes several finalized 
changes in the Medicare Promoting Interoperability Program which allow 
expanded opportunities for additional bonus points as well as new 
measure options that we believe could grant the necessary points to 
achieve more than the required 60-point scoring threshold. As other 
submitted commenters cited, we've balanced this increase against the 
full scope of the Medicare Promoting Interoperability Program changes 
which considers the role of bonus points in meeting or surpassing the 
minimum threshold. Specifically, we'd point to the inclusion of 
finalized changes surrounding 10 bonus points in the Query of PDMP 
measure, an additional 5 bonus points in the Public Health and Clinical 
Data Exchange objective, as well as a new alternative Health 
Information Exchange Bi-Directional Exchange measure. Combined, we 
believe that these finalized efforts would offer more than sufficient 
opportunity for eligible hospitals and CAHs to offset an increase to 
the Medicare Promoting Interoperability Program's minimum scoring 
threshold, therefore negating any need to delay the increase to a 
future calendar year.
    After consideration of the public comments we received, we are 
finalizing our proposals without modification. That is, for CY 2022 and 
subsequent years, we are increasing the minimum scoring threshold from 
50 points to 60 points. We are also finalizing, as proposed, the 
corresponding changes to the regulation text at 42 CFR 
495.24(e)(1)(i)(C).
b. Performance-Based Scoring Methodology Table Updates
    The following table reflects the objectives and measures as 
finalized for CY 2022. As discussed in section IX.F.3.c of this final 
rule, we are finalizing our proposals for CY 2022 to include the 
optional Query of PDMP measure worth 10 bonus points, the adoption of a 
new alternative Health Information Exchange Bi-Directional Exchange 
measure, the adoption of a SAFER Guides measure, and modified 
requirements for the Public Health and Clinical Data Exchange 
objective.
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11. Clinical Quality Measurement for Eligible Hospitals and CAHs 
Participating in the Medicare Promoting Interoperability Program
a. Changes to Clinical Quality Measures in Alignment With the Hospital 
IQR Program
(1) Background
    Under sections 1814(l)(3)(A) and 1886(n)(3)(A) of the Act and the 
definition of ``meaningful EHR user'' under 42 CFR 495.4, eligible 
hospitals and CAHs must report on clinical quality measures (referred 
to as CQMs or eCQMs) selected by CMS using CEHRT, as part of being a 
meaningful EHR user under the Medicare Promoting Interoperability 
Program.
    The following table lists previously finalized eCQMs available for 
eligible hospitals and CAHs to report under the Medicare Promoting 
Interoperability Program (84 FR 42597 through 42599) for the reporting 
period in CY 2021 and in subsequent years. The table includes the Safe 
Use of Opioids--Concurrent Prescribing measure (NQF #3316e) which we 
finalized as mandatory for reporting beginning with CY 2022 (84 FR 
42598 through 42600).
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(2) eCQM Removals
    As we discuss in the Hospital IQR Program section of this final 
rule, we proposed to remove four eCQMs from the Hospital IQR Program's 
measure set effective for the CY 2024 reporting period/FY 2026 payment 
determination in the FY 2022 IPPS/LTCH proposed rule (86 FR 25650). 
Specifically, we proposed to remove:
     STK-03 (Anticoagulation Therapy for Atrial Fibrillation/
Flutter),
     STK-06 (Discharged on Statin Medication),
     PC-05 (Exclusive Breast Milk Feeding), and
     ED-2 (Admit Decision Time to ED Departure Time for 
Admitted Patients).
    We refer readers to section IX.C. of the preamble of this final 
rule for additional discussion of the rationales for these removals 
from the Hospital IQR Program.
    We continue to believe that aligning the CQM requirements that we 
adopt in the Medicare Promoting Interoperability Program with the 
Hospital IQR Program's eCQM requirements benefits hospitals that are 
working to comply with each program's requirements. Aligning the 
requirements and measure sets across programs promotes efficiency and 
harmonizes with our goal of applying a parsimonious set of the most 
meaningful measures available to track patient outcomes and impact. We 
believe that maintaining alignment between the Hospital IQR Program and 
the Medicare Promoting Interoperability Program streamlines our 
approach to data collection, calculation, and reporting using EHRs. We 
further believe that this streamlined approach allows us to leverage 
clinical and patient-centered information for measurement, improvement, 
and learning.
    To maintain this alignment between the Hospital IQR Program and 
Medicare Promoting Interoperability Program, and for the reasons 
described in section IX.C. of the preamble to this final rule, we are 
removing STK-06, PC-05, and ED-2 from the previously finalized set of 
eCQMs for the Medicare Promoting Interoperability Program beginning 
with the reporting period in CY 2024.
    We welcomed public comments on the proposed eCQM removals.
    Comment: Many commenters generally supported our proposal to remove 
STK-03. Several commenters supported our proposal to remove STK-03 
because removing the measure reduces administrative burden, and agree 
that the costs associated with the measure outweigh the benefits of 
retaining it in the Medicare Promoting Interoperability Program. A 
commenter supported our proposal to remove STK-03 because the removal 
will add balance to the core set of eCQMs available for reporting.
    Response: We thank the commenters for their support of our proposal 
to remove STK-03, and agree with commenters that, the costs associated 
with the measure outweigh the benefits of retaining it. Therefore, we 
are not finalizing our proposal, as is detailed below.
    Comment: A number of commenters did not support our proposal to 
remove

[[Page 45494]]

STK-03. Commenters asserted their belief that the STK-02 measure does 
not specifically target prescribing of anticoagulation therapy to 
patients at discharge. Commenters identified that ischemic stroke 
patients are not all the same, noting their belief that patients with 
non-cardioembolic ischemic stroke should be treated with antiplatelet 
medication, rather than anticoagulation. Commenters also pointed out 
the distinction that the STK-03 eCQM makes between the general category 
of antithrombotic therapy and the specific subset of anticoagulant 
therapy, whereas STK-02 does not ensure that stroke patients with 
atrial fibrillation are appropriately prescribed an anticoagulant as 
guidelines recommend. Commenters expressed their belief that 
anticoagulation has historically been dramatically underutilized for 
stroke prevention in patients with atrial fibrillation, such that 
prescribing it at discharge is an important opportunity to improve 
appropriate use in these patients. Commenters were concerned that 
removing STK-03 could result in fewer stroke patients receiving 
appropriate anticoagulant therapy.
    Response: We appreciate commenters' concerns. We have confidence 
that hospitals are committed to providing good quality care to stroke 
patients and we do not have any indication that they will stop doing so 
in these areas for which the quality of care has become standard 
practice. After considering stakeholder concerns, we plan to retain the 
STK-03 eCQM in the Medicare Promoting Interoperability Program's 
measure set and are thus not finalizing the removal in this final rule.
    Comment: A commenter did not support our proposal to remove STK-03 
because of their belief that this removal would magnify racial 
inequities in prescription and treatment that non-white stroke patients 
face.
    Response: We appreciate the commenter's concern related to racial 
disparities. As stated earlier we are focused on and committed to 
closing the health equity gap as seen in the Health Equity RFI (86 FR 
25554 through 25561). We wish to clarify that STK-03 is not stratified 
by race which limits the ability of the measure to directly capture or 
address racial disparities. We note that after consideration of 
stakeholder concerns, we are not finalizing our proposal to remove this 
measure.
    Comment: Several commenters did not support our proposal to remove 
STK-03 because they believed that removing it would decrease the number 
of available eCQMs for hospitals to choose from and discounts the 
investment of resources hospitals must expend to operationalize an 
eCQM.
    Response: We are finalizing our proposal to adopt two additional 
eCQMs and refer readers to sections IX.C.5.d.1. and IX.C.5.d.2. for 
more detail on our finalized proposals to adopt the Hospital Harm-
Severe Hypoglycemia eCQM and Hospital Harm--Severe Hyperglycemia eCQM. 
We note that after consideration of stakeholder concerns, we are not 
finalizing our proposal to remove this measure. We reiterate that we 
intend to introduce additional eCQMs into the program as ones that 
support out evolving program goals become available.
    Comment: Many commenters expressed support for our proposal to 
remove the STK-06 eCQM from Medicare Promoting Interoperability measure 
set. Several stated the proposal would reduce unnecessary 
administrative and reporting burden and expressed appreciation for CMS' 
efforts to continually review the measure set and balance the core set 
of eCQMs reported to CMS.
    Response: We thank commenters for their support of the proposal to 
remove STK-06 from the Medicare Promoting Interoperability Program.
    Comment: A few commenters did not support our proposal to remove 
the STK-06 measure due to concern that small hospitals lack other eCQMs 
to report based upon their patient population. A commenter did not 
support our proposal due to the investment of time and resources 
previously incurred to implement the measure.
    Response: We acknowledge that facilitating quality improvement for 
small hospitals can present unique challenges. We understand the 
concern that the ability to submit zero denominator exemption does not 
provide direct information for supporting quality improvement efforts. 
It remains our goal to expand EHR-based quality reporting in the 
Medicare Promoting Interoperability program which we believe will 
ultimately provide more flexibility for hospitals to choose the 
measures that are most representative of their patient populations. We 
also acknowledge the time, effort and resources that hospitals expend 
on implementing eCQMs. However, we believe that measure removal will be 
less burdensome to hospitals overall than continuing to retain a 
measure in the Medicare Promoting Interoperability Program. As part of 
the Meaningful Measures Initiative to include a parsimonious set of the 
most meaningful measures for patients and clinicians in our quality 
programs to reduce burden, cost and program complexity, our decision to 
remove measures from the Medicare Promoting Interoperability Program is 
an extension of our programmatic goal to continually refine the measure 
set (83 FR 41574).
    Comment: Many commenters supported our proposal to remove the ED-2 
eCQM. Some commenters appreciated that the removal would reduce burden 
on hospitals and others agreed that the costs associated with ED-2 
outweigh the benefit of its continued use in the Medicare Promoting 
Interoperability Program. A few commenters questioned whether boarding 
times accurately reflect quality of care and some suggested that 
quality of care is more impacted by external factors such as access to 
behavioral health treatment, patterns of primary care deliver, and 
nursing shortages.
    Response: We thank the commenters for the support of our proposal 
to remove the ED-2 eCQM. While we continue to believe that prolonged 
emergency department board times is an important issue, we agree that 
the Admit Decision Time to ED Departure Time for Admitted Patients has 
had inconclusive associations with adverse outcomes such as in-hospital 
mortality and the quality of care in the inpatient setting. We 
understand that other factors, in addition to boarding times, impact 
outcomes and note that this measure was not intended to suggest 
otherwise. We note that we will continue measuring ED boarding times in 
the outpatient setting via measure OP-18, Median Time from ED Arrival 
to ED Departure for Discharged ED Patients, in the Outpatient Quality 
Reporting Program. We appreciate the commenters' feedback and will take 
it into consideration as we continually refine the measure sets for our 
quality programs.
    After consideration of the public comments we received, we are not 
finalizing our proposal to remove the Anticoagulation Therapy for 
Atrial Fibrillation/Flutter (STK-03) eCQM. We thank the commenters for 
their comments and suggestions, which we will take into consideration 
when assessing what changes, if any, should be incorporated into this 
important measure for the future. However, after consideration of the 
public comments we received, we are finalizing our proposal to remove 
STK-06 (Discharged on Statin Medication), PC-05 (Exclusive Breast Milk 
Feeding), and ED-2 (Admit Decision Time to ED Departure Time for 
Admitted Patients) from the previously finalized set of eCQMs for the 
Medicare Promoting Interoperability Program

[[Page 45495]]

beginning with the CY 2024 reporting period.
(3) eCQM Adoptions
    As we have stated previously in rulemaking (82 FR 38479), we plan 
to continue to align the CQM reporting requirements for the Promoting 
Interoperability Program with similar requirements under the Hospital 
IQR Program. Further, as we discuss in section IX.C. of the preamble of 
this final rule, we are adopting two new eCQMs in the Hospital IQR 
Program beginning with the CY 2023 reporting period/FY 2025 payment 
determination:
     Hospital Harm--Severe Hypoglycemia (NQF #3503e), and
     Hospital Harm--Severe Hyperglycemia (NQF #3533e).
    We refer readers to section IX.C. of the preamble of this final 
rule for additional discussion of the technical details associated with 
these measures, their data sources, calculations, cohorts, and risk 
adjustment.
    As previously discussed, with respect to eCQM removals, we continue 
to believe that adopting aligned requirements between the Hospital IQR 
and Medicare Promoting Interoperability Program is beneficial to 
participating hospitals. To maintain this alignment and to support 
hospitals' ability to choose amongst a consistent pool of CQMs, as well 
as the clinical importance of these measures as discussed in section 
IX.C. of the preamble to this final rule, in the FY 2022 IPPS/LTCH 
proposed rule (86 FR 25650 through 25651) we proposed to adopt the 
Severe Hypoglycemia and Severe Hyperglycemia CQMs for the Medicare 
Promoting Interoperability Program beginning with the reporting period 
in CY 2023.
    We welcomed public comments on the proposed eCQM adoptions.
    Comment: Many commenters expressed support for the inclusion of the 
Hospital Harm--Severe Hyperglycemia eCQM into the Medicare Promoting 
Interoperability Program measure set. Commenters stated their belief 
that the measure will increase transparency, drive improvements in 
care, and improve patient outcomes. A commenter appreciated that this 
measure can be applied broadly to various sized hospitals and another 
commenter highlighted that this measure will expand the number of eCQMs 
available to rural and specialty hospitals for quality reporting. A 
commenter stated that this measure is in alignment with the goals put 
forth in the National Action Plan for Adverse Drug Event Prevention 
(Action Plan). Commenters supported adoption of the measure and 
appreciated our commitment to align eCQMs in the Medicare Promoting 
Interoperability Program with the Hospital IQR Program.
    Response: We thank commenters for their support and input. We agree 
that this measure, which captures important quality information that is 
critical to patient safety and improving patient outcomes, should be 
included in the Medicare Promoting Interoperability Program measure 
set.
    Comment: Many commenters provided feedback on the implementation 
timeline for the measure. A few commenters agreed that the CY 2023 
reporting period is a reasonable and appropriate timeline for a new 
measure, while several commenters believed that the measure should be 
delayed. A commenter requested an 18-month delay, while others 
requested one additional year, recommending inclusion beginning with 
the CY 2024 reporting period.
    Response: We thank the commenters for their support and input. We 
note that this measure was proposed for inclusion beginning in the CY 
2023 reporting period, which would allow hospitals at least one full 
year to implement. We appreciate commenters' requests for an 18 to 24-
month delay, but respectfully disagree that reporting in CY 2023 is 
unreasonable. We direct readers to the eCQI Resource Center (available 
at: https://ecqi.healthit.gov/pre-rulemaking-eh-cah-ecqms) for the 
draft specifications for this eCQM, several other eCQMs being 
finalized, as well as those we sought comment on in the FY 2022 IPPS/
LTCH PPS proposed rule (86 FR 25070).
    Comment: Several commenters shared feedback on the adoption of 
Hospital Harm--Severe Hypoglycemia as a balancing measure to Hospital 
Harm--Severe Hyperglycemia. A few stated their support for both 
measures, recommending that we allow hospitals to choose which of the 
two measures to report. A commenter recommended CMS require reporting 
of both eCQMs. A commenter recommended that we require hospitals to 
report on the Hospital Harm--Severe Hypoglycemia measure, while a few 
others preferred that reporting on it be kept optional. A few 
commenters stated that they could not support the adoption of these 
balancing measures as they believed they were not aligned. A commenter 
had concerns about complexity of the Hospital Harm--Severe Hypoglycemia 
measure.
    Response: We thank commenters for their feedback. Hospitals will be 
able to report the Severe Hyperglycemia and Severe Hypoglycemia 
measures independently. Balancing measures are measures that can be 
used to demonstrate that an improvement in one area is not negatively 
impacting improvement in another area. For example, we can use these 
measures to assess whether an improvement in the number of severe 
hyperglycemia events ties to an increase in the number of severe 
hypoglycemia events. For that reason, while the two measures may not 
measure the same exact thing, we consider them to be balancing 
measures. We believe that both measures, regardless of the denominator 
used, will trend downward as improvements are made. Additionally, we 
note that hospitals may self-select to report on one, both, or none of 
these two finalized eCQMs. As finalized in the FY 2021 IPPS/LTCH PPS 
final rule (85 FR 58970 through 58975), hospitals are required to 
report on: (a) Three self-selected eCQMs and (b) the Safe Use of 
Opioids--Concurrent Prescribing eCQM (Safe Use eCQM), for a total of 
four eCQMs.
    Comment: Many commenters supported adopting the Hospital Harm--
Severe Hypoglycemia eCQM in the Medicare Promoting Interoperability 
Program. Commenters expressed their belief that the measure will 
improve both transparency and patient outcomes. A commenter highlighted 
that the measure can be easily implemented. A few commenters support 
the inclusion of the measure and emphasized the importance of glycemic 
control for reducing patient harm.
    Response: We thank commenters for their support of and input on the 
inclusion of Hospital Harm--Severe Hypoglycemia (NQF #3503e) in the 
Medicare Promoting Interoperability Program measure set beginning with 
the CY 2023 reporting period. We agree that this measure captures 
important quality information that is critical to patient safety and 
improving patient outcomes.
    Comment: A few commenters did not support the inclusion of Hospital 
Harm--Severe Hypoglycemia into the Medicare Promoting Interoperability 
Program measure set due to testing. These commenters expressed concern 
about the level of testing, requesting that the measure undergo 
additional testing for feasibility and validity prior to finalization. 
Another commenter expressed support for the measure, but also requested 
we conduct additional testing.
    Response: We thank the commenters for their input and feedback on 
this measure. We understand the value of sample size in measure 
testing, and note that measure testing was done in

[[Page 45496]]

compliance with the NQF requirements for eCQM development. The Hospital 
Harm--Severe Hypoglycemia eCQM was tested in 6 hospitals representing 
two EHR systems that provided a good representation of hospitals across 
the country. This aligns with NQF's recommendation to conduct eCQM 
testing in more than one EHR system. Empirical results also showed that 
the measure exhibited high feasibility, reliability, and data element 
validity. The thresholds were found to be feasible, reliable, valid, 
and scientifically acceptable by the NQF Patient Safety Standing 
Committee and the measure was endorsed by the NQF Consensus Standards 
Advisory Committee (CSAC) in the Spring of 2019.
    Comment: Several commenters supported the Hospital Harm--Severe 
Hypoglycemia measure, but requested CMS delay the inclusion of the eCQM 
to allow additional time for hospitals to implement the measure. A 
commenter requested an 18-month delay, while others requested one 
additional year, recommending inclusion beginning with the CY 2024 
reporting period. A few commenters requested additional time to pilot 
the measure before formally adopting it into the Medicare Promoting 
Interoperability Program.
    Response: We thank commenters for their support and input. We 
emphasize that the Hospital Harm--Severe Hypoglycemia measure was 
proposed for inclusion beginning in the CY 2023 reporting period, which 
would allow hospitals at least one full year to implement. We 
appreciate commenters' requests for an 18 to 24-month delay, but 
respectfully disagree that reporting in CY 2023 is unreasonable. We 
direct readers to the eCQI Resource Center (available at: https://ecqi.healthit.gov/pre-rulemaking-eh-cah-ecqms) for the draft 
specifications for this eCQM, several other eCQMs being finalized, as 
well as those we sought comment on in the FY 2022 IPPS/LTCH PPS 
proposed rule (86 FR 25070). We thank commenters for the suggestion to 
allow additional pilot time, but feel that a CY 2023 implementation 
will allow eligible hospitals and CAHs the time necessary to complete 
testing activities.
    Comment: A commenter recommended that we provide sufficient 
guidance on the time windows for ``day'' as it relates to the proposed 
Hospital Harm--Severe Hypoglycemia measure's definition and 
specification description. They noted that the measure could use 
clarification on how hospitals would calculate or count the length of a 
``day'', such as whether it constitutes a calendar day or 24-hour day 
(as clocked from the first point of patient documentation).
    Response: We thank the commenter for their feedback. We note that 
the Hospital Harm--Severe Hypoglycemia eCQM specifies the time window 
as 24 hours. For more detailed information and measure guidance, we 
refer readers to the draft specifications for this measure, available 
on the eCQI Resource Center (available at: https://ecqi.healthit.gov/pre-rulemaking-eh-cah-ecqms). After consideration of the public 
comments we received, we are finalizing the inclusion of Hospital 
Harm--Severe Hypoglycemia eCQM (NQF #3503e) and Hospital Harm--Severe 
Hyperglycemia eCQM (NQF#3533e) to the Medicare Promoting 
Interoperability Program measure set, in alignment with similar 
proposals also finalized by the Hospital IQR Program, beginning with 
the CY 2023 reporting period. We thank the public for their input and 
support.
BILLING CODE 4120-01-P
[GRAPHIC] [TIFF OMITTED] TR13AU21.312


[[Page 45497]]


[GRAPHIC] [TIFF OMITTED] TR13AU21.313

[GRAPHIC] [TIFF OMITTED] TR13AU21.314

BILLING CODE 4120-01-C
(4) Updates to Certification Requirements for eCQM Reporting--2015 
Edition Cures Update
    In the ONC 21st Century Cures Act final rule, ONC revised the 
clinical quality measurement criterion at Sec.  170.315(c)(3) to refer 
to CMS QRDA Implementation Guides and remove the Health Level 7 
(HL7[supreg]) QRDA standard from the relevant health IT certification 
criteria (85 FR 25686). The Sec.  170.315(c)(3) revision was responsive 
to industry feedback that the health IT certified to the prior ``CQMs-
report'' criterion was only primarily being used to submit eCQMs for 
CMS reporting programs. This update was finalized to reduce burden on 
health IT developers under the ONC Health IT certification program and 
has no impact on providers' existing reporting practices for CMS 
quality programs. In the Information Blocking and ONC Health IT 
Certification Program: Extension of Compliance Dates and Timeframes in 
Response to the COVID-19 Public Health Emergency interim final rule 
with comment period (85 FR 70064), ONC finalized that health IT 
developers will have until December 31, 2022, to make updated certified 
technology available in accordance with revised criteria (85 FR 70066 
through 70068).

[[Page 45498]]

    In the FY 2022 IPPS/LTCH proposed rule (86 FR 25652), we proposed 
to require eligible hospitals and CAHs to use only certified technology 
updated consistent with the 2015 Edition Cures Update, as finalized in 
the ONC 21st Century Cures Act final rule (85 FR 25642 through 25667), 
to submit data for eCQMs beginning with the reporting period in CY 
2023. This is in alignment with the policy for the Hospital IQR Program 
discussed in section IX.C. of the preamble of this final rule. We refer 
readers to the ONC 21st Century Cures Act final rule for additional 
information about the updates included in the 2015 Edition Cures Update 
(85 FR 25666 through 25668). We also refer readers to the CY 2021 PFS 
final rule for the Medicare Promoting Interoperability Program (85 FR 
84815 through 84825) and the Hospital IQR Program (85 FR 84825 through 
84828), and section IX.C. of the preamble of this final rule for 
additional information related to this policy.
    We invited public comments on our proposal to require eligible 
hospitals and CAHs to use only certified technology updated consistent 
with the 2015 Edition Cures Update to submit data for eCQMs, beginning 
with the reporting period in CY 2023, in alignment with the Hospital 
IQR Program proposal.
    Comment: Several commenters supported the proposal to require use 
of 2015 Edition Cures Update beginning with the CY 2023 reporting 
period, citing that the requirement will help enhance data 
standardization, interoperability, and quality measurement. Commenters 
recommended CMS monitor vendor and hospital progress to ensure the 
transition to the 2015 Edition Cures Update remains feasible and 
exercise flexibility if there are vendor issues beyond the hospitals' 
control.
    Response: We thank commenters for their support and agree with the 
statement that the 2015 Edition Cures Update aligns with the goals of 
the Medicare Promoting Interoperability Program on such issues. We will 
work with ONC to monitor the availability of EHR technology certified 
to the 2015 Edition Cures Update.
    Comment: Several commenters did not support required use of the 
2015 Edition Cures Update beginning with the CY 2023 reporting period 
citing insufficient time for hospitals to prepare and test for the 
requirement, and concern about health IT developers' timeline to 
develop and deploy technology.
    Response: We appreciate commenters' concerns related to sufficient 
time for hospitals to prepare and test the 2015 Edition Cures Update 
after it is made available by health IT developer, however we 
respectfully disagree. The updates to the certification criteria that 
ONC finalized in the ONC 21st Century Cures Act final rule do not 
constitute a full new Edition of technology, as the scope of updates 
did not warrant implementation of an entirely new Edition of 
certification criteria (see 85 FR 84818 through 84825 for a more 
detailed discussion). The updates finalized in the ONC 21st Century 
Cures Act final rule are limited in scope to build on existing 
functionality and standards in technology certified to the 2015 
Edition, which participants in the Medicare Promoting Interoperability 
Program have been using as part of clinical and administrative 
workflows since the CY 2019 reporting period (83 FR 41635 through 
41636). We reiterate that the updates to the certification criteria do 
not impact providers' current reporting practices for eCQMs under the 
Medicare Promoting Interoperability Program, and, we intend to work 
with all our partners to monitor the timely availability of EHR 
technology certified to the 2015 Edition Cures Update.
    After consideration of the public comments we received, we are 
finalizing our proposal to require eligible hospitals and CAHs to use 
only certified technology updated consistent with the 2015 Edition 
Cures Update beginning with the CY 2023 reporting period to submit eCQM 
data for the Medicare Promoting Interoperability Program, in alignment 
with the Hospital IQR Program's policy.

X. Other Policy Provisions

A. Medicaid Enrollment of Medicare Providers and Suppliers for Purposes 
of Processing Claims for Cost-Sharing for Services Furnished to Dually 
Eligible Beneficiaries

1. Background
    Dually eligible beneficiaries are those enrolled in both Medicare 
(either Part A, Part B, or both) and Medicaid. About 8 million dually 
eligible individuals are enrolled in the Qualified Medicare Beneficiary 
(QMB) program,\1374\ which is a Medicaid benefit that assists low-
income Medicare beneficiaries with Medicare Part A and Part B premiums 
and cost sharing. QMB ``Medicare cost-sharing'' amounts, as defined in 
section 1905(p)(3) of the Act,\1375\ include Medicare Part A and B 
premiums, coinsurance, and deductibles. Section 1902(a)(10)(E) of the 
Act directs States to pay providers for Medicare coinsurance and 
deductibles. Under section 1905(p)(3) of the Act, ``Medicare cost-
sharing'' includes costs incurred with respect to a QMB, regardless of 
whether the costs incurred were for items and services covered under 
the Medicaid State plan. Additionally, some State Medicaid agencies 
also elect to pay the Medicare cost-sharing for other (non-QMB) dually 
eligible beneficiaries.
---------------------------------------------------------------------------

    \1374\ Under 1905(p)(1) of the Act, a QMB is an individual who 
is entitled to hospital insurance benefits under Part A of Medicare, 
with income not exceeding 100 percent of the Federal poverty level, 
and resources not exceeding three times the SSI limit, adjusted 
annually by the Consumer Price Index. For more information about QMB 
eligibility and benefits, see chapter 1, section 1.6.2.1 and 
Appendices 1.A and 1.B of the Manual for the State Payment of 
Medicare Premiums.
    \1375\ A State's requirement to determine its cost-sharing 
liability for QMBs is also set forth at section 3490.14(A) of the 
State Medicaid Manual (SMM) (CMS Pub. 45).
---------------------------------------------------------------------------

    However, section 1902(n)(2) of the Act permits the State to limit 
payment for Medicare cost-sharing to the amount necessary to provide a 
total payment to the provider (including Medicare, Medicaid State plan 
payments, and third-party payments) equal to the amount a State would 
have paid for the service under the Medicaid State plan. This is often 
referred to as the ``lesser-of'' policy.
    If a State has adjudicated its Medicare cost-sharing to a provider 
pursuant to the lesser-of policy for an individual enrolled in the QMB 
program, section 1902(n)(3) of the Act prohibits the provider from 
collecting the remaining amount from the beneficiary.\1376\ However, 
certain providers may recover a portion of these unpaid cost-sharing 
amounts as Medicare ``bad debt'' if they meet all the requirements in 
42 CFR 413.89 and as described further in the Provider Reimbursement 
Manual Part 1 Chapter 3. Pursuant to Sec.  413.89(h), bad debt payments 
are generally 65 percent of the uncollected amount for these services.
---------------------------------------------------------------------------

    \1376\ Medicare providers who violate these billing prohibitions 
are violating their Medicare Provider Agreement and may be subject 
to sanctions (see sections 1902(n)(3), 1905(p), 1866(a)(1)(A), and 
1848(g)(3) of the Act).
---------------------------------------------------------------------------

    Per 42 CFR 413.89, providers must exclude any cost-sharing amount 
legally owed by the State from Medicare bad debt amounts claimed. CMS 
requires a provider that furnishes services to a dually eligible 
beneficiary to determine whether the State's Medicaid program (or 
applicable third party) is responsible for paying all or a portion of 
the beneficiary's Medicare deductible and/or coinsurance (and if so, 
how much) before the provider can claim these amounts as Medicare bad 
debt. Before claiming any unpaid cost-sharing amounts as a Medicare bad 
debt for a

[[Page 45499]]

dually eligible beneficiary, the provider must bill the State or State 
designee, such as a Medicaid managed care organization (MCO) (the 
``must bill'' policy), and obtain from the State or State designee 
documentation of completed claim processing and claim adjudication 
information in the form of a Medicaid remittance advice (RA) \1377\ 
that sets forth the State's cost-sharing liability for the items and 
services the beneficiary received (the ``RA'' policy).
---------------------------------------------------------------------------

    \1377\ The FY 2021 Hospital Inpatient Prospective Payment 
Systems (IPPS) for Acute Care Hospitals and the Long-Term Care 
Hospital (LTCH) Prospective Payment System final rule (85 FR 58432), 
published on October 1, 2020, created the Medicaid RA alternative 
documentation policy with a retroactive effective date. This policy 
allows providers a way to submit alternative documentation to the 
Medicaid RA that sets forth the State's liability for the cost-
sharing when a State does not process a Medicare crossover claim and 
issue a Medicaid RA to the provider. We anticipate the alternative 
documentation policy will only need to be in effect until States 
comply with the existing statute and process crossover cost-sharing 
claims for all Medicare providers. We would consider in future 
rulemaking removing the alternative once States comply with our 
proposal in this notice of proposed rulemaking.
---------------------------------------------------------------------------

2. Claims for Medicare Cost-Sharing for Dually Eligible Beneficiaries 
and Misaligned Medicare and Medicaid Provider Enrollment
    Section 1903(a)(3)(A)(i) of the Act requires each State Medicaid 
Management Information System (MMIS) to process Medicare claims for 
dually eligible beneficiaries for Medicare cost-sharing. Furthermore, 
to comply with sections 1902(a)(10)(E) and 1902(n)(1) and (2) of the 
Act, the State MMIS must be able to process all such claims for 
Medicare cost-sharing liability even if the Medicaid State plan does 
not recognize a service or provider category.\1378\ Nevertheless, some 
states in the past have inhibited enrollment of certain types of 
providers or suppliers that are not explicitly included in their State 
plan. If a Medicare-enrolled provider or supplier has been unable to 
enroll with the State Medicaid program, then the State MMIS may not 
adjudicate the cost-sharing claim and also may not return a Medicaid RA 
to the provider for the purposes of computing Medicare bad debt absent 
further actions by the State or by the provider.
---------------------------------------------------------------------------

    \1378\ https://www.medicaid.gov/Federal-policy-guidance/downloads/cib-06-07-2013.pdf.
---------------------------------------------------------------------------

    To clarify states' obligations regarding claims for Medicare cost-
sharing, we proposed to add a new paragraph (d) to 42 CFR 455.410 to 
clearly specify in regulation how States must meet this obligation. 
Specifically, we proposed that, for purposes of determining Medicare 
cost-sharing obligations, the State Medicaid programs must accept 
enrollment of all Medicare-enrolled providers and suppliers (even if a 
provider or supplier is of a type not recognized as eligible to enroll 
in the State Medicaid program) if the provider or supplier otherwise 
meets all Federal Medicaid enrollment requirements. These Federal 
requirements include, but are not limited to, all applicable provisions 
of 42 CFR part 455, subparts B and E. States must process claims from 
such providers requesting that the State determine its cost-sharing 
liability. States are already directed to issue RAs under section 
11325.A of the State Medicaid Manual (stating that the Medicaid MMIS 
must produce remittance advice to providers) as part of their 
responsibility, already required pursuant to 42 CFR 433.112(b)(3), to 
process claims for dually eligible beneficiaries. We noted that neither 
this existing guidance nor the proposed provisions require States to 
recognize or enroll additional provider types for purposes other than 
submission of cost-sharing claims, adjudication of cost-sharing claims, 
and issuance of a Medicaid RA. Accordingly, we noted that States may 
wish to consider a separate enrollment process or provider enrollment 
category specifically for Medicare providers and suppliers for purposes 
of determining cost-sharing, consistent with existing law, 
acknowledging that individual States are in the best position to assess 
the feasibility of this or other possible approaches. We stated that we 
would leave it to States to determine how best to implement these 
requirements consistent with their system needs and capabilities, 
provisions of their Medicaid State plan and State law, and Federal 
Medicaid provider enrollment regulations and sub-regulatory 
guidance.\1379\ However, we encouraged States to consult with CMS to 
help ensure their compliance with 42 CFR 455.410(d) and other Federal 
provider enrollment requirements related to this provision.
---------------------------------------------------------------------------

    \1379\ Medicaid Provider Enrollment Compendium (MPEC).
---------------------------------------------------------------------------

    We proposed that State Medicaid programs and their applicable 
systems be in compliance with proposed Sec.  455.410(d) in time to 
process cost-sharing claims for dually eligible beneficiaries with 
dates of service beginning January 1, 2023, recognizing that, despite 
current MMIS requirements, some States may need to make systems changes 
to comply. We noted that updates to the State MMIS are likely eligible 
for 90/10 Federal medical assistance percentage (FMAP) as set forth in 
1903(a)(3)(A) of the Act. We stated that, if necessary, we will propose 
specific enforcement penalties for non-compliance in future rulemaking. 
We discuss Medicaid burden associated with these system changes in 
section I.H.9 of Appendix A of this final rule.
    We noted that we believe that the requirements of proposed Sec.  
455.410(d) may reduce the number of future bad debt appeals by ensuring 
certain Medicare-enrolled providers and suppliers can enroll with State 
Medicaid programs, receive Medicaid Remittance Advice (RAs), and claim 
Medicare bad debt. In reducing these appeals, we stated that the 
provision would reduce the cost for providers to pursue such appeals 
and subsequent litigation, as well as the costs for CMS to defend them. 
Therefore, we estimate provider and Federal savings from avoiding 
future Medicare bad debt appeals. We discuss this reduction in provider 
and Federal burden in detail in section I.H.9 of Appendix A of this 
final rule.
    Failure of State MMIS to provide a Medicaid RA for cost-sharing 
claims for dually eligible beneficiaries may also contribute to reduced 
access to care. Some providers may choose not to treat, or continue 
treating, dually eligible beneficiaries due to the provider burden 
associated with getting paid for cost-sharing claims; a decrease in 
providers willing to serve the dually eligible population could result 
in fewer health care options for beneficiaries. We noted that we 
believe this provision may have a positive impact on beneficiary access 
to care through reduced provider burden.
    In response to this proposal, we received comments from close to 50 
stakeholders, including States; hospital systems; physician, hospital, 
and LTCH associations; and beneficiary advocacy organizations. Most 
commenters supported this proposal. Several suggested additional 
modifications to Medicaid enrollment or State processing of claims for 
Medicare cost-sharing. Others sought technical clarifications. A few 
commenters expressed concerns about legality and burden. After review 
and consideration of these comments, we are finalizing this proposal as 
proposed. We summarize the major comments in this section of this rule:
    Comment: Numerous commenters supported our proposal, describing 
difficulties providers experience trying to collect Medicaid RA and 
claim Medicare bad debt when the provider has difficulty enrolling with 
the state Medicaid agency. Commenters specifically noted this new 
policy would remove obstacles to providers

[[Page 45500]]

and suppliers serving dually eligible beneficiaries, facilitate 
providers' ability to submit claims for Medicare bad debt, and better 
align state Medicaid enrollment and billing rules with the requirements 
of the Medicare ``must bill'' policy.
    Response: We appreciate the support.
    Comment: Some commenters sought clarification on whether this 
proposal applies to out-of-state providers.
    Response: Under this policy, state Medicaid programs must accept 
enrollment of all Medicare-enrolled providers and suppliers, including 
out-of-state providers and suppliers, (even if a provider or supplier 
is of a type not recognized as eligible to enroll in the State Medicaid 
program) if the provider or supplier otherwise meets all Federal 
Medicaid enrollment requirements. These Federal requirements include, 
but are not limited to, all applicable provisions of 42 CFR part 455, 
subparts B and E. This policy does not require States to enroll out-of-
state providers for purposes other than submission of cost-sharing 
claims, adjudication of cost-sharing claims, and issuance of a Medicaid 
RA.
    Comment: Some commenters sought clarification on whether, under 
this proposal, States would be obligated to enroll ALL eligible 
Medicare providers and suppliers, or only those that apply to enroll in 
Medicaid. These commenters expressed concern that CMS will penalize 
States for those Medicare-enrolled providers and suppliers who choose 
not to enroll with the state Medicaid agency. A commenter expressed 
concern that Medicare-enrolled providers and suppliers will be required 
to enroll in-network with Medicaid MCOs.
    Response: We understand that a Medicare-enrolled provider or 
supplier may choose not to enroll with a state Medicaid agency or as a 
Medicaid MCO network provider, and the State or Medicaid MCO cannot 
compel the provider or supplier to do so. Under this policy, CMS will 
not penalize States for non-enrollment of providers or suppliers who do 
not apply to enroll. Under this policy, state Medicaid programs must 
accept enrollment of all Medicare-enrolled providers and suppliers, 
including out-of-state providers and suppliers, (even if a provider or 
supplier is of a type not recognized as eligible to enroll in the State 
Medicaid program) if the provider or supplier otherwise meets all 
Federal Medicaid enrollment requirements. These Federal requirements 
include, but are not limited to, all applicable provisions of 42 CFR 
part 455, subparts B and E. This applies only to providers who chose to 
enroll in Medicaid for purposes of submission and adjudication of cost-
sharing claims. We note that this policy does not require States to 
recognize or enroll additional provider types for purposes other than 
submission of cost-sharing claims, adjudication of cost-sharing claims, 
and issuance of a Medicaid RA.
    Comment: Some commenters sought clarification on whether, under 
this proposal, States would be required to process cost-sharing claims 
for providers not enrolled in Medicaid and whether States would be 
required to enroll Medicare-providers and suppliers using Medicare 
claims and provider data for purposes of processing the cost-sharing 
claims. We also received several questions and comments about 
operational considerations related to State processing of claims for 
providers not enrolled in Medicaid.
    Response: This provision does not require States to process claims 
for providers who do not enroll with the state Medicaid agency.
    Comment: We received a few suggestions to expand upon this proposal 
to eliminate or streamline the Medicaid provider enrollment process. A 
commenter requested that CMS modify the proposal to allow States to 
make cost-sharing payments to Medicare-enrolled providers without 
screening or enrolling them in Medicaid. Similarly, another commenter 
requested CMS modify the proposal to allow the State to enroll a 
provider in Medicaid for the purposes of processing claims for cost-
sharing without independently obtaining enrollment information, as long 
as the provider is enrolled in Medicare.
    Response: Under current law, States can rely on the results of 
screening performed by Medicare if certain criteria are met. However, 
the State is still required to separately collect the disclosures and 
enroll the provider in their program in order to make payment to a 
provider. We appreciate these comments and are happy to work with the 
State on enrollment issues related to Sec.  455.410(d), including 
opportunities to streamline enrollment.
    Comment: A commenter opposed the proposed policy, writing that 
instead of requiring States to allow eligible Medicare providers to 
enroll in Medicaid, CMS should allow Medicare-only providers and 
suppliers to document their ineligibility as a Medicaid provider and 
submit it to CMS in order to facilitate payment for bad debt without a 
specific Medicaid RA indicating that the claim was not paid. This would 
require the provider to document the ineligibility for State payment 
once instead of maintaining Medicaid enrollment.
    Response: Per sections 1902(a)(10)(E) and 1905(p)(3) of the Act, 
state Medicaid programs are liable for Medicare cost-sharing, including 
deductibles and co-insurance, for QMBs (and, if elected, certain other 
dually eligible individuals). And per 42 CFR 413.89, providers must 
exclude any cost-sharing amount legally owed by the State from Medicare 
bad debt amounts claimed. CMS understands that there are providers who 
never receive State payment of cost-sharing for the services they 
furnish; however, cost-sharing policy differs by state, service, and 
provider type, and changes over time. Therefore, per 42 CFR 413.89, to 
ensure the Medicare bad debt payments exclude the amounts Medicaid must 
pay, it is necessary for providers nationally to evidence state 
liability when claiming Medicare bad debt. We also encourage providers 
to consider whether they could submit alternative documentation 
pursuant to the policy finalized at 85 FR 58432.
    Comment: Several commenters who supported the proposal suggested 
modifications to require States to make the effective dates of Medicaid 
provider enrollments under this regulation retroactive, to the greatest 
extent possible, and exempt from state Medicaid timely billing rules 
all claims submitted for dates of service back to those effective 
dates.
    Response: We appreciate the commenters' support. This comment goes 
beyond the scope of the proposal. However, depending on applicable 
State law and policy, States may have the flexibility to implement 
additional changes per these suggestions as they modify their systems 
to comply with the new rule. We will continue to monitor and assess 
whether additional regulatory changes are needed as the policy is 
implemented.
    Comment: Commenters noted that they appreciated CMS' encouragement 
for States to consider simplified enrollment forms for providers only 
seeking State payment of Medicare cost-sharing. They noted that filling 
out a multiple-page Medicaid enrollment form for what may well be a 
single interaction with a state Medicaid agency in a state on the other 
side of the country just to get a Medicaid RA with zero payment is an 
onerous burden and may lead both to less willingness to treat dually 
eligible individuals or improper and illegal attempts to get payment 
from the QMB individual.
    Response: We appreciate the commenters' support and thank 
commenters for highlighting provider

[[Page 45501]]

burden and beneficiary access and protection issues. This comment goes 
beyond the scope of the proposal. We continue to encourage States to 
adopt a separate enrollment process or provider enrollment category 
specifically for Medicare providers and suppliers for purposes of 
determining cost-sharing, consistent with existing law. We are happy to 
work with States on these enrollment issues related to Sec.  
455.410(d).
    Comment: A commenter indicated that current or planned claims 
system upgrades may impede a State's ability to enact required changes 
by the January 2023 deadline.
    Response: While we understand that States have limited resources to 
implement systems changes, we continue to believe that an 
implementation date of January 1, 2023 allows States ample time to come 
into compliance. Updates to the State MMIS are likely eligible for 90/
10 Federal medical assistance percentage (FMAP) as set forth in 
1903(a)(3)(A) of the Act. As noted in the proposed rule, if necessary, 
we will propose specific enforcement penalties for non-compliance in 
future rulemaking.
    Comment: A commenter urged CMS to strengthen its work to improve 
processing of claims for cost-sharing and bad debt, and to ensure 
States are not imposing undue burden on providers in the enrollment 
process. This commenter suggested CMS finalize this regulation as part 
of more comprehensive monitoring and enforcement of the existing 
statutory requirements.
    Response: CMS is committed to improving access to care for dually 
eligible individuals, which includes reducing burden and promoting 
payment equity for the providers who serve them. As noted in the 
proposed rule, if necessary, we will propose specific enforcement 
penalties for non-compliance in future rulemaking.
    Comment: Commenters encouraged the continuation of the Medicaid RA 
alternative documentation policy developed in the FY 2021 IPPS 
rulemaking for the foreseeable future, suggesting that it provides 
necessary pragmatic flexibility to providers that would otherwise be 
disadvantaged by a State's failure to issue a Medicaid RA, whether that 
failure is due to inappropriate enrollment restrictions or other 
processes that result in the failure to properly process certain types 
of crossover cost-sharing claims.
    Response: The policy finalized at 85 FR 58432 is still in effect. 
In sum, that policy created the Medicaid RA alternative documentation 
policy with a retroactive effective date, to allow providers a way to 
submit alternative documentation to the Medicaid RA that sets forth the 
State's liability for the cost-sharing when a State does not process a 
Medicare crossover claim and issue a Medicaid RA to the provider.
    Comment: A commenter, citing section 1902(kk) of the Act, wrote 
that CMS exceeded its authority by requiring States to enroll providers 
who meet Medicare requirements and Federal Medicaid requirements, but 
who might not meet state Medicaid requirements. This commenter was 
concerned that the proposed changes would limit the ability of the 
State to implement additional screening requirements outlined in state-
specific law and would force the State to enroll Medicare providers who 
would otherwise be excluded for violations of various state criminal 
laws.
    Response: As stated in section X of this final rule, this new 
regulation only requires that States enroll eligible Medicare-enrolled 
providers and suppliers for the purposes of adjudicating and paying 
Medicare cost-sharing; States do not need to enroll eligible Medicare-
enrolled providers and suppliers for all purposes on par with Medicaid 
providers and suppliers that get paid by the State for furnishing 
Medicaid State plan services. As such, we believe it is appropriate to 
apply only the Federal Medicare and Medicaid enrollment requirements. 
We note that, per 42 CFR 424.530(a)(3) and 424.535(a)(3), CMS denies 
and revokes a provider or supplier's Medicare-enrollment based upon 
certain State or Federal felony convictions.
    Comment: A commenter noted that the authorities relevant to this 
proposal included in the proposed rule were incomplete and should be 
corrected.
    Response: We corrected the authorities to section I.A.1 to include 
Section 1902(kk)(3) of the Act and Section 2107(e)(1) of the Act.
    Comment: A commenter questioned if CMS maintains a list of 
Medicare-enrolled provider types with a crosswalk to Medicaid-enrolled 
provider types.
    Response: States may reference the Medicare Claims Processing 
Manual \1380\ to review the Medicare-enrolled providers and supplier 
types.
---------------------------------------------------------------------------

    \1380\ https://www.cms.gov/Regulations-and-Guidance/Guidance/Manuals/Downloads/clm104c26pdf.pdf.
---------------------------------------------------------------------------

    Comment: A few commenters requested additional clarification 
regarding how this proposal impacts specific claims processing and 
payment methodologies. A commenter questioned how this proposal would 
impact instances where the allowed amount for the Medicaid service is 
less than what Medicare has already paid or instances where the State 
either does not offer additional payment or does not cover the service. 
Another commenter questioned if additional fee schedules are required 
for provider types that are not currently covered by the State plan.
    Response: States should adjudicate cost-sharing claims for dually 
eligible beneficiaries per their approved Medicaid State plan; Medicaid 
State plans detail payment methodologies for services not covered by 
the Medicaid program. We are happy to work with States to discuss 
approvable methodologies or potential revisions to the Medicaid State 
plan.
    Comment: Several commenters urged CMS and Congress to continue 
improving policies regarding dually eligible beneficiaries and provider 
payment by eliminating the lesser-of policy. Commenters explained that 
the lesser-of policy creates a financial penalty every time a provider 
serves a dually eligible beneficiary as the provider does not receive 
full, equitable payment for services. Commenters noted that this 
disincentivizes providers from serving dually eligible beneficiaries, 
further impacting the access to care inequities of dually eligible 
beneficiaries.
    Response: Eliminating the lesser-of policy is beyond the scope of 
the proposal, but CMS thanks commenters for these recommendations and 
affirms our commitment to improve access and equity for dually eligible 
beneficiaries.
    As previously noted, after consideration of the public comments we 
received, we are finalizing our proposal to add a new paragraph (d) to 
42 CFR 455.410 to clearly specify in regulation that the State Medicaid 
agency must allow enrollment of all Medicare enrolled providers and 
suppliers for purposes of processing claims to determine Medicare cost-
sharing (as defined in section 1905(p)(3) of the Act) if the providers 
or suppliers meet all Federal Medicaid enrollment requirements, 
including, but not limited to, all applicable provisions of 42 CFR part 
455, subparts B and E. This paragraph (d) applies even if the Medicare-
enrolled provider or supplier is of a type not recognized by the State 
Medicaid Agency. State Medicaid programs and their applicable systems 
must be in compliance with Sec.  455.410(d) in time to process cost-
sharing claims for dually eligible beneficiaries with dates of service 
beginning January 1, 2023.

[[Page 45502]]

    In the proposed rule we noted that, in addition to certain 
Medicare-recognized provider and supplier types having difficulty 
enrolling in some Medicaid programs for purposes of submitting cost-
sharing claims, we understand that some providers report that some 
States may not process certain cost-sharing claims for services that 
are payable by the State under the terms of the Medicaid State plan. We 
noted that we had received feedback from providers that some States 
determine their cost-sharing liability for a Medicare service by 
applying the Medicaid payment and coverage rules for the service as if 
the service (rather than the cost-sharing) were being paid by Medicaid. 
This means that the State MMIS will reject, deny, or return zero 
liability for a claim for Medicare cost-sharing unless the provider 
completes Medicaid documentation and meets Medicaid coverage and 
payment standards. For example, a provider submits a claim for oxygen 
therapy for use in home with a lifetime length of need and the claim 
meets Medicare payment and coverage standards.\1381\ When the provider 
submits this claim for Medicaid payment of cost-sharing (or when 
Medicare ``crosses over'' the claim to the State), the State denies the 
claim because the claim does not meet the State's conditions of 
Medicaid payment for oxygen therapy (that is, the provider must 
complete and sign a State's Medicaid certificate of medical necessity 
or certificate of need, which requires different Medicaid coding and 
modifiers, and has a maximum length of need of 12 months). A State 
operational policy like this creates unnecessary work for providers, 
suppliers, and beneficiaries. It could also prevent the State from 
meeting its actual cost-sharing liability. Building on the provider 
enrollment requirement in proposed Sec.  455.410(d), we considered 
proposing a policy that States must process claims for Medicare cost-
sharing without requiring that the claim meet the Medicaid State plan 
coverage and payment rules for that service. Instead, we requested 
additional feedback from stakeholders on the scope of this practice, 
including State and service specific examples, and noted we will 
consider whether to include such a policy or otherwise address the 
issue in future rulemaking.
---------------------------------------------------------------------------

    \1381\ We note that any remaining unpaid deductible and 
coinsurance amounts associated with oxygen and oxygen equipment paid 
under a Medicare fee schedule cannot be an allowable Medicare bad 
debt.
---------------------------------------------------------------------------

    Several commenters wrote to offer their support for a proposal to 
require States to process claims for Medicare cost-sharing without 
requiring that the claim meet the Medicaid State plan coverage and 
payment rules for that service. None commented in opposition. We will 
continue to consider this issue for future rulemaking.

C. Medicare Shared Savings Program--Policy Changes (Sec.  425.600)

1. Background
    The Medicare Shared Savings Program (Shared Savings Program) was 
established under section 1899 of the Act to facilitate coordination 
and cooperation among providers and suppliers to improve the quality of 
care for Medicare fee-for-service (FFS) beneficiaries and reduce the 
rate of growth in expenditures under Medicare Parts A and B. Eligible 
groups of providers and suppliers, including physicians, hospitals, and 
other health care providers, may participate in the Shared Savings 
Program by forming or participating in an accountable care organization 
(ACO). The regulations implementing the Shared Savings Program are 
codified at 42 CFR part 425. The final rule establishing the Shared 
Savings Program appeared in the November 2, 2011 Federal Register 
(Medicare Program; Medicare Shared Savings Program: Accountable Care 
Organizations; final rule (76 FR 67802)). A complete list of all of the 
statutes and regulations pertaining to the Shared Savings Program is 
located at https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/sharedsavingsprogram/program-statutes-and-regulations.
    A final rule redesigning the Shared Savings Program appeared in the 
December 31, 2018 Federal Register titled ``Medicare Program: Medicare 
Shared Savings Program; Accountable Care Organizations-Pathways to 
Success and Uncontrollable Circumstances Policies for Performance Year 
2017'' (83 FR 67816) (hereinafter referred to as the ``December 2018 
final rule''). In the December 2018 final rule, we finalized a number 
of policies for the Shared Savings Program, including a redesign of the 
participation options available under the program to encourage ACOs to 
transition to two-sided models (in which they may share in savings and 
are accountable for repaying shared losses); new tools to support 
coordination of care across settings and strengthen beneficiary 
engagement; and revisions to ensure rigorous benchmarking.
    In the December 2018 final rule, we established the BASIC track in 
a new provision at Sec.  [thinsp]425.605. The BASIC track includes an 
option for eligible ACOs to begin participation under a one-sided model 
and incrementally phase-in risk (using a loss recoupment limit 
calculated based on ACO participant revenue and capped at a percentage 
of the ACO's updated benchmark) and potential reward over the course of 
a single agreement period, an approach referred to as the glide path 
(83 FR 67841). The glide path includes five levels: A one-sided model 
available only for the first 2 consecutive performance years (PYs) of 
an ACO's initial 5-year agreement period, each year of which is 
identified as a separate level (Levels A and B); and three levels of 
progressively higher risk and potential reward in PYs 3 through 5 of 
the agreement period (Levels C, D, and E). Eligible ACOs that have 
previously participated in Track 1 of the Shared Savings Program may 
enter the glide path at Level B. ACOs are automatically advanced along 
the progression of risk/reward levels at the start of each performance 
year, over the course of a 5-year agreement period, unless the ACO 
elects to advance more quickly, until ACOs reach the BASIC track's 
maximum level of risk/reward (Level E) (83 FR 67844). Level E qualifies 
as an Advanced Alternative Payment Model and clinicians in ACOs 
participating in Level E of the BASIC track may qualify for APM 
incentive payments under the Quality Payment Program if they meet the 
criteria to become Qualifying APM Participants (QPs). For ACOs that 
entered the BASIC track's glide path for an agreement period beginning 
on July 1, 2019, the progression through the levels of risk and 
potential reward spans 6 performance years, including the ACO's first 
performance year from July 1, 2019, through December 31, 2019; these 
ACOs were not automatically advanced to the next risk/reward level at 
the start of PY 2020 (for more information, see Sec. Sec.  
425.200(b)(4)(ii) and (c)(3) and 425.600(a)(4)(i)(B)(2)(i)).
    As of January 1, 2021, there are 477 Shared Savings Program ACOs 
serving approximately 10.7 million Medicare FFS beneficiaries across 
the country: 41 percent of ACOs (195 of 477) are currently 
participating under two-sided shared savings and shared losses models; 
and 194 ACOs are participating under the BASIC track's glide path, 
including 163 ACOs in one-sided Levels A and B and 31 ACOs in two-sided 
Levels C and D. For PY 2021, 6 ACOs elected to advance more quickly 
along the glide path to Level E for a total of 69 ACOs currently 
participating under Level E of the BASIC track.
    The COVID-19 pandemic and the resulting ongoing public health 
emergency (PHE), as defined in 42 CFR

[[Page 45503]]

400.200, have continued to create a lack of predictability for many 
ACOs regarding the impact of utilization changes on beneficiary 
assignment and performance year expenditures. The PHE has disrupted 
population health activities as clinicians, care coordinators and 
financial and other resources are diverted to address immediate needs, 
including acute care and vaccine delivery. The lack of predictability 
and disrupted population health activities created concern for some 
ACOs regarding the impact on their Shared Savings Program performance 
and the potential for shared losses. In the interim final rule with 
comment period (IFC) that appeared in the May 8, 2020 Federal Register 
(85 FR 27575 and 27576) (hereinafter referred to as the ``May 2020 
COVID-19 IFC''), we modified the Shared Savings Program policy of 
automatic advancement along the glide path to allow BASIC track ACOs 
participating in the glide path the option to forgo the first automatic 
advancement along the glide path's increasing levels of risk and 
potential reward. We subsequently finalized the modified policy without 
change in the CY 2021 Physician Fee Schedule (PFS) final rule (85 FR 
84767 through 84769). Under the terms of the current regulations, BASIC 
track ACOs that elected this option for performance year 2021 will be 
automatically advanced for performance year 2022 to the level at which 
they would have otherwise participated under automatic advancement if 
they had not elected the option. Seventy-four percent of eligible BASIC 
track ACOs (148 of 201) elected the 1-year ``freeze'' for PY 2021. 
Another 18 BASIC track ACOs elected to take on risk, by either 
automatically transitioning to Level C or by advancing more quickly 
along the glide path.
2. Basic Track Risk ``Freeze'' Option for PY 2022
    Due to the continued PHE for COVID-19, ACOs and other stakeholders 
requested that the exception that allowed ACOs in the BASIC track to 
opt for a risk ``freeze'' for PY 2021 be continued for PY 2022. While 
the PHE for COVID-19 remains ongoing, new considerations and challenges 
that impact ACO operations and expenditures continue to emerge: (1) The 
effects of cancelling or delaying services during the PHE, including 
the expectation that beneficiaries who may have gone without routine 
and acute care during the PHE will need increased care; (2) the 
emergence of new variants and mutations of the existing variants of the 
coronavirus that causes COVID-19; and (3) the resources involved in 
vaccinating the Medicare population. Given the inability of ACOs to 
anticipate the extent to which these issues may impact expenditures 
during PY 2022 and effectively prepare for these issues, we believe 
providing additional flexibilities to address the uncertainty produced 
by the ongoing PHE for COVID-19 is essential to encourage ACOs to 
continue participating in the Shared Savings Program during the ongoing 
PHE for COVID-19.
    As noted previously, in the May 2020 COVID-19 IFC, we adopted a new 
provision at Sec.  425.600(a)(4)(i)(B)(2)(iii) to provide the 
opportunity for ACOs participating in the BASIC track's glide path to 
maintain their level of participation for PY 2021 and not automatically 
progress to a higher level along the glide path. For PY 2022, the ACOs 
that voluntarily elected to ``freeze'' their participation level in 
accordance with Sec.  425.600(a)(4)(i)(B)(2)(iii) are currently 
required to progress to the level of participation they would have been 
automatically advanced to, absent the election to maintain their 
participation level for PY 2021. For example, if an ACO in Level B of 
the BASIC track in PY 2020 elected to maintain its participation in 
Level B for PY 2021, the ACO will be automatically transitioned to 
Level D for PY 2022. Level D of the BASIC track is a two-sided model 
with a 50-percent sharing rate and 30-percent loss sharing rate, not to 
exceed 4 percent of ACO participant revenue capped at 2 percent of the 
ACO's updated benchmark.
    As discussed in the FY 2022 IPPS/LTCH PPS proposed rule (86 FR 
25677), stakeholders have expressed concern that as a result of the 
unpredictable circumstances of the PHE and the sustained impacts of the 
COVID-19 pandemic during PY 2021, some ACOs may terminate their 
participation in the program if they are required to automatically 
transition to downside risk or a higher level of downside risk for PY 
2022. Specifically, stakeholders requested that we allow a second 
``freeze'' to permit ACOs participating in the BASIC track's glide path 
to opt out of automatic advancement from their current level of 
participation for PY 2022.
    As detailed in the May 2020 COVID-19 IFC (85 FR 27576), per Sec.  
[thinsp]425.204(f)(3)(iii), an ACO entering an agreement period in 
Level A or Level B of the BASIC track must demonstrate the adequacy of 
its repayment mechanism prior to the start of any performance year in 
which it either elects to participate, or is automatically transitioned 
to a two-sided model of the BASIC track, including Level C, Level D or 
Level E. In the FY 2022 IPPS/LTCH PPS proposed rule, we expressed our 
belief that it would be appropriate to provide the flexibility to ACOs, 
particularly those that would otherwise automatically transition to 
Level C or D of the BASIC track for PY 2022, to delay transitioning to 
two-sided risk, thus delaying the requirement to establish a repayment 
mechanism prior to the start of PY 2022. This flexibility would allow 
these ACOs the option to put financial resources that might otherwise 
be used to establish a repayment mechanism towards continuing to care 
for their beneficiaries during the ongoing pandemic. Currently, the 
Shared Savings Program has 163 ACOs participating under Level A or 
Level B of the BASIC track that are scheduled to automatically advance 
to Level C or Level D on January 1, 2022.
    We also expressed concern that the PHE for COVID-19 has made 
expenditures and utilization more difficult to predict and that ACOs 
may be more risk-averse as patient care patterns have been altered by 
the pandemic. ACOs cannot know the full impact that the PHE for COVID-
19 and the related changes in health care utilization will have on 
their total expenditures or their assigned beneficiary population. In 
addition, we noted that the duration of the PHE for COVID-19 remained 
uncertain, and it is unclear whether the PHE will extend into 2022, 
such that shared losses owed by ACOs participating under two-sided 
payment models would be mitigated under the Shared Savings Program's 
extreme and uncontrollable circumstances policy. Therefore, we proposed 
that ACOs participating in the BASIC track's glide path may elect to 
maintain their current level of risk under the BASIC track for PY 2022. 
Specifically, we proposed that before the automatic advancement for PY 
2022, an applicable ACO may elect to remain in the same level of the 
BASIC track's glide path in which it participated during PY 2021. For 
PY 2023, an ACO that elects this advancement deferral option would be 
automatically advanced to the level of the BASIC track's glide path in 
which it would have participated during PY 2023 if it had advanced 
automatically to the required level for PY 2022 (unless the ACO elects 
to advance more quickly before the start of PY 2023). For example, if 
an ACO that participated in the BASIC track Level A for PY 2020, then 
automatically advanced to Level B in PY 2021, elects to maintain its

[[Page 45504]]

current level of participation for PY 2022, it would participate under 
Level B for PY 2022 and then would automatically advance to Level D for 
PY 2023. The ACO could also elect to advance more quickly by opting to 
move to Level E instead of Level D for PY 2023, in which case the ACO 
would participate under Level E for the remainder of its agreement 
period. In contrast, if an ACO that participated in the BASIC track 
Level B for PY 2020 elected to maintain its participation at Level B 
for PY 2021, but does not elect to maintain its participation under 
Level B for PY 2022, the ACO would automatically advance to Level D for 
PY 2022, unless it chooses to advance more quickly.
    Under this proposal, an ACO that elects to freeze its participation 
level for both PY 2021 and PY 2022 would be automatically advanced for 
PY 2023 to the level of the BASIC track's glide path in which it would 
have participated during PY 2023, absent both of its elections to 
freeze. For example, if an ACO participating in the BASIC track, Level 
B, in PY 2020 elected to maintain its current level of participation 
for PY 2021, and then chose again to maintain its current level of 
participation for PY 2022, it would continue to participate under Level 
B in both PY 2021 and PY 2022, before automatically advancing to Level 
E for PY 2023. In this example, the ACO would participate under Level E 
for the remainder of its agreement period. We provided the following 
table to illustrate the potential scenarios for ACOs that elect to 
maintain their current level of risk for PY 2021 or PY 2022 or both. 
This chart is intended only to address ACOs that may want to elect to 
``freeze'' for PY 2022 and does not address other participation 
options, such as the exception that allows certain ACOs to elect to 
remain in Level B for an additional performance year, and then 
automatically advance to Level E for the final 2 participation years of 
their agreement period as specified at Sec.  
425.600(a)(4)(i)(B)(2)(ii).
[GRAPHIC] [TIFF OMITTED] TR13AU21.315

    We proposed that the ACO's voluntary election to maintain its 
participation level for PY 2022 must be made in the form and manner and 
by a deadline established by CMS, and an ACO executive who has the 
authority to legally bind the ACO must certify the election.
    We proposed to redesignate Sec.  425.600(a)(4)(i)(B)(2)(iv) as 
Sec.  425.600(a)(4)(i)(B)(2)(v). Additionally, we proposed to add a new 
Sec.  425.600(a)(4)(i)(B)(2)(iv) to allow ACOs currently participating 
in the BASIC track's glide path to elect to maintain their current 
participation level for PY 2022. We also noted that we intended to 
continue to monitor the PHE for COVID-19 and assess its impact on the 
Shared Savings Program, and explained that we would address any 
additional flexibilities that may be warranted as a result of the 
ongoing PHE through future notice and comment rulemaking.
    Lastly, we noted that in the May 2020 COVID-19 IFC (85 FR 27625), 
we revised the regulations at Sec.  425.600 to allow BASIC track ACOs 
to maintain their participation level for PY 2021 by redesignating 
paragraph (a)(4)(i)(B)(2)(iii) as paragraph (a)(4)(i)(B)(2)(iv) and 
adding a new paragraph (a)(4)(i)(B)(2)(iii). However, we inadvertently 
omitted the revision to the cross-reference in paragraph 
(a)(4)(i)(B)(3). In the FY 2022 IPPS/LTCH PPS proposed rule, we 
proposed to make further revisions to Sec.  425.600(a)(4)(i)(B)(2), 
which would also affect the cross-reference in paragraph 
(a)(4)(i)(B)(3). Therefore, we proposed to revise Sec.  
425.600(a)(4)(i)(B)(3) to remove the reference to paragraph 
(a)(4)(i)(B)(2)(iii) and replace it with a reference to paragraph 
(a)(4)(i)(B)(2)(v).
    Comment: Many commenters expressed support for CMS' proposal to 
permit eligible ACOs to voluntarily elect to maintain their level of 
risk/reward within the BASIC track's glide path for PY 2022, and 
particularly appreciated the additional stability and flexibility that 
this option would afford them.
    Response: We appreciate commenters' support for allowing ACOs 
participating in the BASIC track's glide path the opportunity to elect 
to remain in the same level of the BASIC track's glide path in which 
they participated for PY 2021, for PY 2022.

[[Page 45505]]

    Comment: A number of commenters urged CMS to reconsider our 
decision to move ACOs at the start of PY 2023 to the level of risk in 
which they would have participated for PY 2023, absent the freeze. 
Commenters expressed concern that skipping a level would be challenging 
under normal circumstances, but the COVID-19 PHE has involved 
continued, extenuating circumstances, the effects of which on cost and 
quality remain to be seen. Therefore, according to these commenters, 
finalizing this automatic advancement policy would not allow ACOs 
sufficient opportunity to focus on recovering financially and on 
patient care, and would jeopardize an ACO's ability to both remain and 
succeed in the program. These commenters recommended instead that ACOs 
that elect to freeze their participation level for PY 2022 at their 
current level for PY 2021 should enter PY 2023 at the level of the 
BASIC track glide path that they would have entered for PY 2022, absent 
the freeze.
    Response: Of the BASIC track ACOs that are participating in PY 
2021, 75 percent are in a second or subsequent agreement period. All of 
these ACOs have prior experience participating in the Shared Savings 
Program; some of these ACOs have participated in the program 
continuously since 2012. Although the PHE for COVID-19 has presented 
unprecedented challenges and diverted ACO attention and resources from 
improving quality and lowering costs of care for their assigned 
beneficiaries, which justifies the ``freeze'' policy for eligible ACOs 
participating on the BASIC track's glide path for PY 2021 and PY 2022, 
we believe that by gaining additional experience in the Shared Savings 
Program during performance years 2021 and 2022 within the context of 
the PHE for COVID-19, ACOs are more prepared to progress to higher 
levels of risk and potential reward within the BASIC track's glide path 
beginning in PY 2023, if not sooner, at the ACO's election. ACOs have 
managed dynamic circumstances during the pandemic, shifting focus from 
preventive and maintenance care to testing and treating beneficiaries 
for COVID-19, and the delivery of the COVID-19 vaccine, as well as 
transitioning health care providers from in-person healthcare visits to 
telehealth. In addition, we believe that it is beneficial for ACOs to 
participate in the highest levels of the BASIC Track prior to renewing 
in a new agreement period where they would be required to participate 
in the ENHANCED Track or Level E of the BASIC Track. For example, a 
Level A ACO that elected the option to maintain their risk level for 
both PY 2021 and PY 2022, would then advance to Level D for PY 2023, 
providing the opportunity to participate at a more moderate level of 
risk before having to advance to the highest level of risk under the 
basic track, Level E. As noted previously, we intend to continue to 
monitor the PHE for COVID-19 and assess its impact on the Shared 
Savings Program, and we will address any additional flexibilities that 
may be warranted through future notice and comment rulemaking.
    Therefore, at this time, we decline commenters' suggestions that we 
further slow ACOs' progression along the BASIC track's glide path by 
allowing ACOs that elect to maintain their current position on the 
glide path for PY 2022 to resume their progression at the level they 
would have entered for PY 2022, absent the freeze.
    Comment: Some commenters expressed concern that, given the timing 
of the application cycle and the display of the final rule, ACOs would 
have insufficient time and information available before having to 
decide whether to freeze their participation level or advance along the 
glide path and submit a repayment mechanism.
    Response: The FY 2022 IPPS/LTCH PPS proposed rule was available for 
public inspection via of the Office of the Federal Register on April 
27, 2021. Therefore, we believe ACOs have had sufficient time to review 
the proposed policy and determine their preferred participation option 
for PY 2022. As discussed in the proposed rule (86 FR 25679), we gave 
ACOs the opportunity during the change request cycle for PY 2022 to 
indicate whether they were interested in maintaining their current 
level of participation in the event the proposed policy were to be 
finalized for PY 2022. During the PY 2022 Change Request Cycle Phase 1 
initial submission period, 79 out of 176 (45 percent) of eligible ACOs 
indicated interest in maintaining participation at their current level 
for PY 2022. This election will remain available through the Phase 1 
second request for information (Phase 1 RFI-2) due by noon Eastern 
Daylight Time on September 10, 2021. We also began educating ACOs about 
this proposed policy after the April 27, 2021 public filing of the FY 
2022 IPPS/LTCH PPS proposed rule. The potential for an election to 
``freeze'' was communicated to currently participating ACOs via the ACO 
Spotlight Newsletter, our ACO-Management System and via conversations 
with our ACO coordinators.
    As a result, we do not believe providing additional time for ACOs 
to determine their preferred participation option for PY 2022 is 
necessary, as ACOs have had time to consider their options, and whether 
they prefer to elect to maintain their participation level for PY 2022. 
Furthermore, ACOs that elect to remain at their current participation 
level, but that would otherwise have been required to enter two-sided 
risk in PY 2022 will not need additional time to secure a repayment 
mechanism. ACOs that do not elect to freeze their current participation 
level for PY 2022 and that will advance to a two-sided model for PY 
2022 should have already anticipated the requirement to have a 
repayment mechanism ready for PY 2022 and started taking the necessary 
steps to establish one.
    Comment: A commenter opposed the proposed policy to allow eligible 
ACOs to maintain their current risk level, citing that the COVID-19 
pandemic has eased significantly in 2021 as a result of widely 
available and effective vaccines, and suggested that such an 
accommodation under the current circumstances was unnecessary.
    Response: We appreciate the commenter's feedback. However, we 
decline to modify the proposal with respect to PY 2022, which we are 
finalizing as proposed. According to other commenters, the COVID-19 PHE 
continues to affect ACO operations, as ACO participants seek to balance 
their response to the PHE, while also managing normal operations, 
implementing care redesigns and improving the quality of care provided 
to beneficiaries. As a result, we continue to believe allowing eligible 
ACOs to maintain their current risk level for PY 2022 is a necessary 
flexibility that will afford ACOs additional stability as they continue 
to deal with the effects of the PHE.
    Comment: A few of the comments received were out outside the scope 
of this rulemaking, including comments concerning quality reporting and 
the use of reinsurance as a repayment mechanism.
    Response: Comments of this nature are beyond the scope of the 
policies discussed in the proposed rule and are not being addressed in 
this final rule.
    After considering the comments received, we are finalizing the 
proposed policy without modification. Accordingly, we are finalizing 
the redesignation of Sec.  425.600(a)(4)(i)(B)(2)(iv) as Sec.  
425.600(a)(4)(i)(B)(2)(v) and the addition of a new Sec.  
425.600(a)(4)(i)(B)(2)(iv) to allow ACOs currently participating in the

[[Page 45506]]

BASIC track's glide path to elect to maintain their current 
participation level for PY 2022. We did not receive comments on the 
proposal to revise Sec.  425.600(a)(4)(i)(B)(3) to remove the reference 
to paragraph (a)(4)(i)(B)(2)(iii) and replace it with a reference to 
paragraph (a)(4)(i)(B)(2)(v); and therefore, we are also finalizing 
this revision as proposed without modification.

XI. MedPAC Recommendations

    Under section 1886(e)(4)(B) of the Act, the Secretary must consider 
MedPAC's recommendations regarding hospital inpatient payments. Under 
section 1886(e)(5) of the Act, the Secretary must publish in the annual 
proposed and final IPPS rules the Secretary's recommendations regarding 
MedPAC's recommendations. We have reviewed MedPAC's March 2021 ``Report 
to the Congress: Medicare Payment Policy'' and have given the 
recommendations in the report consideration in conjunction with the 
policies set forth in this final rule. MedPAC recommendations for the 
IPPS for FY 2022 are addressed in Appendix B to this final rule.
    For further information relating specifically to the MedPAC reports 
or to obtain a copy of the reports, contact MedPAC at (202) 653-7226, 
or visit MedPAC's website at: http://www.medpac.gov.

XII. Other Required Information

A. Publicly Available Files

    IPPS-related data are available on the internet for public use. The 
data can be found on the CMS website at: https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/AcuteInpatientPPS/index. We listed the 
data files available in the FY 2022 IPPS/LTCH PPS proposed rule (86 FR 
25679 through 25681).
    Commenters interested in discussing any data files used in 
construction of this final rule should contact Michael Treitel at (410) 
786-4552.

B. Collection of Information Requirements

1. Statutory Requirement for Solicitation of Comments
    Under the Paperwork Reduction Act (PRA) of 1995, we are required to 
provide 60-day notice in the Federal Register and solicit public 
comment before a collection of information requirement is submitted to 
the Office of Management and Budget (OMB) for review and approval. In 
order to fairly evaluate whether an information collection should be 
approved by OMB, section 3506(c)(2)(A) of the PRA of 1995 requires that 
we solicit comment on the following issues:
     The need for the information collection and its usefulness 
in carrying out the proper functions of our agency.
     The accuracy of our estimate of the information collection 
burden.
     The quality, utility, and clarity of the information to be 
collected.
     Recommendations to minimize the information collection 
burden on the affected public, including automated collection 
techniques.
    In the FY 2022 IPPS/LTCH PPS proposed rule, we solicited public 
comment on each of these issues for the following sections of this 
document that contain information collection requirements (ICRs).
2. ICRs Relating to the Hospital Readmissions Reduction Program
    In section V.G. of the preamble of this final rule, we discuss 
requirements for the Hospital Readmissions Reduction Program. In this 
final rule, we are not removing or adopting any new measures into the 
Hospital Readmissions Reduction Program for FY 2022. All six of the 
current Hospital Readmissions Reduction Program's measures are claims-
based measures. We believe that continuing to use these claims-based 
measures would not create or reduce any information collection burden 
for hospitals because they will continue to be collected using Medicare 
FFS claims that hospitals are already submitting to the Medicare 
program for payment purposes.
    In section V.G.6. of the preamble of this final rule, we are 
finalizing our proposal to suppress the Hospital 30-Day, All-Cause, 
Risk-Standardized Readmission Rate (RSRR) following Pneumonia 
Hospitalization measure (NQF #0506) due to the significant impact of 
the COVID-19 PHE on this measure, for FY 2023, as well as technical 
measure specification updates to the five remaining condition/
procedure-specific readmission measures. However, we believe that the 
updates to these claims-based measures would not create or reduce any 
information collection burden for hospitals because they will continue 
to be collected using Medicare FFS claims that hospitals are already 
submitting to the Medicare program for payment purposes.
    We did not receive comments regarding the ICRs for the Hospital 
Readmissions Reduction Program.
3. ICRs for the Hospital Value-Based Purchasing (VBP) Program
    In section V.H. of the preamble of the final rule, we discuss our 
finalized requirements for the Hospital VBP Program. Specifically with 
respect to quality measures, we are finalizing our proposals to 
suppress the Hospital Consumer Assessment of Healthcare Providers and 
Systems (HCAHPS) Survey, Medicare Spending per Beneficiary (MSPB), and 
the five hospital-acquired infection (HAI) measures for the FY 2022 
program year. We are also finalizing the removal of the CMS PSI 90 
measure beginning with the FY 2023 program year and our proposal to 
suppress the Hospital 30-Day, All-Cause, Risk-Standardized Mortality 
Rate Following Pneumonia Hospitalization (MORT-30-PN) measure for the 
FY 2023 program year. Because the FY 2022 and FY 2023 Hospital VBP 
Program will use data that are also used to calculate quality measures 
in other programs and Medicare FFS claims data that hospitals are 
already submitting to CMS for payment purposes, we stated in the 
proposed rule that we did not anticipate any change in burden 
associated with these policies.
    We did not receive any comments regarding the ICRs for the Hospital 
VBP Program and are finalizing our proposals without modification.
4. ICRs for the Hospital Acquired Condition (HAC) Reduction Program
    In this rule, we are not removing any measures, adopting any new 
measures into the HAC Reduction Program, or updating our validation 
procedures.\1382\ The HAC Reduction Program has previously adopted six 
measures: The CMS PSI 90 measure and five CDC NHSN HAI measures. We do 
not believe that the claims-based CMS PSI 90 measure in the HAC 
Reduction Program creates or reduces any burden for hospitals because 
it is collected using Medicare FFS claims that hospitals are already 
submitting to the Medicare program for payment purposes. Accordingly, 
we do not believe that our policy, finalized in section V.I.3.d. of the 
preamble of this final rule, to suppress third and fourth quarter CY 
2020 data from the CMS PSI 90 measure from FY 2023 and FY 2024 Total 
HAC Scores create or reduce any information collection burden for 
hospitals.
---------------------------------------------------------------------------

    \1382\ Burden associated with the validation procedures in the 
HAC Reduction Program are accounted for under OMB Control Number 
0938-1352.
---------------------------------------------------------------------------

    We note that the burden associated with collecting and submitting 
data for the remaining five measures, the HAI

[[Page 45507]]

measures (CAUTI, CLABSI, Colon and Abdominal Hysterectomy SSI, MRSA 
bacteremia, and CDI) via the NHSN system is captured under a separate 
OMB control number, 0920-0666 (expiration November 30, 2021), and 
therefore our finalized policy to suppress third and fourth quarter CY 
2020 data from these measures from FY 2022 and FY 2023 Total HAC Scores 
did not impact our burden estimates.
    We did not receive comments regarding the ICRs for the HAC 
Reduction Program.
5. ICR for Repeal of Market-Based MS-DRG Relative Weight Data 
Collection
    In the FY 2021 IPPS/LTCH PPS final rule, we finalized a requirement 
for a hospital to report on the Medicare cost report the median payer-
specific negotiated charge that the hospital has negotiated with all of 
its MA organization payers, by MS-DRG, for cost reporting periods 
ending on or after January 1, 2021 (85 FR 58873 through 58892); this 
data collection requirement was specified in 42 CFR 413.20(d)(3). 
Instructions for the reporting of this market-based data on the 
Medicare cost report were discussed in the revision of the currently 
approved OMB control number 0938-0050 published on November 10, 2020 
(for more information we refer readers to (https://www.federalregister.gov/documents/2020/11/10/2020-24948/agency-information-collection-activities-proposed-collection-comment-request 
and https://www.cms.gov/regulations-and-guidancelegislationpaperworkreductionactof1995pra-listing/cms-2552-10).
    As discussed in section V.L. we are repealing this market-based 
data collection requirement and the market-based MS-DRG relative weight 
methodology that was adopted effective for FY 2024, and will continue 
using the existing cost-based methodology for calculating the MS-DRG 
relative weights for FY 2024 and subsequent fiscal years. In the FY 
2021 IPPS/LTCH PPS final rule, we estimated an annual burden per 
hospital and estimated total annual burden for all hospitals to comply 
with the requirements previously set forth in 42 CFR 413.20(d)(3) (85 
FR 59015). These burden estimates were never approved.
6. ICRs for the Hospital Inpatient Quality Reporting (IQR) Program
a. Background
    The Hospital IQR Program (formerly referred to as the Reporting 
Hospital Quality Data for Annual Payment Update (RHQDAPU) Program) was 
originally established to implement section 501(b) of the MMA, Public 
Law 108-173. OMB has currently approved 1,572,443 hours of burden and 
approximately $61 million under OMB control number 0938-1022, 
accounting for information collection burden experienced by 
approximately 3,300 IPPS hospitals and 1,100 non-IPPS hospitals for the 
FY 2023 payment determination. In the proposed rule (86 FR 25682) and 
this final rule, we describe the burden changes regarding collection of 
information under OMB control number 0938-1022 (expiration date 
December 31, 2022) for IPPS hospitals.
    For more detailed information on our finalized policies for the 
Hospital IQR Program, we refer readers to section IX.C. of this final 
rule. We are finalizing most of our proposals which will affect the 
information collection burden associated with the Hospital IQR Program. 
As discussed, we are finalizing the adoption of two measures that we 
expect to affect our collection of information burden estimates: (1) 
The Maternal Morbidity structural measure beginning with a shortened 
reporting period from October 1 through December 31, 2021 (affecting 
the FY 2023 payment determination), followed by annual reporting 
periods for subsequent years; and (2) the Hybrid Hospital-Wide All-Risk 
Standardized Mortality measure with Claims and Electronic Health Record 
Data (Hybrid HWM measure) beginning with a one-year voluntary reporting 
period (July 1, 2022 through June 30, 2023), followed by mandatory 
reporting beginning with the July 1, 2023 through June 30, 2024 
reporting period/FY 2026 payment determination. Details on these 
policies as well as the expected burden changes are discussed further 
in this section of this final rule.
    We are also finalizing several policies which would not affect the 
information collection burden associated with the Hospital IQR Program. 
As discussed in section IX.C. of the preamble to this final rule, we 
are finalizing our proposals to: (1) Adopt the Maternal Morbidity 
structural measure beginning with a shortened reporting period from 
October 1 through December 31, 2021 (affecting the FY 2023 payment 
determination), followed by annual reporting periods (affecting the FY 
2024 payment determination and subsequent years); (2) adopt the 
Hospital Harm--Severe Hyperglycemia electronic clinical quality measure 
(eCQM) beginning with the CY 2023 reporting period/FY 2025 payment 
determination; (3) adopt the Hospital Harm--Severe Hypoglycemia eCQM 
beginning with the CY 2023 reporting period/FY 2025 payment 
determination; (4) adopt the COVID-19 Vaccination Coverage among HCP 
measure beginning with a shortened reporting period from October 1 to 
December 31, 2021, affecting the CY 2021 reporting period/FY 2023 
payment determination; (5) remove the Admit Decision Time to ED 
Departure Time for Admitted Patients (ED-2) eCQM measure beginning with 
the CY 2024 reporting period/FY 2026 payment determination; (6) remove 
the Exclusive Breast Milk Feeding (PC-05) eCQM measure beginning with 
the CY 2024 reporting period/FY 2026 payment determination; (7) remove 
the Discharged on Statin Medication (STK-06) eCQM measure beginning 
with the CY 2024 reporting period/FY 2026 payment determination; (8) 
revise the Program's regulations at 42 CFR 412.140(a)(2) by replacing 
the term ``QualityNet Administrator'' with the term ``QualityNet 
security official'' and 42 CFR 412.140(e)(2)(iii) by replacing the term 
``QualityNet system administrator'' with the term ``QualityNet security 
official''; (9) revise the Program's regulations at 42 CFR 
412.140(a)(1) and 42 CFR 412.140(c)(2)(i) to remove references to 
``QualityNet.org'' and replacing it with ``QualityNet website''; (10) 
require the use of the 2015 Edition Cures Update for certification 
criteria beginning with the CY 2023 reporting period/FY 2025 payment 
determination and for subsequent years for both eCQMs and hybrid 
measures; and (11) extend the effects of educational reviews for fourth 
quarter data such that if an error is identified during the education 
review process for fourth quarter data, we would use the corrected 
quarterly score to compute the final confidence interval used for 
payment determination beginning with validations affecting the FY 2024 
payment determination. As discussed in the preamble of this final rule, 
we do not expect these provisions to affect our information collection 
burden estimates. We note that we are not finalizing our proposals to 
remove: The Anticoagulation Therapy for Atrial Fibrillation/Flutter 
(STK-03) eCQM; and the Death Rate Among Surgical Inpatients with 
Serious Treatable Complications (CMS PSI-04) Claims-Based Measure.
    In the FY 2021 IPPS/LTCH PPS final rule (85 FR 59008), we estimated 
that reporting measures for the Hospital IQR Program could be 
accomplished by staff with a median hourly wage of $19.40 per hour. We 
note that since then, more recent wage data have become available, and 
we are updating the wage rate used

[[Page 45508]]

in these calculations in this proposed rule. The most recent data from 
the Bureau of Labor Statistics reflects a median hourly wage of $20.50 
per hour for a medical records and health information technician 
professional.\1383\ We calculated the cost of overhead, including 
fringe benefits, at 100 percent of the median hourly wage, consistent 
with previous years. This is necessarily a rough adjustment, both 
because fringe benefits and overhead costs vary significantly by 
employer and methods of estimating these costs vary widely in the 
literature. Nonetheless, we believe that doubling the hourly wage rate 
($20.50 x 2 = $41.00) to estimate total cost is a reasonably accurate 
estimation method. Accordingly, we will calculate cost burden to 
hospitals using a wage plus benefits estimate of $41.00 per hour 
throughout the discussion in this section of this rule for the Hospital 
IQR Program.
---------------------------------------------------------------------------

    \1383\ U.S. Bureau of Labor Statistics. Occupational Outlook 
Handbook, Medical Records and Health Information Technicians. 
Accessed on February 18, 2021; available at: https://www.bls.gov/oes/2019/may/oes292098.htm.
---------------------------------------------------------------------------

b. Information Collection Burden Estimate for the Maternal Morbidity 
Structural Measure
    In section IX.C.5.a. of the preamble of this final rule, we are 
finalizing the adoption of the Maternal Morbidity Structural measure 
beginning with the CY 2021 reporting period/FY 2023 payment 
determination as proposed. The shortened data submission period for the 
Maternal Morbidity structural measure would run from October 1 through 
December 31, 2021, followed by annual reporting periods for subsequent 
years. Reporting on the Maternal Morbidity structural measure will 
involve each hospital responding to a single question using a web-based 
tool available via the QualityNet Secure Portal (also referred to as 
the Hospital Quality Reporting (HQR) System) with one of the following 
response options: (A) ``Yes''; (B) ``No''; or (C) ``N/A (our hospital 
does not provide inpatient labor/delivery care).''
    We are finalizing our proposal to require hospitals to submit the 
response on an annual basis during the submission period. In summary, 
because we are finalizing our proposal in section IX.C.5.a. of the 
preamble of this final rule to adopt the Maternal Morbidity structural 
measure, we estimate the information collection burden associated with 
this finalized structural measure to be no more than 5 minutes per 
hospital per year, as it involves responding to a single question one 
time per year for a given reporting period. Using the estimate of 5 
minutes (or 0.083 hours) per hospital per year, and the updated wage 
estimate as described previously, we estimate that this policy will 
result in a total annual burden increase of 275 hours across all 3,300 
IPPS hospitals (0.083 hours x 3,300 IPPS hospitals) at a cost of 
$11,275 (275 hours x $41).
c. Information Collection Burden Estimate for the Voluntary Reporting 
Period and Subsequent Required Submission of the Hybrid Hospital-Wide 
Mortality Measure With Claims and Electronic Health Record Data
    In section IX.C.5.b. of the preamble of this final rule, as 
proposed, we are finalizing to establish a voluntary reporting period 
for the Hybrid Hospital-Wide Mortality Measure with Claims and 
Electronic Health Record Data (NQF #3502) (Hybrid HWM measure). The 
voluntary reporting period would run from July 1, 2022 through June 30, 
2023. We also are finalizing our proposal as proposed to require 
reporting of the Hybrid HWM measure beginning with the reporting period 
which would run from July 1, 2023 through June 30, 2024 affecting the 
FY 2026 payment determination and for subsequent years.
    As a hybrid measure, this measure uses both claims-based data and 
EHR data, specifically, a set of core clinical data elements consisting 
of vital signs and laboratory test information and patient linking 
variables collected from hospitals' EHR systems. We do not expect any 
additional burden to hospitals to report the claims-based portion of 
this measure because these data are already reported to the Medicare 
program for payment purposes.
    However, we do expect that hospitals would experience burden in 
reporting the EHR data. To report the EHR data, hospitals would use the 
same submission process as finalized in the FY 2020 IPPS/LTCH PPS final 
rule for reporting the Hybrid Hospital-Wide All-Cause Readmission 
Measure with Claims and EHR Data (NQF #2879) (Hybrid HWR measure) (84 
FR 42505 through 42508). We expect the burden associated with reporting 
of the Hybrid HWM measure to be similar to our estimates for reporting 
the Hybrid HWR measure, that is, 10 minutes per measure, per quarter. 
Therefore, using the estimate of 10 minutes per measure per quarter (10 
minutes x one measure x four quarters = 40 minutes), we estimate that 
this finalized hybrid measure will result in a burden increase of 40 
minutes (0.67 hours) per hospital per year.
    In summary, beginning with the voluntary reporting period, which 
runs from July 1, 2022 through June 30, 2023, we estimate an annual 
burden increase of 2,200 hours across participating IPPS hospitals 
(0.67 hours x 3,300 IPPS hospitals). Using the updated wage estimate, 
as previously described, we estimate this to represent a cost increase 
of $90,200 across IPPS hospitals ($41 x 2,200 hours). As we are 
finalizing our proposal to adopt the Hybrid HWM measure, we encourage 
all hospitals to submit data for the Hybrid HWM measure during the 
voluntary reporting period. For that reason, our burden estimates 
assume that all hospitals will participate during the voluntary 
reporting period (July 1, 2022 through June 30, 2023) as well as for 
the required reporting period (July 1, 2023 through June 30, 2024) and 
subsequent reporting periods for which public reporting would begin. 
Due to the voluntary reporting period beginning in the third quarter of 
the CY 2022 reporting period/FY 2024 payment determination, the total 
burden for the first year assumes only two quarters of reporting and is 
estimated to be 1,100 hours (0.33 hours x 3,300 IPPS hospitals) at a 
cost of $45,100 ($41 x 1,100 hours). Beginning with the CY 2023 
reporting period/FY 2025 payment determination, the total burden 
estimate will be based on four quarters of reporting.
d. Information Collection Burden Estimate for the Adoption of Two 
Hospital Harm eCQMs Beginning With the CY 2022 Reporting Period/FY 2024 
Payment Determination and Removal of Three eCQMs Beginning With the CY 
2024 Reporting Period/FY 2026 Payment Determination
    In section IX.C.5.d. of the preamble of this final rule, as 
proposed, we are finalizing to adopt two eCQMs beginning with the CY 
2023 reporting period/FY 2025 payment determination: (1) Hospital 
Harm--Severe Hyperglycemia eCQM; and (2) Hospital Harm--Severe 
Hypoglycemia eCQM. Also, in section IX.C.6. of this final rule, we are 
finalizing three of the four proposals as proposed to remove eCQMs 
beginning with the CY 2024 reporting period/FY 2026 payment 
determination: (1) Admit Decision Time to ED Departure Time for 
Admitted Patients (ED-2); (2) Exclusive Breast Milk Feeding (PC-05); 
and (3) Discharged on Statin Medication (STK-06) eCQMs. We are not 
finalizing the removal of the Anticoagulation Therapy for Atrial 
Fibrillation/Flutter (STK-03). We do not believe that finalizing our 
proposals to add two eCQMs and remove three

[[Page 45509]]

eCQMS from the eCQM measure set, nor retaining the STK-03 eCQM, will 
affect the information collection burden of submitting eCQMs under the 
Hospital IQR Program. Current Hospital IQR Program policy requires 
hospitals to select four eCQMs from the eCQM measure set on which to 
report (84 FR 42503 through 4250). In other words, while these 
provisions will result in new eCQMs being added to and some eCQMs being 
removed from the eCQM measure set, hospitals will not be required to 
report more than a total of four eCQMs as is currently required (84 FR 
42603).
    Specifically, we finalized in the FY 2020 IPPS/LTCH PPS final rule 
that, for the CY 2021 reporting period/FY 2023 payment determination, 
hospitals are required to submit data for four self-selected eCQMs each 
year (84 FR 42503). Additionally, for the CY 2022 reporting period/FY 
2024 payment determination, hospitals are required to submit data for 
three self-selected eCQMs and the Safe Use of Opioids--Concurrent 
Prescribing eCQM for a total of four eCQMs (84 FR 42505). We also 
finalized a policy to progressively increase the number of quarters of 
eCQM data reported, from one quarter of data to four quarters of data 
over a 3-year period beginning with two quarters in the CY 2021 
reporting period/FY 2023 payment determination and culminating with 
four quarters in the CY 2023 reporting period/FY 2025 payment 
determination (85 FR 59008 through 59009). The newly adopted eCQMs will 
update the available eCQMs in the eCQM measure set from which hospitals 
may choose to report to satisfy these requirements. Therefore, we do 
not expect that finalizing our proposals to adopt and remove these 
measures or retain one eCQM would impact our information collection 
burden estimates. However, we refer readers to section I.K. of Appendix 
A of this final rule for a discussion of the potential costs associated 
with the implementation and removal of eCQMs which are not strictly 
related to information collection burden.
e. Information Collection Burden Estimate for Retaining the Death Rate 
Among Surgical Inpatients With Serious Treatable Complications (CMS 
PSI-04) Claims-Based Measure Beginning With the FY 2023 Payment 
Determination
    In section IX.C.6.a. of the preamble of this final rule, we are not 
finalizing our proposal to remove the Death Rate Among Surgical 
Inpatients with Serious Treatable Complications (CMS PSI-04) claims-
based measure beginning with the CY 2021 reporting period/FY 2023 
payment determination. Because CMS PSI-04 is calculated using data that 
are already reported to the Medicare program for payment purposes, 
retaining this measure will not result in a change to the burden 
estimates provided in the FY 2022 IPPS/LTCH proposed rule (86 FR 25686 
through 25687).
f. Information Collection Burden Estimate for the Adoption of the 
COVID-19 Vaccination Coverage Among HCP Measure Beginning With an 
Interim Reporting Period in CY 2021
    In section IX.C.5.c. of the preamble of this final rule, we are 
finalizing our proposal to adopt a COVID-19 Vaccination Coverage among 
HCP measure beginning with a shortened reporting period from October 1 
to December 31, 2021, affecting the CY 2021 reporting period/FY 2023 
payment determination, followed by quarterly reporting periods for the 
FY 2024 payment determination and for subsequent years. Regarding 
public reporting of this measure, based on public comment, we are 
finalizing a modification to our proposal. Under this modification, we 
will not finalize our plan to add one additional quarter of data during 
each advancing refresh, until the point that four full quarters of data 
is reached and then publicly report the measure using four rolling 
quarters of data. Instead, we will only publicly report the most recent 
quarter of data. However, this will not change the information 
collection burden for hospitals as we are finalizing the data 
submission requirements as proposed. Hospitals will submit data through 
the Centers for Disease Control and Prevention (CDC) National 
Healthcare Safety Network (NHSN). The NHSN is a secure, internet-based 
system maintained by the CDC and provided free. Currently the CDC does 
not estimate burden for COVID-19 vaccination reporting under the CDC 
PRA (OMB control number 0920-1317) because the agency has been granted 
a waiver under section 321 of the National Childhood Vaccine Injury Act 
(NCVIA).\1384\ As such, this measure will not impose any additional 
information collection burden for IPPS hospitals for the duration of 
the PHE. Although the burden associated with the COVID-19 Vaccination 
Coverage among HCP measure is not accounted for under the CDC PRA 0920-
1317 or 0920-0666 due to the NCVIA waiver, the estimated cost and 
burden information is included in the Regulatory Impact Analysis 
section (Appendix A, section I.K.) of this rule. We will work with CDC 
to ensure that this burden is accounted for in an updated PRA under OMB 
control number 0920-1317.
---------------------------------------------------------------------------

    \1384\ Section 321 of the National Childhood Vaccine Injury Act 
(NCVIA) provides the PRA waiver for activities that come under the 
NCVIA, including those in the NCVIA at section 2102 of the Public 
Health Service Act (42 U.S.C. 300aa-2). Section 321 is not codified 
in the U.S. Code, but can be found in a note at 42 U.S.C. 300aa-1.
---------------------------------------------------------------------------

g. Information Collection Burden Estimates for the Adoption of the 2015 
Edition Cures Update Criteria for Certified EHR Technology (CEHRT) 
Beginning With the CY 2023 Reporting Period/FY 2025 Payment 
Determination for eCQMs and Hybrid Measures
    In sections IX.C.9.e.2.(a). and IX.C.9.f.2.(b). of the preamble of 
this final rule, we are finalizing our proposal to require hospitals to 
use the 2015 Edition Cures Update beginning with the CY 2023 reporting 
period/FY 2025 payment determination and subsequent years. Under this 
policy, hospitals will no longer be able to use the 2015 Edition CEHRT 
criteria to submit data for the Hospital IQR Program data submission 
requirements for eCQMs or hybrid measures beginning with the CY 2023 
reporting period/FY 2025 payment determination. We do not expect that 
the finalization of these proposals will affect our information 
collection burden estimates because this policy does not require 
hospitals to submit new data to CMS (83 FR 41692). With respect to any 
costs unrelated to data submission, we refer readers to section I.K. of 
Appendix A of this final rule.
h. Information Collection Burden Estimate for the Update of References 
and Code of Federal Regulations Text Relating to QualityNet Security 
Official
    In section IX.C.9.c.(2). of the preamble of this final rule, we are 
finalizing our proposal to use the term ``QualityNet security 
official'' instead of ``QualityNet Administrator.'' Specifically, we 
are finalizing our proposal to revise existing Sec.  412.140(a)(2) by 
replacing ``QualityNet Administrator'' with ``QualityNet security 
official'' and Sec.  412.140(e)(2)(iii) by replacing ``QualityNet 
system administrator'' with ``QualityNet security official.'' We expect 
that our provision will not yield a change in burden for the hospitals 
participating in the Hospital IQR Program since the changes only seek 
to refine regulatory text.

[[Page 45510]]

i. Information Collection Burden Estimate for the Update to the 
References to the QualityNet Website in the Hospital IQR Program 
Regulation Text
    In section IX.C.9.c.(1). of the preamble of this final rule, we are 
finalizing our proposal to update the references to the QualityNet 
website from ``QualityNet.org'' to ``the QualityNet website'' in the 
Hospital IQR Program regulation text. Specifically, we are finalizing 
our proposal to revise existing Sec.  412.140(a)(1) and (c) to remove 
references to ``QualityNet.org'' and replace with ``QualityNet 
website.'' We expect that our provision will not yield a change in 
burden for the hospitals participating in the Hospital IQR Program 
since the changes only seek to refine regulatory text.
j. Information Collection Burden Estimate for the Extension of the 
Effects of the Educational Review Process for Chart-Abstracted Measures 
for the FY 2024 Payment Determination and Subsequent Years
    In section IX.C.10.b.(1).(b). of the preamble of this final rule, 
we are finalizing our proposal to extend the educational review policy 
to use the corrected quarterly score identified through an educational 
review to compute the final confidence interval for all 4 quarters of 
validation for chart-abstracted measures. We expect that our policy 
will not yield a change in burden as it does not affect the 
requirements for data submission for hospitals, but only modifies how 
CMS uses the data already being submitted.
k. Summary of Information Collection Burden Estimates for the Hospital 
IQR Program
    In summary, under OMB control number 0938-1022, we estimate that 
the policies promulgated in this final rule will result in a total 
increase of 2,475 hours annually for 3,300 IPPS hospitals from the CY 
2022 reporting period/FY 2024 payment determination through the CY 2025 
reporting period/FY 2027 payment determination. The total cost increase 
related to this information collection is approximately $101,475 (2,475 
hours x $41.00/hour) (which also reflects use of an updated hourly wage 
rate as previously discussed). The tables summarize the total burden 
changes for each respective FY payment determination compared to our 
currently approved information collection burden estimates (the table 
for the FY 2027 payment determination reflects the cumulative burden 
changes). We will submit the revised information collection estimates 
to OMB for approval under OMB control number 0938-1022.
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[[Page 45512]]


[GRAPHIC] [TIFF OMITTED] TR13AU21.317


[[Page 45513]]


BILLING CODE 4120-01-C
7. ICRs for the PPS-Exempt Cancer Hospital Quality Reporting (PCHQR) 
Program
    In section IX.D.5. of the preamble of this final rule, we are 
finalizing our proposal to adopt the COVID-19 Vaccination Coverage 
among HCP measure beginning with a shortened reporting period from 
October 1, 2021 through December 31, 2021, affecting the FY 2023 
program year, followed by quarterly reporting periods (affecting the FY 
2024 program year and for subsequent years).\1385\ As proposed, PCHs 
will submit data on the measure through the Centers for Disease Control 
and Prevention (CDC) National Healthcare Safety Network (NHSN). 
Currently, the CDC does not estimate burden for COVID-19 vaccination 
reporting under the CDC PRA package approved under OMB control number 
0920-1317 because the agency has been granted a waiver under section 
321 of the National Childhood Vaccine Injury Act (NCVIA).\1386\ 
Although the burden as associated with the COVID-19 Vaccination 
Coverage among HCP measure is not currently accounted for under the CDC 
package approved under OMB control number 0920-1317 or 0920-0666, the 
estimated cost and burden information is included in the Regulatory 
Impact Analysis section (see section I.K. of Appendix A of this rule). 
We will work with CDC to ensure that this burden is accounted for in an 
updated PRA package prepared by the CDC under OMB control number 0920-
1317 after expiration of the waiver.
---------------------------------------------------------------------------

    \1385\ We note that the proposed rule incorrectly read ``annual 
reporting periods'' however the section of the proposed rule on data 
submission (IX.D.5.c.) correctly described the data submission 
process and timelines.
    \1386\ Section 321 of the National Childhood Vaccine Injury Act 
(NCVIA) provides the PRA waiver for activities that come under the 
NCVIA, including those in the NCVIA at section 2102 of the Public 
Health Service Act (42 U.S.C. 300aa-2). Section 321 is not codified 
in the U.S. Code, but can be found in a note at 42 U.S.C. 300aa-1.
---------------------------------------------------------------------------

    In section IX.D.4. of the preamble of this final rule, we are 
finalizing the removal of the Oncology: Plan of Care for Pain--Medical 
Oncology and Radiation Oncology (NQF #0383/PCH-15) measure beginning 
with the FY 2024 program year. We previously finalized in the FY 2019 
IPPPS/LTCH PPS final rule that we would utilize a time estimate of 15 
minutes per measure when assessing web-based and/or structural measures 
(83 FR 41694). As such, we estimated that the removal of this measure 
from the PCHQR measure set will result in a reduction of 15 minutes 
(0.25 hours) per PCH per year, with a total annual reduction in 
reporting burden across all PCHs of 2.75 hours (0.25 hours x 11 PCHs) 
and a total annual reduction in cost across all PCHs of $113 (2.75 
hours x $41.00/hr), beginning with the FY 2024 program year. As 
previously stated, we are finalizing these provisions as proposed.
    We did not receive any comments regarding the ICRs for the PCHQR 
Program, however, while analyzing them for this final rule, we reviewed 
the Program's measure set for the FY 2024 program year and concluded 
that the currently approved burden is overestimated. We included that 
overestimation in section X.II.B.7. of the proposed rule and are 
correcting it here.
    The overestimation originated in the FY 2019 IPPS/LTCH PPS final 
rule PRA Supporting Statement A for OMB 0938-1175,\1387\ wherein we 
addressed the incorrect prior inclusion of burden data associated with 
NHSN measures (which are covered under OMB 0920-0666) and the HCAHPS 
measure (which is covered under OMB 0938-0981) and updated burden 
estimates to account for the finalized removal of web-based measures. 
The FY 2019 IPPS/LTCH PPS final rule PRA Supporting Statement A 
ultimately overcalculated the number of measures that are not claims-
based, and therefore overestimated the burden included in that PRA.
---------------------------------------------------------------------------

    \1387\ Supporting Statement--Part A Quality Measures and 
Procedures for the PPS-Exempt Cancer Hospital Quality Reporting 
Program (PCHQR Program) for the FY 2021 Program Year, https://www.reginfo.gov/public/do/PRAViewDocument?ref_nbr=201812-0938-018.
---------------------------------------------------------------------------

    The currently approved burden for the PCHQR Program for the FY 2023 
program year is 75,779 hours at a cost of $2,940,225 (75,779 hours x 
$38.80/hour). As discussed, the currently approved burden hours are 
incorrectly based on an overestimated assumption of the total number of 
chart-abstracted measures, structural measures, and measures that 
utilize a web-based tool. Upon review of the measure set for the PCHQR 
Program currently approved for the FY 2023 program year, including the 
eight measures accounted for under OMB control number 0938-1175, the 
total number of chart-abstracted measures, structural measures, and 
measures that utilize a web-based tool is 1 (Oncology: Plan of Care for 
Moderate to Severe Pain--Medical Oncology and Radiation Oncology (NQF 
#0383) (PCH-15)). The other seven measures are claims-based measures. 
As a result, the currently approved burden estimate should be decreased 
to 2.75 hours (11 PCHs x 0.25 hours) at a cost of $107 (2.75 hours x 
$38.80/hr).
    As described previously, the removal of the Oncology: Plan of Care 
for Pain--Medical Oncology and Radiation Oncology (NQF #0383/PCH-15) 
measure beginning with the FY 2024 program year results in a total 
annual reduction in reporting burden across all PCHs of 2.75 hours 
(0.25 hours x 11 PCHs) and a total annual reduction in cost across all 
PCHs of $113 (2.75 hours x $41.00/hr), beginning with the FY 2024 
program year. The combination of the correction to currently approved 
burden estimates and the reduction to burden estimates associated with 
the measure's removal result in zero hours' reporting burden across all 
PCHs beginning with the FY 2024 program year.
8. ICRs for the Long-Term Care Hospital Quality Reporting Program (LTCH 
QRP)
    The provisions discussed in section IX.E. of this final rule did 
not impose any new information collection requirements. However, there 
are references associated with the information collection requirements 
for the LTCH QRP that are not discussed in the regulation text 
contained in this document. The following is a discussion of those 
information collections, some of which have already received OMB 
approval.
    As stated in section IX.E. of the preamble of this final rule, we 
are finalizing our proposal that LTCHs submit data on one new quality 
measure: COVID-19 Vaccination Coverage among Healthcare Personnel 
(HCP). The data source for this quality measure is the Centers for 
Disease Control and Prevention (CDC)/National Healthcare Safety Network 
(NHSN). LTCHs will submit the COVID-19 Vaccination Coverage among 
Healthcare Personnel (HCP) measure data to CMS using the NHSN, a web-
based tool hosted by the CDC. This reporting service is provided free 
of charge to LTCHs. LTCHs currently utilize the NHSN for purposes of 
meeting other LTCH QRP requirements.
    We believe that the burden associated with the LTCH QRP is the time 
and effort associated with complying with the requirements of the LTCH 
QRP. The burden associated with the COVID-19 Vaccination Coverage among 
HCP measure is not accounted for under the CDC PRA package currently 
approved under OMB control number 0920-1317 (expiration 1/31/2024). 
However, the CDC currently has a PRA waiver for the collection and 
reporting of vaccination data under section 321 of the National 
Childhood Vaccine Injury Act of 1986 (Pub. L. 99-660, enacted on 
November

[[Page 45514]]

14, 1986 (NCVIA)).\1388\ CMS has provided an estimate of the burden and 
cost to LTCHs, and note that the CDC will include it in a revised 
information collection request for 0920-1317.
---------------------------------------------------------------------------

    \1388\ Section 321 of the National Childhood Vaccine Injury Act 
(NCVIA) provides the PRA waiver for activities that come under the 
NCVIA, including those in the NCVIA at section 2102 of the Public 
Health Service Act (42 U.S.C. 300aa-2). Section 321 is not codified 
in the U.S. Code, but can be found in a note at 42 U.S.C. 300aa-1.
---------------------------------------------------------------------------

    Consistent with the CDC's experience of collecting data using the 
NHSN, we estimate that it would take each LTCH an average of 1 hour per 
month to collect data for the COVID-19 Vaccination Coverage among HCP 
measure and enter it into NHSN. We have estimated the time to complete 
this entire activity, since it could vary based on provider systems and 
staff availability. We believe it will take an administrative assistant 
from 45 minutes up to 1 hour and 15 minutes to enter this data into 
NHSN. For the purposes of calculating the costs associated with the 
collection of information requirements, we obtained mean hourly wages 
from the U.S. Bureau of Labor Statistics' May 2019 National 
Occupational Employment and Wage Estimates. To account for overhead and 
fringe benefits, we have doubled the hourly wage.
    Based on the time range, it would cost each LTCH between $27.47 and 
$45.78 per hour each month or an average cost of $36.62 each month, and 
between $329.64 and $549.36 each year, or an average cost of $439.44 
each year. We believe the data submission for the COVID-19 Vaccination 
Coverage among HCP would cause LTCHs to incur additional average burden 
of 12 hours per year for each LTCH and a total annual burden of 4,608 
hours for all LTCHs. The estimated annual cost across all 363 LTCHs in 
the U.S. for the submission of the COVID-19 Vaccination Coverage among 
HCP measure would be between $119,659.32 and $199,417.68, and an 
average of $159,516.72.
    We recognize that many LTCHs may also be reporting other COVID-19 
data to HHS. However, we believe the benefits of reporting data on the 
COVID-19 Vaccination Coverage among HCP measure to assess whether LTCHs 
are taking steps to limit the spread of COVID-19 among HCP, reduce risk 
of transmission of COVID-19 within their facilities, and to help 
sustain the ability of LTCHs to continue serving their communities 
throughout the PHE and beyond outweigh the costs of reporting. We 
welcome comments on the estimated time to collect data and enter it 
into CDC/NHSN.
    We did not receive any comments on the estimated time to collect 
and enter data into the NHSN for the COVID-19 Vaccination Coverage 
among HCP measure, and are finalizing the revisions as proposed.
9. ICRs for the Medicare Promoting Interoperability Program
a. Historical Background
    In section IX.F. of the preamble of the proposed rule and this 
final rule, we discussed several proposals for the Medicare Promoting 
Interoperability Program. OMB has currently approved 621,318 total 
burden hours and approximately $61 million under OMB control number 
0938-1278, accounting for information collection burden experienced by 
approximately 3,300 eligible hospitals and CAHs (Medicare-only and 
dual-eligible) that attest to CMS under the Medicare Promoting 
Interoperability Program. The collection of information burden analysis 
in this final rule focuses on eligible hospitals and CAHs that attest 
to the objectives and measures, and report eCQMs, under the Medicare 
Promoting Interoperability Program for the reporting period in CY 2022, 
CY 2023, and CY 2024.
b. Summary of Policies for Eligible Hospitals and CAHs That Attest to 
CMS Under the Medicare Promoting Interoperability Program for CY 2022
    In section IX.F.3.b. of the preamble of this final rule, we are 
finalizing the following changes for eligible hospitals and CAHs that 
attest to CMS under the Medicare Promoting Interoperability Program: 
(1) To maintain the Electronic Prescribing Objective's Query of PDMP 
measure as optional while increasing its available bonus from five 
points to 10 points for the EHR reporting period in CY 2022; (2) to add 
a new Health Information Exchange (HIE) Bi-Directional Exchange measure 
as a yes/no attestation, to the HIE objective as an optional 
alternative to the two existing measures beginning with the EHR 
reporting period in CY 2022; (3) to require reporting on four of the 
existing Public Health and Clinical Data Exchange Objective measures 
(Syndromic Surveillance Reporting, Immunization Registry Reporting, 
Electronic Case Reporting, and Electronic Reportable Laboratory Result 
Reporting); (4) to add a new measure to the Protect Patient Health 
Information objective that requires eligible hospitals and CAHs to 
attest to having completed an annual assessment of the SAFER Guides 
beginning with EHR reporting period in CY 2022; (5) to remove 
attestation statements 2 and 3 from the Medicare Promoting 
Interoperability Program's prevention of information blocking 
requirement; and (6) to increase the minimum required scoring threshold 
for the objectives and measures from 50 points to 60 points (out of 100 
points) in order to be considered a meaningful EHR user. We are not 
finalizing the proposed change to the Provide Patients Electronic 
Access to Their Health Information Measure (specifically, a proposal to 
establish a data availability requirement). We are amending the 
regulations as necessary to incorporate these final policies.
c. Summary of Policies for Eligible Hospitals and CAHs That Attest to 
CMS Under the Medicare Promoting Interoperability Program for CY 2023
    In section IX.F.3.b. of the preamble of this final rule, we are 
finalizing the following changes for eligible hospitals and CAHs that 
attest to CMS under the Medicare Promoting Interoperability Program: 
(1) An EHR reporting period of a minimum of any continuous 90-day 
period in CY 2023 for new and returning participants (eligible 
hospitals and CAHs); and (2) to adopt two new eCQMs to the Medicare 
Promoting Interoperability Program's eCQM measure set beginning with 
the reporting period in CY 2023, which is in alignment with the 
provisions under the Hospital IQR Program as discussed in section IX.C. 
of the preamble of this final rule. We are amending the regulations as 
necessary to incorporate these final policies.
d. Summary of Policies for Eligible Hospitals and CAHs That Attest to 
CMS Under the Medicare Promoting Interoperability Program for CY 2024
    As discussed in section IX.F.3.b. of the preamble of this final 
rule, we are finalizing the following changes for eligible hospitals 
and CAHs that attest to CMS under the Medicare Promoting 
Interoperability Program: (1) An EHR reporting period of a minimum of 
any continuous 180-day period in CY 2024 for new and returning 
participants (eligible hospitals and CAHs); and (2) to remove three 
eCQMs from the Medicare Promoting Interoperability Program's eCQM 
measure set beginning with the reporting period in CY 2024, which is in 
alignment with the provisions under the Hospital IQR Program as 
discussed in section IX.C. We are amending the regulations as necessary 
to incorporate these final policies.

[[Page 45515]]

e. Summary of Collection of Information Burden Estimates
(1) Summary of Estimates Used To Calculate the Collection of 
Information Burden
    In the Medicare and Medicaid Programs; Electronic Health Record 
Incentive Program--Stage 3 and Modifications to Meaningful Use in 2015 
Through 2017 final rule (80 FR 62917), we estimated it will take an 
individual provider or designee approximately 10 minutes to attest to 
each objective and associated measure that requires a numerator and 
denominator to be generated. The measures that require a ``yes/no'' 
response will take approximately 1 minute to complete. We estimated 
that the Security Risk Analysis measure will take approximately 6 hours 
for an individual provider or designee to complete (we note this 
measure is still part of the program, but is not subject to 
performance-based scoring).
    For this final rule, we are finalizing two proposed measure changes 
which lead to an increase in overall burden to the Medicare Promoting 
Interoperability Program. First is the updated requirement for the 
Public Health and Clinical Data Exchange Objective which increases the 
total number of measures which must be reported from two to four. For 
the CY 2021 EHR reporting period, the estimated burden associated with 
reporting on this Objective was one minute, therefore by doubling the 
number of required measures from two to four, we are estimating the 
time for CY 2022 reporting would be 2 minutes (or an increase in 0.03 
hours per reporting hospital). Although the Objective's Syndromic 
Surveillance Reporting measure is changing its setting for which data 
are required to be submitted, we do not anticipate the update from 
``urgent care'' to ``emergency department'' to change burden hours 
given that the capacity to submit reports is already an existing part 
of built-in CEHRT functionality. Secondly, we are finalizing the 
requirement for a new measure based on SAFER Guides Reporting, which we 
have anticipated will take 1 minute to report (as it is proposed to be 
completed via a single yes/no attestation response). The inclusion of 
reporting on this SAFER Guides measure will increase the total burden 
by 0.02 hours. Lastly, we are finalizing the proposed inclusion of a 
new HIE Bi-Directional Exchange measure, which would not have any 
effect on the estimated reporting burden given that it will be 
available as an optional, alternative reporting method to the two 
current Support Electronic Referral Loops measures, therefore resulting 
in no net change in burden. Providers will only be required to respond 
with either the two existing measures OR choose the new Bi-Directional 
Exchange measure, but the amount of associated burden equals the same 
regardless of their selection and thus does not require any additional 
change in hours.
    As discussed in section IX.F. of this final rule, we are finalizing 
the proposal to continue the EHR reporting period as any self-selected 
continuous 90-days in CY 2023 and to increase the EHR reporting period 
as any self-selected continuous 180-days in CY 2024. We do not 
anticipate additional burden due to how the QualityNet attestation 
system (also referred to as the Hospital Quality Reporting system) is 
setup and operated to account for the estimated time spent with 
reporting to CMS (submitting automated reports via CEHRT or attesting 
to the Program's objectives and measures would not be impacted by a 
longer EHR reporting period). A similar approach applies to the final 
policy for increasing the scoring threshold from 50 to 60 points, which 
does not require any expectation that submitting providers would endure 
a longer time duration of reporting or attesting to the Program (the 
threshold only indicates the minimum score necessary to be considered a 
meaningful EHR user). Finally, we do not believe that our provisions 
aligned with the Hospital IQR Program to add two eCQMs and remove three 
eCQMs from the eCQM measure set would affect the information collection 
burden of submitting eCQMs under the Medicare Promoting 
Interoperability Program. Previously finalized policy requires 
hospitals to select eCQMs from the eCQM measure set on which to report 
(85 FR 58970 through 58976). In other words, while these provisions 
will result in new eCQMs being added to and some eCQMs being removed 
from the eCQM measure set, hospitals would not be required to report 
more than a total of four eCQMs as is currently required (85 FR 58970 
through 58971). We believe these are appropriate burden estimates for 
reporting and have used this methodology in our collection of 
information burden estimates for this final rule.
    Given the provisions, we estimate a total burden estimate of 6 
hours 33 minutes per respondent (approximately 6.5 hours) which is an 
increase of 2 minutes from the FY 2021 IPPS/LTCH PPS final rule (85 FR 
58432).

[[Page 45516]]

[GRAPHIC] [TIFF OMITTED] TR13AU21.318

(2) Hourly Labor Costs
    In the Medicare and Medicaid Programs; Electronic Health Record 
Incentive Program--Stage 3 and Modifications to Meaningful Use in 2015 
Through 2017 final rule (80 FR 62917), we estimated a mean hourly rate 
of $63.46 for the staff involved in attesting to EHR technology, 
meaningful use objectives and associated measures, and electronically 
submitting the clinical quality measures. This reflected the mean 
hourly rate of a lawyer. We had previously used the mean hourly rate of 
$68.22 for the necessary staff involved in attesting to the objectives 
and measures under 42 CFR 495.24(e) in the FY 2020 IPPS/LTCH PPS final 
rule (84 FR 42609). This rate was updated to $69.34 in the FY 2021 
IPPS/LTCH PPS final rule (85 FR 59014) based upon then recently 
released 2018 data from the Bureau of Labor Statistics (BLS).\1389\
---------------------------------------------------------------------------

    \1389\ https://www.bls.gov/oes/current/oes231011.htm. Accessed 
April 21, 2021.
---------------------------------------------------------------------------

    The Medicare Promoting Interoperability Program has previously 
utilized this lawyer hourly wage rate; however, we have determined that 
it is no longer the most accurate professional among the hospital staff 
members who are most likely to complete the program's required 
electronic responses and attestations for the Program. Rather, we 
believe hospital staff similar to the staff who report for the Hospital 
Inpatient Quality Reporting Program are utilized to report for the 
Medicare Promoting Interoperability Program, specifically, a medical 
records and health information technician staffing role. We believe 
that both current and anticipated labor performed by participating 
hospitals in order to successfully complete the Program's reporting 
requirements is accomplished by this technical role and not the 
position of a lawyer. Therefore, in properly calculating our estimated 
burden, we replaced the existing lawyer's wage rate of $69.34 with that 
of a medical records and health information technician's median wage 
rate ($20.50 according to the 2019 U.S. Bureau of Labor 
Statistics).\1390\ We believe it more accurately reflects the real-
world scenario of those staff members performing the required labor.
---------------------------------------------------------------------------

    \1390\ https://www.bls.gov/ooh/healthcare/medical-records-and-health-information-technicians.htm#tab-1. Accessed on February 21, 
2021.
---------------------------------------------------------------------------

    We calculated the cost of overhead, including fringe benefits, at 
100 percent of the median hourly wage, consistent with the Hospital IQR 
Program. This is necessarily a rough adjustment, both because fringe 
benefits and overhead costs vary significantly by employer and methods 
of estimating these costs vary widely in the literature. Nonetheless, 
we believe that doubling the hourly wage rate ($20.50 x 2 = $41) to 
estimate total cost is a reasonably accurate estimation method. 
Accordingly, we calculated cost burden to hospitals using a wage plus 
benefits estimate of $41 per hour throughout the discussion in this 
section of this final rule for the Medicare Promoting Interoperability 
Program.
    In summary, we finalized our proposals and estimate a minimal 
increase in total burden hours for the Medicare Promoting 
Interoperability Program for CY 2022 (an increase of 2 additional 
minutes per hospital). Using the median hourly wage for a medical 
records and health information technician, we estimate a burden cost 
increase for CY 2022 of $1.37 per hospital. We estimate the total 
annual burden of 21,450 burden hours across 3,300 responses for the 
Program's objectives and measures, and we estimate the total burden 
cost for CY 2022 to be $879,450 (21,450 hours x $41). Given that the 
total cost estimate for CY 2021 in last year's final rule was 
$1,487,343, these updates will result in a net cost decrease of 
$607,893 for the Medicare Promoting Interoperability Program.
    We are finalizing our provisions for CY 2023 and CY 2024 as 
proposed and we do not estimate any net change in total burden hours 
for the Medicare Promoting Interoperability Program when compared to CY 
2022 estimates. CY 2023 provisions only include an extension of the 
current 90-day EHR reporting period and the adoption of two new eCQMs 
to the Program's eCQM

[[Page 45517]]

measure set (in alignment with the proposals being finalized under the 
Hospital IQR Program), whereas CY 2024 provisions include a 180-day EHR 
reporting period and the removal of three eCQMs from the Program's eCQM 
measure set (in alignment with proposals being finalized under the 
Hospital IQR Program). Both provisions for CY 2023 and CY 2024 have 
already been detailed to create no net change to the total burden hours 
and therefore we estimate both years as having the same total cost of 
$879,450 (21,450 hours x $41).
    The burden hours associated with reporting program requirements is 
currently approved under OMB control number 0938-1278. The updated 
burden cost estimates discussed in this section will be revised and 
submitted to OMB for final approval.
    We did not receive any comments regarding the ICRs for the Medicare 
Promoting Interoperability Program and are finalizing without 
modification.
[GRAPHIC] [TIFF OMITTED] TR13AU21.319

[GRAPHIC] [TIFF OMITTED] TR13AU21.320

10. Summary of All Burden in This Final Rule
    The following chart reflects the total burden and associated costs 
for the provisions included in this final rule.
[GRAPHIC] [TIFF OMITTED] TR13AU21.321

    I, Chiquita Brooks-LaSure, Administrator of the Centers for 
Medicare & Medicaid Services, approved this document on July 26, 2021.

List of Subjects

42 CFR Part 412

    Administrative practice and procedure, Health facilities, Medicare, 
Puerto Rico, and Reporting and recordkeeping requirements.

42 CFR Part 413

    Diseases, Health facilities, Medicare, Puerto Rico, Reporting and 
recordkeeping requirements.

42 CFR Part 425

    Administrative practice and procedure, Health facilities, Health

[[Page 45518]]

professions, Medicare, and Reporting and recordkeeping requirements.

42 CFR Part 455

    Fraud, Grant programs-health, Health facilities, Health 
professions, Investigations, Medicaid, Reporting and recordkeeping 
requirements.

42 CFR Part 495

    Administrative practice and procedure, Health facilities, Health 
maintenance organizations (HMO), Health professions, Health records, 
Medicaid, Medicare, Penalties, Privacy, and Reporting and recordkeeping 
requirements.

    For the reasons set forth in the preamble, the Centers for Medicare 
and Medicaid Services is amending 42 CFR chapter IV as set forth below:

PART 412--PROSPECTIVE PAYMENT SYSTEMS FOR INPATIENT HOSPITAL 
SERVICES

0
1. The authority citation for Part 412 continues to read as follows:

    Authority: 42 U.S.C. 1302 and 1395hh.


0
2. Section 412.1 is amended by adding paragraph (a)(7) and revising 
paragraph (b)(2) to read as follows:


Sec.  412.1  Scope of part.

    (a) * * *
    (7) This part implements section 1866(k) of the Act, which directs 
hospitals described in section 1886(d)(1)(B)(v) of the Act to submit 
data on quality measures to the Secretary.
    (b) * * *
    (2) Subpart B of this part sets forth all of the following:
    (i)(A) The classifications of hospitals that are included in and 
excluded from the prospective payment systems specified in paragraph 
(a)(1) of this section.
    (B) Requirements governing the inclusion or exclusion of hospitals 
in the systems as a result of changes in their classification.
    (ii) Requirements for the PPS-Exempt Cancer Hospital Quality 
Reporting (PCHQR) Program.
* * * * *

0
3. Section 412.23 is amended by adding paragraph (f)(3) to read as 
follows:


Sec.  412.23  Excluded Hospitals: Classifications.

* * * * *
    (f) * * *
    (3) PCHQR Program. All hospitals classified as cancer hospitals 
under this paragraph must comply with the requirements of the PPS-
Exempt Cancer Hospital Quality Reporting Program, as described in Sec.  
412.24.
* * * * *

0
4. Section 412.24 is added to read as follows:


Sec.  412.24  Requirements under the PPS-Exempt Cancer Hospital Quality 
Reporting (PCHQR) Program.

    (a) Applicability. The PCHQR Program applies to hospitals that are 
classified as cancer hospitals (PCHs) under the criteria described in 
Sec.  412.23(f)(1) or (2).
    (b) Participation in the PCHQR Program. In order to participate in 
the PCHQR Program, a PCH must do both of the following:
    (1) Register with QualityNet (http://qualitynet.cms.gov) prior to 
reporting, including designating a QualityNet security official who 
completes all steps of the PCHQR Program registration process as 
described on the QualityNet website.
    (2) Enroll in CDC's National Healthcare Safety Network (https://www.cdc.gov/nhsn/enrollment/index.html).
    (c) Submission of PCHQR Program data. Except as provided in 
paragraph (e) of this section, PCHs that participate in the PCHQR 
Program must submit to CMS data on quality measures specified under 
section 1833(k)(3) of the Act in a form and manner, and at a time, 
specified by CMS. PCHs that participate in the PCHQR Program must also 
submit an annual online Data Accuracy and Completeness Acknowledgement 
via the Hospital Quality Reporting (HQR) system that attests to the 
accuracy and completeness of these data by the deadline specified by 
CMS on the QualityNet website (http://qualitynet.cms.gov).
    (d) Quality measure updates, retention, and removal--(1) Updating 
of measure specifications. CMS uses rulemaking to make substantive 
updates to the specifications of measures used in the PCHQR Program. 
CMS announces technical measure specification updates through the 
QualityNet website (http://qualitynet.cms.gov) and listserv 
announcements.
    (2) Measure retention. All quality measures specified under section 
1866(k)(3) for the PCHQR Program measure set remain in the measure set 
unless CMS, through rulemaking, removes or replaces them.
    (3) Measure removal factors--(i) General rule. CMS may remove or 
replace a quality measure based on one or more of the following 
factors:
    (A) Factor 1. Measure performance among PCHs is so high and 
unvarying that meaningful distinctions and improvements in performance 
can no longer be made.
    (B) Factor 2. A measure does not align with current clinical 
guidelines or practice.
    (C) Factor 3. The availability of a more broadly applicable measure 
(across settings or populations) or the availability of a measure that 
is more proximal in time to desired patient outcomes for the particular 
topic.
    (D) Factor 4. Performance or improvement on a measure does not 
result in better patient outcomes.
    (E) Factor 5. The availability of a measure that is more strongly 
associated with desired patient outcomes for the particular topic.
    (F) Factor 6. The collection or public reporting of a measure leads 
to negative unintended consequences other than patient harm.
    (G) Factor 7. It is not feasible to implement the measure 
specifications.
    (H) Factor 8. The costs associated with a measure outweigh the 
benefit of its continued use in the program.
    (ii) Exception. CMS may retain a quality measure that meets one or 
more of the measure removal factors described in paragraph (d)(3)(i) of 
this section if the continued collection of data on the quality measure 
would align with a stated CMS or HHS policy objective, including, but 
not limited to, an objective to increase the number of quality measures 
that a PCH can report electronically, or an objective to collect data 
on the measure in one or more other CMS quality reporting programs.
    (e) Extraordinary circumstances exceptions (ECEs). (1) CMS may 
grant an ECE to a PCH that has requested an extension or exception with 
respect to quality data reporting requirements in the event of 
extraordinary circumstances beyond the control of the PCH.
    (2) CMS may grant an ECE to one or more PCHs that has not requested 
an exception if CMS determines that--
    (i) An extraordinary circumstance has affected an entire region or 
locale; or
    (ii) A systemic problem with one of CMS' data collection systems 
has directly affected the ability of the PCH to submit data in 
accordance with paragraph (c) of this section.
    (3) A PCH participating in the PCHQR Program that wishes to request 
an ECE must submit an ECE request to CMS via the QualityNet website 
(https://qualitynet.cms.gov/pch/pchqr/resource) within 90 days of the 
date that the extraordinary circumstances occurred, along with the 
following information:
    (i) The PCH's CCN, name, reason for requesting an extension or 
exception, and evidence of the impact of

[[Page 45519]]

extraordinary circumstances, including but not limited to photographs 
and media articles;
    (ii) The date when the PCH will again be able to submit PCHQR 
Program data and a justification for that proposed date;
    (iii) The following contact information for the PCH's CEO and any 
other designated personnel:
    (A) Name.
    (B) Email address.
    (C) Telephone number.
    (D) Physical mailing address (not a post office box); and
    (iv) The signature of the PCH's CEO or designee on the ECE request.
    (f) Public reporting of PCHQR Program data. CMS makes data 
submitted by PCHs under the PCHQR Program available to the public on 
the Provider Data Catalog website (https://data.cms.gov/provider-data/
). Prior to making any such data submitted by a PCH available to the 
public, CMS gives the PCH an opportunity to review the data via the 
Hospital Quality Reporting (HQR) system (https://hqr.cms.gov/hqrng/login) and announces the timeline for review on the QualityNet website 
(http://qualitynet.cms.gov) and applicable listservs.

0
5. Section 412.64 is amended--
0
a. In paragraph (e)(1)(ii), by removing the phrase ``paragraph (e)(4) 
of this section'' and adding in its place the phrase ``paragraphs 
(e)(4) and (h)(4)(vii) of this section'';
0
b. In paragraph (e)(4) introductory text, by removing the phrase ``and 
the imputed floor under paragraph (h)(4)'' and adding in its place the 
phrase ``and, for discharges on or after October 1, 2004, and before 
October 1, 2018, the imputed floor under paragraph (h)(4)'';
0
c. In paragraph (h)(4) introductory text, by removing the phrase 
``October 1, 2018, CMS establishes'' and adding in its place the phrase 
``October 1, 2018, and for discharges on or after October 1, 2021, CMS 
establishes'';
0
d. In paragraph (h)(4)(vi) introductory text, by removing the phrase 
``October 1, 2018, the minimum'' and adding in its place the phrase 
``October 1, 2018, and for discharges on or after October 1, 2021, the 
minimum'';
0
e. By adding paragraph (h)(4)(vii); and
0
f. By revising paragraph (h)(5).
    The addition and revision read as follows:


Sec.  412.64   Federal rates for inpatient operating costs for Federal 
fiscal year 2005 and subsequent fiscal years.

* * * * *
    (h) * * *
    (4) * * *
    (vii) For discharges on or after October 1, 2021, the minimum wage 
index computed under this paragraph must not be applied in a budget 
neutral manner.
    (5)(i) For purposes of paragraph (h)(4) of this section, for 
discharges on or after October 1, 2004 and before October 1, 2018, an 
all-urban State is a State with no rural areas, as defined in this 
section, or a State in which there are no hospitals classified as 
rural. For purposes of this definition, a State with rural areas and 
with hospitals reclassified as rural under Sec.  412.103 is not an all-
urban State.
    (ii) For purposes of paragraph (h)(4) of this section, for 
discharges on or after October 1, 2021, an all-urban State is a State 
with no rural areas, as defined in this section, or a State in which 
there are no hospitals classified as rural under section 1886 of the 
Act. For purposes of this definition, a hospital is classified as rural 
under section 1886 of the Act if it is assigned the State's rural area 
wage index value.
* * * * *

0
6. Section 412.96 is amended by revising paragraphs (c)(1) introductory 
text, (h)(1), and (i)(1) and (2) to read as follows:


Sec.  412.96  Special treatment: Referral centers.

* * * * *
    (c) * * *
    (1) Case-mix index. CMS sets forth national and regional case-mix 
index values in each year's annual notice of prospective payment rates 
published under Sec.  412.8(b). The methodology CMS uses to calculate 
these criteria is described in paragraph (h) of this section. The case-
mix index value to be used for an individual hospital in the 
determination of whether it meets the case-mix index criteria is that 
calculated by CMS from the hospital's own billing records for Medicare 
discharges as processed by the fiscal intermediary and submitted to 
CMS. The hospital's case-mix index for discharges (not including 
discharges from units excluded from the prospective payment system 
under subpart B of this part) during the same Federal fiscal year used 
to compute the case mix index values under paragraph (h) of this 
section must be at least equal to--
* * * * *
    (h) * * *
    (1) Updating process. CMS updates the national and regional case-
mix index standards using the best available data from hospitals 
subject to the prospective payment system for the Federal fiscal year.
* * * * *
    (i) * * *
    (1) Updating process. CMS updates the national and regional number 
of discharges using the best available data for levels of admissions or 
discharges or both.
    (2) Source of data. In making the calculations described in 
paragraph (i)(1) of this section, CMS uses the best available hospital 
admissions or discharge data.
* * * * *

0
7. Section 412.103 is amended by--
0
a. Revising paragraph (g(3);
0
b. Redesignating paragraph (g)(4) as (g)(5); and
0
c. Adding a new paragraph (g)(4).
    The revision and addition read as follows:


Sec.  412.103   Special treatment: Hospitals located in urban areas and 
that apply for reclassification as rural.

* * * * *
    (g) * * *
    (3) Cancellation of rural reclassification on or after October 1, 
2019, and before October 1, 2021. For all written requests submitted by 
hospitals on or after October, 1, 2019, and before October 1, 2021, to 
cancel rural reclassifications, a hospital may cancel its rural 
reclassification by submitting a written request to the CMS Regional 
Office not less than 120 days prior to the end of a Federal fiscal 
year. The hospital's cancellation of the classification is effective 
beginning with the next Federal fiscal year.
    (4) Cancellation of rural reclassification on or after October 1, 
2021. For all written requests submitted by hospitals on or after 
October 1, 2021, to cancel rural reclassifications, a hospital may 
cancel its rural reclassification by submitting a written request to 
the CMS Regional Office not less than 1 calendar year after the 
effective date of the rural reclassification and not less than 120 days 
prior to the end of a Federal fiscal year. The hospital's cancellation 
of the classification is effective beginning with the next Federal 
fiscal year.
* * * * *

0
8. Section 412.106 is amended by revising paragraph (g)(1)(iii)(C)(8) 
and adding paragraph (g)(1)(iii)(C)(9) to read as follows:


Sec.  412.106  Special treatment: Hospitals that serve a 
disproportionate share of low-income patients.

* * * * *
    (g) * * *
    (1) * * *
    (iii) * * *
    (C) * * *
    (8) For each subsequent fiscal year, for all eligible hospitals, 
except Indian

[[Page 45520]]

Health Service and Tribal hospitals and Puerto Rico hospitals that have 
a cost report for 2013, CMS will base its estimates of the amount of 
hospital uncompensated care on data on uncompensated care costs, 
defined as charity care costs plus non-Medicare and non-reimbursable 
Medicare bad debt costs from cost reports from the most recent cost 
reporting year for which audits have been conducted.
    (9) For fiscal year 2022, for Indian Health Service and Tribal 
hospitals and Puerto Rico hospitals that have a cost report for 2013, 
CMS will base its estimates of the amount of hospital uncompensated 
care on utilization data for Medicaid and Medicare Supplemental 
Security Income (SSI) patients, as determined by CMS in accordance with 
paragraphs (b)(2)(i) and (b)(4) of this section, using data on Medicaid 
utilization from 2013 cost reports from the most recent HCRIS database 
extract and the most recent available year of data on Medicare SSI 
utilization (or, for Puerto Rico hospitals, a proxy for Medicare SSI 
utilization data).
* * * * *


Sec.  412.140   [Amended]

0
9. Section 412.140 is amended--
0
a. In paragraph (a)(1), by removing the term ``QualityNet.org'' and 
adding in its place the terms ``QualityNet website'';
0
b. In paragraph (a)(2), by removing the term ``QualityNet 
Administrator'' and adding in its place the phrase ``QualityNet 
security official'';
0
c. In paragraph (c)(2)(i), by removing the term ``QualityNet.org'' and 
adding in its place the terms ``QualityNet website''; and
0
d. In paragraph (e)(2)(iii), by removing the term ``QualityNet system 
administrator'' and adding in its place the phrase ``QualityNet 
security official''.

0
10. Section 412.154 is amended by revising paragraph (f)(4) to read as 
follows:


Sec.  412.154  Payment adjustments under the Hospital Readmissions 
Reduction Program.

* * * * *
    (f) * * *
    (4) CMS posts the excess readmission ratios for the applicable 
conditions for a fiscal year for each applicable hospital on the 
Hospital Compare website or successor website(s).


Sec.  412.160  [Amended]

0
11. Section 412.160 is amended in the introductory text by removing the 
phrase ``in Sec. Sec.  412.161 through 412.167'' and adding in its 
place the phrase ``in Sec. Sec.  412.161 through 412.168''.


Sec.  412.163   [Amended]

0
12. Section 412.163 is amended in paragraph (d) by removing the phrase 
``the Hospital Compare website'' and adding in its place the phrase 
``the Hospital Compare website, which can be accessed via the Care 
Compare website at https://www.medicare.gov/care-compare/''.


Sec.  412.164   [Amended]

0
13. Section 412.164 is amended in paragraph (b) by removing the phrase 
``the Hospital Compare website'' and adding in its place the phrase 
``the Hospital Compare website, which can be accessed via the Care 
Compare website at https://www.medicare.gov/care-compare/''.


Sec.  412.165   [Amended]

0
14. Section 412.165 is amended--
0
a. In paragraph (c)(2), by removing ``QualityNet website 
(QualityNet.org)'' and adding in its place ``QualityNet website 
(https://qualitynet.cms.gov/)''; and
0
b. In paragraph (c)(4), by removing ``QualityNet website (see https://www.qualitynet.org)'' and adding in its place ``QualityNet website 
(https://qualitynet.cms.gov/).


Sec.  412.167  [Amended]

0
15. Section 412.167 is amended in paragraph (b)(5) by removing 
``QualityNet System Administrator'' and adding in its place 
``QualityNet security official''.

0
16. Section 412.168 is added to read as follows:


Sec.  412.168  Special rule for FY 2022.

    (a) This section sets forth the scoring and payment methodology for 
the fiscal year 2022 Hospital VBP Program.
    (b) CMS calculates a measure rate for all measures selected under 
Sec.  412.164(a) for fiscal year 2022 but only applies Sec.  412.165(a) 
to the measures included in the Clinical Outcomes Domain for that 
fiscal year, which are the following:
    (1) Hospital 30-Day, All-Cause, Risk-Standardized Mortality Rate 
Following Acute Myocardial Infarction (AMI) Hospitalization (MORT-30-
AMI).
    (2) Hospital 30-Day, All-Cause, Risk-Standardized Mortality Rate 
Following Heart Failure (HF) Hospitalization (MORT-30-HF).
    (3) Hospital 30-Day, All-Cause, Risk-Standardized Mortality Rate 
Following Pneumonia Hospitalization (MORT-30-PN (updated cohort)).
    (4) Hospital 30-Day, All-Cause, Risk-Standardized Mortality Rate 
Following Chronic Obstructive Pulmonary Disease (COPD) Hospitalization 
(MORT-30-COPD).
    (5) Hospital 30-Day, All-Cause, Risk-Standardized Mortality Rate 
Following Coronary Artery Bypass Graft (CABG) Surgery (MORT-30-CABG).
    (6) Hospital-Level Risk-Standardized Complication Rate Following 
Elective Primary Total Hip Arthroplasty (THA) and/or Total Knee 
Arthroplasty (TKA) (COMP-HIP-KNEE).
    (c) CMS calculates a domain score for the measures described in 
paragraph (b)(1) of this section for hospitals that report the minimum 
number of measures in the Clinical Outcomes Domain.
    (d) CMS does not award a Total Performance Score to any hospital.
    (e) The total amount available for value-based incentive payments 
for fiscal year 2022 is equal to the total amount of base-operating DRG 
payment reductions for that fiscal year, as estimated by the Secretary.
    (f) CMS awards value-based incentive payment percentages (as 
defined in Sec.  412.160) for all hospitals to ensure that each 
hospital receives an incentive payment amount equal to the amount of 
the reduction made to its base-operating DRG payment amounts.

0
17. Section 412.172 is amended by revising paragraph (f)(4) to read as 
follows:


Sec.  412.172  Reporting of hospital specific information.

* * * * *
    (f) * * *
    (4) CMS posts the total hospital-acquired condition score, the 
domain score, and the score on each measure for each hospital on the 
Hospital Compare website or successor website.
* * * * *

0
18. Section 412.278 is amended by revising the first sentence of 
paragraph (b)(1) and revising paragraph (f)(2)(ii) to read as follows:


Sec.  412.278   Administrator's review.

* * * * *
    (b) * * *
    (1) The hospital's request for review must be in writing and sent 
to the Administrator, in care of the Office of the Attorney Advisor, in 
the manner directed by the Office of the Attorney Advisor. * * *
* * * * *
    (f) * * *
    (2) * * *
    (ii) Not later than 105 days following issuance of the MGCRB 
decision in the case of review at the discretion of the Administrator, 
except the Administrator may, at his or her discretion, for good cause 
shown, toll such 105 days.
* * * * *

[[Page 45521]]

PART 413--PRINCIPLES OF REASONABLE COST REIMBURSEMENT; PAYMENT FOR 
END-STAGE RENAL DISEASE SERVICES; OPTIONAL PROSPECTIVELY DETERMINED 
PAYMENT RATES FOR SKILLED NURSING FACILITIES

0
19. The authority citation for part 413 continues to read as follows:

    Authority: 42 U.S.C. 1302, 1395d(d), 1395f(b), 1395g, 1395l(a), 
(i), and (n), 1395x(v), 1395hh, 1395rr, 1395tt, and 1395ww.


0
20. Section 413.20 is amended by revising paragraph (d)(3) to read as 
follows:


Sec.  413.20  Financial data and reports.

* * * * *
    (d) * * *
    (3)(i) The provider must furnish the contractor, upon request, 
copies of patient service charge schedules and changes thereto as they 
are put into effect; and
    (ii) The contractor evaluates the charge schedules as specified in 
paragraph (d)(3)(i) of this section to determine the extent to which 
they may be used for determining program payment.
* * * * *

0
21. Section 413.24 is amended by revising paragraphs (f)(5)(i) 
introductory text and (f)(5)(i)(A) to read as follows:


Sec.  413.24   Adequate cost data and cost finding.

* * * * *
    (f) * * *
    (5) * * *
    (i) The provider must accurately complete and submit the required 
cost reporting forms, including all necessary signatures and supporting 
documents. For providers claiming costs on their cost reports that are 
allocated from a home office or chain organization, the Home Office 
Cost statement must be submitted by the home office or chain 
organization as set forth in paragraph (f)(5)(i)(E) of this section. A 
cost report is rejected for lack of supporting documentation if it does 
not include the following, except as provided in paragraph (f)(5)(i)(E) 
of this section:
    (A) Teaching hospitals. For teaching hospitals, effective for cost 
reporting periods beginning on or after October 1, 2021, the Intern and 
Resident Information System (IRIS) data which must contain the same 
total counts of direct GME FTE residents (unweighted and weighted) and 
IME FTE residents as the total counts of direct GME FTE and IME FTE 
residents reported in the provider's cost report.
* * * * *

PART 425--MEDICARE SHARED SAVINGS PROGRAM

0
22. The authority for part 425 continues to read as follows:

    Authority: 42 U.S.C. 1302, 1306, 1395hh, and 1395jjj.


0
23. Section 425.600 is amended by--
0
a. Redesignating paragraph (a)(4)(i)(B)(2)(iv) as paragraph 
(a)(4)(i)(B)(2)(v);
0
b. Adding new paragraph (a)(4)(i)(B)(2)(iv); and
0
c. In paragraph (a)(4)(i)(B)(3), removing the phrase ``paragraph 
(a)(4)(i)(B)(2)(iii)'' and adding in its place the phrase ``paragraph 
(a)(4)(i)(B)(2)(v).''
    The addition reads as follows:


Sec.  425.600  Selection of risk model.

    (a) * * *
    (4) * * *
    (i) * * *
    (B) * * *
    (2) * * *
    (iv) Exception for ACOs participating in the BASIC track's glide 
path that elect to maintain their participation level for performance 
year 2022. Prior to the automatic advancement for performance year 
2022, an ACO that is participating in the BASIC track's glide path for 
performance year 2021 may elect to remain in the same level of the 
BASIC track's glide path in which it participated during the 2021 
performance year, for performance year 2022. For performance year 2023, 
the ACO is automatically advanced to the level of the BASIC track's 
glide path to which the ACO would have automatically advanced absent 
the election to maintain its participation level for performance year 
2022 and, if applicable, the election to maintain its participation 
level for performance year 2021 under paragraph (a)(4)(i)(B)(2)(iii) of 
this section, unless the ACO elects to transition to a higher level of 
risk and potential reward within the BASIC track's glide path as 
provided in Sec.  425.226(a)(2)(i). A voluntary election by an ACO 
under this paragraph must be made in the form and manner and by a 
deadline established by CMS.
* * * * *

PART 455--PROGRAM INTEGRITY: MEDICAID

0
24. The authority citation for part 455 continues to read as follows:

    Authority:  42 U.S.C. 1302.


0
25. Section 455.410 is amended by adding paragraph (d) to read as 
follows:


Sec.  455.410   Enrollment and screening of providers.

* * * * *
    (d) The State Medicaid agency must allow enrollment of all 
Medicare-enrolled providers and suppliers for purposes of processing 
claims to determine Medicare cost-sharing (as defined in section 
1905(p)(3) of the Act) if the providers or suppliers meet all Federal 
Medicaid enrollment requirements, including, but not limited to, all 
applicable provisions of 42 CFR part 455, subparts B and E. This 
paragraph (d) applies even if the Medicare-enrolled provider or 
supplier is of a type not recognized by the State Medicaid Agency.

PART 495--STANDARDS FOR THE ELECTRONIC HEALTH RECORD TECHNOLOGY 
INCENTIVE PROGRAM

0
26. The authority citation for part 495 continues to read as follows:

    Authority:  42 U.S.C. 1302 and 1395hh.


0
27. Section 495.4 is amended by--
0
a. Adding paragraphs (2)(vii) and (viii) and (3)(vii) and (viii) to the 
definition of ``EHR reporting period for a payment adjustment year''; 
and
0
b. Revising the introductory text and paragraph (1) of the definition 
of ``Meaningful EHR user''.
    The additions and revisions read as follows:


Sec.  495.4  Definitions.

* * * * *
    EHR reporting period for a payment adjustment year. * * *
    (2) * * *
    (vii) The following are applicable for 2023:
    (A) If an eligible hospital has not successfully demonstrated it is 
a meaningful EHR user in a prior year, the EHR reporting period is any 
continuous 90-day period within CY 2023 and applies for the FY 2024 and 
2025 payment adjustment years. For the FY 2024 payment adjustment year, 
the EHR reporting period must end before and the eligible hospital must 
successfully register for and attest to meaningful use no later than 
October 1, 2023.
    (B) If in a prior year an eligible hospital has successfully 
demonstrated it is a meaningful EHR user, the EHR reporting period is 
any continuous 90-day period within CY 2023 and applies for the FY 2025 
payment adjustment year.
    (viii) The following are applicable for 2024:
    (A) If an eligible hospital has not successfully demonstrated it is 
a

[[Page 45522]]

meaningful EHR user in a prior year, the EHR reporting period is any 
continuous 180-day period within CY 2024 and applies for the FY 2025 
and 2026 payment adjustment years. For the FY 2025 payment adjustment 
year, the EHR reporting period must end before and the eligible 
hospital must successfully register for and attest to meaningful use no 
later than October 1, 2024.
    (B) If in a prior year an eligible hospital has successfully 
demonstrated it is a meaningful EHR user, the EHR reporting period is 
any continuous 180-day period within CY 2024 and applies for the FY 
2026 payment adjustment year.
    (3) * * *
    (vii) The following are applicable for 2023:
    (A) If a CAH has not successfully demonstrated it is a meaningful 
EHR user in a prior year, the EHR reporting period is any continuous 
90-day period within CY 2023 and applies for the FY 2023 payment 
adjustment year.
    (B) If in a prior year a CAH has successfully demonstrated it is a 
meaningful EHR user, the EHR reporting period is any continuous 90-day 
period within CY 2023 and applies for the FY 2023 payment adjustment 
year.
    (viii) The following are applicable for 2024:
    (A) If a CAH has not successfully demonstrated it is a meaningful 
EHR user in a prior year, the EHR reporting period is any continuous 
180-day period within CY 2024 and applies for the FY 2024 payment 
adjustment year.
    (B) If in a prior year a CAH has successfully demonstrated it is a 
meaningful EHR user, the EHR reporting period is any continuous 180-day 
period within CY 2024 and applies for the FY 2024 payment adjustment 
year.
* * * * *
    Meaningful EHR user means all of the following:
    (1) Subject to paragraph (3) of this definition, an EP, eligible 
hospital or CAH that, for an EHR reporting period for a payment year or 
payment adjustment year--
    (i) Demonstrates in accordance with Sec.  495.40 meaningful use of 
certified EHR technology by meeting the applicable objectives and 
associated measures under Sec. Sec.  495.20, 495.22, 495.24;
    (ii) Does not knowingly and willfully take action (such as to 
disable functionality) to limit or restrict the compatibility or 
interoperability of CEHRT;
    (iii) Engages in activities related to supporting providers with 
the performance of CEHRT; and
    (iv) Successfully reports the clinical quality measures selected by 
CMS to CMS or the States, as applicable, in the form and manner 
specified by CMS or the States, as applicable.
* * * * *

0
28. Section 495.24 is amended by--
0
a. Revising paragraphs (e)(1)(i) and (e)(4)(ii);
0
b. Adding paragraph (e)(4)(iv);
0
c. Revising paragraphs (e)(5)(ii)(B), (e)(5)(iii)(B), and (e)(6)(ii) 
introductory text;
0
d. Adding paragraph (e)(6)(ii)(C);
0
e. In paragraph (e)(7)(ii) introductory text, removing the en dash and 
adding in its place ``all of the following:'';
0
f. In paragraph (e)(7)(ii)(A), by removing ``; and'' and adding in its 
place a period;
0
g. In paragraph (e)(7)(ii)(B), by removing the sentence ``This measure 
is worth up to 40 points beginning in CY 2019.''; and
0
h. Revising paragraphs (e)(8)(ii) introductory text, (e)(8)(ii)(A) and 
(e)(8)(iii) introductory text, (e)(8)(iii)(A)(1) and (2), and 
(e)(8)(iii)(D) and (E).
    The revisions and additions read as follows:


Sec.  495.24  Stage 3 meaningful use objectives and measures for EPs, 
eligible hospitals and CAHs for 2019 and subsequent years.

* * * * *
    (e) * * *
    (1) * * *
    (i) Except as specified in paragraph (e)(2) of this section, 
eligible hospitals and CAHs must do all of the following as part of 
meeting the definition of a meaningful EHR user under Sec.  495.4:
    (A) Meet all objectives and associated measures of the Stage 3 
criteria specified in this paragraph (e).
    (B) In 2019, 2020, and 2021, earn a total score of at least 50 
points.
    (C) In 2022 and subsequent years, earn a total score of at least 60 
points.
* * * * *
    (4) * * *
    (ii) Measure scoring. Eligible hospitals and CAHs are required to 
report on the security risk analysis measure in paragraph (e)(4)(iii) 
of this section, but no points are available for this measure. In 2022 
and subsequent years, eligible hospitals and CAHs are required to 
report on the SAFER Guides measure in paragraph (e)(4)(iv) of this 
section, but no points are available for this measure.
* * * * *
    (iv) SAFER Guides measure. Conduct an annual self- assessment using 
all nine SAFER Guides at any point during the calendar year in which 
the EHR reporting period occurs.
* * * * *
    (5) * * *
    (ii) * * *
    (B) In 2020 and subsequent years, eligible hospitals and CAHs must 
meet the e-Prescribing measure in paragraph (e)(5)(iii)(A) of this 
section, and have the option to report on the query of PDMP measure in 
paragraph (e)(5)(iii)(B) of this section.
    (1) In 2020 and 2021, the electronic prescribing objective in 
paragraph (e)(5)(i) of this section is worth up to 15 points.
    (2) In 2022, the electronic prescribing objective in paragraph 
(e)(5)(i) of this section is worth up to 20 points.
    (iii) * * *
    (B) Query of prescription drug monitoring program (PDMP) measure. 
Subject to paragraph (e)(3) of this section, for at least one Schedule 
II opioid electronically prescribed using CEHRT during the EHR 
reporting period, the eligible hospital or CAH uses data from CEHRT to 
conduct a query of a Prescription Drug Monitoring Program (PDMP) for 
prescription drug history, except where prohibited and in accordance 
with applicable law. This measure is worth--
    (1) 5 bonus points in CYs 2019, 2020, and 2021; and
    (2) 10 bonus points in CY 2022.
* * * * *
    (6) * * *
    (ii) Measures. For CYs 2019, 2020, and 2021, eligible hospitals and 
CAHs must meet both of the measures specified in paragraphs 
(e)(6)(ii)(A) and (B) of this section (each worth up to 20 points). For 
CY 2022, eligible hospitals and CAHs either must meet both of the 
measures specified in paragraphs (e)(6)(ii)(A) and (B) of this section 
(each worth up to 20 points) or must meet the measure specified in 
paragraph (e)(6)(ii)(C) of this section (worth 40 points).
* * * * *
    (C) Health information exchange (HIE) bi-directional exchange 
measure. Subject to paragraph (e)(3) of this section, the eligible 
hospital or CAH must attest to the following:
    (1) Participating in an HIE in order to enable secure, bi-
directional exchange of information to occur for all unique patients 
discharged from the eligible hospital or CAH inpatient or emergency 
department (POS 21 or 23), and all unique patient records stored or 
maintained in the EHR for these departments, during the EHR reporting 
period in accordance with applicable law and policy.

[[Page 45523]]

    (2) Participating in an HIE that is capable of exchanging 
information across a broad network of unaffiliated exchange partners 
including those using disparate EHRs, and not engaging in exclusionary 
behavior when determining exchange partners.
    (3) Using the functions of CEHRT to support bi-directional exchange 
with an HIE.
* * * * *
    (8) * * *
    (ii) Measures. For CYs 2019, 2020, and 2021, eligible hospitals and 
CAHs could receive a total of 10 points for the objective under 
paragraph (e)(8)(i) of this section. In order to meet the objective 
under paragraph (e)(8)(i) of this section, an eligible hospital or CAH 
must meet any two measures specified in paragraphs (e)(8)(ii)(A) 
through (F) of this section. For CY 2022 and subsequent years, eligible 
hospitals and CAHs could receive a total of 15 points for the objective 
under paragraph (e)(8)(i) of this section. In order to meet the 
objective under paragraph (e)(8)(i) of this section and receive 10 
points, an eligible hospital or CAH must meet each of the four measures 
specified in paragraphs (e)(8)(ii)(A), (B), (C), and (F) of this 
section. An eligible hospital or CAH receives a bonus of 5 points for 
this objective if they meet one of the measures specified in paragraph 
(e)(8)(ii)(D) or (E).
    (A) Syndromic surveillance reporting measure. For CYs 2019, 2020, 
and 2021, the eligible hospital or CAH is in active engagement with a 
public health agency to submit syndromic surveillance data from an 
urgent care setting. For CY 2022 and subsequent years, the eligible 
hospital or CAH is in active engagement with a public health agency to 
submit syndromic surveillance data from an emergency department setting 
(POS 23).
* * * * *
    (iii) Exclusions in accordance with paragraph (e)(2) of this 
section. For CYs 2019, 2020, and 2021, if an exclusion is claimed under 
paragraphs (e)(8)(iii)(A) through (F) of this section for each of the 
two measures selected for reporting, the 10 points for the objective 
specified in paragraph (e)(8)(i) of this section will be redistributed 
to the provide patients electronic access to their health information 
measure under paragraph (e)(7)(ii) of this section. For CY 2022 and 
subsequent years, if an exclusion is claimed under paragraphs 
(e)(8)(iii)(A) through (F) of this section for each of the four 
measures required for reporting, the 10 points for the objective 
specified in paragraph (e)(8)(i) of this section will be redistributed 
to the provide patients electronic access to their health information 
measure under paragraph (e)(7)(ii) of this section.
    (A) * * *
    (1) For CYs 2019, 2020 and 2021, does not have an emergency or 
urgent care department.
    (2) For CY 2022 and subsequent years, does not have an emergency 
department.
* * * * *
    (D)(1) For CYs 2019, 2020, and 2021, any eligible hospital or CAH 
meeting at least one of the following criteria may be excluded from the 
public health registry reporting measure specified in paragraph 
(e)(8)(ii)(D) of this section if the eligible hospital or CAH:
    (i) Does not diagnose or directly treat any disease or condition 
associated with a public health registry in its jurisdiction during the 
EHR reporting period.
    (ii) Operates in a jurisdiction for which no public health agency 
is capable of accepting electronic registry transactions in the 
specific standards required to meet the CEHRT definition at the start 
of the EHR reporting period.
    (iii) Operates in a jurisdiction where no public health registry 
for which the eligible hospital or CAH is eligible has declared 
readiness to receive electronic registry transactions as of 6 months 
prior to the start of the EHR reporting period.
    (2) For CY 2022 and subsequent years, the exclusions specified in 
paragraph (D)(1) of this paragraph are no longer available.
    (E)(1) For CYs 2019, 2020, and 2021, any eligible hospital or CAH 
meeting at least one of the following criteria may be excluded from the 
clinical data registry reporting measure specified in paragraph 
(e)(8)(ii)(E) of this section if the eligible hospital or CAH:
    (i) Does not diagnose or directly treat any disease or condition 
associated with a clinical data registry in their jurisdiction during 
the EHR reporting period.
    (ii) Operates in a jurisdiction for which no clinical data registry 
is capable of accepting electronic registry transactions in the 
specific standards required to meet the CEHRT definition at the start 
of the EHR reporting period.
    (iii) Operates in a jurisdiction where no clinical data registry 
for which the eligible hospital or CAH is eligible has declared 
readiness to receive electronic registry transactions as of 6 months 
prior to the start of the EHR reporting period.
    (2) For CY 2022 and subsequent years, the exclusions specified in 
paragraph (E)(1) of this paragraph are no longer available.
* * * * *

0
29. Section 495.40 is amended by revising paragraphs (b) introductory 
text and (b)(2)(i)(I) introductory text and adding paragraph 
(b)(2)(i)(J) to read as follows:


Sec.  495.40   Demonstration of meaningful use criteria.

* * * * *
    (b) Demonstration by eligible hospitals and CAHs. An eligible 
hospital or CAH must demonstrate that it satisfies each of the 
applicable objectives and associated measures under Sec.  495.20, Sec.  
495.22, or Sec.  495.24; supports health information exchange and the 
prevention of health information blocking or does not take actions to 
limit or restrict the compatibility or interoperability of CEHRT, as 
applicable for the EHR reporting period; and engages in activities 
related to supporting providers with the performance of CEHRT.
    (2) * * *
    (i) * * *
    (I) Support for health information exchange and the prevention of 
information blocking. For an EHR reporting period in CYs 2017 through 
2021, the eligible hospital or CAH must attest that it--
* * * * *
    (J) Actions to limit or restrict the compatibility or 
interoperability of CEHRT. For an EHR reporting period in CY 2022 and 
subsequent years, the eligible hospital or CAH must attest that it did 
not knowingly and willfully take action (such as to disable 
functionality) to limit or restrict the compatibility or 
interoperability of certified EHR technology.
* * * * *

    Dated: July 29, 2021.
Xavier Becerra,
Secretary, Department of Health and Human Services.

    Note: The following Addendum and Appendixes will not appear in 
the Code of Federal Regulations.

Addendum--Schedule of Standardized Amounts, Update Factors, Rate-of-
Increase Percentages Effective With Cost Reporting Periods Beginning on 
or After October 1, 2021, and Payment Rates for LTCHs Effective for 
Discharges Occurring on or After October 1, 2021

I. Summary and Background

    In this Addendum, we are setting forth a description of the methods 
and data we used to determine the prospective payment rates for 
Medicare hospital inpatient operating costs and

[[Page 45524]]

Medicare hospital inpatient capital-related costs for FY 2022 for acute 
care hospitals. We also are setting forth the rate-of-increase 
percentage for updating the target amounts for certain hospitals 
excluded from the IPPS for FY 2022. We note that, because certain 
hospitals excluded from the IPPS are paid on a reasonable cost basis 
subject to a rate-of-increase ceiling (and not by the IPPS), these 
hospitals are not affected by the figures for the standardized amounts, 
offsets, and budget neutrality factors. Therefore, in this final rule, 
we are setting forth the rate-of-increase percentage for updating the 
target amounts for certain hospitals excluded from the IPPS that will 
be effective for cost reporting periods beginning on or after October 
1, 2021.
    In addition, we are setting forth a description of the methods and 
data we used to determine the LTCH PPS standard Federal payment rate 
that will be applicable to Medicare LTCHs for FY 2022.
    In general, except for SCHs and MDHs, for FY 2022, each hospital's 
payment per discharge under the IPPS is based on 100 percent of the 
Federal national rate, also known as the national adjusted standardized 
amount. This amount reflects the national average hospital cost per 
case from a base year, updated for inflation.
    SCHs are paid based on whichever of the following rates yields the 
greatest aggregate payment: The Federal national rate (including, as 
discussed in section IV.E. of the preamble of this final rule, 
uncompensated care payments under section 1886(r)(2) of the Act); the 
updated hospital-specific rate based on FY 1982 costs per discharge; 
the updated hospital-specific rate based on FY 1987 costs per 
discharge; the updated hospital-specific rate based on FY 1996 costs 
per discharge; or the updated hospital-specific rate based on FY 2006 
costs per discharge.
    Under section 1886(d)(5)(G) of the Act, MDHs historically were paid 
based on the Federal national rate or, if higher, the Federal national 
rate plus 50 percent of the difference between the Federal national 
rate and the updated hospital-specific rate based on FY 1982 or FY 1987 
costs per discharge, whichever was higher. However, section 5003(a)(1) 
of Public Law 109-171 extended and modified the MDH special payment 
provision that was previously set to expire on October 1, 2006, to 
include discharges occurring on or after October 1, 2006, but before 
October 1, 2011. Under section 5003(b) of Public Law 109-171, if the 
change results in an increase to an MDH's target amount, we must rebase 
an MDH's hospital specific rates based on its FY 2002 cost report. 
Section 5003(c) of Public Law 109-171 further required that MDHs be 
paid based on the Federal national rate or, if higher, the Federal 
national rate plus 75 percent of the difference between the Federal 
national rate and the updated hospital specific rate. Further, based on 
the provisions of section 5003(d) of Public Law 109-171, MDHs are no 
longer subject to the 12-percent cap on their DSH payment adjustment 
factor. Section 50205 of the Bipartisan Budget Act of 2018 extended the 
MDH program for discharges on or after October 1, 2017 through 
September 30, 2022.
    As discussed in section V.A.2. of the preamble of this final rule, 
section 1886(n)(6)(B) of the Act was amended to specify that the 
adjustments to the applicable percentage increase under section 
1886(b)(3)(B)(ix) of the Act apply to subsection (d) Puerto Rico 
hospitals that are not meaningful EHR users, effective beginning FY 
2022. In general, Puerto Rico hospitals are paid 100 percent of the 
national standardized amount and are subject to the same national 
standardized amount as subsection (d) hospitals that receive the full 
update. Accordingly, our discussion later in this section does not 
include references to the Puerto Rico standardized amount or the Puerto 
Rico-specific wage index.
    As discussed in section II. of this Addendum, we are making changes 
in the determination of the prospective payment rates for Medicare 
inpatient operating costs for acute care hospitals for FY 2022. In 
section III. of this Addendum, we discuss our policy changes for 
determining the prospective payment rates for Medicare inpatient 
capital-related costs for FY 2022. In section IV. of this Addendum, we 
are setting forth the rate-of-increase percentage for determining the 
rate-of-increase limits for certain hospitals excluded from the IPPS 
for FY 2022. In section V. of this Addendum, we discuss policy changes 
for determining the LTCH PPS standard Federal rate for LTCHs paid under 
the LTCH PPS for FY 2022. The tables to which we refer in the preamble 
of this final rule are listed in section VI. of this Addendum and are 
available via the internet on the CMS website.

II. Changes to Prospective Payment Rates for Hospital Inpatient 
Operating Costs for Acute Care Hospitals for FY 2022

    The basic methodology for determining prospective payment rates for 
hospital inpatient operating costs for acute care hospitals for FY 2005 
and subsequent fiscal years is set forth under Sec.  412.64. The basic 
methodology for determining the prospective payment rates for hospital 
inpatient operating costs for hospitals located in Puerto Rico for FY 
2005 and subsequent fiscal years is set forth under Sec. Sec.  412.211 
and 412.212. In this section, we discuss the factors we are using for 
determining the prospective payment rates for FY 2022.
    In summary, the standardized amounts set forth in Tables 1A, 1B, 
and 1C that are listed and published in section VI. of this Addendum 
(and available via the internet on the CMS website) reflect--
     Equalization of the standardized amounts for urban and 
other areas at the level computed for large urban hospitals during FY 
2004 and onward, as provided for under section 1886(d)(3)(A)(iv)(II) of 
the Act.
     The labor-related share that is applied to the 
standardized amounts to give the hospital the highest payment, as 
provided for under sections 1886(d)(3)(E) and 1886(d)(9)(C)(iv) of the 
Act. For FY 2022, depending on whether a hospital submits quality data 
under the rules established in accordance with section 
1886(b)(3)(B)(viii) of the Act (hereafter referred to as a hospital 
that submits quality data) and is a meaningful EHR user under section 
1886(b)(3)(B)(ix) of the Act (hereafter referred to as a hospital that 
is a meaningful EHR user), there are four possible applicable 
percentage increases that can be applied to the national standardized 
amount. We refer readers to section V.A. of the preamble of this final 
rule for a complete discussion on the FY 2022 inpatient hospital 
update. The table that follows shows these four scenarios:

[[Page 45525]]

[GRAPHIC] [TIFF OMITTED] TR13AU21.322

    We note that section 1886(b)(3)(B)(viii) of the Act, which 
specifies the adjustment to the applicable percentage increase for 
``subsection (d)'' hospitals that do not submit quality data under the 
rules established by the Secretary, is not applicable to hospitals 
located in Puerto Rico.
    In addition, section 602 of Public Law 114-113 amended section 
1886(n)(6)(B) of the Act to specify that Puerto Rico hospitals are 
eligible for incentive payments for the meaningful use of certified EHR 
technology, effective beginning FY 2016, and also to apply the 
adjustments to the applicable percentage increase under section 
1886(b)(3)(B)(ix) of the Act to subsection (d) Puerto Rico hospitals 
that are not meaningful EHR users, effective beginning FY 2022. 
Accordingly, for FY 2022, section 1886(b)(3)(B)(ix) of the Act in 
conjunction with section 602(d) of Public Law 114-113 requires that any 
subsection (d) Puerto Rico hospital that is not a meaningful EHR user 
(as defined in section 1886(n)(3) of the Act) and not subject to an 
exception under section 1886(b)(3)(B)(ix) of the Act will have ``three-
quarters'' of the applicable percentage increase (prior to the 
application of other statutory adjustments), or three-quarters of the 
applicable market basket update, reduced by 33\1/3\ percent. The 
reduction to three-quarters of the applicable percentage increase for 
subsection (d) Puerto Rico hospitals that are not meaningful EHR users 
increases to 66\2/3\ percent for FY 2023, and, for FY 2024 and 
subsequent fiscal years, to 100 percent. In the FY 2019 IPPS/LTCH PPS 
final rule, we finalized the payment reductions (83 FR 41674). (We note 
that section 1886(b)(3)(B)(viii) of the Act, which specifies the 
adjustment to the applicable percentage increase for ``subsection (d)'' 
hospitals that do not submit quality data under the rules established 
by the Secretary, is not applicable to hospitals located in Puerto 
Rico.) The regulations at 42 CFR 412.64(d)(3)(ii) reflect the current 
law for the update for subsection (d) Puerto Rico hospitals for FY 2022 
and subsequent fiscal years.
     An adjustment to the standardized amount to ensure budget 
neutrality for DRG recalibration and reclassification, as provided for 
under section 1886(d)(4)(C)(iii) of the Act.
     An adjustment to ensure the wage index and labor-related 
share changes (depending on the fiscal year) are budget neutral, as 
provided for under section 1886(d)(3)(E)(i) of the Act (as discussed in 
the FY 2006 IPPS final rule (70 FR 47395) and the FY 2010 IPPS final 
rule (74 FR 44005). We note that section 1886(d)(3)(E)(i) of the Act 
requires that when we compute such budget neutrality, we assume that 
the provisions of section 1886(d)(3)(E)(ii) of the Act (requiring a 62 
percent labor-related share in certain circumstances) had not been 
enacted.
     An adjustment to ensure the effects of geographic 
reclassification are budget neutral, as provided for under section 
1886(d)(8)(D) of the Act, by removing the FY 2020 budget neutrality 
factor and applying a revised factor.
     A positive adjustment of 0.5 percent in FYs 2019 through 
2023 as required under section 414 of the MACRA.
     An adjustment to ensure the effects of the Rural Community 
Hospital Demonstration program required under section 410A of Public 
Law 108-173 (as amended by sections 3123 and 10313 of Public Law 111-
148, which extended the demonstration program for an additional 5 years 
and section 15003 of Public Law 114-255), are budget neutral as 
required under section 410A(c)(2) of Public Law 108-173.
     An adjustment to the standardized amount to implement in a 
budget neutral manner the increase in the wage index values for 
hospitals with a wage index value below the 25th percentile wage index 
value across all hospitals (as described in section III.N. of the 
preamble of this final rule).
     As discussed in this section and in section III.2.d of the 
preamble of this final rule, an adjustment to the standardized amount 
(using our exceptions and adjustments authority under section 
1886(d)(5)(I)(i) of the Act) to continue to implement in a budget 
neutral manner our transition for hospitals negatively impacted due to 
changes as a result of the implementation of the revised OMB market 
labor delineations. We refer reader to section III.A.2 of the preamble 
of this final rule, for a detailed discussion.
     An adjustment to remove the FY 2021 outlier offset and 
apply an offset for FY 2022, as provided for in section 1886(d)(3)(B) 
of the Act.
    For FY 2022, consistent with current law, we are applying the rural 
floor budget neutrality adjustment to hospital wage indexes. Also, 
consistent with section 3141 of the Affordable Care Act, instead of 
applying a State-level rural floor budget neutrality adjustment to the 
wage index, we are applying a uniform, national budget neutrality 
adjustment to the FY 2022 wage index for the rural floor.
    For FY 2022, we proposed to not remove the FY 2021 Stem Cell 
Acquisition Budget Neutrality Factor from the prior year's standardized 
amount and not to apply a new factor. As discussed in the proposed 
rule, if we removed the prior year's adjustment, we would not satisfy 
budget neutrality. We

[[Page 45526]]

stated that we believed this approach ensures the effects of the 
reasonable cost based payment for allogeneic hematopoietic stem cell 
acquisition costs under section 108 of the Further Consolidated 
Appropriations Act, 2020 (Pub. L. 116-94) are budget neutral as 
required under section 108 of Public Law 116-94. For a discussion of 
Stem Cell Acquisition Budget Neutrality Factor, we refer the reader to 
the FY 2021 IPPS/LTCH PPS final rule (85 FR 59032 and 59033). When cost 
report data regarding reasonable cost of acquisition become available, 
we intend to consider using that reasonable cost data in future 
rulemaking for budget neutrality.
    Comment: A commenter stated that the budget neutrality factor 
should be removed for FY 2022 because the availability of reliable cost 
data on stem cell acquisition costs will be delayed due to the COVID-19 
PHE.
    Response: We appreciate the commenter's input on the potential 
impact of the COVID-19 PHE on stem cell acquisition cost data. However, 
section 108 of the Further Consolidated Appropriations Act, 2020 (Pub. 
L. 116-94) requires that the reasonable cost based payments for 
allogeneic hematopoietic stem cell acquisition costs are budget 
neutral, and, as stated above, if we removed the prior year's 
adjustment we would not satisfy budget neutrality.
    After consideration of comments received, we are finalizing our 
proposal without modification. We are not removing the FY 2021 Stem 
Cell Acquisition Budget Neutrality Factor from the prior year's 
standardized amount and we are not applying a new factor.

A. Calculation of the Adjusted Standardized Amount

1. Standardization of Base-Year Costs or Target Amounts
    In general, the national standardized amount is based on per 
discharge averages of adjusted hospital costs from a base period 
(section 1886(d)(2)(A) of the Act), updated and otherwise adjusted in 
accordance with the provisions of section 1886(d) of the Act. The 
September 1, 1983 interim final rule (48 FR 39763) contained a detailed 
explanation of how base-year cost data (from cost reporting periods 
ending during FY 1981) were established for urban and rural hospitals 
in the initial development of standardized amounts for the IPPS.
    Sections 1886(d)(2)(B) and 1886(d)(2)(C) of the Act require us to 
update base-year per discharge costs for FY 1984 and then standardize 
the cost data in order to remove the effects of certain sources of cost 
variations among hospitals. These effects include case-mix, differences 
in area wage levels, cost-of-living adjustments for Alaska and Hawaii, 
IME costs, and costs to hospitals serving a disproportionate share of 
low-income patients.
    For FY 2022, as we proposed, we are rebasing and revising the 
national labor-related and nonlabor-related shares (based on the 2018-
based IPPS market basket discussed in section IV.B.3. of the preamble 
of this final rule). Specifically, under section 1886(d)(3)(E) of the 
Act, the Secretary estimates, from time to time, the proportion of 
payments that are labor-related and adjusts the proportion (as 
estimated by the Secretary from time to time) of hospitals' costs which 
are attributable to wages and wage-related costs of the DRG prospective 
payment rates. We refer to the proportion of hospitals' costs that are 
attributable to wages and wage-related costs as the ``labor-related 
share.'' For FY 2022, as discussed in section IV.B.3. of the preamble 
of this final rule, as we proposed, we are using a labor-related share 
of 67.6 percent for the national standardized amounts for all IPPS 
hospitals (including hospitals in Puerto Rico) that have a wage index 
value that is greater than 1.0000. Consistent with section 
1886(d)(3)(E) of the Act, as we proposed, we are applying the wage 
index to a labor-related share of 62 percent of the national 
standardized amount for all IPPS hospitals (including hospitals in 
Puerto Rico) whose wage index values are less than or equal to 1.0000.
    The standardized amounts for operating costs appear in Tables 1A, 
1B, and 1C that are listed and published in section VI. of the Addendum 
to this final rule and are available via the internet on the CMS 
website.
    Comment: Some commenters asserted a calculation error regarding the 
treatment of transfers in setting the standardized amount in 1983 and 
that this alleged error impacts the FY 2022 standardized amount. This 
same commenter questioned if CMS had statutory authority to include 
transfers in the standardized amount for FY 2022.
    Response: We disagree with the commenters. The calculations of the 
standardized amounts since the inception of the IPPS have proceeded 
through notice and comment rulemaking, and there have been numerous 
statutory changes to the standardized amounts in the intervening years 
since the inception of the IPPS. There is no basis for a change to the 
standardized amount now in FY2022.
    Comment: Some commenters stated that CMS misinterpreted ATRA 
section 631 recoupment related to FY 2017, and that CMS should apply a 
MS-DRG documentation and coding positive adjustment of 0.7 percentage 
points in addition to the 0.5 percentage point adjustment proposed. 
Some commenters believed that would stop the continuation of a 
recoupment adjustment that no longer serves any recoupment purpose.
    Response: We received similar comments on the ATRA requirements 
related to FY 2017 in response to prior years' rulemaking, such as the 
FY 2020 proposed rule, and we refer readers to that response. (84 FR 
42057). In addition, we refer readers to section II.C of this final 
rule for additional discussion.
2. Computing the National Average Standardized Amount
    Section 1886(d)(3)(A)(iv)(II) of the Act requires that, beginning 
with FY 2004 and thereafter, an equal standardized amount be computed 
for all hospitals at the level computed for large urban hospitals 
during FY 2003, updated by the applicable percentage update. 
Accordingly, as we proposed, we calculated the FY 2022 national average 
standardized amount irrespective of whether a hospital is located in an 
urban or rural location.
3. Updating the National Average Standardized Amount
    Section 1886(b)(3)(B) of the Act specifies the applicable 
percentage increase used to update the standardized amount for payment 
for inpatient hospital operating costs. We note that, in compliance 
with section 404 of the MMA, as we proposed, we used the 2018-based 
IPPS operating and capital market baskets for FY 2022. As discussed in 
section IV.B. of the preamble of this final rule, in accordance with 
section 1886(b)(3)(B) of the Act, as amended by section 3401(a) of the 
Affordable Care Act, as we proposed, we reduced the FY 2022 applicable 
percentage increase (which for this final rule is based on IGI's second 
quarter 2021 forecast of the 2018-based IPPS market basket) by the 
productivity adjustment, as discussed elsewhere in this final rule.
    Based on IGI's second quarter 2021 forecast of the hospital market 
basket increase (as discussed in Appendix B of this final rule), the 
forecast of the hospital market basket increase for FY 2022 for this 
final rule is 2.7 percent. As discussed earlier, for FY 2022, depending 
on whether a hospital submits quality data under the rules

[[Page 45527]]

established in accordance with section 1886(b)(3)(B)(viii) of the Act 
and is a meaningful EHR user under section 1886(b)(3)(B)(ix) of the 
Act, there are four possible applicable percentage increases that can 
be applied to the standardized amount. We refer readers to section V.A. 
of the preamble of this final rule for a complete discussion on the FY 
2022 inpatient hospital update to the standardized amount. We also 
refer readers to the previous table for the four possible applicable 
percentage increases that will be applied to update the national 
standardized amount. The standardized amounts shown in Tables 1A 
through 1C that are published in section VI. of this Addendum and that 
are available via the internet on the CMS website reflect these 
differential amounts.
    Although the update factors for FY 2022 are set by law, we are 
required by section 1886(e)(4) of the Act to recommend, taking into 
account MedPAC's recommendations, appropriate update factors for FY 
2022 for both IPPS hospitals and hospitals and hospital units excluded 
from the IPPS. Section 1886(e)(5)(A) of the Act requires that we 
publish our recommendations in the Federal Register for public comment. 
Our recommendation on the update factors is set forth in Appendix B of 
this final rule.
4. Methodology for Calculation of the Average Standardized Amount
    As discussed in section I.F. of the preamble of this final rule, as 
we proposed, we are finalizing to use alternative data for the FY 2022 
ratesetting in situations where the latest data available that would 
typically be used for the final rule is significantly impacted by the 
COVID-19 PHE. We refer the reader to section I.F. of the preamble of 
this final rule for further discussion of this final policy and our 
analysis of the best available data for purposes of FY 2022 
ratesetting. In this section, we discuss the data we are finalizing to 
use for our FY 2022 ratesetting process for the modeling of payments 
for the budget neutrality factors and the outlier fixed-loss cost 
threshold.
     Ordinarily, the best available MedPAR data for our 
ratesetting process would be the most recent MedPAR file that contains 
claims from discharges for the fiscal year that is 2 years prior to the 
fiscal year that is the subject of the rulemaking. For FY 2022, under 
ordinary circumstances, the best available data to model payments for 
FY 2022 and calculate the budget neutrality adjustments described in 
this section would be the FY 2020 MedPAR file (discharges on or after 
October 1, 2019 through discharges on or before September 30, 2020). 
However, for the reasons discussed in section I.F. of the preamble this 
final rule, we are finalizing to use the FY 2019 MedPAR claims data, 
including for purposes of calculating the budget neutrality adjustments 
and outlier fixed-loss cost threshold.
     The inpatient Provider Specific File (PSF) is maintained 
by the Medicare Administrative Contractor and contains information 
about data specific to the provider that affects computations for the 
IPPS. Typically, for the IPPS ratesetting, to model payments, we use 
the most recent available data at the time of the development of the 
proposed and final rules, which is typically from the December update 
of the PSF for the proposed rule and the March update of the PSF for 
the final rule. For example, for the FY 2022 rulemaking, the PSF we 
would typically use for the FY 2022 proposed rule would be the December 
2020 update of the PSF and the PSF we would typically use for the final 
rule would be the March 2021 update of the PSF. The fields used from 
the PSF in our ratesetting are listed in the impact file posted with 
each proposed and final rule, which includes provider-specific 
information such as CCRs, bed size, and Medicaid utilization ratio. For 
some IPPS hospitals, the provider data for these fields in the March 
2021 update of the PSF may have come from cost reports that ended 
during the COVID-19 PHE, and therefore we believe these fields may be 
affected by the PHE. For FY 2022, in general, we are finalizing to use 
the March 2020 update of the PSF, the latest update of the PSF prior to 
the PHE, except for those fields on the PSF not affected by the PHE, 
such as provider-type. For those fields on the PSF that we believe were 
not impacted by the PHE, as we proposed, we are using the March 2021 
update of the PSF for this final rule, consistent with our typical 
process. In the FY 2022 final rule impact file, we have indicated which 
PSF update the applicable fields were sourced from.
    The methodology we used to calculate the FY 2022 standardized 
amount is as follows:
     To ensure we are only including hospitals paid under the 
IPPS in the calculation of the standardized amount, we applied the 
following inclusion and exclusion criteria: Include hospitals whose 
last four digits fall between 0001 and 0879 (section 2779A1 of Chapter 
2 of the State Operations Manual on the CMS website at: https://www.cms.gov/Regulations-and-Guidance/Guidance/Manuals/Downloads/som107c02.pdf); exclude CAHs at the time of this final rule; exclude 
hospitals in Maryland (because these hospitals are paid under an all 
payer model under section 1115A of the Act); and remove PPS excluded-
cancer hospitals that have a ``V'' in the fifth position of their 
provider number or a ``E'' or ``F'' in the sixth position.
     As in the past, we adjusted the FY 2022 standardized 
amount to remove the effects of the FY 2021 geographic 
reclassifications and outlier payments before applying the FY 2022 
updates. We then applied budget neutrality offsets for outliers and 
geographic reclassifications to the standardized amount based on FY 
2022 payment policies.
     We do not remove the prior year's budget neutrality 
adjustments for reclassification and recalibration of the DRG relative 
weights and for updated wage data because, in accordance with sections 
1886(d)(4)(C)(iii) and 1886(d)(3)(E) of the Act, estimated aggregate 
payments after updates in the DRG relative weights and wage index 
should equal estimated aggregate payments prior to the changes. If we 
removed the prior year's adjustment, we would not satisfy these 
conditions.
    Budget neutrality is determined by comparing aggregate IPPS 
payments before and after making changes that are required to be budget 
neutral (for example, changes to MS-DRG classifications, recalibration 
of the MS-DRG relative weights, updates to the wage index, and 
different geographic reclassifications). We include outlier payments in 
the simulations because they may be affected by changes in these 
parameters.
     Consistent with our methodology established in the FY 2011 
IPPS/LTCH PPS final rule (75 FR 50422 through 50433), because IME 
Medicare Advantage payments are made to IPPS hospitals under section 
1886(d) of the Act, we believe these payments must be part of these 
budget neutrality calculations. However, we note that it is not 
necessary to include Medicare Advantage IME payments in the outlier 
threshold calculation or the outlier offset to the standardized amount 
because the statute requires that outlier payments be not less than 5 
percent nor more than 6 percent of total ``operating DRG payments,'' 
which does not include IME and DSH payments. We refer readers to the FY 
2011 IPPS/LTCH PPS final rule for a complete discussion on our 
methodology of identifying and adding the total Medicare Advantage IME 
payment amount to the budget neutrality adjustments.

[[Page 45528]]

     Consistent with the methodology in the FY 2012 IPPS/LTCH 
PPS final rule, in order to ensure that we capture only fee-for-service 
claims, we are only including claims with a ``Claim Type'' of 60 (which 
is a field on the MedPAR file that indicates a claim is an FFS claim).
     Consistent with our methodology established in the FY 2017 
IPPS/LTCH PPS final rule (81 FR 57277), in order to further ensure that 
we capture only FFS claims, we are excluding claims with a ``GHOPAID'' 
indicator of 1 (which is a field on the MedPAR file that indicates a 
claim is not an FFS claim and is paid by a Group Health Organization).
     Consistent with our methodology established in the FY 2011 
IPPS/LTCH PPS final rule (75 FR 50422 through 50423), we examine the 
MedPAR file and remove pharmacy charges for anti-hemophilic blood 
factor (which are paid separately under the IPPS) with an indicator of 
``3'' for blood clotting with a revenue code of ``0636'' from the 
covered charge field for the budget neutrality adjustments. We also 
remove organ acquisition charges, except for cases that group to MS-DRG 
018, from the covered charge field for the budget neutrality 
adjustments because organ acquisition is a pass-through payment not 
paid under the IPPS. Revenue centers 081X-089X are typically excluded 
from ratesetting, however, we are not removing revenue center 891 
charges from MS-DRG 018 claims during ratesetting, because those 
revenue 891 charges were included in the relative weight calculation 
for MS-DRG 018, which is consistent with the policy finalized in FY 
2021 final rule (85 FR 58600). We note that a new MedPAR variable for 
revenue code 891 charges was introduced in April 2020.
     For FY 2022 and subsequent fiscal years, as we proposed, 
we are removing allogeneic hematopoietic stem cell acquisition charges 
from the covered charge field for budget neutrality adjustments. As 
discussed in the FY 2021 IPPS/LTCH PPS final rule, payment for 
allogeneic hematopoietic stem cell acquisition costs is made on a 
reasonable cost basis for cost reporting periods beginning on or after 
October 1, 2020 (85 FR 58835 through 58842).
     The participation of hospitals under the BPCI (Bundled 
Payments for Care Improvement) Advanced model started on October 1, 
2018. The BPCI Advanced model, tested under the authority of section 
3021 of the Affordable Care Act (codified at section 1115A of the Act), 
is comprised of a single payment and risk track, which bundles payments 
for multiple services beneficiaries receive during a Clinical Episode. 
Acute care hospitals may participate in the BPCI Advanced model in one 
of two capacities: As a model Participant or as a downstream Episode 
Initiator. Regardless of the capacity in which they participate in the 
BPCI Advanced model, participating acute care hospitals will continue 
to receive IPPS payments under section 1886(d) of the Act. Acute care 
hospitals that are Participants also assume financial and quality 
performance accountability for Clinical Episodes in the form of a 
reconciliation payment. For additional information on the BPCI Advanced 
model, we refer readers to the BPCI Advanced web page on the CMS Center 
for Medicare and Medicaid Innovation's website at: https://innovation.cms.gov/initiatives/bpci-advanced/.
    For FY 2022, consistent with how we treated hospitals that 
participated in the BPCI Advanced Model in the FY 2021 IPPS/LTCH PPS 
final rule (85 FR 59029-59030), as we proposed, we also are including 
all applicable data from subsection (d) hospitals participating in the 
BPCI Advanced model in our IPPS payment modeling and ratesetting 
calculations. We believe it is appropriate to include all applicable 
data from the subsection (d) hospitals participating in the BPCI 
Advanced model in our IPPS payment modeling and ratesetting 
calculations because these hospitals are still receiving IPPS payments 
under section 1886(d) of the Act. For the same reasons, as we also 
proposed, we included all applicable data from subsection (d) hospitals 
participating in the Comprehensive Care for Joint Replacement (CJR) 
Model in our IPPS payment modeling and ratesetting calculations.
     Consistent with our methodology established in the FY 2013 
IPPS/LTCH PPS final rule (77 FR 53687 through 53688), we believe that 
it is appropriate to include adjustments for the Hospital Readmissions 
Reduction Program and the Hospital VBP Program (established under the 
Affordable Care Act) within our budget neutrality calculations.
    Both the hospital readmissions payment adjustment (reduction) and 
the hospital VBP payment adjustment (redistribution) are applied on a 
claim-by-claim basis by adjusting, as applicable, the base-operating 
DRG payment amount for individual subsection (d) hospitals, which 
affects the overall sum of aggregate payments on each side of the 
comparison within the budget neutrality calculations.
    In order to properly determine aggregate payments on each side of 
the comparison, consistent with the approach we have taken in prior 
years, for FY 2022, we are continuing to apply a proxy based on the 
prior fiscal year hospital readmissions payment adjustment (for FY 2022 
this would be FY 2021 final adjustment factors from Table 15 of the FY 
2021 IPPS/LTCH PPS final rule) and a proxy based on the prior fiscal 
year hospital VBP payment adjustment (for FY 2022 this would be FY 2021 
final adjustment factors from Table 16B of the FY 2021 IPPS/LTCH PPS 
final rule) on each side of the comparison, consistent with the 
methodology that we adopted in the FY 2013 IPPS/LTCH PPS final rule (77 
FR 53687 through 53688). That is, as we proposed, we applied a proxy 
readmissions payment adjustment factor and a proxy hospital VBP payment 
adjustment factor from the prior final rule on both sides of our 
comparison of aggregate payments when determining all budget neutrality 
factors described in section II.A.4. of this Addendum.
     The Affordable Care Act also established section 1886(r) 
of the Act, which modifies the methodology for computing the Medicare 
DSH payment adjustment beginning in FY 2014. Beginning in FY 2014, IPPS 
hospitals receiving Medicare DSH payment adjustments receive an 
empirically justified Medicare DSH payment equal to 25 percent of the 
amount that would previously have been received under the statutory 
formula set forth under section 1886(d)(5)(F) of the Act governing the 
Medicare DSH payment adjustment. In accordance with section 1886(r)(2) 
of the Act, the remaining amount, equal to an estimate of 75 percent of 
what otherwise would have been paid as Medicare DSH payments, reduced 
to reflect changes in the percentage of individuals who are uninsured 
and any additional statutory adjustment, will be available to make 
additional payments to Medicare DSH hospitals based on their share of 
the total amount of uncompensated care reported by Medicare DSH 
hospitals for a given time period. In order to properly determine 
aggregate payments on each side of the comparison for budget 
neutrality, prior to FY 2014, we included estimated Medicare DSH 
payments on both sides of our comparison of aggregate payments when 
determining all budget neutrality factors described in section II.A.4. 
of this Addendum.
    To do this for FY 2022 (as we did for the last 8 fiscal years), as 
we proposed, we are including estimated empirically justified Medicare 
DSH payments that will be paid in accordance with section 1886(r)(1) of 
the Act and estimates of the additional uncompensated care payments 
made to hospitals receiving Medicare DSH payment adjustments as

[[Page 45529]]

described by section 1886(r)(2) of the Act. That is, we are considered 
estimated empirically justified Medicare DSH payments at 25 percent of 
what would otherwise have been paid, and also the estimated additional 
uncompensated care payments for hospitals receiving Medicare DSH 
payment adjustments on both sides of our comparison of aggregate 
payments when determining all budget neutrality factors described in 
section II.A.4. of this Addendum.
     When calculating total payments for budget neutrality, to 
determine total payments for SCHs, we model total hospital-specific 
rate payments and total Federal rate payments and then include 
whichever one of the total payments is greater. As discussed in section 
V.E. of the preamble to this final rule and later in this section, we 
are continuing to use the FY 2014 finalized methodology under which we 
take into consideration uncompensated care payments in the comparison 
of payments under the Federal rate and the hospital-specific rate for 
SCHs. Therefore, we included estimated uncompensated care payments in 
this comparison.
    Similarly, for MDHs, as discussed in section V.E. of the preamble 
of this final rule, when computing payments under the Federal national 
rate plus 75 percent of the difference between the payments under the 
Federal national rate and the payments under the updated hospital-
specific rate, as we proposed, we are continuing to take into 
consideration uncompensated care payments in the computation of 
payments under the Federal rate and the hospital-specific rate for 
MDHs.
     As we proposed, we included an adjustment to the 
standardized amount for those hospitals that are not meaningful EHR 
users in our modeling of aggregate payments for budget neutrality for 
FY 2022. Similar to FY 2021, we are including this adjustment based on 
data on the prior year's performance. Payments for hospitals will be 
estimated based on the applicable standardized amount in Tables 1A and 
1B for discharges occurring in FY 2022.
     In our determination of all budget neutrality factors 
described in section II.A.4. of this Addendum, we used transfer-
adjusted discharges. Specifically, we calculated the transfer-adjusted 
discharges using the statutory expansion of the postacute care transfer 
policy to include discharges to hospice care by a hospice program as 
discussed in section IV.A.2.b. of the preamble of this final rule.
a. Reclassification and Recalibration of MS-DRG Relative Weights
    Section 1886(d)(4)(C)(iii) of the Act specifies that, beginning in 
FY 1991, the annual DRG reclassification and recalibration of the 
relative weights must be made in a manner that ensures that aggregate 
payments to hospitals are not affected. As discussed in section II.G. 
of the preamble of this final rule, we normalized the recalibrated MS-
DRG relative weights by an adjustment factor so that the average case 
relative weight after recalibration is equal to the average case 
relative weight prior to recalibration. However, equating the average 
case relative weight after recalibration to the average case relative 
weight before recalibration does not necessarily achieve budget 
neutrality with respect to aggregate payments to hospitals because 
payments to hospitals are affected by factors other than average case 
relative weight. Therefore, as we have done in past years, we are 
making a budget neutrality adjustment to ensure that the requirement of 
section 1886(d)(4)(C)(iii) of the Act is met.
    For this FY 2022 final rule, as we proposed, to comply with the 
requirement that MS-DRG reclassification and recalibration of the 
relative weights be budget neutral for the standardized amount and the 
hospital-specific rates, we used FY 2019 discharge data to simulate 
payments and compared the following:
     Aggregate payments using the FY 2021 labor-related share 
percentages, the FY 2021 relative weights, and the FY 2021 pre-
reclassified wage data, and applied the estimated FY 2022 hospital 
readmissions payment adjustments and estimated FY 2022 hospital VBP 
payment adjustments; and
     Aggregate payments using the FY 2021 labor-related share 
percentages, the FY 2022 relative weights, and the FY 2021 pre-
reclassified wage data, and applied the estimated FY 2022 hospital 
readmissions payment adjustments and estimated FY 2022 hospital VBP 
payment adjustments applied previously. Because this payment simulation 
uses the FY 2022 relative weights, consistent with our policy in 
section V.F. of the preamble to this final rule, we applied the 
finalized adjustor for certain cases that group to MS-DRG 018 in our 
simulation of these payments. We note that because the simulations of 
payments for all of the budget neutrality factors discussed in this 
section also use the FY 2022 relative weights, as we proposed, we 
applied the adjustor for certain MS-DRG 18 cases in all simulations of 
payments for the budget neutrality factors discussed later in this 
section. We refer the reader to section V.F. of the preamble of this 
final rule for a complete discussion on the finalized adjustor for 
certain cases that group to MS-DRG 018 and to section II.E.2.b. of the 
preamble of this final rule, for a complete discussion of the finalized 
adjustment to the FY 2022 relative weights to account for certain cases 
that group to MS-DRG 018.
    Based on this comparison, we computed a budget neutrality 
adjustment factor and applied this factor to the standardized amount. 
As discussed in section IV. of this Addendum, as we proposed, we 
applied the MS-DRG reclassification and recalibration budget neutrality 
factor to the hospital-specific rates that are effective for cost 
reporting periods beginning on or after October 1, 2021. Please see the 
table later in this section setting forth each of the FY 2022 budget 
neutrality factors.
b. Updated Wage Index--Budget Neutrality Adjustment
    Section 1886(d)(3)(E)(i) of the Act requires us to update the 
hospital wage index on an annual basis beginning October 1, 1993. This 
provision also requires us to make any updates or adjustments to the 
wage index in a manner that ensures that aggregate payments to 
hospitals are not affected by the change in the wage index. Section 
1886(d)(3)(E)(i) of the Act requires that we implement the wage index 
adjustment in a budget neutral manner. However, section 
1886(d)(3)(E)(ii) of the Act sets the labor-related share at 62 percent 
for hospitals with a wage index less than or equal to 1.0000, and 
section 1886(d)(3)(E)(i) of the Act provides that the Secretary shall 
calculate the budget neutrality adjustment for the adjustments or 
updates made under that provision as if section 1886(d)(3)(E)(ii) of 
the Act had not been enacted. In other words, this section of the 
statute requires that we implement the updates to the wage index in a 
budget neutral manner, but that our budget neutrality adjustment should 
not take into account the requirement that we set the labor-related 
share for hospitals with wage indexes less than or equal to 1.0000 at 
the more advantageous level of 62 percent. Therefore, for purposes of 
this budget neutrality adjustment, section 1886(d)(3)(E)(i) of the Act 
prohibits us from taking into account the fact that hospitals with a 
wage index less than or equal to 1.0000 are paid using a labor-related 
share of 62 percent. Consistent with current policy, for FY 2022, as we 
proposed, we are adjusting 100 percent

[[Page 45530]]

of the wage index factor for occupational mix. We describe the 
occupational mix adjustment in section III.E. of the preamble of this 
final rule.
    To compute a budget neutrality adjustment factor for wage index and 
labor-related share percentage changes, we used FY 2019 discharge data 
to simulate payments and compared the following:
     Aggregate payments using the FY 2022 relative weights and 
the FY 2021 pre-reclassified wage indexes, applied the FY 2021 labor-
related share of 68.3 percent to all hospitals (regardless of whether 
the hospital's wage index was above or below 1.0000), and applied the 
FY 2022 hospital readmissions payment adjustment and the estimated FY 
2022 hospital VBP payment adjustment; and
     Aggregate payments using the FY 2022 relative weights and 
the FY 2022 pre-reclassified wage indexes, applied the labor-related 
share for FY 2022 of 67.6 percent to all hospitals (regardless of 
whether the hospital's wage index was above or below 1.0000), and 
applied the same FY 2022 hospital readmissions payment adjustments and 
estimated FY 2022 hospital VBP payment adjustments applied previously.
    In addition, we applied the MS-DRG reclassification and 
recalibration budget neutrality adjustment factor (derived in the first 
step) to the payment rates that were used to simulate payments for this 
comparison of aggregate payments from FY 2021 to FY 2022. Based on this 
comparison, we computed a budget neutrality adjustment factor and 
applied this factor to the standardized amount for changes to the wage 
index. Please see the table later in this section for a summary of the 
FY 2022 budget neutrality factors.
c. Reclassified Hospitals--Budget Neutrality Adjustment
    Section 1886(d)(8)(B) of the Act provides that certain rural 
hospitals are deemed urban. In addition, section 1886(d)(10) of the Act 
provides for the reclassification of hospitals based on determinations 
by the MGCRB. Under section 1886(d)(10) of the Act, a hospital may be 
reclassified for purposes of the wage index.
    Under section 1886(d)(8)(D) of the Act, the Secretary is required 
to adjust the standardized amount to ensure that aggregate payments 
under the IPPS after implementation of the provisions of sections 
1886(d)(8)(B) and (C) and 1886(d)(10) of the Act are equal to the 
aggregate prospective payments that would have been made absent these 
provisions. We note, with regard to the requirement under section 
1886(d)(8)(C)(iii) of the Act, as finalized in the FY 2020 IPPS/LTCH 
PPS final rule (84 FR 42333 through 42336), we excluded the wage data 
of urban hospitals that have reclassified as rural under section 
1886(d)(8)(E) of the Act (as implemented in Sec.  412.103) from the 
calculation of the wage index for rural areas in the State in which the 
county is located. We refer the reader to the FY 2015 IPPS final rule 
(79 FR 50371 and 50372) for a complete discussion regarding the 
requirement of section 1886(d)(8)(C)(iii) of the Act. We further note 
that the wage index adjustments provided for under section 1886(d)(13) 
of the Act are not budget neutral. Section 1886(d)(13)(H) of the Act 
provides that any increase in a wage index under section 1886(d)(13) of 
the Act shall not be taken into account in applying any budget 
neutrality adjustment with respect to such index under section 
1886(d)(8)(D) of the Act. To calculate the budget neutrality adjustment 
factor for FY 2022, we used FY 2019 discharge data to simulate payments 
and compared the following:
     Aggregate payments using the FY 2022 labor-related share 
percentage, the FY 2022 relative weights, and the FY 2022 wage data 
prior to any reclassifications under sections 1886(d)(8)(B) and (C) and 
1886(d)(10) of the Act, and applied the estimated FY 2022 hospital 
readmissions payment adjustments and the estimated FY 2022 hospital VBP 
payment adjustments; and
     Aggregate payments using the FY 2022 labor-related share 
percentage, the FY 2022 relative weights, and the FY 2022 wage data 
after such reclassifications, and applied the same estimated FY 2022 
hospital readmissions payment adjustments and the estimated FY 2022 
hospital VBP payment adjustments applied previously.
    We note that the reclassifications applied under the second 
simulation and comparison are those listed in Table 2 associated with 
this final rule, which is available via the internet on the CMS 
website. This table reflects reclassification crosswalks for FY 2022, 
and applies the policies explained in section III. of the preamble of 
this final rule. Based on this comparison, we computed a budget 
neutrality adjustment factor and applied this factor to the 
standardized amount to ensure that the effects of these provisions are 
budget neutral, consistent with the statute. Please see the table later 
in this section for a summary of the FY 2022 budget neutrality factors.
    The FY 2022 budget neutrality adjustment factor was applied to the 
standardized amount after removing the effects of the FY 2021 budget 
neutrality adjustment factor. We note that the FY 2022 budget 
neutrality adjustment reflects FY 2022 wage index reclassifications 
approved by the MGCRB or the Administrator at the time of development 
of this final rule.
    As discussed in the preamble of this final rule, we are finalizing 
the provisions of the May 10, 2021 IFC (``Modification of Limitations 
on Redesignation by the Medicare Geographic Classification Review Board 
(MGCRB)'' (CMS-1762-IFC)) without modification, including our revisions 
to the regulations at Sec.  412.230 to allow hospitals with a rural 
redesignation under section 1886(d)(8)(E) of the Act to reclassify 
under the MGCRB using the rural reclassified area as the geographic 
area in which the hospital is located effective with reclassifications 
beginning with FY 2023. Therefore, we included any amounts hospitals 
receive by reason of a higher wage index due to the IFC in the 
calculation of the budget neutrality factor, pursuant to our authority 
at section 1886(d)(8)(D) and 1886(d)(5)(I)(i). For a complete 
discussion regarding finalizing the provisions of the May 10, 2021 IFC, 
we refer the reader to section III.K.3 of this final rule.
d. Rural Floor Budget Neutrality Adjustment
    Under Sec.  412.64(e)(4), we make an adjustment to the wage index 
to ensure that aggregate payments after implementation of the rural 
floor under section 4410 of the BBA (Pub. L. 105-33) is equal to the 
aggregate prospective payments that would have been made in the absence 
of this provision. Consistent with section 3141 of the Affordable Care 
Act and as discussed in section III.G. of the preamble of this final 
rule and codified at Sec.  412.64(e)(4)(ii), the budget neutrality 
adjustment for the rural floor is a national adjustment to the wage 
index. We note, as finalized in the FY 2020 IPPS/LTCH final rule (84 FR 
42332 through 42336), for FY 2022 we are calculating the rural floor 
without including the wage data of urban hospitals that have 
reclassified as rural under section 1886(d)(8)(E) of the Act (as 
implemented in Sec.  412.103).
    Similar to our calculation in the FY 2015 IPPS/LTCH PPS final rule 
(79 FR 50369 through 50370), for FY 2022, as we proposed, we calculated 
a national rural Puerto Rico wage index. Because there are no rural 
Puerto Rico hospitals with established wage data, our calculation of 
the FY 2021 rural Puerto Rico wage index is based on the policy adopted 
in the FY 2008 IPPS final rule with comment period (72 FR 47323).

[[Page 45531]]

That is, we use the unweighted average of the wage indexes from all 
CBSAs (urban areas) that are contiguous (share a border with) to the 
rural counties to compute the rural floor (72 FR 47323; 76 FR 51594). 
Under the OMB labor market area delineations, except for Arecibo, 
Puerto Rico (CBSA 11640), all other Puerto Rico urban areas are 
contiguous to a rural area. Therefore, based on our existing policy, 
the FY 2022 rural Puerto Rico wage index is calculated based on the 
average of the FY 2022 wage indexes for the following urban areas: 
Aguadilla-Isabela, PR (CBSA 10380); Guayama, PR (CBSA 25020); Mayaguez, 
PR (CBSA 32420); Ponce, PR (CBSA 38660); San German, PR (CBSA 41900); 
and San Juan-Carolina-Caguas, PR (CBSA 41980).
    To calculate the national rural floor budget neutrality adjustment 
factor, we used FY 2019 discharge data to simulate payments, and the 
post-reclassified national wage indexes and compared the following:
     National simulated payments without the rural floor; and
     National simulated payments with the rural floor.
    Based on this comparison, we determined a national rural floor 
budget neutrality adjustment factor. The national adjustment was 
applied to the national wage indexes to produce rural floor budget 
neutral wage indexes. Please see the table later in this section for a 
summary of the FY 2022 budget neutrality factors.
    As further discussed in section III.G.2 of this final rule, we note 
that section 9831 of the American Rescue Plan Act of 2021 (Pub. L. 117-
2), enacted on March 11, 2021 amended section 1886(d)(3)(E)(i) of the 
Act (42 U.S.C. 1395ww(d)(3)(E)(i)) and added section 1886(d)(3)(E)(iv) 
of the Act to establish a minimum area wage index (or imputed floor) 
for hospitals in all-urban States for discharges occurring on or after 
October 1, 2021. Unlike the imputed floor that was in effect from FY 
2005 through FY 2018, section 1886(d)(3)(E)(iv)(III) of the Act 
provides that the imputed floor wage index shall not be applied in a 
budget neutral manner Specifically, section 9831(b) of Public Law 117-2 
amends section 1886(d)(3)(E)(i) of the Act to exclude the imputed floor 
from the budget neutrality requirement under section 1886(d)(3)(E)(i) 
of the Act. In the past, we budget neutralized the estimated increase 
in payments each year resulting from the imputed floor that was in 
effect from FY 2005 through FY 2018. For FY 2022 and subsequent years, 
in applying the imputed floor required under section 1886(d)(3)(E)(iv) 
of the Act, we are applying the imputed floor after the application of 
the rural floor and will apply no reductions to the standardized amount 
or to the wage index to fund the increase in payments to hospitals in 
all-urban States resulting from the application of the imputed floor. 
As noted in section III.G.2 of the propose rule, given the recent 
enactment of section 9831 of Public Law 117-2 on March 11, 2021, there 
was not sufficient time available to incorporate the changes required 
by this statutory provision (which provides for the application of the 
imputed floor adjustment in a non-budget neutral manner beginning in FY 
2022) into the calculation of the provider wage index for this final 
rule. In this final rule, we have included the imputed floor adjustment 
in the calculation of the provider wage index in the FY 2022 final 
rule. We refer the reader to section III.G.2 of the preamble of this 
final rule for a complete discussion regarding the imputed floor.
e. Rural Community Hospital Demonstration Program Adjustment
    In section V.K. of the preamble of this final rule, we discuss the 
Rural Community Hospital Demonstration program, which was originally 
authorized for a 5-year period by section 410A of the Medicare 
Prescription Drug, Improvement, and Modernization Act of 2003 (MMA) 
(Pub. L. 108-173), and extended for another 5-year period by sections 
3123 and 10313 of the Affordable Care Act (Pub. L. 111-148). 
Subsequently, section 15003 of the 21st Century Cures Act (Pub. L. 114-
255), enacted December 13, 2016, amended section 410A of Public Law 
108-173 to require a 10-year extension period (in place of the 5-year 
extension required by the Affordable Care Act, as further discussed 
later in this section). We make an adjustment to the standardized 
amount to ensure the effects of the Rural Community Hospital 
Demonstration program are budget neutral as required under section 
410A(c)(2) of Public Law 108-173. Finally, Division CC, section 128(a) 
of the Consolidated Appropriations Act of 2021 (Pub. L. 116-260) again 
amended section 410A to require a 15-year extension period in place of 
the 10-year period. We refer readers to section V.K. of the preamble of 
this final rule for complete details regarding the Rural Community 
Hospital Demonstration.
    With regard to budget neutrality, as mentioned earlier, we make an 
adjustment to the standardized amount to ensure the effects of the 
Rural Community Hospital Demonstration are budget neutral, as required 
under section 410A(c)(2) of Public Law 108-173. For FY 2022, based on 
the latest data for this final rule, the total amount that we are 
applying to make an adjustment to the standardized amounts to ensure 
the effects of the Rural Community Hospital Demonstration program are 
budget neutral is $69,577,797. Accordingly, using the most recent data 
available to account for the estimated costs of the demonstration 
program, for FY 2022, we computed a factor for the Rural Community 
Hospital Demonstration budget neutrality adjustment that would be 
applied to the standardized amount. Please see the table later in this 
section for a summary of the FY 2022 budget neutrality factors. We 
refer readers to section V.K. of the preamble of this final rule on 
complete details regarding the calculation of the amount we are 
applying to make an adjustment to the standardized amounts.
f. Continuation of the Low Wage Index Hospital Policy--Budget 
Neutrality Adjustment
    As discussed in section III.G.3. of the preamble of this final 
rule, we are continuing the wage index policy finalized in the FY 2020 
IPPS/LTCH PPS final rule to address wage index disparities by 
increasing the wage index values for hospitals with a wage index value 
below the 25th percentile wage index value across all hospitals (the 
low wage index hospital policy). As discussed in section III.G.3 of 
this final rule, consistent with our current methodology for 
implementing wage index budget neutrality under section 1886(d)(3)(E) 
of the Act, we are making a budget neutrality adjustment to the 
national standardized amount for all hospitals so that the increase in 
the wage index for hospitals with a wage index below the 25th 
percentile wage index, is implemented in a budget neutral manner.
    To calculate this budget neutrality adjustment factor for FY 2022, 
we used FY 2019 discharge data to simulate payments and compared the 
following:
     Aggregate payments using the FY 2022 labor-related share 
percentage, the FY 2022 relative weights, and the FY 2022 wage index 
for each hospital before adjusting the wage indexes under the low wage 
index hospital policy, and applied the estimated FY 2022 hospital 
readmissions payment adjustments and the estimated FY 2022 hospital VBP 
payment adjustments, and the operating outlier reconciliation adjusted 
outlier percentage discussed later in this section; and
     Aggregate payments using the FY 2022 labor-related share 
percentage, the FY 2022 relative weights, and the FY

[[Page 45532]]

2022 wage index for each hospital after adjusting the wage indexes 
under the low wage index hospital policy, and applied the same 
estimated FY 2022 hospital readmissions payment adjustments and the 
estimated FY 2022 hospital VBP payment adjustments applied previously, 
and the operating outlier reconciliation adjusted outlier percentage 
discussed later in this section.
    This FY 2022 budget neutrality adjustment factor was applied to the 
standardized amount.
g. Transition Budget Neutrality Adjustment
    In the FY 2021 IPPS/LTCH PPS final rule (85 FR 58743 through 58755) 
we adopted the updates set forth in OMB Bulletin No. 18-04 effective 
October 1, 2020, beginning with the FY 2021 wage index. For a complete 
discussion of the adoption of the updates set forth in OMB Bulletin No. 
18-04, we refer readers to the FY 2021 IPPS/LTCH PPS final rule.
    In connection with our adoption in FY 2021 of the updates in OMB 
Bulletin 18-04, we adopted a policy to place a 5 percent cap, for FY 
2021, on any decrease in a hospital's wage index from the hospital's 
final wage index in FY 2020 so that a hospital's final wage index for 
FY 2021 would not be less than 95 percent of its final wage index for 
FY 2020. We refer the reader to the FY 2021 IPPS/LTCH PPS final rule 
(85 FR 58753 through 58755) for a complete discussion of this 
transition. As finalized in the FY 2021 IPPS/LTCH PPS final rule, this 
transition is set to expire at the end of FY 2021.
    In the FY 2022 IPPS/LTCH proposed rule, given the unprecedented 
nature of the ongoing COVID-19 PHE, we sought comment on whether it 
would be appropriate to continue to apply a transition to the FY 2022 
wage index for hospitals negatively impacted by our adoption of the 
updates in OMB Bulletin 18-04. In section III.A.2. of the preamble to 
this final rule, we noted that we received several comments strongly 
recommending CMS extend a transition policy similar to that implemented 
in FY 2020 and FY 2021.
    After consideration of the comments, we are finalizing to apply an 
extended transition to the FY 2022 wage index for hospitals. 
Specifically, for hospitals that received the transition in FY 2021, we 
are continuing a wage index transition for FY 2022 under which we will 
apply a 5 percent cap on any decrease in the hospital's wage index 
compared to its wage index for FY 2021 to mitigate significant negative 
impacts of, and provide additional time for hospitals to adapt to, the 
revised OMB delineations. Also, as discussed in the FY 2021 IPPS/LTCH 
final rule, we believe applying a 5-percent cap on any decrease in a 
hospital's wage index from the hospital's final wage index from the 
prior fiscal year is an appropriate transition as it provides 
predictability in payment levels from FY 2021 to the upcoming FY 2022 
as well as effectively mitigating any significant decreases in the wage 
index for FY 2022. We refer the reader to section III.A.2. of the 
preamble to this final rule for a complete discussion on the rationale 
of this transition.
    For FY 2022, after taking into consideration comments received to 
the proposed rule, we are using our exceptions and adjustments 
authority under section 1886(d)(5)(I)(i) of the Act to apply a budget 
neutrality adjustment to the standardized amount so that our transition 
for hospitals receiving this transition is implemented in a budget 
neutral manner. We refer readers to section III.A.2. of the preamble of 
this final rule for a complete discussion. To calculate a transition 
budget neutrality adjustment factor for FY 2022, we used FY 2019 
discharge data to simulate payments and compared the following:
     Aggregate payments without the 5- percent cap using the FY 
2022 labor-related share percentages, the revised OMB labor market area 
delineations for FY 2021, the FY 2022 relative weights, the FY 2022 
wage index for each hospital after adjusting the wage indexes under the 
low wage index hospital policy with the associated budget neutrality 
adjustment to the standardized amount, and applied the FY 2022 hospital 
readmissions payment adjustments and the estimated FY 2022 hospital VBP 
payment adjustments, and the operating outlier reconciliation adjusted 
outlier percentage; and
     Aggregate payments with the 5-percent cap using the FY 
2022 labor-related share percentages, the revised OMB labor market area 
delineations for FY 2021, the FY 2022 relative weights, the FY 2022 
wage index for each hospital after adjusting the wage indexes under the 
low wage index hospital policy with the associated budget neutrality 
adjustment to the standardized amount, and applied the same FY 2022 
hospital readmissions payment adjustments and the estimated FY 2022 
hospital VBP payment adjustments applied previously, and the operating 
outlier reconciliation adjusted outlier percentage.
    This FY 2022 budget neutrality adjustment factor was applied to the 
standardized amount. Please see the table later in this section setting 
forth each of the FY 2022 budget neutrality factors.
    We note, Table 2 associated with this final rule, which is 
available via the internet on the CMS website contains the wage index 
by provider before and after applying the low wage index hospital 
policy and the transition.
    The following table is a summary of the FY 2022 budget neutrality 
factors, as discussed in the previous sections.
[GRAPHIC] [TIFF OMITTED] TR13AU21.323


[[Page 45533]]


    In order to facilitate comments on the alternative approach 
discussed in section I.F. of the FY 2022 IPPS/LTCH proposed rule of 
using the same FY 2020 data that we would ordinarily use for purposes 
of FY 2022 ratesetting, and which we stated we might consider 
finalizing for FY 2022 based on consideration of comments received, for 
the proposed rule, we made available budget neutrality and other 
ratesetting adjustments calculated under this alternative approach, 
which can be found on the CMS website at: https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/AcuteInpatientPPS/index. For this 
final rule, as discussed in section I.F. of this FY 2022 IPPS/LTCH 
final rule, after consideration of the comments we received, we are 
finalizing as proposed to use alternative data for the FY 2022 
ratesetting in situations where the latest data available that would 
typically be used for the final rule is significantly impacted by the 
COVID-19 PHE.
h. Adjustment for FY 2022 Required Under Section 414 of Public Law 114-
10 (MACRA)
    As stated in the FY 2017 IPPS/LTCH PPS final rule (81 FR 56785), 
once the recoupment required under section 631 of the ATRA was 
complete, we had anticipated making a single positive adjustment in FY 
2018 to offset the reductions required to recoup the $11 billion under 
section 631 of the ATRA. However, section 414 of the MACRA (which was 
enacted on April 16, 2015) replaced the single positive adjustment we 
intended to make in FY 2018 with a 0.5 percent positive adjustment for 
each of FYs 2018 through 2023. (As noted in the FY 2018 IPPS/LTCH PPS 
proposed and final rules, section 15005 of the 21st Century Cures Act 
(Pub. L. 114-255), which was enacted December 13, 2016, reduced the 
adjustment for FY 2018 from 0.5 percentage points to 0.4588 percentage 
points.) Therefore, for FY 2022, we are implementing the required +0.5 
percent adjustment to the standardized amount. This is a permanent 
adjustment to the payment rates.
i. Outlier Payments
    Section 1886(d)(5)(A) of the Act provides for payments in addition 
to the basic prospective payments for ``outlier'' cases involving 
extraordinarily high costs. To qualify for outlier payments, a case 
must have costs greater than the sum of the prospective payment rate 
for the MS-DRG, any IME and DSH payments, uncompensated care payments, 
any new technology add-on payments, and the ``outlier threshold'' or 
``fixed-loss'' amount (a dollar amount by which the costs of a case 
must exceed payments in order to qualify for an outlier payment). We 
refer to the sum of the prospective payment rate for the MS-DRG, any 
IME and DSH payments, uncompensated care payments, any new technology 
add-on payments, and the outlier threshold as the outlier ``fixed-loss 
cost threshold.'' To determine whether the costs of a case exceed the 
fixed-loss cost threshold, a hospital's CCR is applied to the total 
covered charges for the case to convert the charges to estimated costs. 
Payments for eligible cases are then made based on a marginal cost 
factor, which is a percentage of the estimated costs above the fixed-
loss cost threshold. The marginal cost factor for FY 2022 is 80 
percent, or 90 percent for burn MS-DRGs 927, 928, 929, 933, 934 and 
935. We have used a marginal cost factor of 90 percent since FY 1989 
(54 FR 36479 through 36480) for designated burn DRGs as well as a 
marginal cost factor of 80 percent for all other DRGs since FY 1995 (59 
FR 45367).
    In accordance with section 1886(d)(5)(A)(iv) of the Act, outlier 
payments for any year are projected to be not less than 5 percent nor 
more than 6 percent of total operating DRG payments (which does not 
include IME and DSH payments) plus outlier payments. When setting the 
outlier threshold, we compute the percent target by dividing the total 
operating outlier payments by the total operating DRG payments plus 
outlier payments. As discussed in the next section, for FY 2022, we are 
incorporating an estimate of outlier reconciliation when setting the 
outlier threshold. We do not include any other payments such as IME and 
DSH within the outlier target amount. Therefore, it is not necessary to 
include Medicare Advantage IME payments in the outlier threshold 
calculation. Section 1886(d)(3)(B) of the Act requires the Secretary to 
reduce the average standardized amount by a factor to account for the 
estimated proportion of total DRG payments made to outlier cases. More 
information on outlier payments may be found on the CMS website at: 
http://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/AcuteInpatientPPS/outlier.htm.
(1) Methodology To Incorporate an Estimate of Outlier Reconciliation in 
the FY 2022 Outlier Fixed-Loss Cost Threshold
    The regulations in 42 CFR 412.84(i)(4) state that any outlier 
reconciliation at cost report settlement will be based on operating and 
capital cost-to-charge ratios (CCRs) calculated based on a ratio of 
costs to charges computed from the relevant cost report and charge data 
determined at the time the cost report coinciding with the discharge is 
settled. We have instructed MACs to identify for CMS any instances 
where: (1) A hospital's actual CCR for the cost reporting period 
fluctuates plus or minus 10 percentage points compared to the interim 
CCR used to calculate outlier payments when a bill is processed; and 
(2) the total outlier payments for the hospital exceeded $500,000.00 
for that cost reporting period. If we determine that a hospital's 
outlier payments should be reconciled, we reconcile both operating and 
capital outlier payments. We refer readers to section 20.1.2.5 of 
Chapter 3 of the Medicare Claims Processing Manual (available on the 
CMS website at: https://www.cms.gov/Regulations-and-Guidance/Guidance/Manuals/Downloads/clm104c03.pdf) for complete details regarding outlier 
reconciliation. The regulation at Sec.  412.84(m) further states that 
at the time of any outlier reconciliation under Sec.  412.84(i)(4), 
outlier payments may be adjusted to account for the time value of any 
underpayments or overpayments. Section 20.1.2.6 of Chapter 3 of the 
Medicare Claims Processing Manual contains instructions on how to 
assess the time value of money for reconciled outlier amounts.
    If the operating CCR of a hospital subject to outlier 
reconciliation is lower at cost report settlement compared to the 
operating CCR used for payment, the hospital will owe CMS money because 
it received an outlier overpayment at the time of claim payment. 
Conversely, if the operating CCR increases at cost report settlement 
compared to the operating CCR used for payment, CMS will owe the 
hospital money because the hospital outlier payments were underpaid.
    In the FY 2020 IPPS/LTCH PPS final rule (84 FR 42623 through 
42635), we finalized a methodology to incorporate outlier 
reconciliation in the FY 2020 outlier fixed loss cost threshold. As 
discussed in the FY 2020 IPPS/LTCH PPS proposed rule (84 FR 19592), we 
stated that rather than trying to predict which claims and/or hospitals 
may be subject to outlier reconciliation, we believe a methodology that 
incorporates an estimate of outlier reconciliation dollars based on 
actual outlier reconciliation amounts reported in historical cost 
reports would be a more feasible approach and provide a better estimate 
and predictor of outlier reconciliation for the upcoming fiscal year. 
We also stated that we believe the

[[Page 45534]]

methodology addresses stakeholder's concerns on the impact of outlier 
reconciliation on the modeling of the outlier threshold. For a detailed 
discussion of additional background regarding outlier reconciliation, 
we refer the reader to the FY 2020 IPPS/LTCH PPS final rule.
(a) Incorporating a Projection of Outlier Payment Reconciliations for 
the FY 2022 Outlier Threshold Calculation
    Based on the methodology finalized in the FY 2020 IPPS/LTCH PPS 
final rule (84 FR 42623 through 42625), for FY 2022, as we proposed, we 
are continuing to incorporate outlier reconciliation in the FY 2022 
outlier fixed loss cost threshold.
    As discussed in the FY 2020 IPPS/LTCH PPS final rule, for FY 2020, 
we used the historical outlier reconciliation amounts from the FY 2014 
cost reports (cost reports with a begin date on or after October 1, 
2013, and on or before September 30, 2014), which we believed would 
provide the most recent and complete available data to project the 
estimate of outlier reconciliation. We refer the reader to the FY 2020 
IPPS/LTCH PPS final rule (84 FR 42623 through 42625) for a discussion 
on the use of the FY 2014 cost report data for purposes of projecting 
outlier payment reconciliations for the FY 2020 outlier threshold 
calculation. For FY 2022, we applied the same methodology finalized in 
FY 2020, using the historical outlier reconciliation amounts from the 
FY 2015 cost reports (cost reports with a begin date on or after 
October 1, 2014, and on or before September 30, 2015).
    Similar to the FY 2021 methodology, in this final rule, we are 
determining a projection of outlier payment reconciliations for the FY 
2022 outlier threshold calculation, by advancing the methodology by 1 
year. Specifically, we are using FY 2016 cost reports (cost reports 
with a begin date on or after October 1, 2015, and on or before 
September 30, 2016).
    For FY 2022, we proposed to use the same methodology from FY 2020 
to incorporate a projection of operating outlier payment 
reconciliations for the FY 2022 outlier threshold calculation. The 
following steps are the same as those finalized in the FY 2020 final 
rule but with updated data for FY 2022:
    Step 1.--Use the Federal FY 2016 cost reports for hospitals paid 
under the IPPS from the most recent publicly available quarterly HCRIS 
extract available at the time of development of the proposed and final 
rules, and exclude sole community hospitals (SCHs) that were paid under 
their hospital-specific rate (that is, if Worksheet E, Part A, Line 48 
is greater than Line 47). We note that when there are multiple columns 
available for the lines of the cost report described in the following 
steps and the provider was paid under the IPPS for that period(s) of 
the cost report, then we believe it is appropriate to use multiple 
columns to fully represent the relevant IPPS payment amounts, 
consistent with our methodology for the FY 2020 final rule.
    Step 2.--Calculate the aggregate amount of historical total of 
operating outlier reconciliation dollars (Worksheet E, Part A, Line 
2.01) using the Federal FY 2016 cost reports from Step 1.
    Step 3.--Calculate the aggregate amount of total Federal operating 
payments using the Federal FY 2016 cost reports from Step 1. The total 
Federal operating payments consist of the Federal payments (Worksheet 
E, Part A, Line 1.01 and Line 1.02, plus Line 1.03 and Line 1.04), 
outlier payments (Worksheet E, Part A, Line 2 and Line 2.02), and the 
outlier reconciliation payments (Worksheet E, Part A, Line 2.01). We 
note that a negative amount on Worksheet E, Part A, Line 2.01 for 
outlier reconciliation indicates an amount that was owed by the 
hospital, and a positive amount indicates this amount was paid to the 
hospital.
    Step 4.--Divide the amount from Step 2 by the amount from Step 3 
and multiply the resulting amount by 100 to produce the percentage of 
total operating outlier reconciliation dollars to total Federal 
operating payments for FY 2016. This percentage amount would be used to 
adjust the outlier target for FY 2022 as described in Step 5.
    Step 5.--Because the outlier reconciliation dollars are only 
available on the cost reports, and not in the Medicare claims data in 
the MedPAR file used to model the outlier threshold, we proposed to 
target 5.1 percent minus the percentage determined in Step 4 in 
determining the outlier threshold. Using the FY 2016 cost reports based 
on the December 2020 HCRIS extract, because the aggregate outlier 
reconciliation dollars from Step 2 are negative, we stated we are 
targeting an amount higher than 5.1 percent for outlier payments for FY 
2022 under our proposed methodology.
    For the FY 2022 proposed rule, we used the December 2020 HCRIS 
extract of the cost report data to calculate the proposed percentage 
adjustment for outlier reconciliation. For the FY 2022 final rule, we 
proposed to use the latest quarterly HCRIS extract that is publically 
available at the time of the development of that rule which, for FY 
2022, would be the March 2021 extract. Similar to the FY 2021 final 
rule, we stated that we might also consider the use of more recent data 
that may become available for purposes of projecting the estimate of 
operating outlier reconciliation used in the calculation of the final 
FY 2022 outlier threshold.
    In the FY 2022 proposed rule, based on the December 2020 HCRIS, 12 
hospitals had an outlier reconciliation amount recorded on Worksheet E, 
Part A, Line 2.01 for total operating outlier reconciliation dollars of 
negative $12,140,344 (Step 2). The total Federal operating payments 
based on the December 2020 HCRIS was $88,239,764,644 (Step 3). The 
ratio (Step 4) is a negative 0.013758 percent, which, when rounded to 
the second digit, is -0.01 percent. Therefore, for FY 2022, we proposed 
to incorporate a projection of outlier reconciliation dollars by 
targeting an outlier threshold at 5.11 percent [5.1 percent-(-.01 
percent)].
    When the percentage of operating outlier reconciliation dollars to 
total Federal operating payments rounds to a negative value (that is, 
when the aggregate amount of outlier reconciliation as a percent of 
total operating payments rounds to a negative percent), the effect is a 
decrease to the outlier threshold compared to an outlier threshold that 
is calculated without including this estimate of operating outlier 
reconciliation dollars. In section II.A.4.i.(2). of the Addendum to the 
proposed rule, we provide the FY 2022 outlier threshold as calculated 
for the proposed rule both with and without including this proposed 
percentage estimate of operating outlier reconciliation.
    As explained in the FY 2020 IPPS/LTCH PPS final rule, we proposed 
to continue to use a 5.1 percent target (or an outlier offset factor of 
0.949) in calculating the outlier offset to the standardized amount. In 
the past, the outlier offset was six decimals because we targeted and 
set the threshold at 5.1 percent by adjusting the standardized amount 
by the outlier offset until operating outlier payments divided by total 
operating Federal payments plus operating outlier payments equaled 
approximately 5.1 percent (this approximation resulted in an offset 
beyond three decimals). However, under our methodology, we believe a 
three decimal offset of 0.949 reflecting 5.1 percent is appropriate 
rather than the unrounded six decimal offset that we have calculated 
for prior fiscal years. Specifically, as discussed in section II.A.5. 
of this Addendum, we proposed to determine an outlier adjustment by 
applying a factor to the standardized

[[Page 45535]]

amount that accounts for the projected proportion of total estimated FY 
2022 operating Federal payments paid as outliers. Our proposed 
modification to the outlier threshold methodology is designed to adjust 
the total estimated outlier payments for FY 2022 by incorporating the 
projection of negative outlier reconciliation. That is, under this 
proposal, total estimated outlier payments for FY 2022 would be the sum 
of the estimated FY 2022 outlier payments based on the claims data from 
the outlier model and the estimated FY 2022 total operating outlier 
reconciliation dollars. We stated that we believe the proposed 
methodology would more accurately estimate the outlier adjustment to 
the standardized amount by increasing the accuracy of the calculation 
of the total estimated FY 2022 operating Federal payments paid as 
outliers. In other words, the net effect of our outlier proposal to 
incorporate a projection for outlier reconciliation dollars into the 
threshold methodology would be that FY 2022 outlier payments (which 
included the proposed estimated recoupment percentage for FY 2022 of 
0.01 percent) would be 5.1 percent of total operating Federal payments 
plus total outlier payments. Therefore, the proposed operating outlier 
offset to the standardized amount was 0.949 (1-0.051).
    We invited public comment on our proposed methodology for 
projecting an estimate of outlier reconciliation and incorporating that 
estimate into the modeling for the fixed-loss cost outlier threshold 
for FY 2022.
    Comment: A commenter supported incorporating an estimate of outlier 
reconciliation. A commenter stated that they were successful in 
replicating the proposed calculations.
    Response: We thank the commenter for their feedback on the proposed 
calculation methodology.
    After consideration of the comments received, and for the reasons 
discussed in the proposed rule and in this final rule, we are 
finalizing the methodology described previously for incorporating the 
outlier reconciliation in the outlier threshold calculation. Therefore, 
for this final rule we used the same steps described previously and in 
the proposed rule to incorporate a projection of operating outlier 
payment reconciliations for the calculation of the FY 2022 outlier 
threshold calculation. The March 2021 HCRIS contained data for 20 
hospitals. As stated previously, while we proposed to use the March 
2021 HCRIS extract to calculate the reconciliation adjustment for this 
FY 2022 IPPS final rule, we also stated that similar to the FY 2021 
final rule, we might consider the use of more recent data that may 
become available for purpose of projecting the estimate of operating 
outlier reconciliation used in the calculation of the final FY 2022 
outlier threshold. Data for 4 additional outlier reconciliations were 
made available to CMS outside of the March 2021 HCRIS update. Similar 
to our discussion of the estimated operating outlier reconciliation for 
FY 2021 in the FY 2021 IPPS/LTCH final rule (85 FR 59036), we believe 
supplementing with 4 hospitals' outlier reconciliation data will lend 
additional accuracy to project the estimate of operating outlier 
reconciliation used in the calculation of the outlier threshold. 
Therefore, in order to use the most complete data for FY 2016 cost 
reports, we are using the March 2021 HCRIS extract, supplemented by 
these 4 additional hospitals' data for this FY 2022 IPPS final rule. 
Without the 4 additional hospitals' data, the rounded operating outlier 
reconciliation percentage would have been 0.02 (unrounded of 0.02196). 
As we gain more experience with this policy, we also are considering 
adding additional lines to the cost report in order to ensure we 
capture the maximum cost report data with the March HCRIS extract to 
calculate the percentage adjustment for outlier reconciliation for the 
final rule for future rulemaking, as we generally expect historical 
cost reports for the applicable fiscal year to be available by March. 
Based on March 2021 HCRIS and supplemental data for 4 hospitals, a 
total of 2 hospitals had an outlier reconciliation amount recorded on 
Worksheet E, Part A, Line 2.01 for total operating outlier 
reconciliation dollars of negative $19,370,904 (Step 2). The total 
Federal operating payments based on the March 2021 HCRIS and 
supplemental 4 reports is $88,220,077,932 (Step 3). The ratio (Step 4) 
is a negative 0.02196 percent, which, when rounded to the second digit, 
is negative 0.02 percent. Therefore, for FY 2022, using the finalized 
methodology, we incorporated a projection of outlier reconciliation 
dollars by targeting an outlier threshold at 5.12 percent [5.1 percent-
(-0.02 percent)]. As noted previously, when the percentage of operating 
outlier reconciliation dollars to total Federal operating payments is 
negative (such is the case when the aggregate amount of outlier 
reconciliation is negative), the effect is a decrease to the outlier 
threshold compared to an outlier threshold that is calculated without 
including this estimate of operating outlier reconciliation dollars. In 
section II.A.4.i.(2). of this Addendum of this final rule, we provide 
the FY 2022 outlier threshold as calculated both with and without 
including this percentage estimate of operating outlier reconciliation.
(b) Reduction to the FY 2021 Capital Standard Federal Rate by an 
Adjustment Factor To Account for the Projected Proportion of Capital 
IPPS Payments Paid as Outliers
    We establish an outlier threshold that is applicable to both 
hospital inpatient operating costs and hospital inpatient capital 
related costs (58 FR 46348). Similar to the calculation of the 
adjustment to the standardized amount to account for the projected 
proportion of operating payments paid as outlier payments, as discussed 
in greater detail in section III.A.2. of this Addendum, we proposed to 
reduce the FY 2022 capital standard Federal rate by an adjustment 
factor to account for the projected proportion of capital IPPS payments 
paid as outliers. The regulations in 42 CFR 412.84(i)(4) state that any 
outlier reconciliation at cost report settlement would be based on 
operating and capital CCRs calculated based on a ratio of costs to 
charges computed from the relevant cost report and charge data 
determined at the time the cost report coinciding with the discharge is 
settled. As such, any reconciliation also applies to capital outlier 
payments.
    For FY 2022, we proposed to use the same methodology from FY 2020 
to adjust the FY 2022 capital standard Federal rate by an adjustment 
factor to account for the projected proportion of capital IPPS payments 
paid as outliers. Similar to FY 2020, as part of our proposals for FY 
2022 to incorporate into the outlier model the total outlier 
reconciliation dollars from the most recent and most complete fiscal 
year cost report data, we also proposed to adjust our estimate of FY 
2022 capital outlier payments to incorporate a projection of capital 
outlier reconciliation payments when determining the adjustment factor 
to be applied to the capital standard Federal rate to account for the 
projected proportion of capital IPPS payments paid as outliers. To do 
so, we proposed to use the following methodology, which generally 
parallels the methodology to incorporate a projection of operating 
outlier reconciliation payments for the FY 2022 outlier threshold 
calculation.
    Step 1.--Use the Federal FY 2016 cost reports for hospitals paid 
under the IPPS from the most recent publicly available quarterly HCRIS 
extract available at the time of development of

[[Page 45536]]

the proposed and final rules, and exclude SCHs that were paid under 
their hospital-specific rate (that is, if Worksheet E, Part A, Line 48 
is greater than Line 47). We note that when there are multiple columns 
available for the lines of the cost report described in the following 
steps and the provider was paid under the IPPS for that period(s) of 
the cost report, then we believe it is appropriate to use multiple 
columns to fully represent the relevant IPPS payment amounts, 
consistent with our methodology for the FY 2020 final rule. We used the 
December 2020 HCRIS extract for the proposed rule and stated that we 
expected to use the March 2020 HCRIS extract for the FY 2022 final 
rule. Similar to the FY 2020 final rule, we stated that we may also 
consider the use of more recent data that may become available for 
purposes of projecting the estimate of capital outlier reconciliation 
used in the calculation of the final FY 2022 adjustment to the FY 2022 
capital standard Federal rate.
    Step 2.--Calculate the aggregate amount of the historical total of 
capital outlier reconciliation dollars (Worksheet E, Part A, Line 93, 
Column 1) using the Federal FY 2016 cost reports from Step 1.
    Step 3.--Calculate the aggregate amount of total capital Federal 
payments using the Federal FY 2016 cost reports from Step 1. The total 
capital Federal payments consist of the capital DRG payments, including 
capital indirect medical education (IME) and capital disproportionate 
share hospital (DSH) payments (Worksheet E, Part A, Line 50, Column 1) 
and the capital outlier reconciliation payments (Worksheet E, Part A, 
Line 93, Column 1). We note that a negative amount on Worksheet E, Part 
A, Line 93 for capital outlier reconciliation indicates an amount that 
was owed by the hospital, and a positive amount indicates this amount 
was paid to the hospital.
    Step 4.--Divide the amount from Step 2 by the amount from Step 3 
and multiply the resulting amount by 100 to produce the percentage of 
total capital outlier reconciliation dollars to total capital Federal 
payments for FY 2016. This percentage amount would be used to adjust 
the estimate of capital outlier payments for FY 2022 as described in 
Step 5.
    Step 5.--Because the outlier reconciliation dollars are only 
available on the cost reports, and not in the specific Medicare claims 
data in the MedPAR file used to estimate outlier payments, we proposed 
that the estimate of capital outlier payments for FY 2022 would be 
determined by adding the percentage in Step 4 to the estimated 
percentage of capital outlier payments otherwise determined using the 
shared outlier threshold that is applicable to both hospital inpatient 
operating costs and hospital inpatient capital-related costs. (We note 
that this percentage is added for capital outlier payments but 
subtracted in the analogous step for operating outlier payments. We 
have a unified outlier payment methodology that uses a shared threshold 
to identify outlier cases for both operating and capital payments. The 
difference stems from the fact that operating outlier payments are 
determined by first setting a ``target'' percentage of operating 
outlier payments relative to aggregate operating payments which 
produces the outlier threshold. Once the shared threshold is set, it is 
used to estimate the percentage of capital outlier payments to total 
capital payments based on that threshold. Because the threshold is 
already set based on the operating target, rather than adjusting the 
threshold (or operating target), we adjust the percentage of capital 
outlier to total capital payments to account for the estimated effect 
of capital outlier reconciliation payments. This percentage is adjusted 
by adding the capital outlier reconciliation percentage from Step 4 to 
the estimate of the percentage of capital outlier payments to total 
capital payments based on the shared threshold.) Because the aggregate 
capital outlier reconciliation dollars from Step 2 are negative, the 
estimate of capital outlier payments for FY 2022 under our proposed 
methodology would be lower than the percentage of capital outlier 
payments otherwise determined using the shared outlier threshold.
    Similarly, for the FY 2022 proposed rule, we used the December 2020 
HCRIS extract of the cost report data to calculate the proposed 
percentage adjustment for outlier reconciliation. For this FY 2022 
final rule, we proposed to use the latest quarterly HCRIS extract that 
is publically available at the time of the development of this rule 
which, for FY 2022, would be the March 2021 extract. As previously 
noted, we stated that we may also consider the use of more recent data 
that may become available for purposes of projecting the estimate of 
capital outlier reconciliation used in the calculation of the final FY 
2022 adjustment to the FY 2022 capital standard Federal rate.
    For the FY 2022 proposed rule, the estimated percentage of FY 2022 
capital outlier payments otherwise determined using the shared outlier 
threshold was 5.34 percent (estimated capital outlier payments of 
$431,821,043 divided by (estimated capital outlier payments of 
$431,821,043 plus the estimated total capital Federal payment of 
$7,651,022,484)). Based on the December 2020 HCRIS, 12 hospitals had an 
outlier reconciliation amount recorded on Worksheet E, Part A, Line 93 
for total capital outlier reconciliation dollars of negative $915,421 
(Step 2). The total Federal capital payments based on the December 2020 
HCRIS was $7,961,217,741 (Step 3) which resulted in a ratio (Step 4) of 
-0.01 percent. Therefore, for FY 2022, taking into account projected 
capital outlier reconciliation payments under our proposed methodology 
would decrease the estimated percentage of FY 2022 aggregate capital 
outlier payments by 0.01 percent.
    As discussed in section III.A.2. of this Addendum, we proposed to 
incorporate the capital outlier reconciliation dollars from Step 5 when 
applying the outlier adjustment factor in determining the capital 
Federal rate based on the estimated percentage of capital outlier 
payments to total capital Federal rate payments for FY 2022.
    We invited public comment on our proposed methodology for 
projecting an estimate of capital outlier reconciliation and 
incorporating that estimate into the modeling of the estimate of FY 
2022 capital outlier payments for purposes of determining the capital 
outlier adjustment factor.
    We did not receive comments about the proposed capital outlier 
reconciliation methodology.
    For the reasons discussed, we are finalizing the methodology for 
projecting an estimate of capital outlier reconciliation. Therefore, 
for this final rule we used the same steps as described in the proposed 
rule and this final rule to reduce the FY 2022 capital standard Federal 
rate by an adjustment factor to account for the projected proportion of 
capital IPPS payments paid as outliers.
    For projecting the estimate of capital outlier reconciliation, 
similar to our projection of the estimate of operating outlier 
reconciliation, we are using cost report data of 19 hospitals from the 
March 2021 HCRIS supplemented for 3 hospitals for a total of 22 
hospitals, which we believe will lend additional accuracy to the 
projection of estimated capital outlier reconciliation for FY 2022. 
Without the 3 additional reports, the step 4 unrounded value for 
capital outlier reconciliation would have been 0.02, which rounds to 
0.02. We note that a difference in the number of cost reports for the 
operating and capital outlier reconciliation projections is possible 
and may be due to new hospitals defined in the regulations at

[[Page 45537]]

42 CFR 412.300(b) that may receive capital cost-based payments (in lieu 
of Federal rate payments), and therefore would not receive capital 
outlier payments. As a result, capital outlier reconciliation is not 
applicable to such hospitals since there is no capital outlier payment.
    The estimated percentage of FY 2022 capital outlier payments 
otherwise determined using the shared outlier threshold is 5.31 percent 
(estimated capital outlier payments of $ 430,689,396 divided by 
(estimated capital outlier payments of $430,689,396 plus the estimated 
total capital Federal payment of $7,676,990,253)). Based on the March 
2021 HCRIS supplemented by the data for 3 additional providers, 22 
hospitals had an outlier reconciliation amount recorded on Worksheet E, 
Part A, Line 93 for total capital outlier reconciliation dollars of 
negative $ 1,784,117 (Step 2). The total Federal capital payments based 
on the March 2021 HCRIS and supplemental 3 reports is approximately $ 
7,960,571,775 (Step 3). The ratio (Step 4) is a negative 0.02241 
percent, which, when rounded to the second digit, is negative 0.02 
percent (Step 4). Therefore, for FY 2022, taking into account projected 
capital outlier reconciliation payments under our methodology would 
decrease the estimated percentage of FY 2022 aggregate capital outlier 
payments by 0.02 percent.
(2) FY 2022 Outlier Fixed-Loss Cost Threshold
    In the FY 2014 IPPS/LTCH PPS final rule (78 FR 50977 through 
50983), in response to public comments on the FY 2013 IPPS/LTCH PPS 
proposed rule, we made changes to our methodology for projecting the 
outlier fixed-loss cost threshold for FY 2014. We refer readers to the 
FY 2014 IPPS/LTCH PPS final rule for a detailed discussion of the 
changes.
    As we have done in the past, to calculate the FY 2022 outlier 
threshold, we simulated payments by applying FY 2022 payment rates and 
policies using cases from the FY 2019 MedPAR file. As noted in section 
II.C. of this Addendum, we specify the formula used for actual claim 
payment which is also used by CMS to project the outlier threshold for 
the upcoming fiscal year. The difference is the source of some of the 
variables in the formula. For example, operating and capital CCRs for 
actual claim payment are from the PSF while CMS uses an adjusted CCR 
(as described later in this section) to project the threshold for the 
upcoming fiscal year. In addition, charges for a claim payment are from 
the bill while charges to project the threshold are from the MedPAR 
data with an inflation factor applied to the charges (as described 
earlier).
    In order to determine the proposed FY 2022 outlier threshold, we 
inflated the charges on the MedPAR claims by 3 years, from FY 2019 to 
FY 2022. Consistent with the FY 2020 IPPS/LTCH PPS final rule (84 FR 
42626 and 42627), we proposed to use the following methodology to 
calculate the charge inflation factor for FY 2022:
     Include hospitals whose last four digits fall between 0001 
and 0899 (section 2779A1 of Chapter 2 of the State Operations Manual on 
the CMS website at https://www.cms.gov/Regulations-and-Guidance/Guidance/Manuals/Downloads/som107c02.pdf); include CAHs that were IPPS 
hospitals for the time period of the MedPAR data being used to 
calculate the charge inflation factor; include hospitals in Maryland; 
and remove PPS-excluded cancer hospitals who have a ``V'' in the fifth 
position of their provider number or a ``E'' or ``F'' in the sixth 
position.
     Include providers that are in both periods of charge data 
that are used to calculate the 1-year average annual rate of-change in 
charges per case. We note this is consistent with the methodology used 
since FY 2014.
     We excluded Medicare Advantage IME claims for the reasons 
described in section I.A.4. of this Addendum. We refer readers to the 
FY 2011 IPPS/LTCH PPS final rule for a complete discussion on our 
methodology of identifying and adding the total Medicare Advantage IME 
payment amount to the budget neutrality adjustments.
     In order to ensure that we capture only FFS claims, we 
included claims with a ``Claim Type'' of 60 (which is a field on the 
MedPAR file that indicates a claim is an FFS claim).
     In order to further ensure that we capture only FFS 
claims, we excluded claims with a ``GHOPAID'' indicator of 1 (which is 
a field on the MedPAR file that indicates a claim is not an FFS claim 
and is paid by a Group Health Organization).
     We examined the MedPAR file and removed pharmacy charges 
for anti-hemophilic blood factor (which are paid separately under the 
IPPS) with an indicator of ``3'' for blood clotting with a revenue code 
of ``0636'' from the covered charge field. We also removed organ 
acquisition charges from the covered charge field because organ 
acquisition is a pass-through payment not paid under the IPPS. As noted 
previously, we are removing allogeneic hematopoietic stem cell 
acquisition charges from the covered charge field for budget neutrality 
adjustments. As discussed in the FY 2021 IPPS/LTCH PPS final rule, 
payment for allogeneic hematopoietic stem cell acquisition costs is 
made on a reasonable cost basis for cost reporting periods beginning on 
or after October 1, 2020 (85 FR 58835-58842).
     Because this payment simulation uses the FY 2022 relative 
weights, consistent with our policy discussed in section IV.I. of the 
preamble to this final rule, we applied the adjustor for certain cases 
that group to MS-DRG 018 in our simulation of these payments. As 
discussed in section II.E.2.b. of the preamble of this final rule, we 
are applying a adjustment to account for certain cases that group to 
MS-DRG 018 in calculating the FY 2022 relative weights and for purposes 
of budget neutrality and outlier simulations.
    Our general methodology to inflate the charges computes the 1-year 
average annual rate-of-change in charges per case which is then applied 
twice to inflate the charges on the MedPAR claims by 2 years since we 
typically use claims data for the fiscal year that is 2 years prior to 
the upcoming fiscal year. However, in the FY 2022 proposed rule, we 
proposed to use the FY 2019 MedPAR claims data, which is 3 years prior 
to FY 2022. Therefore, we proposed to inflate the charges on the MedPAR 
claims data by 3 years.
    In the FY 2020 IPPS/LTCH PPS final rule (84 FR 42627), we modified 
our charge inflation methodology. We stated that we believe balancing 
our preference to use the latest available data from the MedPAR files 
and stakeholders' concerns about being able to use publicly available 
MedPAR files to review the charge inflation factor can be achieved by 
modifying our methodology to use the publicly available Federal fiscal 
year period (that is, for FY 2020, we used the charge data from Federal 
fiscal years 2017 and 2018), rather than the most recent data available 
to CMS which, under our prior methodology, was based on calendar year 
data. We refer the reader to the FY 2020 IPPS/LTCH PPS final rule for a 
complete discussion regarding this change. For the same reasons 
discussed in that rulemaking, and consistent with our proposal to use 
the FY 2019 MedPAR for purposes of FY 2022 ratesetting, for FY 2022, we 
proposed to use the same methodology as FY 2020, and based on the same 
data used in the FY 2021 IPPS/LTCH PPS final rule to determine the 
charge inflation factor for this final rule. That is, for FY 2022, we 
proposed to use the MedPAR files for the two most recent available 
Federal fiscal year time periods prior to the COVID-19 PHE to

[[Page 45538]]

calculate the charge inflation factor. Specifically, for the proposed 
rule we used the March 2019 MedPAR file of FY 2018 (October 1, 2017 to 
September 30, 2018) charge data (released for the FY 2020 IPPS/LTCH PPS 
final rule) and the March 2020 MedPAR file of FY 2019 (October 1, 2018 
to September 30, 2019) charge data (released for the FY 2021 IPPS/LTCH 
PPS final rule) to compute the proposed charge inflation factor. We 
proposed for the FY 2022 IPPS/LTCH PPS final rule to continue to use 
the charge inflation estimate from the FY 2021 IPPS/LTCH PPS final 
rule. In addition, we solicited comments on the alternative approach of 
using the same data we would ordinarily use for purposes of FY 2022 
ratesetting, as discussed in section I.F. of this final rule, and noted 
that under this alternative approach, if finalized, we would anticipate 
using more recently updated data for purposes of the FY 2022 IPPS/LTCH 
PPS final rule. Under this proposed methodology, to compute the 1-year 
average annual rate-of-change in charges per case for FY 2022, we 
compared the average covered charge per case of $61,578.82 
($584,618,863,834/9,493,830 cases) from October 1, 2017 through 
September 31, 2018, to the average covered charge per case of 
$65,522.10 ($604,209,834,327/9,221,466 cases) from October 1, 2018 
through September 31, 2019. This rate-of-change was 6.4 percent 
(1.06404) or 20.4 percent over 3 years. Because we proposed to use the 
FY 2019 MedPAR for the FY 2022 ratesetting, we applied a factor of 20.4 
percent (1.20469) over 3 years. The billed charges are obtained from 
the claim from the MedPAR file and inflated by the inflation factor 
specified previously.
    In order to facilitate comments on the alternative approach 
discussed in section I.F. of the proposed rule and this final rule of 
using the same data that we would ordinarily use for purposes of FY 
2022 ratesetting, and which we stated we may consider finalizing for FY 
2022 based on consideration of comments received, we made available 
budget neutrality and other ratesetting adjustments, including the 
charge inflation factor, calculated under this alternative approach, 
which can be found on the CMS website at: https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/AcuteInpatientPPS/index. We included 
in a supplemental data file the following: Budget neutrality factors, 
charge inflation factor, the CCR adjustment factors, and outlier 
threshold based on this alternative approach. Consistent with 
historical practice, we stated that if we were to finalize this 
alternative approach, we would use the most recent available data for 
the final rule, as appropriate.
    As discussed previously, in the FY 2022 IPPS/LTCH PPS proposed 
rule, we proposed to establish the FY 2022 outlier threshold using 
hospital CCRs from the March 2020 update to the Provider-Specific File 
(PSF), which is consistent with our approach of not using data that may 
have been significantly impacted by the COVID-19 PHE. We proposed to 
apply the following edits to providers' CCRs in the PSF. We stated that 
we believe these edits are appropriate in order to accurately model the 
outlier threshold. We first searched for Indian Health Service 
providers and those providers assigned the statewide average CCR from 
the current fiscal year. We then replaced these CCRs with the statewide 
average CCR for the upcoming fiscal year. We also assigned the 
statewide average CCR (for the upcoming fiscal year) to those providers 
that have no value in the CCR field in the PSF or whose CCRs exceed the 
ceilings described later in this section (3.0 standard deviations from 
the mean of the log distribution of CCRs for all hospitals). We did not 
apply the adjustment factors described later in this section to 
hospitals assigned the statewide average CCR. For FY 2022, we also 
proposed to continue to apply an adjustment factor to the CCRs to 
account for cost and charge inflation (as explained later in this 
section).
    In the FY 2014 IPPS/LTCH PPS final rule (78 FR 50979), we adopted a 
new methodology to adjust the CCRs. Specifically, we finalized a policy 
to compare the national average case-weighted operating and capital CCR 
from the most recent update of the PSF to the national average case-
weighted operating and capital CCR from the same period of the prior 
year.
    In the FY 2022 IPPS/LTCH proposed rule we stated that ordinarily, 
for the proposed rule, we would use CCRs from the December 2020 update 
of the PSF and apply an adjustment factor to adjust the CCRs from the 
December 2020 update of the PSF by comparing the percentage change in 
the national average case-weighted operating CCR and capital CCR from 
the December 2019 update of the PSF to the national average case-
weighted operating CCR and capital CCR from the December 2020 PSF. 
However, as discussed previously, we believe the operating and capital 
CCRs in the December 2020 PSF may be significantly impacted by the PHE. 
Therefore, we proposed to adjust the CCRs from the March 2020 update of 
the PSF (the latest update of the PSF prior to the PHE) by comparing 
the percentage change in the national average case-weighted operating 
CCR and capital CCR from the March 2019 update of the PSF to the 
national average case-weighted operating CCR and capital CCR from the 
March 2020 update of the PSF. We noted that we used total transfer-
adjusted cases from FY 2019 to determine the national average case-
weighted CCRs for both sides of the comparison. As stated in the FY 
2014 IPPS/LTCH PPS final rule (78 FR 50979), we believe that it is 
appropriate to use the same case count on both sides of the comparison, 
because this would produce the true percentage change in the average 
case-weighted operating and capital CCR from 1 year to the next without 
any effect from a change in case count on different sides of the 
comparison.
    Using this proposed methodology, for the proposed rule, we 
calculated a March 2019 operating national average case-weighted CCR of 
0.254027 and a March 2020 operating national average case-weighted CCR 
of 0.247548. We then calculated the percentage change between the two 
national operating case-weighted CCRs by subtracting the March 2019 
operating national average case-weighted CCR from the March 2020 
operating national average case-weighted CCR and then dividing the 
result by the March 2019 national operating average case-weighted CCR. 
This resulted in a one-year national operating CCR adjustment factor of 
0.974495. In the proposed rule, we noted that because we proposed to 
use CCRs from the March 2020 update of the PSF for FY 2022, we 
calculated a 2-year national operating CCR adjustment by multiplying 
0.974495 * 0.974495.
    We used the same proposed methodology to adjust the capital CCRs. 
Specifically, we calculated a March 2019 capital national average case-
weighted CCR of 0.02073 and a March 2020 capital national average case-
weighted CCR of 0.019935. We then calculated the percentage change 
between the two national capital case-weighted CCRs by subtracting the 
March 2019 capital national average case-weighted CCR from the March 
2020 capital national average case-weighted CCR and then dividing the 
result by the March 2019 capital national average case-weighted CCR. 
This resulted in a one-year national capital CCR adjustment factor of 
0.96165. In the proposed rule, we noted that because we proposed to use 
CCRs from the March 2020 update of the PSF for FY 2022, we calculated a 
2-year national

[[Page 45539]]

capital CCR adjustment by multiplying 0.96165 * 0.96165.
    As discussed in section I.F. of the proposed rule and in section 
I.O of Appendix A of the proposed rule, we solicited comments on an 
alternative approach of using the same data we would ordinarily use for 
purposes of FY 2022 ratesetting, which we stated we may consider 
finalizing for FY 2022 based on consideration of comments received, and 
made available supplemental data files to facilitate comments on this 
alternative approach. As noted previously, we included in a 
supplemental data file the following: Budget neutrality factors, charge 
inflation factor, the CCR adjustment factors, and outlier threshold 
based on this alternative approach. Consistent with historical 
practice, we stated in the proposed rule if we were to finalize this 
alternative approach, we would use the most recent available data for 
the final rule, as appropriate.
    For purposes of estimating the proposed outlier threshold for FY 
2022, we used a wage index that reflects the policies discussed in the 
proposed rule. This includes the proposed frontier State floor 
adjustments in accordance with section 10324(a) of the Affordable Care 
Act, the proposed out-migration adjustment as added by section 505 of 
Public Law 108-173, as well as incorporating the FY 2022 wage index 
adjustment for hospitals with a wage index value below the 25th 
percentile, where the increase in the wage index value for these 
hospitals would be equal to half the difference between the otherwise 
applicable final wage index value for a year for that hospital and the 
25th percentile wage index value for that year across all hospitals. We 
stated that if we did not take the aforementioned into account, our 
estimate of total FY 2022 payments would be too low, and, as a result, 
our proposed outlier threshold would be too high, such that estimated 
outlier payments would be less than our projected 5.1 percent of total 
payments (which includes outlier reconciliation). We noted, given the 
recent enactment of section 9831 of Public Law 117-2 on March 11, 2021, 
there was not sufficient time available to incorporate the changes 
required by this statutory provision (which provides for the 
application of the imputed floor adjustment in a non-budget neutral 
manner beginning in FY 2022) into the calculation of the provider wage 
index for the proposed rule. We stated that we will include the imputed 
floor adjustment in the calculation of the provider wage index in the 
FY 2022 final rule.
    As described in sections V.K. and IV.L., respectively, of the 
preamble of this final rule, sections 1886(q) and 1886(o) of the Act 
establish the Hospital Readmissions Reduction Program and the Hospital 
VBP Program, respectively. We stated in the proposed rule that we do 
not believe that it is appropriate to include the hospital VBP payment 
adjustments and the hospital readmissions payment adjustments in the 
outlier threshold calculation or the outlier offset to the standardized 
amount. Specifically, consistent with our definition of the base 
operating DRG payment amount for the Hospital Readmissions Reduction 
Program under Sec.  412.152 and the Hospital VBP Program under Sec.  
412.160, outlier payments under section 1886(d)(5)(A) of the Act are 
not affected by these payment adjustments. Therefore, outlier payments 
would continue to be calculated based on the unadjusted base DRG 
payment amount (as opposed to using the base-operating DRG payment 
amount adjusted by the hospital readmissions payment adjustment and the 
hospital VBP payment adjustment). Consequently, we proposed to exclude 
the estimated hospital VBP payment adjustments and the estimated 
hospital readmissions payment adjustments from the calculation of the 
outlier fixed-loss cost threshold.
    We noted in the proposed rule that, to the extent section 1886(r) 
of the Act modifies the DSH payment methodology under section 
1886(d)(5)(F) of the Act, the uncompensated care payment under section 
1886(r)(2) of the Act, like the empirically justified Medicare DSH 
payment under section 1886(r)(1) of the Act, may be considered an 
amount payable under section 1886(d)(5)(F) of the Act such that it 
would be reasonable to include the payment in the outlier determination 
under section 1886(d)(5)(A) of the Act. As we have done since the 
implementation of uncompensated care payments in FY 2014, for FY 2022, 
we proposed to allocate an estimated per-discharge uncompensated care 
payment amount to all cases for the hospitals eligible to receive the 
uncompensated care payment amount in the calculation of the outlier 
fixed-loss cost threshold methodology. We stated that we continue to 
believe that allocating an eligible hospital's estimated uncompensated 
care payment to all cases equally in the calculation of the outlier 
fixed-loss cost threshold would best approximate the amount we would 
pay in uncompensated care payments during the year because, when we 
make claim payments to a hospital eligible for such payments, we would 
be making estimated per-discharge uncompensated care payments to all 
cases equally. Furthermore, we stated that we continue to believe that 
using the estimated per-claim uncompensated care payment amount to 
determine outlier estimates provides predictability as to the amount of 
uncompensated care payments included in the calculation of outlier 
payments. Therefore, consistent with the methodology used since FY 2014 
to calculate the outlier fixed-loss cost threshold, for FY 2022, we 
proposed to include estimated FY 2022 uncompensated care payments in 
the computation of the outlier fixed-loss cost threshold. Specifically, 
we proposed to use the estimated per-discharge uncompensated care 
payments to hospitals eligible for the uncompensated care payment for 
all cases in the calculation of the outlier fixed-loss cost threshold 
methodology.
    Using this methodology, we used the formula described in section 
I.C.1. of this Addendum to simulate and calculate the Federal payment 
rate and outlier payments for all claims. In addition, as described in 
the earlier section to this Addendum, proposed to incorporate an 
estimate of FY 2022 outlier reconciliation in the methodology for 
determining the outlier threshold. As noted previously, for the FY 2022 
proposed rule, the ratio of outlier reconciliation dollars to total 
Federal Payments (Step 4) was a negative 0.013758 percent, which, when 
rounded to the second digit, is -0.01 percent. Therefore, for FY 2022, 
we proposed to incorporate a projection of outlier reconciliation 
dollars by targeting an outlier threshold at 5.11 percent [5.1 percent-
(-.01 percent)]. Under this proposed approach, we determined a proposed 
threshold of $30,967 and calculated total outlier payments of 
$5,081,824,613 and total operating Federal payments of $94,365,941,593. 
We then divided total outlier payments by total operating Federal 
payments plus total outlier payments and determined that this threshold 
matched with the 5.11 percent target, which reflected our proposal to 
incorporate an estimate of outlier reconciliation in the determination 
of the outlier threshold (as discussed in more detail in the previous 
section of this Addendum). We noted that, if calculated without 
applying our proposed methodology for incorporating an estimate of 
outlier reconciliation in the determination of the outlier threshold, 
the threshold would be $31,027. We proposed an outlier fixed-loss cost 
threshold for FY 2022 equal to

[[Page 45540]]

the prospective payment rate for the MS-DRG, plus any IME, empirically 
justified Medicare DSH payments, estimated uncompensated care payment, 
and any add-on payments for new technology, plus $30,967. As discussed 
further in section I.A of this final rule, we noted that the estimate 
of the proposed outlier threshold using the FY 2020 MedPAR file was 
$36,483.
    Comment: Multiple commenters supported CMS' proposal to continue 
using claims data and cost report data from prior to the pandemic to 
set the FY 2022 outlier threshold. Another commenter supported our 
proposal to use the MedPAR files for the two most recent available 
Federal fiscal year time periods prior to the COVID-19 PHE to calculate 
the charge inflation factor and stated that it believes the charge 
inflation recorded during the PHE is aberrant and, thus, is unlikely to 
provide a reasonably accurate forecast of charge inflation.
    Response: We thank the commenters for their support and are 
finalizing as proposed to use alternative data for the FY 2022 
ratesetting in situations where the latest data available that would 
typically be used for the final rule is significantly impacted by the 
COVID-19 PHE.
    Comment: Regarding the proposed charge inflation methodology, a 
commenter stated it supported CMS' proposal to use the pre-PHE data, as 
it believes the charge inflation recorded during the PHE is aberrant 
and, thus, is unlikely to provide a reasonably accurate forecast of 
charge inflation. The commenter believes that CMS' decision to move to 
publicly available data sets continues to be a thoughtful choice for 
the Proposed Rule.
    The commenter also stated that it believes that CMS should disclose 
all aspects of its edits to the most current data used for the Proposed 
Rule and commit to the same process and methods when it recalculates 
the threshold for purposes of the final rule. Additionally, the 
commenter stated CMS should commit to make public the data files it 
uses for the final rule, including all edits and calculations, when it 
publishes the final rule. A commenter noted that using the FY 2019 
data, it calculated a fixed loss threshold of $30,943 versus the 
published threshold in the proposed rule of $30,967, a difference of 
$24 or about 0.08%.
    Response: We thank the commenter for its input and are finalizing 
as proposed to use the MedPAR files for the two most recent available 
Federal fiscal year time periods prior to the COVID-19 PHE to calculate 
the charge inflation factor. For FY 2022, we have not made any 
modification to the proposed charge inflation methodology in this final 
rule. Our inclusion and exclusion criteria of hospitals claims in our 
measure of charge inflation is discussed above and the claims data we 
used to measure charge inflation is readily available for the public to 
replicate the charge inflation factor. In addition, we refer the reader 
to the detailed discussion in the FY 2020 IPPS/LTCH PPS final rule 
regarding the use of publicly available data in the charge inflation 
methodology initially adopted in the FY 2020 IPPS final rule (84 FR 
42627).
    Finally, the commenter stated that CMS should make public the data 
files it uses for the final rule, including all edits and calculations, 
when it publishes the final rule but did not specify which files it was 
referring to. We believe the data the commenters are requesting is 
publicly available and, as noted, the commenter indicated it calculated 
a fixed loss threshold of $30,943, which differed from the published 
threshold in the proposed rule of $30,967 by $24, or about 0.08%.
    Comment: Some commenters requested that CMS consider whether it is 
appropriate to include extreme cases when calculating the threshold. A 
commenter explained that high charge cases have a significant impact on 
the threshold. The commenter stated that it examined the data to 
understand the factors that drove an increase in the threshold over 
$5,000 between FY 2017 and FY 2021, and the proposed increase in the 
threshold by an additional almost $2,000 in FY 2022, and stated that it 
observed that the inclusion of extreme cases in the calculation of the 
threshold, the rate of which are increasing over time, significantly 
impacts CMS' determination of the fixed-loss threshold. If this trend 
continues (that is, if the number (and proportion) of extreme cases 
continues to increase each year), the commenter stated that the impact 
of this population of cases on the threshold will likewise increase. 
Thus, the commenter recommended that CMS carefully consider what is 
causing this trend, whether the inclusion of these cases in the 
calculation of the threshold is appropriate, or whether a separate 
outlier mechanism should apply to these cases that more closely hews 
outlier payments to marginal costs. The commenter believes this is 
consistent with the calculation process used for IPPS rate setting 
generally, but would also produce a threshold that more accurately 
reflects the universe of cases. The commenter asserted that a 2013 
Office of Inspector General (OIG) Report, Medicare Hospital Outlier 
Payments Warrant Increased Scrutiny, https://oig.hhs.gov/oei/reports/oei-06-10-00520.asp, concurs with this view.
    A commenter stated that the calculation of the outlier threshold is 
flawed considering the changes in payment for new technology and CAR T-
cell therapy. The commenter explained that these are high-cost cases 
that should be removed from the calculation. This commenter concluded 
that the increase to the threshold will reduce the number of cases that 
qualify for outlier payment and will result in payments being well 
below the 5.1 percent outlier target.
    Response: As we explained when responding to a similar comment in 
the FY 2018 IPPS/LTCH PPS final rule (82 FR 38526), the methodology 
used to calculate the outlier threshold includes all claims in order to 
account for all different types of cases, including high charge cases, 
to ensure that CMS meets the 5.1 percent target. As the commenter 
pointed out, the volume of these cases continues to rise, making their 
impact on the threshold significant. We believe excluding these cases 
would artificially lower the threshold. We believe it is important to 
include all cases in the calculation of the threshold no matter how 
high or low the charges. Including these cases with high charges lends 
more accuracy to the threshold, as these cases have an impact on the 
threshold and continue to rise in volume. Therefore, we believe the 
inclusion of the high-cost outlier cases in the calculation of the 
outlier threshold is appropriate.
    Also, with regard to the 2013 OIG report that the commenter 
references, this report studied the distribution of outlier payments 
and made recommendations based on the OIG findings, but did not mention 
concerns or make any recommendations with regard to the calculation of 
the outlier threshold. Therefore, we do not agree with the commenter 
that the OIG report concurs with its view.
    Comment: A commenter stated that it believes that ordinarily it is 
important to the process for setting the outlier threshold that CMS 
accurately calculate prior year actual payment comparisons to the 5.1% 
target. Without doing so, the commenter stated it is impossible for CMS 
to appropriately modify its methodology to achieve an accurate result. 
The commenter also noted that CMS' estimates of past outlier payments 
also routinely exceed the calculations of outlier payments based on 
HCRIS cost report data. The commenter emphasized the importance of CMS 
using the most recent data available to more accurately

[[Page 45541]]

assess the outlier payment level. The commenter stated that CMS has 
generally fallen short of its 5.1% outlier target virtually every FY 
since at least 2013 (the exceptions being meeting it in FY 2019 and 
exceeding it during the PHE) and yet is still proposing a significant 
increase in the threshold this year with no rationale offered to 
explain the prior years' shortfalls in outlier payments.
    A commenter noted that in many recent years, the outlier payments 
have been below the 5.1 percent target, and no adjustments were adopted 
to make up for the possible outlier payment shortfall in those years. 
The commenter stated that based on the most recent data, it believes 
the FY 2022 outlier threshold should be the same amount as in FY 2021, 
or an amount near $29,064, and reflect at a minimum no increase to the 
threshold.
    Another commenter stated that to the extent an increase in the 
fixed loss threshold is necessary, it should be limited to the market 
basket increase.
    A commenter noted that, for a given year, typically the final 
outlier threshold established by CMS in the final rule is lower than 
the threshold set forth in the proposed rule. The commenter emphasized 
that CMS should use the most recent data available when the Agency 
calculates the outlier threshold.
    Response: As noted previously, section 1886(d)(5)(A)(iv) of the Act 
states that outlier payments may not be not less than 5 percent nor 
more than 6 percent of the total payments projected or estimated to be 
made based on DRG prospective payment rates for discharges in that 
year. We believe that maintaining the FY 2021 outlier fixed-loss cost 
threshold for FY 2022 would be inconsistent with the statute because we 
would be setting a threshold based on the prior fiscal year. Also, when 
we calculate the threshold, we typically use the updated data that is 
available at the time of the development of the proposed and final 
rule. As previously noted, we are finalizing to use alternative data 
for the FY 2022 ratesetting in situations where the latest data 
available that would typically be used for the final rule is 
significantly impacted by the COVID-19 PHE, including for purposes of 
calculating the FY 2022 outlier threshold.
    With regard to the comment that CMS has generally fallen short of 
its 5.1% outlier target virtually every FY since at least 2013 (the 
exceptions being meeting it in FY 2019 and exceeding it during the PHE) 
and yet is still proposing a significant increase in the threshold this 
year with no rationale offered to explain the prior year shortfalls in 
payment, as we have previously stated in the FY 2015 IPPS/LTCH PPS 
final rule (79 FR 50379) and the FY 2016 IPPS/LTCH PPS final rule (80 
FR 49783), when we conduct our modeling to determine the outlier 
threshold, we generally factor in all payments and policies that would 
affect actual payments for the current year in order to estimate that 
outlier payments are 5.1 percent of total MS-DRG payments. While we 
recognize that outlier payments have been below the 5.1 percent target 
in prior fiscal years, we do not believe that these lower payouts are 
relevant to the current fiscal year because they do not lend greater 
accuracy to the estimate of payments that are 5.1 percent of total MS-
DRG payments for FY 2022. We also note that in response to commenters' 
concerns, over the years we have modified our outlier threshold 
calculation by changing the way we adjust the CCRs, changing the 
measure of inflation and incorporating an adjustment for outlier 
reconciliation. As in prior years, CMS will continue to consider any 
suggestions made by the commenters to improve the accuracy of the 
calculation of the outlier threshold.
    Also, CMS' historical policy is to use the best available data when 
setting the payment rates and factors in both the proposed and final 
rules. Sometimes there are variables that change between the proposed 
and final rule as result of the availability of more recent data, such 
as the charge inflation factor and the CCR adjustment factors that can 
cause fluctuations in the threshold amount. For FY 2022 we used the 
same charge inflation factor and CCR adjustment factors as the proposed 
rule which is based on the data from the FY 2021 IPPS/LTCH final rule. 
However, other factors such as changes to the wage indexes and market 
basket applicable percentage increase were updated from FY 2021 to FY 
2022 and from the proposed rule to the final rule which can also cause 
the outlier fixed loss cost threshold to fluctuate.
    With regard to the comment that CMS should use the most recent data 
available when CMS calculates the outlier threshold, as noted above, 
when we calculate the threshold, we typically use the updated data that 
is available at the time of the development of the proposed and final 
rule. As previously noted, we are finalizing to use alternative data 
for the FY 2022 ratesetting in situations where the latest data 
available that would typically be used for the final rule is 
significantly impacted by the COVID-19 PHE, including for purposes of 
calculating the FY 2022 outlier threshold. We also note that under this 
finalized policy, the MedPAR data used for this final rule is from the 
March 2020 update of the FY 2019 MedPAR claims, which is the same 
update that was used for the proposed rule.
    While most of the data and variables for the fixed loss threshold 
remain the same from the proposed rule to this final rule, we are 
updating the wage index and other variables such as the applicable 
percentage increase. The applicable percentage increase may contribute 
to the slight increase in the final outlier threshold set forth in this 
final rule $30,988 as compared to the proposed rule $ 30,967. In the 
proposed rule, the proposed applicable percentage increase was 2.3 
percent and in this final rule, the final applicable percentage 
increase is 2.0 percent. A lower applicable percentage increase 
typically results in hospitals receiving less Federal payments and more 
outlier payments per case. Therefore, it seems the lower applicable 
percentage increases from the proposed rule to the final rule would 
cause an increase to the fixed-loss outlier threshold so that less 
cases receive outlier payments to ensure we reach the projected 5.1 
percent of total payments. Additionally, changes to the wage index year 
to year and from the proposed rule to the final rule can impact the 
fixed-loss outlier threshold.
    Comment: A commenter stated that it recognizes that with the 
release of the MedPAR final data with additional claims, which will 
lead to new weights being calculated, and with updated cost to charge 
ratios, it is appropriate to recalculate the fixed loss threshold from 
the data that will be released with the final rule.
    Response: As noted above, when we calculate the threshold, we 
typically use the updated data that is available at the time of the 
development of the proposed and final rule. As noted, we are finalizing 
to use alternative data for the FY 2022 ratesetting in situations where 
the latest data available that would typically be used for the final 
rule is significantly impacted by the COVID-19 PHE, including for 
purposes of the FY 2022 outlier threshold and calculation of the 
relative weights. Therefore, under this final policy, for FY 2022 we 
are using the March 2020 update of the FY 2019 MedPAR claims file, as 
we proposed. Also, we used the updated FY 2022 final rule MS-DRG 
weights in our calculation of the outlier threshold.
    After consideration of the public comments we received, we are 
using the same methodology we proposed to calculate the final outlier 
threshold. As discussed previously, we are adopting for this final rule 
to calculate charge inflation using the publicly available FY

[[Page 45542]]

2018 and FY 2019 claims data and to incorporate a projection of outlier 
payment reconciliations for the FY 2022 outlier threshold calculation. 
For the FY 2022 final outlier threshold, we used the March 2019 MedPAR 
file of FY 2018 (October 1, 2017 through September 30, 2018) charge 
data (released in conjunction with the FY 2020 IPPS/LTCH PPS final 
rule) and the March 2020 MedPAR file of FY 2019 (October 1, 2018 
through September 30, 2019) charge data (released in conjunction with 
the FY 2021 IPPS/LTCH PPS final rule) to determine the charge inflation 
factor. To compute the 1 year average annual rate of change in charges 
per case, we compared the average covered charge per case of $61,578.82 
($584,618,863,834/9,493,830 cases) from October 1, 2017 through 
September 31, 2018, to the average covered charge per case of 
$65,522.10 ($604,209,834,327/9,221,466 cases) from October 1, 2018 
through September 31, 2019. This rate-of-change was 6.4 percent 
(1.06404) or 20.4 percent over 3 years. Consistent with using the FY 
2019 MedPAR for the FY 2022 ratesetting, as we proposed, we are 
applying a factor of 20.4 percent over 3 years. The billed charges are 
obtained from the claims from the MedPAR file and inflated by the 
inflation factor specified previously.
    For FY 2022, as we proposed, we are establishing the FY 2022 
outlier threshold using hospital CCRs from the March 2020 update to the 
Provider-Specific File (PSF). We applied the following edits to 
providers' CCRs in the PSF. We believe these edits are appropriate in 
order to accurately model the outlier threshold. We first search for 
Indian Health Service providers and those providers assigned the 
statewide average CCR from the current fiscal year. We then replaced 
these CCRs with the statewide average CCR for the upcoming fiscal year. 
We also assigned the statewide average CCR (for the upcoming fiscal 
year) to those providers that have no value in the CCR field in the PSF 
or whose CCRs exceed the ceilings described later in this section (3.0 
standard deviations from the mean of the log distribution of CCRs for 
all hospitals). We did not apply the adjustment factors described below 
to hospitals assigned the statewide average CCR. For FY 2022, we also 
are continuing to apply an adjustment factor to the CCRs to account for 
cost and charge inflation (as explained below).
    For this final rule, similar to the approach since FY 2014, we 
adjusted the CCRs from the March 2020 update of the PSF by comparing 
the percentage change in the national average case-weighted operating 
CCR and capital CCR from the March 2019 update of the PSF to the 
national average case-weighted operating CCR and capital CCR from the 
March 2020 update of the PSF. We note that we used total transfer-
adjusted cases from FY 2019 to determine the national average case 
weighted CCRs for both sides of the comparison. As stated in the FY 
2014 IPPS/LTCH PPS final rule (78 FR 50979), we believe that it is 
appropriate to use the same case count on both sides of the comparison 
because this will produce the true percentage change in the average 
case-weighted operating and capital CCR from one year to the next 
without any effect from a change in case count on different sides of 
the comparison.
    Using the methodology described previously, for this final rule, we 
calculated a March 2019 operating national average case-weighted CCR of 
0.254027 and a March 2020 operating national average case weighted CCR 
of 0.247548. We then calculated the percentage change between the two 
national operating case-weighted CCRs by subtracting the March 2019 
operating national average case-weighted CCR from the March 2020 
operating national average case-weighted CCR and then dividing the 
result by the March 2019 national operating average case-weighted CCR. 
This resulted in a national operating CCR adjustment factor of 
0.974495. As we proposed, because we are using CCRs from the March 2020 
update of the PSF for FY 2022, we calculated a two-year proposed 
national operating CCR adjustment by multiplying 0.974495 * 0.974495.
    We used the same methodology to adjust the capital CCRs. 
Specifically, for this final rule, we calculated a March 2019 capital 
national average case-weighted CCR of 0.02073 and a March 2020 capital 
national average case-weighted CCR of 0.019935. We then calculated the 
percentage change between the two national capital case weighted CCRs 
by subtracting the March 2019 capital national average case-weighted 
CCR from the March 2020 capital national average case-weighted CCR and 
then dividing the result by the March 2019 capital national average 
case-weighted CCR. This resulted in a national capital CCR adjustment 
factor of 0.96165. As we proposed, because we are using CCRs from the 
March 2020 update of the PSF for FY 2022, we calculated a two-year 
proposed national capital CCR adjustment by multiplying 0.96165 * 
0.96165.
    As discussed previously, consistent with the proposed rule, for FY 
2022, we applied the following policies (as discussed in more detail 
earlier):
     We used a wage index based on the FY 2022 wage index that 
hospitals will be paid. This included our policy to remove urban to 
rural reclassifications from the calculation of the rural floor, 
applying the imputed floor adjustment, the frontier State floor 
adjustment in accordance with section 10324(a) of the Affordable Care 
Act, and the out migration adjustment as added by section 505 of Public 
Law 108-173, and incorporates our wage index policies to: (1) Increase 
the wage index values for hospitals with a wage index value below the 
25th percentile wage index value across all hospitals, and (2) apply a 
5 percent cap for FY 2022 for a hospital that was eligible for the 5 
percent cap in FY 2021 and who had an additional 5 percent decrease in 
the hospital's final FY 2022 wage index from the hospital's final wage 
index in FY 2021. As stated previously, if we did not take the above 
into account, our estimate of total FY 2022 payments would be too low, 
and, as a result, our outlier threshold would be too high, such that 
estimated outlier payments would be less than our projected 5.12 
percent of total payments (which reflects the estimate of outlier 
reconciliation calculated for this final rule).
     We excluded the hospital VBP payment adjustments and the 
hospital readmissions payment adjustments from the calculation of the 
outlier fixed-loss cost threshold.
     We used the estimated per-discharge uncompensated care 
payments to hospitals eligible for the uncompensated care payment for 
all cases in the calculation of the outlier fixed-loss cost threshold 
methodology.
    Using this methodology, we used the formula described in section 
I.C.1 of this Addendum to simulate and calculate the Federal payment 
rate and outlier payments for all claims. In addition, as described in 
the earlier section to this Addendum, we are finalizing to incorporate 
an estimate of FY 2022 outlier reconciliation in the methodology for 
determining the outlier threshold. As noted previously, for this FY 
2022 final rule, the ratio of outlier reconciliation dollars to total 
Federal Payments (Step 4) is a negative 0.021957 percent, which, when 
rounded to the second digit, is 0.02 percent. Therefore, for FY 2022, 
we incorporated a projection of outlier reconciliation dollars by 
targeting an outlier threshold at 5.12 percent [5.1 percent - (0.02 
percent)]. Under this approach, we determined a threshold of $30,988 
and calculated total outlier payments of $ 5,326,356,951 and total 
operating

[[Page 45543]]

Federal payments of $ 100,164,666,975. We then divided total outlier 
payments by total operating Federal payments plus total outlier 
payments and determined that this threshold matched with the 5.12 
percent target, which reflects our methodology to incorporate an 
estimate of outlier reconciliation in the determination of the outlier 
threshold (as discussed in more detail in the previous section of this 
Addendum). We note that, if calculated without applying our finalized 
methodology for incorporating an estimate of outlier reconciliation in 
the determination of the outlier threshold, the threshold would have 
been $31,108. We are finalizing an outlier fixed-loss cost threshold 
for FY 2022 equal to the prospective payment rate for the MS-DRG, plus 
any IME, empirically justified Medicare DSH payments, estimated 
uncompensated care payment, and any addon payments for new technology, 
plus $30,988.
    Comment: A commenter stated that the COVID-19 PHE increased case 
acuity and payments increased due to the suspension of the 2% 
sequestration. Therefore, the commenter recommended that payments 
should be adjusted from the FY 2022 estimated outlier threshold because 
of the temporal nature of these additional payments.
    Response: We appreciate the commenter's input. The sequestration 
reduction is a 2-percent reduction to overall payments and is applied 
after calculating individual payments such as outlier payments. 
Therefore, CMS has not made any adjustments that consider the 2-percent 
reduction in our modeling of outlier payments. As a result, no change 
to the outlier model for FY 2022 is necessary. With regard to the 
commenter noting the increased case acuity, we refer the reader to 
section I.F. of this FY 2022 IPPS/LTCH final rule for a discussion of 
our final policy to use FY 2019 claims in our FY 2022 ratesetting, 
which applies to modeling of the outlier threshold.
(3) Other Changes Concerning Outliers
    As stated in the FY 1994 IPPS final rule (58 FR 46348), we 
establish an outlier threshold that is applicable to both hospital 
inpatient operating costs and hospital inpatient capital-related costs. 
When we modeled the combined operating and capital outlier payments, we 
found that using a common threshold resulted in a higher percentage of 
outlier payments for capital-related costs than for operating costs. We 
project that the threshold for FY 2022 (which reflects our methodology 
to incorporate an estimate of operating outlier reconciliation) will 
result in outlier payments that would equal 5.1 percent of operating 
DRG payments and we estimate that capital outlier payments would equal 
5.31 percent of capital payments based on the Federal rate (which 
reflects our methodology discussed previously to incorporate an 
estimate of capital outlier reconciliation).
    In accordance with section 1886(d)(3)(B) of the Act and as 
discussed previously, we are reducing the FY 2022 standardized amount 
by 5.1 percent to account for the projected proportion of payments paid 
as outliers.
    The outlier adjustment factors that would be applied to the 
operating standardized amount and capital Federal rate based on the FY 
2022 outlier threshold are as follows:
[GRAPHIC] [TIFF OMITTED] TR13AU21.324

    We are applying the outlier adjustment factors to the FY 2022 
payment rates after removing the effects of the FY 2020 outlier 
adjustment factors on the standardized amount.
    To determine whether a case qualifies for outlier payments, we 
currently apply hospital-specific CCRs to the total covered charges for 
the case. Estimated operating and capital costs for the case are 
calculated separately by applying separate operating and capital CCRs. 
These costs are then combined and compared with the outlier fixed-loss 
cost threshold.
    Under our current policy at Sec.  412.84, we calculate operating 
and capital CCR ceilings and assign a statewide average CCR for 
hospitals whose CCRs exceed 3.0 standard deviations from the mean of 
the log distribution of CCRs for all hospitals. Based on this 
calculation, for hospitals for which the MAC computes operating CCRs 
greater than 1.142 or capital CCRs greater than 0.135, or hospitals for 
which the MAC is unable to calculate a CCR (as described under Sec.  
412.84(i)(3) of our regulations), statewide average CCRs are used to 
determine whether a hospital qualifies for outlier payments. Table 8A 
listed in section VI. of this Addendum (and available via the internet 
on the CMS website) contains the statewide average operating CCRs for 
urban hospitals and for rural hospitals for which the MAC is unable to 
compute a hospital-specific CCR within the range previously specified. 
These statewide average ratios would be effective for discharges 
occurring on or after October 1, 2021 and would replace the statewide 
average ratios from the prior fiscal year. Table 8B listed in section 
VI. of this Addendum (and available via the internet on the CMS 
website) contains the comparable statewide average capital CCRs. As 
previously stated, the CCRs in Tables 8A and 8B would be used during FY 
2022 when hospital-specific CCRs based on the latest settled cost 
report either are not available or are outside the range noted 
previously. Table 8C listed in section VI. of this Addendum (and 
available via the internet on the CMS website) contains the statewide 
average total CCRs used under the LTCH PPS as discussed in section V. 
of this Addendum.
    We finally note that section 20.1.2 of chapter three of the 
Medicare Claims Processing Manual (on the internet at https://www.cms.gov/Regulations-and-Guidance/Guidance/Manuals/Downloads/clm104c03.pdf) covers an array of topics, including CCRs, 
reconciliation, and the time value of money. We encourage hospitals 
that are assigned the statewide average operating and/or capital CCRs 
to work with their MAC on a possible alternative operating and/or 
capital CCR as explained in the manual. Use of an alternative CCR 
developed by the hospital in conjunction with the MAC can avoid 
possible overpayments or underpayments at cost report settlement, 
thereby ensuring better accuracy when making outlier payments and 
negating the need for outlier reconciliation. We also note that a 
hospital may request an alternative operating or capital CCR at any 
time as long as the guidelines of the manual are followed. In addition, 
the manual outlines the outlier reconciliation

[[Page 45544]]

process for hospitals and Medicare contractors. We refer hospitals to 
the manual instructions for complete details on outlier reconciliation.
(4) FY 2020 Outlier Payments
    Our current estimate, using available FY 2020 claims data, is that 
actual outlier payments for FY 2020 were approximately 5.47 percent of 
actual total MS-DRG payments. Therefore, the data indicate that, for FY 
2020, the percentage of actual outlier payments relative to actual 
total payments is higher than we projected for FY 2020. Consistent with 
the policy and statutory interpretation we have maintained since the 
inception of the IPPS, we do not make retroactive adjustments to 
outlier payments to ensure that total outlier payments for FY 2020 are 
equal to 5.1 percent of total MS-DRG payments. As explained in the FY 
2003 Outlier Final Rule (68 FR 34502), if we were to make retroactive 
adjustments to all outlier payments to ensure total payments are 5.1 
percent of MS-DRG payments (by retroactively adjusting outlier 
payments), we would be removing the important aspect of the prospective 
nature of the IPPS. Because such an across-the-board adjustment would 
either lead to more or less outlier payments for all hospitals, 
hospitals would no longer be able to reliably approximate their payment 
for a patient while the patient is still hospitalized. We believe it 
would be neither necessary nor appropriate to make such an aggregate 
retroactive adjustment. Furthermore, we believe it is consistent with 
the statutory language at section 1886(d)(5)(A)(iv) of the Act not to 
make retroactive adjustments to outlier payments. This section states 
that outlier payments be equal to or greater than 5 percent and less 
than or equal to 6 percent of projected or estimated (not actual) MS-
DRG payments. We believe that an important goal of a PPS is 
predictability. Therefore, we believe that the fixed-loss outlier 
threshold should be projected based on the best available historical 
data and should not be adjusted retroactively. A retroactive change to 
the fixed-loss outlier threshold would affect all hospitals subject to 
the IPPS, thereby undercutting the predictability of the system as a 
whole.
    We note that, because the MedPAR claims data for the entire FY 2021 
period would not be available until after September 30, 2021, we are 
unable to provide an estimate of actual outlier payments for FY 2021 
based on FY 2021 claims data in this final rule. We will provide an 
estimate of actual FY 2021 outlier payments in the FY 2023 IPPS/LTCH 
PPS proposed rule.
5. FY 2022 Standardized Amount
    The adjusted standardized amount is divided into labor-related and 
nonlabor-related portions. Tables 1A and 1B listed and published in 
section VI. of this Addendum (and available via the internet on the CMS 
website) contain the national standardized amounts that we are applying 
to all hospitals, except hospitals located in Puerto Rico, for FY 2022. 
The standardized amount for hospitals in Puerto Rico is shown in Table 
1C listed and published in section VI. of this Addendum (and available 
via the internet on the CMS website). The amounts shown in Tables 1A 
and 1B differ only in that the labor-related share applied to the 
standardized amounts in Table 1A is 67.6 percent, and the labor-related 
share applied to the standardized amounts in Table 1B is 62 percent. In 
accordance with sections 1886(d)(3)(E) and 1886(d)(9)(C)(iv) of the 
Act, we are applying a labor-related share of 62 percent, unless 
application of that percentage would result in lower payments to a 
hospital than would otherwise be made. In effect, the statutory 
provision means that we would apply a labor-related share of 62 percent 
for all hospitals whose wage indexes are less than or equal to 1.0000.
    In addition, Tables 1A and 1B include the standardized amounts 
reflecting the applicable percentage increases for FY 2022.
    The labor-related and nonlabor-related portions of the national 
average standardized amounts for Puerto Rico hospitals for FY 2022 are 
set forth in Table 1C listed and published in section VI. of this 
Addendum (and available via the internet on the CMS website). 
Similarly, section 1886(d)(9)(C)(iv) of the Act, as amended by section 
403(b) of Public Law 108-173, provides that the labor-related share for 
hospitals located in Puerto Rico be 62 percent, unless the application 
of that percentage would result in lower payments to the hospital.
    The following table illustrates the changes from the FY 2021 
national standardized amounts to the FY 2022 national standardized 
amounts. The second through fifth columns display the changes from the 
FY 2021 standardized amounts for each applicable FY 2022 standardized 
amount. The first row of the table shows the updated (through FY 2021) 
average standardized amount after restoring the FY 2021 offsets for 
outlier payments, geographic reclassification, rural demonstration, 
lowest quartile, and transition budget neutrality. The MS-DRG 
reclassification and recalibration, wage index, and stem cell 
acquisition budget neutrality factors are cumulative. Accordingly, 
those FY 2021 adjustment factors have not been removed from the base 
rate in the following table. Additionally, for FY 2022 we have applied 
the budget neutrality factors for the lowest quartile hospital policy, 
described previously.
BILLING CODE 4120-01-P

[[Page 45545]]

[GRAPHIC] [TIFF OMITTED] TR13AU21.325


[[Page 45546]]


BILLING CODE 4120-01-C

B. Adjustments for Area Wage Levels and Cost-of-Living

    Tables 1A through 1C, as published in section VI. of this Addendum 
(and available via the internet on the CMS website), contain the labor-
related and nonlabor-related shares that we are using to calculate the 
prospective payment rates for hospitals located in the 50 States, the 
District of Columbia, and Puerto Rico for FY 2022. This section 
addresses two types of adjustments to the standardized amounts that are 
made in determining the prospective payment rates as described in this 
Addendum.
1. Adjustment for Area Wage Levels
    Sections 1886(d)(3)(E) and 1886(d)(9)(C)(iv) of the Act require 
that we make an adjustment to the labor-related portion of the national 
prospective payment rate to account for area differences in hospital 
wage levels. This adjustment is made by multiplying the labor-related 
portion of the adjusted standardized amounts by the appropriate wage 
index for the area in which the hospital is located. For FY 2022, as 
discussed in section IV.B.3. of the preamble of this final rule, we are 
applying a labor-related share of 67.6 percent for the national 
standardized amounts for all IPPS hospitals (including hospitals in 
Puerto Rico) that have a wage index value that is greater than 1.0000. 
Consistent with section 1886(d)(3)(E) of the Act, we are applying the 
wage index to a labor-related share of 62 percent of the national 
standardized amount for all IPPS hospitals (including hospitals in 
Puerto Rico) whose wage index values are less than or equal to 1.0000. 
In section III. of the preamble of this final rule, we discussed the 
data and methodology for the FY 2022 wage index.
2. Adjustment for Cost-of-Living in Alaska and Hawaii
    Section 1886(d)(5)(H) of the Act provides discretionary authority 
to the Secretary to make adjustments as the Secretary deems appropriate 
to take into account the unique circumstances of hospitals located in 
Alaska and Hawaii. Higher labor-related costs for these two States are 
taken into account in the adjustment for area wages described 
previously. To account for higher nonlabor-related costs for these two 
States, we multiply the nonlabor-related portion of the standardized 
amount for hospitals in Alaska and Hawaii by an adjustment factor. For 
FY 2011 and in prior fiscal years, we used the most recent cost-of-
living adjustment (COLA) factors obtained from the U.S. Office of 
Personnel Management (OPM) website at https://www.opm.gov/policy-data-oversight/pay-leave/pay-systems/nonforeign-areas/#url=COLA-Rates to 
update this nonlabor portion.
    In the FY 2012 IPPS/LTCH PPS final rule (76 FR 51797), we explained 
that sections 1911 through 1919 of the Nonforeign Area Retirement 
Equity Assurance Act, as contained in subtitle B of title XIX of the 
National Defense Authorization Act (NDAA) for Fiscal Year 2010 (Pub. L. 
111-84, October 28, 2009), transitions the Alaska and Hawaii COLAs to 
locality pay. We finalized that, for FY 2012, as OPM transitioned away 
from COLAs, we would continue to use the same ``frozen'' COLA factors 
(published by OPM) that we used to adjust payments in FY 2011 (which 
were based on OPM's 2009 COLA factors) to adjust the nonlabor-related 
portion of the standardized amount for hospitals located in Alaska and 
Hawaii. We refer readers to the FY 2012 IPPS/LTCH PPS final rule for a 
more detailed discussion of our rationale for continuing to use the 
frozen COLAs in FY 2012.
    In the FY 2013 IPPS/LTCH PPS final rule (77 FR 53700 and 53701), 
for FY 2013, we continued to use the same COLA factors that were used 
to adjust payments in FY 2012 (as originally used to adjust payments in 
FY 2011, which were based on OPM's 2009 COLA factors). We also 
established a methodology to update the COLA factors published by OPM 
every 4 years (at the same time as the update of the labor-related 
share of the IPPS market basket), beginning in FY 2014. We refer 
readers to the FY 2013 IPPS/LTCH PPS proposed rule (77 FR 28145 and 
28146) for a detailed description of this methodology. For FY 2014, we 
updated the COLA factors for Alaska and Hawaii published by OPM for 
2009 using the methodology finalized in the FY 2013 IPPS/LTCH PPS final 
rule (77 FR 53700 and 53701). In the FY 2018 IPPS/LTCH PPS final rule, 
we again updated the COLA factors using this same methodology (82 FR 
38530).
    For FY 2022, we are updating the COLA factors published by OPM for 
2009 (as these are the last COLA factors OPM published prior to 
transitioning from COLAs to locality pay) using the methodology that we 
finalized in the FY 2013 IPPS/LTCH PPS final rule. Specifically, we are 
updating the 2009 OPM COLA factors by a comparison of the growth in the 
Consumer Price Indices (CPIs) for the areas of Urban Alaska and Urban 
Hawaii, relative to the growth in the CPI for the average U.S. city as 
published by the Bureau of Labor Statistics (BLS). We note that for the 
prior update to the COLA factors, we used the growth in the CPI for 
Anchorage and the CPI for Honolulu. Beginning in 2018, these indexes 
were renamed to the CPI for Urban Alaska and the CPI for Urban Hawaii 
due to the BLS updating its sample to reflect the data from the 2010 
Decennial Census on the distribution of the urban population (https://www.bls.gov/regions/west/factsheet/2018cpirevisionwest.pdf, accessed 
January 22, 2021). The CPI for Urban Alaska area covers Anchorage and 
Matanuska-Susitna Borough in the State of Alaska and the CPI for Urban 
Hawaii covers Honolulu in the State of Hawaii. BLS notes that the 
indexes are considered continuous over time, regardless of name or 
composition changes.
    Because BLS publishes CPI data for only Urban Alaska and Urban 
Hawaii, using the methodology we finalized in the FY 2013 IPPS/LTCH PPS 
final rule, we are using the comparison of the growth in the overall 
CPI relative to the growth in the CPI for those areas to update the 
COLA factors for all areas in Alaska and Hawaii, respectively. We 
believe that the relative price differences between these urban areas 
and the United States (as measured by the CPIs mentioned previously) 
are appropriate proxies for the relative price differences between the 
``other areas'' of Alaska and Hawaii and the United States.
    BLS publishes the CPI for All Items for Urban Alaska, Urban Hawaii, 
and for the average U.S. city. However, consistent with our methodology 
finalized in the FY 2013 IPPS/LTCH PPS final rule, we are creating 
reweighted CPIs for each of the respective areas to reflect the 
underlying composition of the IPPS market basket nonlabor-related 
share. The current composition of the CPI for All Items for all of the 
respective areas is approximately 40 percent commodities and 60 percent 
services. However, the IPPS nonlabor-related share for the 2018-based 
IPPS market basket is comprised of a different mix of commodities and 
services. Therefore, we are creating reweighted indexes for Urban 
Alaska, Urban Hawaii, and the average U.S. city using the respective 
CPI commodities index and CPI services index and using the approximate 
57 percent commodities/43 percent services shares obtained from the 
2018-based IPPS market basket. We created reweighted indexes using BLS 
data for 2009 through 2020--the most recent data available at the time 
of this final rulemaking. In the FY 2018 IPPS/LTCH PPS final rule (82 
FR 38530), we created

[[Page 45547]]

reweighted indexes based on the 2014-based IPPS market basket (which 
was adopted for the FY 2018 IPPS update) and BLS data for 2009 through 
2016 (the most recent BLS data at the time of the FY 2018 IPPS/LTCH PPS 
rulemaking).
    We continue to believe this methodology is appropriate because we 
continue to make a COLA for hospitals located in Alaska and Hawaii by 
multiplying the nonlabor-related portion of the standardized amount by 
a COLA factor. We note that OPM's COLA factors were calculated with a 
statutorily mandated cap of 25 percent. As stated in the FY 2018 IPPS/
LTCH PPS final rule ((82 FR 38530), under the COLA update methodology 
we finalized in the FY 2013 IPPS/LTCH PPS final rule, we exercised our 
discretionary authority to adjust payments to hospitals in Alaska and 
Hawaii by incorporating this cap. In applying this finalized 
methodology for updating the COLA factors, we are continuing to use a 
cap of 25 percent, as our policy is based on OPM's COLA factors 
(updated by the methodology described previously).
    Applying this methodology, the COLA factors that we are 
establishing effective for FY 2022 to adjust the nonlabor-related 
portion of the standardized amount for hospitals located in Alaska and 
Hawaii are shown in the table in this section. For comparison purposes, 
we also are showing the COLA factors effective FY 2018 to FY 2021. We 
note that the COLA factors effective for FY 2022 for City and County of 
Honolulu, County of Kauai, and County of Maui and County of Kalawao are 
a result of applying the 25 percent cap as described previously.
    Lastly, as we finalized in the FY 2013 IPPS/LTCH PPS final rule (77 
FR 53700 and 53701), we intend to update the COLA factors based on our 
methodology every 4 years, at the same time as the update to the labor-
related share of the IPPS market basket.
[GRAPHIC] [TIFF OMITTED] TR13AU21.326

    We received no comments in response to our discussion of the 
proposed FY 2022 COLA factors and therefore are finalizing the COLA 
factors as proposed, effective for FY 2022 .

C. Calculation of the Prospective Payment Rates

1. General Formula for Calculation of the Prospective Payment Rates for 
FY 2022
    In general, the operating prospective payment rate for all 
hospitals (including hospitals in Puerto Rico) paid under the IPPS, 
except SCHs and MDHs, for FY 2022 equals the Federal rate (which 
includes uncompensated care payments).
    Under current law, the MDH program has been extended for discharges 
occurring through September 30, 2022.
    SCHs are paid based on whichever of the following rates yields the 
greatest aggregate payment: The Federal national rate (which, as 
discussed in section VI.G. of the preamble of this final rule, includes 
uncompensated care payments); the updated hospital-specific rate based 
on FY 1982 costs per discharge; the updated hospital-specific rate 
based on FY 1987 costs per discharge; the updated hospital-specific 
rate based on FY 1996 costs per discharge; or the updated hospital-
specific rate based on FY 2006 costs per discharge to determine the 
rate that yields the greatest aggregate payment.
    The prospective payment rate for SCHs for FY 2022 equals the higher 
of the applicable Federal rate, or the hospital-specific rate as 
described later in this section. The prospective payment rate for MDHs 
for FY 2022 equals the higher of the Federal rate, or the Federal rate 
plus 75 percent of the difference between the Federal rate and the 
hospital-specific rate as described in this section. For MDHs, the 
updated hospital-specific rate is based on FY 1982, FY 1987, or FY 2002 
costs per discharge, whichever yields the greatest aggregate payment.
2. Operating and Capital Federal Payment Rate and Outlier Payment 
Calculation
    Note: The formula specified in this section is used for actual 
claim payment and is also used by CMS to project the outlier threshold 
for the upcoming fiscal year. The difference is the source of some of 
the variables in the formula. For example, operating and capital CCRs 
for actual claim payment are from the PSF while CMS uses an adjusted 
CCR (as described previously) to project the threshold for the upcoming 
fiscal year. In addition, charges for a claim payment are from the bill 
while charges to project the threshold are from the MedPAR data with an 
inflation factor applied to the charges (as described earlier).
    Step 1--Determine the MS-DRG and MS-DRG relative weight (from Table 
5) for each claim based on the ICD-10-CM diagnosis and ICD-10-PCS 
procedure codes on the claim.
    Step 2--Select the applicable average standardized amount depending 
on

[[Page 45548]]

whether the hospital submitted qualifying quality data and is a 
meaningful EHR user, as described previously.
    Step 3--Compute the operating and capital Federal payment rate:

--Federal Payment Rate for Operating Costs = MS-DRG Relative Weight x 
[(Labor-Related Applicable Standardized Amount x Applicable CBSA Wage 
Index) + (Nonlabor-Related Applicable Standardized Amount x Cost-of-
Living Adjustment)] x (1 + IME + (DSH * 0.25))
--Federal Payment for Capital Costs = MS-DRG Relative Weight x Federal 
Capital Rate x Geographic Adjustment Fact x (l + IME + DSH)

    Step 4--Determine operating and capital costs:

--Operating Costs = (Billed Charges x Operating CCR)
--Capital Costs = (Billed Charges x Capital CCR).

    Step 5--Compute operating and capital outlier threshold (CMS 
applies a geographic adjustment to the operating and capital outlier 
threshold to account for local cost variation):

-- Operating CCR to Total CCR = (Operating CCR)/(Operating CCR + 
Capital CCR)
--Operating Outlier Threshold = [Fixed Loss Threshold x ((Labor-Related 
Portion x CBSA Wage Index) + Nonlabor-Related portion)] x Operating CCR 
to Total CCR + Federal Payment with IME, DSH + Uncompensated Care 
Payment + New Technology Add-On Payment Amount
--Capital CCR to Total CCR = (Capital CCR)/(Operating CCR + Capital 
CCR)
--Capital Outlier Threshold = (Fixed Loss Threshold x Geographic 
Adjustment Factor x Capital CCR to Total CCR) + Federal Payment with 
IME and DSH

    Step 6--Compute operating and capital outlier payments:

--Marginal Cost Factor = 0.80 or 0.90 (depending on the MS-DRG)
--Operating Outlier Payment = (Operating Costs - Operating Outlier 
Threshold) x Marginal Cost Factor
--Capital Outlier Payment = (Capital Costs - Capital Outlier Threshold) 
x Marginal Cost Factor

    The payment rate may then be further adjusted for hospitals that 
qualify for a low-volume payment adjustment under section 1886(d)(12) 
of the Act and 42 CFR 412.101(b). The base-operating DRG payment amount 
may be further adjusted by the hospital readmissions payment adjustment 
and the hospital VBP payment adjustment as described under sections 
1886(q) and 1886(o) of the Act, respectively. Payments also may be 
reduced by the 1-percent adjustment under the HAC Reduction Program as 
described in section 1886(p) of the Act. We also make new technology 
add-on payments in accordance with section 1886(d)(5)(K) and (L) of the 
Act. Finally, we add the uncompensated care payment to the total claim 
payment amount. As noted in the previous formula, we take uncompensated 
care payments and new technology add-on payments into consideration 
when calculating outlier payments.
3. Hospital-Specific Rate (Applicable Only to SCHs and MDHs)
a. Calculation of Hospital-Specific Rate
    Section 1886(b)(3)(C) of the Act provides that SCHs are paid based 
on whichever of the following rates yields the greatest aggregate 
payment: The Federal rate; the updated hospital-specific rate based on 
FY 1982 costs per discharge; the updated hospital-specific rate based 
on FY 1987 costs per discharge; the updated hospital-specific rate 
based on FY 1996 costs per discharge; or the updated hospital-specific 
rate based on FY 2006 costs per discharge to determine the rate that 
yields the greatest aggregate payment.
    As noted previously, the MDH program has been extended under 
current law for discharges occurring through September 30, 2022. For 
MDHs, the updated hospital-specific rate is based on FY 1982, FY 1987, 
or FY 2002 costs per discharge, whichever yields the greatest aggregate 
payment.
    For a more detailed discussion of the calculation of the hospital-
specific rates, we refer readers to the FY 1984 IPPS interim final rule 
(48 FR 39772); the April 20, 1990 final rule with comment period (55 FR 
15150); the FY 1991 IPPS final rule (55 FR 35994); and the FY 2001 IPPS 
final rule (65 FR 47082).
b. Updating the FY 1982, FY 1987, FY 1996, FY 2002 and FY 2006 
Hospital-Specific Rate for FY 2022
    Section 1886(b)(3)(B)(iv) of the Act provides that the applicable 
percentage increase applicable to the hospital-specific rates for SCHs 
and MDHs equals the applicable percentage increase set forth in section 
1886(b)(3)(B)(i) of the Act (that is, the same update factor as for all 
other hospitals subject to the IPPS). Because the Act sets the update 
factor for SCHs and MDHs equal to the update factor for all other IPPS 
hospitals, the update to the hospital-specific rates for SCHs and MDHs 
is subject to the amendments to section 1886(b)(3)(B) of the Act made 
by sections 3401(a) and 10319(a) of the Affordable Care Act. 
Accordingly, the applicable percentage increases to the hospital-
specific rates applicable to SCHs and MDHs are the following:
[GRAPHIC] [TIFF OMITTED] TR13AU21.327


[[Page 45549]]


    For a complete discussion of the applicable percentage increase 
applied to the hospital-specific rates for SCHs and MDHs, we refer 
readers to section V.B. of the preamble of this final rule.
    In addition, because SCHs and MDHs use the same MS-DRGs as other 
hospitals when they are paid based in whole or in part on the hospital-
specific rate, the hospital-specific rate is adjusted by a budget 
neutrality factor to ensure that changes to the MS-DRG classifications 
and the recalibration of the MS-DRG relative weights are made in a 
manner so that aggregate IPPS payments are unaffected. Therefore, the 
hospital specific-rate for an SCH or an MDH is adjusted by the MS-DRG 
reclassification and recalibration budget neutrality factor, as 
discussed in section III. of this Addendum and listed in the table in 
section II. of this Addendum. The resulting rate is used in determining 
the payment rate that an SCH or MDH will receive for its discharges 
beginning on or after October 1, 2021. We note that, in this final 
rule, for FY 2022, we are not making a documentation and coding 
adjustment to the hospital specific-rate. We refer readers to section 
II.D. of the preamble of this final rule for a complete discussion 
regarding our policies and previously finalized policies (including our 
historical adjustments to the payment rates) relating to the effect of 
changes in documentation and coding that do not reflect real changes in 
case mix.

III. Changes to Payment Rates for Acute Care Hospital Inpatient 
Capital-Related Costs for FY 2022

    The PPS for acute care hospital inpatient capital-related costs was 
implemented for cost reporting periods beginning on or after October 1, 
1991. The basic methodology for determining Federal capital prospective 
rates is set forth in the regulations at 42 CFR 412.308 through 
412.352. In this section of this Addendum, we discuss the factors that 
we used to determine the capital Federal rate for FY 2022, which would 
be effective for discharges occurring on or after October 1, 2021.
    All hospitals (except ``new'' hospitals under Sec.  412.304(c)(2)) 
are paid based on the capital Federal rate. We annually update the 
capital standard Federal rate, as provided in Sec.  412.308(c)(1), to 
account for capital input price increases and other factors. The 
regulations at Sec.  412.308(c)(2) also provide that the capital 
Federal rate be adjusted annually by a factor equal to the estimated 
proportion of outlier payments under the capital Federal rate to total 
capital payments under the capital Federal rate. In addition, Sec.  
412.308(c)(3) requires that the capital Federal rate be reduced by an 
adjustment factor equal to the estimated proportion of payments for 
exceptions under Sec.  412.348. (We note that, as discussed in the FY 
2013 IPPS/LTCH PPS final rule (77 FR 53705), there is generally no 
longer a need for an exceptions payment adjustment factor.) However, in 
limited circumstances, an additional payment exception for 
extraordinary circumstances is provided for under Sec.  412.348(f) for 
qualifying hospitals. Therefore, in accordance with Sec.  
412.308(c)(3), an exceptions payment adjustment factor may need to be 
applied if such payments are made. Section 412.308(c)(4)(ii) requires 
that the capital standard Federal rate be adjusted so that the effects 
of the annual DRG reclassification and the recalibration of DRG weights 
and changes in the geographic adjustment factor (GAF) are budget 
neutral.
    Section 412.374 provides for payments to hospitals located in 
Puerto Rico under the IPPS for acute care hospital inpatient capital-
related costs, which currently specifies capital IPPS payments to 
hospitals located in Puerto Rico are based on 100 percent of the 
Federal rate.

A. Determination of the Federal Hospital Inpatient Capital-Related 
Prospective Payment Rate Update for FY 2022

    In the discussion that follows, we explain the factors that we used 
to determine the capital Federal rate for FY 2022. In particular, we 
explain why the FY 2022 capital Federal rate would increase 
approximately 1.37 percent, compared to the FY 2021 capital Federal 
rate. As discussed in the impact analysis in Appendix A to this FY 2022 
IPPS/LTCH PPS final rule, we estimate that capital payments per 
discharge will increase approximately 0.9 percent during that same 
period. Because capital payments constitute approximately 10 percent of 
hospital payments, a 1-percent change in the capital Federal rate 
yields only approximately a 0.1 percent change in actual payments to 
hospitals.
    As discussed in section I.F. of the preamble to this final rule, we 
are finalizing our proposal to use FY 2019 data for the FY 2022 
ratesetting in situations where the FY 2020 data were significantly 
impacted by the COVID-19 PHE. Ordinarily, for this final rule, we would 
use claims from the FY 2020 MedPAR file for purposes of calculating the 
budget neutrality adjustment factors for changes resulting from the 
annual DRG reclassification and recalibration and changes in the GAF. 
However, as discussed in section I.F. of the preamble to this final 
rule, we believe the FY 2020 claims data were significantly impacted by 
the COVID-19 PHE. Therefore, for the purposes of calculating these 
budget neutrality adjustment factors for FY 2022, we used claims from 
the March 2020 update of the FY 2019 MedPAR file. Similarly, for this 
final rule, we ordinarily would use provider data from the March 2021 
update of the Provider Specific File (PSF) for purposes of calculating 
these budget neutrality adjustment factors. However, for some IPPS 
hospitals, the provider data in the March 2021 update of the PSF may 
have come from cost reports that ended during the COVID-19 PHE, and 
therefore we believe these data may be affected by the PHE. Therefore, 
for the purposes of calculating these budget neutrality adjustment 
factors for FY 2022, as proposed, we used provider data from the March 
2020 update of the PSF, which was derived from cost reports ending 
prior to the COVID-19 PHE, except for those fields on the PSF not 
affected by the PHE.
1. Projected Capital Standard Federal Rate Update
    Under Sec.  412.308(c)(1), the capital standard Federal rate is 
updated on the basis of an analytical framework that takes into account 
changes in a capital input price index (CIPI) and several other policy 
adjustment factors. Specifically, we adjust the projected CIPI rate of 
change, as appropriate, each year for case-mix index-related changes, 
for intensity, and for errors in previous CIPI forecasts. The update 
factor for FY 2022 under that framework is 0.8 percent based on a 
projected 1.1 percent increase in the 2018-based CIPI, a 0.0 percentage 
point adjustment for intensity, a 0.0 percentage point adjustment for 
case-mix, a 0.0 percentage point adjustment for the DRG 
reclassification and recalibration, and a forecast error correction of 
-0.3 percentage point. As discussed in section III.C. of this Addendum, 
we continue to believe that the CIPI is the most appropriate input 
price index for capital costs to measure capital price changes in a 
given year. We also explain the basis for the FY 2022 CIPI projection 
in that same section of this Addendum. In this final rule, we describe 
the policy adjustments that we applied in the update framework for FY 
2022.
    The case-mix index is the measure of the average DRG weight for 
cases paid under the IPPS. Because the DRG weight determines the 
prospective payment for each case, any percentage increase in the case-
mix index corresponds to an

[[Page 45550]]

equal percentage increase in hospital payments.
    The case-mix index can change for any of several reasons--
     The average resource use of Medicare patient changes 
(``real'' case-mix change);
     Changes in hospital documentation and coding of patient 
records result in higher-weighted DRG assignments (``coding effects''); 
or
     The annual DRG reclassification and recalibration changes 
may not be budget neutral (``reclassification effect'').
    We define real case-mix change as actual changes in the mix (and 
resource requirements) of Medicare patients, as opposed to changes in 
documentation and coding behavior that result in assignment of cases to 
higher-weighted DRGs, but do not reflect higher resource requirements. 
The capital update framework includes the same case-mix index 
adjustment used in the former operating IPPS update framework (as 
discussed in the May 18, 2004 IPPS proposed rule for FY 2005 (69 FR 
28816)). (We no longer use an update framework to make a recommendation 
for updating the operating IPPS standardized amounts, as discussed in 
section II. of Appendix B to the FY 2006 IPPS final rule (70 FR 
47707).)
    For FY 2022, we projected a 0.5 percent total increase in the case-
mix index. We estimated that the real case-mix increase will equal 0.5 
percent for FY 2022. The net adjustment for change in case-mix is the 
difference between the projected real increases in case mix and the 
projected total increase in case mix. Therefore, the net adjustment for 
case-mix change in FY 2022 is 0.0 percentage point.
    The capital update framework also contains an adjustment for the 
effects of DRG reclassification and recalibration. This adjustment is 
intended to remove the effect on total payments of prior year's changes 
to the DRG classifications and relative weights, in order to retain 
budget neutrality for all case-mix index-related changes other than 
those due to patient severity of illness. Due to the lag time in the 
availability of data, there is a 2-year lag in data used to determine 
the adjustment for the effects of DRG reclassification and 
recalibration. For example, for this FY 2022 IPPS/LTCH PPS final rule, 
we ordinarily would use the FY 2020 MedPAR claims data to evaluate the 
effects of the FY 2020 DRG reclassification and recalibration. However, 
for the reasons discussed in section I.F. of the preamble of this final 
rule, we believe the FY 2020 MedPAR claims data were significantly 
impacted by the COVID-19 PHE. Due to these impacts, as we proposed, we 
are not evaluating the effects of the FY 2020 DRG reclassification and 
recalibration as part of our update for FY 2022. Therefore, as we 
proposed, we are making a 0.0 percentage point adjustment for 
reclassification and recalibration in the update framework for FY 2022.
    The capital update framework also contains an adjustment for 
forecast error. The input price index forecast is based on historical 
trends and relationships ascertainable at the time the update factor is 
established for the upcoming year. In any given year, there may be 
unanticipated price fluctuations that may result in differences between 
the actual increase in prices and the forecast used in calculating the 
update factors. In setting a prospective payment rate under the 
framework, we make an adjustment for forecast error only if our 
estimate of the change in the capital input price index for any year is 
off by 0.25 percentage point or more. There is a 2-year lag between the 
forecast and the availability of data to develop a measurement of the 
forecast error. Historically, when a forecast error of the CIPI is 
greater than 0.25 percentage point in absolute terms, it is reflected 
in the update recommended under this framework. A forecast error of -
0.3 percentage point was calculated for the FY 2020 update, for which 
there are historical data. That is, current historical data indicated 
that the forecasted FY 2020 CIPI (1.5 percent) used in calculating the 
FY 2020 update factor was not the same percentage increase as the 
actual realized price increase (1.2 percent). As this exceeds the 0.25 
percentage point threshold, as we proposed, we are making an adjustment 
of -0.3 percentage point for the forecast error in the update for FY 
2022.
    Under the capital IPPS update framework, we also make an adjustment 
for changes in intensity. Historically, we calculate this adjustment 
using the same methodology and data that were used in the past under 
the framework for operating IPPS. The intensity factor for the 
operating update framework reflects how hospital services are utilized 
to produce the final product, that is, the discharge. This component 
accounts for changes in the use of quality-enhancing services, for 
changes within DRG severity, and for expected modification of practice 
patterns to remove noncost-effective services. Our intensity measure is 
based on a 5-year average.
    We calculate case-mix constant intensity as the change in total 
cost per discharge, adjusted for price level changes (the CPI for 
hospital and related services) and changes in real case-mix. Without 
reliable estimates of the proportions of the overall annual intensity 
changes that are due, respectively, to ineffective practice patterns 
and the combination of quality-enhancing new technologies and 
complexity within the DRG system, we assume that one-half of the annual 
change is due to each of these factors. Thus, the capital update 
framework provides an add-on to the input price index rate of increase 
of one-half of the estimated annual increase in intensity, to allow for 
increases within DRG severity and the adoption of quality-enhancing 
technology.
    In this final rule, as we proposed, we are continuing to use a 
Medicare-specific intensity measure that is based on a 5-year adjusted 
average of cost per discharge for FY 2022 (we refer readers to the FY 
2011 IPPS/LTCH PPS final rule (75 FR 0436) for a full description of 
our Medicare-specific intensity measure). Specifically, for FY 2022, we 
are using an intensity measure that is based on an average of cost-per-
discharge data from the 5-year period beginning with FY 2015 and 
extending through FY 2019. Based on these data, we estimated that case-
mix constant intensity declined during FYs 2015 through 2019. In the 
past, when we found intensity to be declining, we believed a zero 
(rather than a negative) intensity adjustment was appropriate. 
Consistent with this approach, because we estimated that intensity 
would decline during that 5-year period, we believe it is appropriate 
to continue to apply a zero-intensity adjustment for FY 2022. 
Therefore, as we proposed, we are making a 0.0 percentage point 
adjustment for intensity in the update for FY 2022.
    Earlier, we described the basis of the components we used to 
develop the 0.8 percent capital update factor under the capital update 
framework for FY 2022, as shown in the following table.

[[Page 45551]]

[GRAPHIC] [TIFF OMITTED] TR13AU21.328

2. Outlier Payment Adjustment Factor
    Section 412.312(c) establishes a unified outlier payment 
methodology for inpatient operating and inpatient capital-related 
costs. A shared threshold is used to identify outlier cases for both 
inpatient operating and inpatient capital-related payments. Section 
412.308(c)(2) provides that the standard Federal rate for inpatient 
capital-related costs be reduced by an adjustment factor equal to the 
estimated proportion of capital-related outlier payments to total 
inpatient capital-related PPS payments. The outlier threshold is set so 
that operating outlier payments are projected to be 5.1 percent of 
total operating IPPS DRG payments. For FY 2022, we have incorporated 
the estimated outlier reconciliation payment amounts into the outlier 
threshold model, as we did for FY 2021. (For more details on our 
incorporation of the estimated outlier reconciliation payment amounts 
into the outlier threshold model, please see section II.A. of this 
Addendum to this final rule.)
    For FY 2021, we estimated that outlier payments for capital-related 
PPS payments would equal 5.34 percent of inpatient capital-related 
payments based on the capital Federal rate in FY 2021. Based on the 
threshold discussed in section II.A. of this Addendum, we estimate that 
prior to taking into account projected capital outlier reconciliation 
payments, outlier payments for capital-related costs will equal 5.31 
percent for inpatient capital-related payments based on the capital 
Federal rate in FY 2022. However, using the methodology outlined in 
section II.A. of this Addendum, we estimate that taking into account 
projected capital outlier reconciliation payments will decrease FY 2022 
aggregate estimated capital outlier payments by 0.02 percent. 
Therefore, accounting for estimated capital outlier reconciliation, the 
estimated outlier payments for capital-related PPS payments would equal 
5.29 percent (5.31 percent-0.02 percent) of inpatient capital-related 
payments based on the capital Federal rate in FY 2022. Accordingly, we 
applied an outlier adjustment factor of 0.9471 in determining the 
capital Federal rate for FY 2022. Thus, we estimate that the percentage 
of capital outlier payments to total capital Federal rate payments for 
FY 2022 will be lower than the percentage for FY 2021.
    The outlier reduction factors are not built permanently into the 
capital rates; that is, they are not applied cumulatively in 
determining the capital Federal rate. The FY 2022 outlier adjustment of 
0.9471 is a 0.05 percent change from the FY 2021 outlier adjustment of 
0.9466. Therefore, the net change in the outlier adjustment to the 
capital Federal rate for FY 2022 is 1.0005 (0.9471/0.9466) so that the 
outlier adjustment will increase the FY 2022 capital Federal rate by 
approximately 0.05 percent compared to the FY 2021 outlier adjustment.
3. Budget Neutrality Adjustment Factor for Changes in DRG 
Classifications and Weights and the GAF
    Section 412.308(c)(4)(ii) requires that the capital Federal rate be 
adjusted so that aggregate payments for the fiscal year based on the 
capital Federal rate, after any changes resulting from the annual DRG 
reclassification and recalibration and changes in the GAF, are 
projected to equal aggregate payments that would have been made on the 
basis of the capital Federal rate without such changes.
    As discussed in section III.G.3. of the preamble of this final 
rule, in the FY 2020 IPPS/LTCH PPS final rule (84 FR 42325 through 
42339), we finalized a policy to help reduce wage index disparities 
between high and low wage index hospitals by increasing the wage index 
values for hospitals with a wage index value below the 25th percentile 
wage index. We stated that this policy will be effective for at least 4 
years, beginning in FY 2020. Therefore, as discussed in section III.G.3 
of the preamble of this final rule, this policy was applied in FYs 2020 
and 2021, and will continue to apply in FY 2022. In FYs 2020 and 2021, 
we also placed a 5-percent cap on any decrease in a hospital's wage 
index from the hospital's final wage index in the prior fiscal year 
(see (84 FR 42336 through 42338) and (85 FR 58753 through 58755), 
respectively). As discussed in section III.A.2 of the preamble of this 
final rule, we solicited comments in the proposed rule on whether it 
would be appropriate to continue to apply a transition to the FY 2022 
wage index for hospitals negatively impacted by our adoption of the 
updates in OMB Bulletin 18-04. After consideration of comments 
received, in section III.A.2 of the preamble of this final rule, we are 
finalizing a policy that for hospitals that received the transition in 
FY 2021, we are continuing a wage index transition for FY 2022 under 
which we will apply a 5 percent cap on any decrease in the hospital's 
wage index compared to its

[[Page 45552]]

wage index for FY 2021. Accordingly, our methodology for computing the 
budget neutrality factor for changes in the GAFs as set forth in this 
final rule reflects this finalized policy for FY 2022. For this final 
rule, as noted in the proposed rule, it also reflects the incorporation 
of imputed floor adjustment.
    As we discussed in the FY 2020 IPPS/LTCH PPS final rule (84 FR 
42638 through 42639), we augmented our historical methodology for 
computing the budget neutrality factor for changes in the GAFs in light 
of the effect of those wage index changes on the GAFs. Specifically, we 
established a 2-step methodology, under which we first calculate a 
factor to ensure budget neutrality for changes to the GAFs due to the 
update to the wage data, wage index reclassifications and 
redesignations, and application of the rural floor policy, consistent 
with our historical GAF budget neutrality factor methodology. (We note 
that in FY 2020 we adopted a policy to calculate the rural floor 
without including the wage data of urban hospitals that have 
reclassified as rural under Sec.  412.103. We did not change this 
policy for FY 2022.) In the second step, we calculate a factor to 
ensure budget neutrality for changes to the GAFs due to our policy to 
increase the wage index for hospitals with a wage index value below the 
25th percentile wage index and our policy to place a 5-percent cap on 
any decrease in a hospital's wage index from the hospital's final wage 
index in the prior fiscal year in FYs 2020 and 2021. In this section, 
we refer to these two policies as the lowest quartile hospital wage 
index adjustment and the 5-percent cap on wage index decreases. 
Although we calculated separate factors for changes to the GAFs under 
each step of this 2-step methodology, our GAF/DRG budget neutrality 
factor reflected a single combined GAF budget neutrality factor that 
accounted for the budget neutrality calculations determined under each 
step of that methodology.
    The budget neutrality factors applied for changes to the GAFs due 
to the update to the wage data, wage index reclassifications and 
redesignations, and application of the rural floor policy are built 
permanently into the capital Federal rate; that is, they are applied 
cumulatively in determining the capital Federal rate. In FY 2021, in 
using the single combined GAF budget neutrality factor that accounted 
for both steps of our 2-step methodology, we also treated the FY 2020 
budget neutrality factor for the lowest quartile hospital wage index 
adjustment and the 5 percent cap on wage index decreases as a permanent 
factor and did not remove it from the FY 2021 capital Federal rate. In 
this final rule, as we proposed, we are no longer permanently applying 
the budget neutrality factor for the lowest quartile hospital wage 
index adjustment and the 5-percent cap on wage index decreases such 
that they will not be applied cumulatively in determining the capital 
Federal rate. We believe this is more technically appropriate because 
the GAFs with the lowest quartile hospital wage index adjustment and 
the 5-percent cap on wage index decreases policies applied from the 
previous year are not used in the budget neutrality factor calculations 
for the current year. These GAFs are not used because the lowest 
quartile hospital wage index adjustment and the 5-percent cap on wage 
index decreases policies (when applicable) are applied after the 
imputed floor, out-migration, and frontier state adjustments, which are 
not subject to budget neutrality. Therefore, in order to continue to 
exclude the imputed floor, out-migration and frontier state adjustments 
from budget neutrality, our budget neutrality calculations for 
permanent factors, as described in more detail later in this section, 
are determined from aggregate payments calculated using the GAFs from 
the previous year prior to the application of the imputed floor, out-
migration, and frontier state adjustment (and by extension the lowest 
quartile hospital wage index adjustment and 5-percent cap on wage index 
decreases). As a result, the budget neutrality factor for the lowest 
quartile hospital wage index adjustment and the 5-percent cap on wage 
index decreases only ensures budget neutrality for the application of 
those policies within the year, but not for a change in the policy as 
compared to the prior year. Accordingly and consistent with this 
approach, prior to calculating the GAF budget neutrality factors for FY 
2022, as we proposed, we removed from the capital Federal rate the 
cumulative effect of the budget neutrality factor applied in FYs 2020 
and 2021 for the lowest quartile hospital wage index adjustment and the 
5-percent cap on wage index decreases. Specifically, we divided the 
capital Federal rate by a factor of 0.9927, which accounts for the 
cumulative effect of the FY 2020 budget neutrality factor of 0.9964 (84 
FR 42639) and the FY 2021 budget neutrality factor of 0.9963 (85 FR 
59047) (0.9964 x 0.9963 = 0.9927).
    In light of the changes to the wage index and other wage index 
policies for FY 2022 discussed previously, which directly affects the 
GAF, we continue to compute a budget neutrality factor for changes in 
the GAFs in two steps. We discuss our 2-step calculation of the GAF 
budget neutrality factors for FY 2022 as follows.
    To determine the GAF budget neutrality factors for FY 2022, we 
first compared estimated aggregate capital Federal rate payments based 
on the FY 2021 MS-DRG classifications and relative weights and the FY 
2021 GAFs to estimated aggregate capital Federal rate payments based on 
the FY 2021 MS-DRG classifications and relative weights and the FY 2022 
GAFs without incorporating the lowest quartile hospital wage index 
adjustment and the 5-percent cap on wage index decreases policy. To 
achieve budget neutrality for these changes in the GAFs, we calculated 
an incremental GAF budget neutrality adjustment factor of 1.0003 for FY 
2022. Next, we compared estimated aggregate capital Federal rate 
payments based on the FY 2022 GAFs with and without the lowest quartile 
hospital wage index adjustment and the 5-percent cap on wage index 
decreases policy. For this calculation, estimated aggregate capital 
Federal rate payments were calculated using the FY 2022 MS-DRG 
classifications and relative weights and the FY 2022 GAFs (both with 
and without the lowest quartile hospital wage index adjustment and the 
5-percent cap on wage index decreases policy). (We note, for this 
calculation the GAFs included the imputed floor, out-migration, and 
frontier state adjustments.) To achieve budget neutrality for the 
effects of the lowest quartile hospital wage index adjustment and the 
5-percent cap on wage index decreases policy on the FY 2022 GAFs, we 
calculated an incremental GAF budget neutrality adjustment factor of 
0.9974. As discussed earlier in this section, we are finalizing that 
the budget neutrality factor for the lowest quartile hospital wage 
index adjustment and the 5-percent cap on wage index decreases not be 
permanently built into the capital Federal rate. Consistent with this 
policy, and unlike in previous rules, we present the calculated budget 
neutrality factor for the lowest quartile hospital wage index 
adjustment and the 5-percent cap on wage index decreases calculated 
under the second step of this 2-step methodology separately from the 
other calculated budget neutrality factors in the discussion that 
follows, and this factor is not included in the calculation of the 
combined GAF/DRG adjustment factor described later in this section.
    We compared estimated aggregate capital Federal rate payments based 
on the FY 2021 MS-DRG classifications and relative weights and the FY 
2022 GAFs (without the lowest quartile

[[Page 45553]]

hospital wage index adjustment and the 5-percent cap on wage index 
decreases) to estimated aggregate capital Federal rate payments based 
on the FY 2022 MS-DRG classifications and relative weights and the FY 
2022 GAFs (without the lowest quartile hospital wage index adjustment 
and the 5-percent cap on wage index decreases). The incremental 
adjustment factor for DRG classifications and changes in relative 
weights is 1.0001.
    The incremental adjustment factor for MS-DRG classifications and 
changes in relative weights (1.0001) and for changes in the FY 2022 
GAFs due to the update to the wage data, wage index reclassifications 
and redesignations, and application of the rural floor policy (1.0003) 
is 1.0004 (1.0001 x 1.0003). This incremental adjustment factor is 
built permanently into the capital Federal rates. To achieve budget 
neutrality for the effects of the lowest quartile hospital wage index 
adjustment and the 5-percent cap on wage index decreases policy on the 
FY 2022 GAFs, as described previously, we calculated a budget 
neutrality adjustment factor of 0.9974 for FY 2022. We refer to this 
budget neutrality factor for the remainder of this section as the 
``Quartile/Cap'' adjustment factor.
    We applied the budget neutrality adjustment factors described 
previously to the capital Federal rate. This follows the requirement 
under Sec.  412.308(c)(4)(ii) that estimated aggregate payments each 
year be no more or less than they would have been in the absence of the 
annual DRG reclassification and recalibration and changes in the GAFs.
    The methodology used to determine the recalibration and geographic 
adjustment factor (GAF/DRG) budget neutrality adjustment is similar to 
the methodology used in establishing budget neutrality adjustments 
under the IPPS for operating costs. One difference is that, under the 
operating IPPS, the budget neutrality adjustments for the effect of 
updates to the wage data, wage index reclassifications and 
redesignations, and application of the rural floor policy are 
determined separately. Under the capital IPPS, there is a single budget 
neutrality adjustment factor for changes in the GAF that result from 
updates to the wage data, wage index reclassifications and 
redesignations, and application of the rural floor policy. In addition, 
there is no adjustment for the effects that geographic 
reclassification, the lowest quartile hospital wage index adjustment, 
or the 5-percent cap on wage index decreases policy described 
previously have on the other payment parameters, such as the payments 
for DSH or IME.
    The incremental GAF/DRG adjustment factor of 1.0004 accounts for 
the MS-DRG reclassifications and recalibration and for changes in the 
GAFs that result from updates to the wage data, the effects on the GAFs 
of FY 2022 geographic reclassification decisions made by the MGCRB 
compared to FY 2021 decisions, and the application of the rural floor 
policy. The Quartile/Cap adjustment factor of 0.9974 accounts for 
changes in the GAFs that result from our policy to increase the wage 
index values for hospitals with a wage index value below the 25th 
percentile wage index, and the 5-percent cap on wage index decreases 
policy. However, these factors do not account for changes in payments 
due to changes in the DSH and IME adjustment factors.
4. Capital Federal Rate for FY 2022
    For FY 2021, we established a capital Federal rate of $466.21 (85 
FR 59048, as corrected in 85 FR 78756). We are establishing an update 
of 0.8 percent in determining the FY 2022 capital Federal rate for all 
hospitals. As a result of this update and the budget neutrality factors 
discussed earlier, we are establishing a national capital Federal rate 
of $472.60 for FY 2022. The national capital Federal rate for FY 2022 
was calculated as follows:
     The FY 2022 update factor is 1.008; that is, the update is 
0.8 percent.
     The FY 2022 GAF/DRG budget neutrality adjustment factor 
that is applied to the capital Federal rate for changes in the MS-DRG 
classifications and relative weights and changes in the GAFs that 
result from updates to the wage data, wage index reclassifications and 
redesignations, and application of the rural floor policy is 1.0004.
     The FY 2022 Quartile/Cap budget neutrality factor that is 
applied to the capital Federal rate for changes in the GAFs that result 
from our policy to increase the wage index values for hospitals with a 
wage index value below the 25th percentile wage index and the 5-percent 
cap on wage index decreases policy is 0.9974.
     The FY 2022 outlier adjustment factor is 0.9471.
    We are providing the following chart that shows how each of the 
factors and adjustments for FY 2022 affects the computation of the FY 
2022 national capital Federal rate in comparison to the FY 2021 
national capital Federal rate. The FY 2022 update factor has the effect 
of increasing the capital Federal rate by 0.80 percent compared to the 
FY 2021 capital Federal rate. The GAF/DRG budget neutrality adjustment 
factor has the effect of increasing the capital Federal rate by 0.04 
percent. The FY 2022 Quartile/Cap budget neutrality adjustment factor 
has the effect of increasing the capital Federal rate by 0.47 percent 
compared to the FY 2021 capital Federal rate. The FY 2022 outlier 
adjustment factor has the effect of increasing the capital Federal rate 
by 0.05 percent compared to the FY 2021 capital Federal rate. The 
combined effect of all the changes would increase the national capital 
Federal rate by approximately 1.37 percent, compared to the FY 2021 
national capital Federal rate.

[[Page 45554]]

[GRAPHIC] [TIFF OMITTED] TR13AU21.329

B. Calculation of the Inpatient Capital-Related Prospective Payments 
for FY 2022

    For purposes of calculating payments for each discharge during FY 
2022, the capital Federal rate is adjusted as follows: (Standard 
Federal Rate) x (DRG weight) x (GAF) x (COLA for hospitals located in 
Alaska and Hawaii) x (1 + DSH Adjustment Factor + IME Adjustment 
Factor, if applicable). The result is the adjusted capital Federal 
rate.
    Hospitals also may receive outlier payments for those cases that 
qualify under the threshold established for each fiscal year. Section 
412.312(c) provides for a shared threshold to identify outlier cases 
for both inpatient operating and inpatient capital-related payments. 
The outlier threshold for FY 2022 is in section II.A. of this Addendum. 
For FY 2022, a case will qualify as a cost outlier if the cost for the 
case plus the (operating) IME and DSH payments (including both the 
empirically justified Medicare DSH payment and the estimated 
uncompensated care payment, as discussed in section II.A.4.j. of this 
Addendum) is greater than the prospective payment rate for the MS-DRG 
plus the fixed-loss amount of $30,988.
    Currently, as provided under Sec.  412.304(c)(2), we pay a new 
hospital 85 percent of its reasonable costs during the first 2 years of 
operation, unless it elects to receive payment based on 100 percent of 
the capital Federal rate. Effective with the third year of operation, 
we pay the hospital based on 100 percent of the capital Federal rate 
(that is, the same methodology used to pay all other hospitals subject 
to the capital PPS).

C. Capital Input Price Index

1. Background
    Like the operating input price index, the capital input price index 
(CIPI) is a fixed-weight price index that measures the price changes 
associated with capital costs during a given year. The CIPI differs 
from the operating input price index in one important aspect--the CIPI 
reflects the vintage nature of capital, which is the acquisition and 
use of capital over time. Capital expenses in any given year are 
determined by the stock of capital in that year (that is, capital that 
remains on hand from all current and prior capital acquisitions). An 
index measuring capital price changes needs to reflect this vintage 
nature of capital. Therefore, the CIPI was developed to capture the 
vintage nature of capital by using a weighted-average of past capital 
purchase prices up to and including the current year.
    We periodically update the base year for the operating and capital 
input price indexes to reflect the changing composition of inputs for 
operating and capital expenses. For this FY 2022 IPPS/LTCH PPS final 
rule, we are rebasing and revising the IPPS operating and capital 
market baskets to reflect a 2018 base year. For a complete discussion 
of this rebasing, we refer readers to section IV. of the preamble of 
this final rule.
2. Forecast of the CIPI for FY 2022
    Based on IHS Global Inc.'s second quarter 2021 forecast, for this 
final rule, we are forecasting the 2018-based CIPI to increase 1.1 
percent in FY 2022. This reflects a projected 1.7 percent increase in 
vintage-weighted depreciation prices (building and fixed equipment, and 
movable equipment), and a projected 2.8 percent increase in other 
capital expense prices in FY 2022, partially offset by a projected 3.2 
percent decline in vintage-weighted interest expense prices in FY 2022. 
The weighted average of these three factors produces the forecasted 1.1 
percent increase for the 2018-based CIPI in FY 2022. As proposed, we 
are using the more recent data available for this final rule to 
determine the FY 2022 increase in the 2018-based CIPI for the final 
rule.

IV. Changes to Payment Rates for Excluded Hospitals: Rate-of-Increase 
Percentages for FY 2022

    Payments for services furnished in children's hospitals, 11 cancer 
hospitals, and hospitals located outside the 50 States, the District of 
Columbia and Puerto Rico (that is, short-term acute care hospitals 
located in the U.S.

[[Page 45555]]

Virgin Islands, Guam, the Northern Mariana Islands, and American Samoa) 
that are excluded from the IPPS are made on the basis of reasonable 
costs based on the hospital's own historical cost experience, subject 
to a rate-of-increase ceiling. A per discharge limit (the target 
amount, as defined in Sec.  413.40(a) of the regulations) is set for 
each hospital, based on the hospital's own cost experience in its base 
year, and updated annually by a rate-of-increase percentage specified 
in Sec.  413.40(c)(3). In addition, as specified in the FY 2018 IPPS/
LTCH PPS final rule (82 FR 38536), effective for cost reporting periods 
beginning during FY 2018, the annual update to the target amount for 
extended neoplastic disease care hospitals (hospitals described in 
Sec.  412.22(i) of the regulations) also is the rate-of-increase 
percentage specified in Sec.  413.40(c)(3). (We note that, in 
accordance with Sec.  403.752(a), religious nonmedical health care 
institutions (RNHCIs) are also subject to the rate-of increase limits 
established under Sec.  413.40 of the regulations.)
    As proposed, we are rebasing and revising the IPPS operating basket 
to a 2018 base year. Therefore, we are using the percentage increase in 
the 2018-based IPPS operating market basket to update the target 
amounts for children's hospitals, the 11 cancer hospitals, RNHCIs, 
short-term acute care hospitals located in the U.S. Virgin Islands, 
Guam, the Northern Mariana Islands, and American Samoa, and extended 
neoplastic disease care hospitals for FY 2022 and subsequent fiscal 
years. Accordingly, for FY 2022, the rate-of-increase percentage to be 
applied to the target amount for these hospitals is the FY 2022 
percentage increase in the 2018-based IPPS operating market basket.
    For this FY 2022 IPPS/LTCH PPS final rule, based on IGI's 2021 
second quarter forecast, we estimate that the 2018-based IPPS operating 
market basket update for FY 2022 will be 2.7 percent (that is, the 
estimate of the market basket rate-of-increase). Based on this 
estimate, the FY 2022 rate-of-increase percentage that will be applied 
to the FY 2021 target amounts in order to calculate the FY 2022 target 
amounts for children's hospitals, the 11 cancer hospitals, RNCHIs, 
short-term acute care hospitals located in the U.S. Virgin Islands, 
Guam, the Northern Mariana Islands, and American Samoa, and extended 
neoplastic disease care hospitals will be 2.7 percent, in accordance 
with the applicable regulations at 42 CFR 413.40.
    IRFs and rehabilitation distinct part units, IPFs and psychiatric 
units, and LTCHs are excluded from the IPPS and paid under their 
respective PPSs. The IRF PPS, the IPF PPS, and the LTCH PPS are updated 
annually. We refer readers to section VIII. of the preamble of this 
final rule and section V. of the Addendum to this final rule for the 
changes to the Federal payment rates for LTCHs under the LTCH PPS for 
FY 2022. The annual updates for the IRF PPS and the IPF PPS are issued 
by the agency in separate Federal Register documents.
    We did not receive comments on this proposal and therefore are 
finalizing this provision without modification.

V. Changes to the Payment Rates for the LTCH PPS for FY 2022

A. LTCH PPS Standard Federal Payment Rate for FY 2022

1. Overview
    In section VIII. of the preamble of this final rule, we discuss our 
annual updates to the payment rates, factors, and specific policies 
under the LTCH PPS for FY 2022.
    Under Sec.  412.523(c)(3) of the regulations, for FY 2012 and 
subsequent years, we updated the standard Federal payment rate by the 
most recent estimate of the LTCH PPS market basket at that time, 
including additional statutory adjustments required by sections 
1886(m)(3) (citing sections 1886(b)(3)(B)(xi)(II) and 1886(m)(4) of the 
Act as set forth in the regulations at Sec.  412.523(c)(3)(viii) 
through (xvii)). (For a summary of the payment rate development prior 
to FY 2012, we refer readers to the FY 2018 IPPS/LTCH PPS final rule 
(82 FR 38310 through 38312) and references therein.)
    Section 1886(m)(3)(A) of the Act specifies that, for rate year 2012 
and each subsequent rate year, any annual update to the standard 
Federal payment rate shall be reduced by the productivity adjustment 
described in section 1886(b)(3)(B)(xi)(II) of the Act as discussed in 
section VIII.C.2 of the preamble of this final rule. This section of 
the Act further provides that the application of section 1886(m)(3)(B) 
of the Act may result in the annual update being less than zero for a 
rate year, and may result in payment rates for a rate year being less 
than such payment rates for the preceding rate year. (As noted in 
section VIII.C.2. of the preamble of this final rule, the annual update 
to the LTCH PPS occurs on October 1 and we have adopted the term 
``fiscal year'' (FY) rather than ``rate year'' (RY) under the LTCH PPS 
beginning October 1, 2010. Therefore, for purposes of clarity, when 
discussing the annual update for the LTCH PPS, including the provisions 
of the Affordable Care Act, we use the term ``fiscal year'' rather than 
``rate year'' for 2011 and subsequent years.)
    For LTCHs that fail to submit the required quality reporting data 
in accordance with the LTCH QRP, the annual update is reduced by 2.0 
percentage points as required by section 1886(m)(5) of the Act.
2. Development of the FY 2022 LTCH PPS Standard Federal Payment Rate
    Consistent with our historical practice and Sec.  
412.523(c)(3)(xvii), for FY 2022, as we proposed, we are applying the 
annual update to the LTCH PPS standard Federal payment rate from the 
previous year. Furthermore, in determining the LTCH PPS standard 
Federal payment rate for FY 2022, we also are making certain regulatory 
adjustments, consistent with past practices. Specifically, in 
determining the FY 2022 LTCH PPS standard Federal payment rate, as we 
proposed, we are applying a budget neutrality adjustment factor for the 
changes related to the area wage level adjustment (that is, changes to 
the wage data and labor-related share) as discussed in section V.B.5. 
of this Addendum to this final rule.
    In this final rule, we are establishing an annual update to the 
LTCH PPS standard Federal payment rate of 1.9 percent (that is, the 
most recent estimate of the LTCH PPS market basket increase of 2.6 
percent less the productivity adjustment of 0.7 percentage point). 
Therefore, in accordance with Sec.  412.523(c)(3)(xvii), we are 
applying a factor of 1.019 to the FY 2021 LTCH PPS standard Federal 
payment rate of $ 43,755.34 to determine the FY 2022 LTCH PPS standard 
Federal payment rate. Also, in accordance with Sec.  
412.523(c)(3)(xvii) and Sec.  412.523(c)(4), we are required to reduce 
the annual update to the LTCH PPS standard Federal payment rate by 2.0 
percentage points for LTCHs that fail to submit the required quality 
reporting data for FY 2022 as required under the LTCH QRP. Therefore, 
we are establishing an annual update to the LTCH PPS standard Federal 
payment rate of -0.1 percent (that is, an update factor of 0.999) for 
FY 2022 for LTCHs that fail to submit the required quality reporting 
data for FY 2022 as required under the LTCH QRP. Consistent with Sec.  
412.523(d)(4), we are applying an area wage level budget neutrality 
factor to the FY 2022 LTCH PPS standard Federal payment rate of 
1.002848, based on the best available data at this time, to ensure that 
any changes to the area wage level adjustment (that is, the annual 
update of the wage index and labor-related share) will not result in 
any change (increase

[[Page 45556]]

or decrease) in estimated aggregate LTCH PPS standard Federal payment 
rate payments. Accordingly, we are establishing an LTCH PPS standard 
Federal payment rate of $44,713.67 (calculated as $43,755.34 x 1.019 x 
1.002848) for FY 2022. For LTCHs that fail to submit quality reporting 
data for FY 2022, in accordance with the requirements of the LTCH QRP 
under section 1866(m)(5) of the Act, we are establishing an LTCH PPS 
standard Federal payment rate of $43,836.08 (calculated as $43,755.34 x 
0.999 x 1.002848) for FY 2022.

B. Adjustment for Area Wage Levels Under the LTCH PPS for FY 2022

1. Background
    Under the authority of section 123 of the BBRA, as amended by 
section 307(b) of the BIPA, we established an adjustment to the LTCH 
PPS standard Federal payment rate to account for differences in LTCH 
area wage levels under Sec.  412.525(c). The labor-related share of the 
LTCH PPS standard Federal payment rate is adjusted to account for 
geographic differences in area wage levels by applying the applicable 
LTCH PPS wage index. The applicable LTCH PPS wage index is computed 
using wage data from inpatient acute care hospitals without regard to 
reclassification under section 1886(d)(8) or section 1886(d)(10) of the 
Act.
    The FY 2022 LTCH PPS standard Federal payment rate wage index 
values that will be applicable for LTCH PPS standard Federal payment 
rate discharges occurring on or after October 1, 2021, through 
September 30, 2022, are presented in Table 12A (for urban areas) and 
Table 12B (for rural areas), which are listed in section VI. of the 
Addendum to this final rule and available via the internet on the CMS 
website.
2. Geographic Classifications (Labor Market Areas) for the LTCH PPS 
Standard Federal Payment Rate
    In adjusting for the differences in area wage levels under the LTCH 
PPS, the labor-related portion of an LTCH's Federal prospective payment 
is adjusted by using an appropriate area wage index based on the 
geographic classification (labor market area) in which the LTCH is 
located. Specifically, the application of the LTCH PPS area wage level 
adjustment under existing Sec.  412.525(c) is made based on the 
location of the LTCH--either in an ``urban area,'' or a ``rural area,'' 
as defined in Sec.  412.503. Under Sec.  412.503, an ``urban area'' is 
defined as a Metropolitan Statistical Area (MSA) (which includes a 
Metropolitan division, where applicable), as defined by the Executive 
OMB, and a ``rural area'' is defined as any area outside of an urban 
area (75 FR 37246).
    The geographic classifications (labor market area definitions) 
currently used under the LTCH PPS, effective for discharges occurring 
on or after October 1, 2014, are based on the Core Based Statistical 
Areas (CBSAs) established by OMB, which are based on the 2010 decennial 
census data. In general, the current statistical areas (which were 
implemented beginning with FY 2015) are based on revised OMB 
delineations issued on February 28, 2013 in OMB Bulletin No. 13-01. (We 
note we have adopted minor revisions and updates in the years between 
the decennial censuses.) We adopted these labor market area 
delineations because they were at that time based on the best available 
data that reflect the local economies and area wage levels of the 
hospitals that are currently located in these geographic areas. We also 
believed that these OMB delineations would ensure that the LTCH PPS 
area wage level adjustment most appropriately accounted for and 
reflected the relative hospital wage levels in the geographic area of 
the hospital as compared to the national average hospital wage level. 
We noted that this policy was consistent with the IPPS policy adopted 
in FY 2015 under Sec.  412.64(b)(1)(ii)(D) (79 FR 49951 through 49963). 
(For additional information on the CBSA-based labor market area 
(geographic classification) delineations currently used under the LTCH 
PPS and the history of the labor market area definitions used under the 
LTCH PPS, we refer readers to the FY 2015 IPPS/LTCH PPS final rule (79 
FR 50180 through 50185).)
    In general, it is our historical practice to update the CBSA-based 
labor market area delineations annually based on the most recent 
updates issued by OMB. Generally, OMB issues major revisions to 
statistical areas every 10 years, based on the results of the decennial 
census. However, OMB occasionally issues minor updates and revisions to 
statistical areas in the years between the decennial censuses. OMB 
Bulletin No. 17-01, issued August 15, 2017, established the 
delineations for the Nation's statistical areas, and the corresponding 
changes to the CBSA-based labor market areas were adopted in the FY 
2019 IPPS/LTCH PPS final rule (83 FR 41731). A copy of this bulletin 
may be obtained on the website at: https://www.whitehouse.gov/sites/whitehouse.gov/files/omb/bulletins/2017/b-17-01.pdf. On April 10, 2018, 
OMB issued OMB Bulletin No. 18-03, which superseded the August 15, 2017 
OMB Bulletin No. 17-01. On September 14, 2018, OMB issued OMB Bulletin 
No. 18-04, which superseded the April 10, 2018 OMB Bulletin No. 18-03. 
Historically OMB bulletins issued between decennial censuses have only 
contained minor modifications to CBSA delineations based on changes in 
population counts. However, OMB's 2010 Standards for Delineating 
Metropolitan and Micropolitan Standards created a larger mid-decade 
redelineation that takes into account commuting data from the American 
Commuting Survey. As a result, the September 14, 2018 OMB Bulletin No. 
18-04 included more modifications to the CBSAs than are typical for OMB 
bulletins issued between decennial censuses. We adopted the updates set 
forth in OMB Bulletin No. 18-04 in the FY 2021 IPPS/LTCH PPS final rule 
(85 FR 59050 through 59051). A copy of the September 14, 2018 OMB 
Bulletin No. 18-04, may be obtained at https://www.whitehouse.gov/wp-content/uploads/2018/09/Bulletin-18-04.pdf.
    On March 6, 2020, OMB issued Bulletin No. 20-01, which provided 
updates to and superseded OMB Bulletin No. 18-04, which was issued on 
September 14, 2018. The attachments to OMB Bulletin No. 20-01 provided 
detailed information on the update to statistical areas since September 
14, 2018. (For a copy of this bulletin, we refer readers to the 
following website: https://www.whitehouse.gov/wp-content/uploads/2020/03/Bulletin-20-01.pdf). In OMB Bulletin No. 20-01, OMB announced one 
new Micropolitan Statistical Area and one new component of an existing 
Combined Statistical Area.
    After reviewing OMB Bulletin No. 20-01, we have determined that the 
changes in Bulletin 20-01 encompassed delineation changes that would 
not affect the CBSA-based labor market area delineations used under the 
LTCH PPS. Specifically, all changes were to New England City and Town 
Area delineations (NECTA) and the redesignation of a single rural 
county into a newly created Micropolitan Statistical Area. The LTCH PPS 
CBSA-based labor market area delineations do not utilize NECTA 
definitions, and considers hospitals located in Micropolitan 
Statistical Areas in each State's rural area. Therefore, we are 
adopting the updates set forth in OMB Bulletin No. 20-01; however, 
specific wage index updates are not necessary as a result of the 
adopting the updates.
    We believe the CBSA-based labor market area delineations as 
established in OMB Bulletin 20-01 will ensure that

[[Page 45557]]

the LTCH PPS area wage level adjustment most appropriately accounts for 
and reflects the relative hospital wage levels in the geographic area 
of the hospital as compared to the national average hospital wage level 
based on the best available data that reflect the local economies and 
area wage levels of the hospitals that are currently located in these 
geographic areas (81 FR 57298). Therefore, in this final rule, under 
the authority of section 123 of the BBRA, as amended by section 307(b) 
of the BIPA, we are adopting the revisions announced in OMB Bulletin 
No. 20-01 to the CBSA-based labor market area delineations under the 
LTCH PPS, effective October 1, 2022. As already noted, our adoption of 
the updates set forth in OMB Bulletin No. 20-01 will not alter the LTCH 
PPS area wage level adjustment because our CBSA-based labor market area 
delineations are the same as the CBSA-based labor market area 
delineations adopted in the FY 2021 IPPS/LTCH PPS final rule based on 
OMB Bulletin No. 18-04 (85 FR 59050 through 59051). We also note that, 
as discussed in section III.A.2. of the preamble of this final rule, we 
are also using these CBSA-based delineations under the IPPS.
    We note that, in connection with our adoption in FY 2021 of the 
updates in OMB bulletin 18-04, for FY 2021 we adopted a policy to place 
a 5-percent cap on any decrease in an LTCH's wage index from the LTCH's 
final wage index in FY 2020, so that an LTCH's wage index for FY 2021 
would not be less than 95 percent of its wage index for FY 2020. We 
refer the reader to the FY 2021 IPPS/LTCH PPS final rule (85 FR 59052 
through 59053) for a complete discussion of this transition. As 
finalized in the FY 2021 IPPS/LTCH PPS final rule, this transition 
expires at the end of FY 2021.
    Comment: We received comments expressing disappointment that CMS 
did not propose an LTCH wage index transition policy for FY 2022. The 
commenters cited the severity and continuing impact of changes related 
to the OMB updates and the unprecedented nature of the ongoing COVID-19 
PHE as reasons why CMS should continue to apply a transition policy in 
FY 2022.
    Response: We note that certain changes to wage index policy may 
significantly affect Medicare payments. These changes may arise from 
revisions to the OMB delineations of statistical areas resulting from 
the decennial census data, periodic updates to the OMB delineations in 
the years between the decennial censuses, or other wage index policy 
changes. While we consider how best to address these potential 
scenarios in a consistent and thoughtful manner, we reiterate that our 
policy principles with regard to the wage index include generally using 
the most current data and information available and providing that data 
and information, as well as any approaches to addressing any 
significant effects on Medicare payments resulting from these potential 
scenarios, in notice and comment rulemaking.
3. Labor-Related Share for the LTCH PPS Standard Federal Payment Rate
    Under the payment adjustment for the differences in area wage 
levels under Sec.  412.525(c), the labor-related share of an LTCH's 
standard Federal payment rate payment is adjusted by the applicable 
wage index for the labor market area in which the LTCH is located. The 
LTCH PPS labor-related share currently represents the sum of the labor-
related portion of operating costs and a labor-related portion of 
capital costs using the applicable LTCH market basket. Additional 
background information on the historical development of the labor-
related share under the LTCH PPS can be found in the RY 2007 LTCH PPS 
final rule (71 FR 27810 through 27817 and 27829 through 27830) and the 
FY 2012 IPPS/LTCH PPS final rule (76 FR 51766 through 51769 and 51808).
    For FY 2013, we rebased and revised the market basket used under 
the LTCH PPS by adopting a 2009-based LTCH market basket. In addition, 
for FY 2013 through FY 2016, we determined the labor-related share 
annually as the sum of the relative importance of each labor-related 
cost category of the 2009-based LTCH market basket for the respective 
fiscal year based on the best available data. (For more details, we 
refer readers to the FY 2013 IPPS/LTCH PPS final rule (77 FR 53477 
through 53479).) For FY 2017, we rebased and revised the 2009-based 
LTCH market basket to reflect a 2013 base year. In addition, for FY 
2017 through FY 2020, we determined the labor-related share annually as 
the sum of the relative importance of each labor-related cost category 
of the 2013-based LTCH market basket for the respective fiscal year 
based on the best available data. (For more details, we refer readers 
to the FY 2017 IPPS/LTCH PPS final rule (81 FR 57085 through 57096).) 
Then, effective for FY 2021, we rebased and revised the 2013-based LTCH 
market basket to reflect a 2017 base year and determined the labor-
related share annually as the sum of the relative importance of each 
labor-related cost category in the 2017 based LTCH market basket using 
the most recent available data. (For more details, we refer readers to 
the FY 2021 IPPS/LTCH PPS final rule (85 FR 58909 through 58926).)
    In this final rule, consistent with our historical practice, as we 
proposed, we are establishing that the LTCH PPS labor-related share for 
FY 2022 is the sum of the FY 2022 relative importance of each labor-
related cost category in the LTCH market basket using the most recent 
available data. Specifically, we are establishing that the labor-
related share for FY 2022 includes the sum of the labor-related portion 
of operating costs from the 2017-based LTCH market basket (that is, the 
sum of the FY 2022 relative importance shares of Wages and Salaries; 
Employee Benefits; Professional Fees: Labor-Related; Administrative and 
Facilities Support Services; Installation, Maintenance, and Repair 
Services; All Other: Labor-related Services) and a portion of the 
relative importance of Capital-Related cost weight from the 2017-based 
LTCH market basket. The relative importance reflects the different 
rates of price change for these cost categories between the base year 
(2017) and FY 2022. Based on IHS Global Inc.'s second quarter 2021 
forecast of the 2017-based LTCH market basket, the sum of the FY 2022 
relative importance for Wages and Salaries, Employee Benefits, 
Professional Fees: Labor-related, Administrative and Facilities Support 
Services, Installation Maintenance & Repair Services, and All Other: 
Labor-related Services is 63.6 percent. The portion of capital-related 
costs that is influenced by the local labor market is estimated to be 
46 percent (that is, the same percentage applied to the 2009-based and 
2013-based LTCH market baskets). Since the FY 2022 relative importance 
for capital-related costs is 9.3 percent based on IHS Global Inc.'s 
second quarter 2021 forecast of the 2017-based LTCH market basket, we 
took 46 percent of 9.3 percent to determine the labor-related share of 
capital-related costs for FY 2022 of 4.3 percent. Therefore, we are 
establishing a total labor-related share for FY 2022 of 67.9 percent 
(the sum of 63.6 percent for the operating cost and 4.3 percent for the 
labor-related share of capital-related cost).
4. Wage Index for FY 2022 for the LTCH PPS Standard Federal Payment 
Rate
    Historically, we have established LTCH PPS area wage index values 
calculated from acute care IPPS hospital wage data without taking into 
account geographic reclassification under sections 1886(d)(8) and 
1886(d)(10) of the Act (67 FR 56019). The area wage

[[Page 45558]]

level adjustment established under the LTCH PPS is based on an LTCH's 
actual location without regard to the ``urban'' or ``rural'' 
designation of any related or affiliated provider.
    In the FY 2021 IPPS/LTCH PPS final rule (85 FR 59051 through 
59052), we calculated the FY 2021 LTCH PPS area wage index values using 
the same data used for the FY 2021 acute care hospital IPPS (that is, 
data from cost reporting periods beginning during FY 2017), without 
taking into account geographic reclassification under sections 
1886(d)(8) and 1886(d)(10) of the Act, as these were the most recent 
complete data available at that time. In that same final rule, we 
indicated that we computed the FY 2021 LTCH PPS area wage index values 
consistent with the urban and rural geographic classifications (labor 
market areas) that were in place at that time and consistent with the 
pre-reclassified IPPS wage index policy (that is, our historical policy 
of not taking into account IPPS geographic reclassifications in 
determining payments under the LTCH PPS). As with the IPPS wage index, 
wage data for multicampus hospitals with campuses located in different 
labor market areas (CBSAs) are apportioned to each CBSA where the 
campus (or campuses) are located. We also continued to use our existing 
policy for determining area wage index values for areas where there are 
no IPPS wage data.
    Consistent with our historical methodology, to determine the 
applicable area wage index values for the FY 2022 LTCH PPS standard 
Federal payment rate, under the broad authority of section 123 of the 
BBRA, as amended by section 307(b) of the BIPA, as we proposed, we are 
continuing to employ our historical practice of using the same data we 
used to compute the FY 2022 acute care hospital inpatient wage index, 
as discussed in section III. of the preamble of this final rule (that 
is, wage data collected from cost reports submitted by IPPS hospitals 
for cost reporting periods beginning during FY 2018) because these data 
are the most recent complete data available.
    In addition, as we proposed, we computed the FY 2022 LTCH PPS 
standard Federal payment rate area wage index values consistent with 
the ``urban'' and ``rural'' geographic classifications (that is, the 
labor market area delineations as previously discussed in section V.B. 
of this Addendum) and our historical policy of not taking into account 
IPPS geographic reclassifications under sections 1886(d)(8) and 
1886(d)(10) of the Act in determining payments under the LTCH PPS. As 
we proposed, we also continued to apportion the wage data for 
multicampus hospitals with campuses located in different labor market 
areas to each CBSA where the campus or campuses are located, consistent 
with the IPPS policy. Lastly, consistent with our existing methodology 
for determining the LTCH PPS wage index values and as we proposed, for 
FY 2022 we continued to use our existing policy for determining area 
wage index values for areas where there are no IPPS wage data. Under 
our existing methodology, the LTCH PPS wage index value for urban CBSAs 
with no IPPS wage data is determined by using an average of all of the 
urban areas within the State, and the LTCH PPS wage index value for 
rural areas with no IPPS wage data is determined by using the 
unweighted average of the wage indices from all of the CBSAs that are 
contiguous to the rural counties of the State.
    Based on the FY 2018 IPPS wage data that we used to determine the 
FY 2022 LTCH PPS standard Federal payment rate area wage index values 
in this final rule, there are no IPPS wage data for the urban area of 
Hinesville, GA (CBSA 25980). Consistent with our existing methodology, 
we calculated the FY 2022 wage index value for CBSA 25980 as the 
average of the wage index values for all of the other urban areas 
within the State of Georgia (that is, CBSAs 10500, 12020, 12060, 12260, 
15260, 16860, 17980, 19140, 23580, 31420, 40660, 42340, 46660 and 
47580), as shown in Table 12A, which is listed in section VI. of the 
Addendum to this final rule and available via the internet on the CMS 
website at: https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/LongTermCareHospitalPPS/wageindex.
    Based on the FY 2018 IPPS wage data that we used to determine the 
FY 2022 LTCH PPS standard Federal payment rate area wage index values 
in this final rule, there are no rural areas without IPPS hospital wage 
data. Therefore, it is not necessary to use our established methodology 
to calculate a LTCH PPS standard Federal payment rate wage index value 
for rural areas with no IPPS wage data for FY 2022. We note that, as 
IPPS wage data are dynamic, it is possible that the number of rural 
areas without IPPS wage data will vary in the future.
5. Budget Neutrality Adjustments for Changes to the LTCH PPS Standard 
Federal Payment Rate Area Wage Level Adjustment
    Historically, the LTCH PPS wage index and labor-related share are 
updated annually based on the latest available data. Under Sec.  
412.525(c)(2), any changes to the area wage index values or labor-
related share are to be made in a budget neutral manner such that 
estimated aggregate LTCH PPS payments are unaffected; that is, will be 
neither greater than nor less than estimated aggregate LTCH PPS 
payments without such changes to the area wage level adjustment. Under 
this policy, we determine an area wage level adjustment budget 
neutrality factor that is applied to the standard Federal payment rate 
to ensure that any changes to the area wage level adjustments are 
budget neutral such that any changes to the area wage index values or 
labor-related share would not result in any change (increase or 
decrease) in estimated aggregate LTCH PPS payments. Accordingly, under 
Sec.  412.523(d)(4), we have applied an area wage level adjustment 
budget neutrality factor in determining the standard Federal payment 
rate, and we also established a methodology for calculating an area 
wage level adjustment budget neutrality factor. (For additional 
information on the establishment of our budget neutrality policy for 
changes to the area wage level adjustment, we refer readers to the FY 
2012 IPPS/LTCH PPS final rule (76 FR 51771 through 51773 and 51809).)
    For FY 2022, in accordance with Sec.  412.523(d)(4), as we 
proposed, we applied an area wage level budget neutrality factor to 
adjust the LTCH PPS standard Federal payment rate to account for the 
estimated effect of the adjustments or updates to the area wage level 
adjustment under Sec.  412.525(c)(1) on estimated aggregate LTCH PPS 
payments, consistent with the methodology we established in the FY 2012 
IPPS/LTCH PPS final rule (76 FR 51773).
    Specifically, as we proposed, we determined an area wage level 
adjustment budget neutrality factor that is applied to the LTCH PPS 
standard Federal payment rate under Sec.  412.523(d)(4) for FY 2022 
using the following methodology:
    Step 1--Simulate estimated aggregate LTCH PPS standard Federal 
payment rate payments using the FY 2021 wage index values and the FY 
2021 labor-related share of 68.1 percent.
    Step 2--Simulate estimated aggregate LTCH PPS standard Federal 
payment rate payments using the FY 2022 wage index values and the FY 
2022 labor-related share of 67.9 percent. (As noted previously, the 
changes to the wage index values based on updated hospital wage data 
are discussed in section V.B.4. of this Addendum to this final

[[Page 45559]]

rule and the labor-related share is discussed in section V.B.3. of this 
Addendum to this final rule.)
    Step 3--Calculate the ratio of these estimated total LTCH PPS 
standard Federal payment rate payments by dividing the estimated total 
LTCH PPS standard Federal payment rate payments using the FY 2021 area 
wage level adjustments (calculated in Step 1) by the estimated total 
LTCH PPS standard Federal payment rate payments using the FY 2022 
updates to the area wage level adjustment (calculated in Step 2) to 
determine the budget neutrality factor for updates to the area wage 
level adjustment for FY 2022 LTCH PPS standard Federal payment rate 
payments.
    Step 4--Apply the FY 2022 updates to the area wage level adjustment 
budget neutrality factor from Step 3 to determine the FY 2022 LTCH PPS 
standard Federal payment rate after the application of the FY 2022 
annual update.
    We note that, because the area wage level adjustment under Sec.  
412.525(c) is an adjustment to the LTCH PPS standard Federal payment 
rate, consistent with historical practice, we only used data from 
claims that qualified for payment at the LTCH PPS standard Federal 
payment rate under the dual rate LTCH PPS to calculate the FY 2022 LTCH 
PPS standard Federal payment rate area wage level adjustment budget 
neutrality factor.
    For this final rule, using the steps in the methodology previously 
described, we determined a FY 2022 LTCH PPS standard Federal payment 
rate area wage level adjustment budget neutrality factor of 1.002848. 
Accordingly, in section V.A. of the Addendum to this final rule, we 
applied the area wage level adjustment budget neutrality factor of 
1.002848 to determine the FY 2022 LTCH PPS standard Federal payment 
rate, in accordance with Sec.  412.523(d)(4).

C. Cost-of-Living Adjustment (COLA) for LTCHs Located in Alaska and 
Hawaii

    Under Sec.  412.525(b), a cost-of-living adjustment (COLA) is 
provided for LTCHs located in Alaska and Hawaii to account for the 
higher costs incurred in those States. Specifically, we apply a COLA to 
payments to LTCHs located in Alaska and Hawaii by multiplying the 
nonlabor-related portion of the standard Federal payment rate by the 
applicable COLA factors established annually by CMS. Higher labor-
related costs for LTCHs located in Alaska and Hawaii are taken into 
account in the adjustment for area wage levels previously described. 
The methodology used to determine the COLA factors for Alaska and 
Hawaii is based on a comparison of the growth in the Consumer Price 
Indexes (CPIs) for Anchorage, Alaska, and Honolulu, Hawaii, relative to 
the growth in the CPI for the average U.S. city as published by the 
Bureau of Labor Statistics (BLS). It also includes a 25-percent cap on 
the CPI-updated COLA factors. Under our current policy, we update the 
COLA factors using the methodology as previously described every 4 
years (at the same time as the update to the labor-related share of the 
IPPS market basket); the first year of our current policy was FY 2014. 
We refer readers to the FY 2013 IPPS/LTCH PPS final rule (77 FR 53481 
through 53482) for a detailed description of this methodology. For the 
FY 2014 IPPS/LTCH PPS final rule, we updated the COLA factors for 
Alaska and Hawaii published by OPM for 2009 using this methodology (78 
FR 50997 through 50998). For the FY 2018 IPPS/LTCH PPS final rule, we 
again updated the COLA factors using this same methodology (82 FR 38539 
through 38540). As discussed in this final rule, we continue to believe 
that determining updated COLA factors using this methodology would 
appropriately adjust the nonlabor-related portion of the LTCH PPS 
standard Federal payment rate for LTCHs located in Alaska and Hawaii.
    For FY 2022, we are updating the COLA factors published by OPM for 
2009 (as these are the last COLA factors OPM published prior to 
transitioning from COLAs to locality pay) using the methodology that we 
finalized in the FY 2013 IPPS/LTCH PPS final rule. Specifically, we are 
updating the 2009 OPM COLA factors by a comparison of the growth in the 
Consumer Price Indices (CPIs) for the areas of Urban Alaska and Urban 
Hawaii, relative to the growth in the CPI for the average U.S. city as 
published by the Bureau of Labor Statistics (BLS). We note that for the 
prior update to the COLA factors, we used the growth in the CPI for 
Anchorage and the CPI for Honolulu. Beginning in 2018, these indexes 
were renamed to the CPI for Urban Alaska and the CPI for Urban Hawaii, 
respectively, due to the BLS updating its sample to reflect the data 
from the 2010 decennial census on the distribution of the urban 
population (https://www.bls.gov/regions/west/factsheet/2018cpirevisionwest.pdf, accessed January 22, 2021). The CPI for Urban 
Alaska area covers Anchorage and Matanuska-Susitna Borough in the State 
of Alaska and the CPI for Urban Hawaii covers Honolulu in the State of 
Hawaii. BLS notes that the indexes are considered continuous over time, 
regardless of name or composition changes.
    Because BLS publishes CPI data for only Urban Alaska and Urban 
Hawaii, using the methodology we finalized in the FY 2013 IPPS/LTCH PPS 
final rule, we are using the comparison of the growth in the overall 
CPI relative to the growth in the CPI for those areas to update the 
COLA factors for all areas in Alaska and Hawaii, respectively. We 
believe that the relative price differences between these urban areas 
and the United States (as measured by the CPIs mentioned previously) 
are appropriate proxies for the relative price differences between the 
``other areas'' of Alaska and Hawaii and the United States.
    BLS publishes the CPI for All Items for Urban Alaska, Urban Hawaii, 
and for the average U.S. city. However, consistent with our methodology 
finalized in the FY 2013 IPPS/LTCH PPS final rule, we are creating 
reweighted CPIs for each of the respective areas to reflect the 
underlying composition of the IPPS market basket nonlabor-related 
share. The current composition of the CPI for All Items for all of the 
respective areas is approximately 40 percent commodities and 60 percent 
services. However, the IPPS nonlabor-related share for the 2018-based 
IPPS market basket is comprised of a different mix of commodities and 
services. Therefore, we created reweighted indexes for Urban Alaska, 
Urban Hawaii, and the average U.S. city using the respective CPI 
commodities index and CPI services index and using the approximate 57 
percent commodities/43 percent services shares obtained from the 2018-
based IPPS market basket. We created reweighted indexes using BLS data 
for 2009 through 2020--the most recent data available at the time of 
this final rulemaking. In the FY 2018 IPPS/LTCH PPS final rule (82 FR 
38539 through 38540) we created reweighted indexes based on the 2014-
based IPPS market basket (which was adopted for the FY 2018 IPPS 
update) and BLS data for 2009 through 2016 (the most recent BLS data at 
the time of the FY 2018 IPPS/LTCH PPS rulemaking).
    We continue to believe this methodology is appropriate because we 
continue to make a COLA for LTCHs located in Alaska and Hawaii by 
multiplying the nonlabor-related portion of the LTCH PPS standard 
Federal payment rate by a COLA factor. We note that OPM's COLA factors 
were calculated with a statutorily mandated cap of 25 percent. As 
stated in the FY 2018 IPPS/LTCH PPS final rule (82 FR 38539 through 
38540) under the COLA

[[Page 45560]]

update methodology we finalized in the FY 2013 IPPS/LTCH PPS final 
rule, we exercised our discretionary authority to adjust payments to 
LTCHs in Alaska and Hawaii by incorporating this cap. In applying this 
finalized methodology for updating the COLA factors, we are continuing 
to use a cap of 25 percent, as our policy is based on OPM's COLA 
factors (updated by the methodology described previously). We received 
no comments on this proposal and therefore are finalizing this 
provision without modification.
    Applying this methodology, the COLA factors that we are 
establishing effective for FY 2022 to adjust the nonlabor-related 
portion of the LTCH PPS standard Federal rate for LTCHs located in 
Alaska and Hawaii are shown in this table. For comparison purposes, we 
also are showing the COLA factors effective FY 2018 to FY 2021. We note 
that the COLA factors effective for FY 2022 for City and County of 
Honolulu, County of Kauai, and County of Maui and County of Kalawao are 
a result of applying the 25 percent cap as described previously.
[GRAPHIC] [TIFF OMITTED] TR13AU21.330

D. Adjustment for LTCH PPS High Cost Outlier (HCO) Cases

1. HCO Background
    From the beginning of the LTCH PPS, we have included an adjustment 
to account for cases in which there are extraordinarily high costs 
relative to the costs of most discharges. Under this policy, additional 
payments are made based on the degree to which the estimated cost of a 
case (which is calculated by multiplying the Medicare allowable covered 
charge by the hospital's overall hospital CCR) exceeds a fixed-loss 
amount. This policy results in greater payment accuracy under the LTCH 
PPS and the Medicare program, and the LTCH sharing the financial risk 
for the treatment of extraordinarily high-cost cases.
    We retained the basic tenets of our HCO policy in FY 2016 when we 
implemented the dual rate LTCH PPS payment structure under section 1206 
of Public Law 113-67. LTCH discharges that meet the criteria for 
exclusion from the site neutral payment rate (that is, LTCH PPS 
standard Federal payment rate cases) are paid at the LTCH PPS standard 
Federal payment rate, which includes, as applicable, HCO payments under 
Sec.  412.523(e). LTCH discharges that do not meet the criteria for 
exclusion are paid at the site neutral payment rate, which includes, as 
applicable, HCO payments under Sec.  412.522(c)(2)(i). In the FY 2016 
IPPS/LTCH PPS final rule, we established separate fixed-loss amounts 
and targets for the two different LTCH PPS payment rates. Under this 
bifurcated policy, the historic 8-percent HCO target was retained for 
LTCH PPS standard Federal payment rate cases, with the fixed-loss 
amount calculated using only data from LTCH cases that would have been 
paid at the LTCH PPS standard Federal payment rate if that rate had 
been in effect at the time of those discharges. For site neutral 
payment rate cases, we adopted the operating IPPS HCO target (currently 
5.1 percent) and set the fixed-loss amount for site neutral payment 
rate cases at the value of the IPPS fixed-loss amount. Under the HCO 
policy for both payment rates, an LTCH receives 80 percent of the 
difference between the estimated cost of the case and the applicable 
HCO threshold, which is the sum of the LTCH PPS payment for the case 
and the applicable fixed-loss amount for such case.
    In order to maintain budget neutrality, consistent with the budget 
neutrality requirement at Sec.  412.523(d)(1) for HCO payments to LTCH 
PPS standard Federal rate payment cases, we also adopted a budget 
neutrality requirement for HCO payments to site neutral payment rate 
cases by applying a budget neutrality factor to the LTCH PPS payment 
for those site neutral payment rate cases. (We refer readers to Sec.  
412.522(c)(2)(i) of the regulations for further details.) We note that, 
during the 4-year transitional period, the site neutral payment rate 
HCO budget neutrality factor did not apply to the LTCH PPS standard 
Federal payment rate portion of the blended payment rate at Sec.  
412.522(c)(3) payable to site neutral payment rate cases. (For 
additional details on the HCO policy adopted for site neutral payment 
rate cases under the dual rate LTCH PPS payment structure, including 
the budget neutrality adjustment for HCO payments to site neutral 
payment rate cases, we refer readers to the FY 2016 IPPS/LTCH PPS final 
rule (80 FR 49617 through 49623).)
2. Determining LTCH CCRs Under the LTCH PPS
a. Background
    As noted previously, CCRs are used to determine payments for HCO 
adjustments for both payment rates

[[Page 45561]]

under the LTCH PPS and also are used to determine payments for site 
neutral payment rate cases. As noted earlier, in determining HCO and 
the site neutral payment rate payments (regardless of whether the case 
is also an HCO), we generally calculate the estimated cost of the case 
by multiplying the LTCH's overall CCR by the Medicare allowable charges 
for the case. An overall CCR is used because the LTCH PPS uses a single 
prospective payment per discharge that covers both inpatient operating 
and capital-related costs. The LTCH's overall CCR is generally computed 
based on the sum of LTCH operating and capital costs (as described in 
Section 150.24, Chapter 3, of the Medicare Claims Processing Manual 
(Pub. 100-4)) as compared to total Medicare charges (that is, the sum 
of its operating and capital inpatient routine and ancillary charges), 
with those values determined from either the most recently settled cost 
report or the most recent tentatively settled cost report, whichever is 
from the latest cost reporting period. However, in certain instances, 
we use an alternative CCR, such as the statewide average CCR, a CCR 
that is specified by CMS, or one that is requested by the hospital. (We 
refer readers to Sec.  412.525(a)(4)(iv) of the regulations for further 
details regarding CCRs and HCO adjustments for either LTCH PPS payment 
rate and Sec.  412.522(c)(1)(ii) for the site neutral payment rate.)
    The LTCH's calculated CCR is then compared to the LTCH total CCR 
ceiling. Under our established policy, an LTCH with a calculated CCR in 
excess of the applicable maximum CCR threshold (that is, the LTCH total 
CCR ceiling, which is calculated as 3 standard deviations from the 
national geometric average CCR) is generally assigned the applicable 
statewide CCR. This policy is premised on a belief that calculated 
CCRs, as previously noted, the LTCH total CCR ceiling are most likely 
due to faulty data reporting or entry, and CCRs based on erroneous data 
should not be used to identify and make payments for outlier cases.
b. LTCH Total CCR Ceiling
    Ordinarily, for this FY 2022 final rule, we would use IPPS total 
CCR data from the March 2021 update of the Provider Specific File (PSF) 
for the purposes of calculating the LTCH total CCR ceiling for FY 2022. 
However, for many IPPS hospitals, these IPPS total CCR data were 
derived from cost reports that ended during the COVID-19 PHE. As 
discussed in section VIII.A.4. of the preamble of this final rule, we 
believe the utilization patterns reflected in these cost reports were 
significantly impacted by the COVID-19 PHE. Since the IPPS total CCR 
data from the March 2020 update of the PSF was derived from cost 
reports ending prior to the COVID-19 PHE, we believe for the reasons 
discussed in section VIII.A.4. of the preamble of this final rule that 
these are the best available data at this time for the purposes of 
calculating the LTCH total CCR ceiling for FY 2022. Therefore, in this 
final rule, using our established methodology for determining the LTCH 
total CCR ceiling but using the IPPS total CCR data from the March 2020 
update of the PSF, we are establishing an LTCH total CCR ceiling of 
1.236 under the LTCH PPS for FY 2022 in accordance with Sec.  
412.525(a)(4)(iv)(C)(2) for HCO cases under either payment rate and 
Sec.  412.522(c)(1)(ii) for the site neutral payment rate. (For 
additional information on our methodology for determining the LTCH 
total CCR ceiling, we refer readers to the FY 2007 IPPS final rule (71 
FR 48117 through 48119).)
    We did not receive any public comments on our proposals. Therefore, 
we are finalizing our proposals as described above, without 
modification.
c. LTCH Statewide Average CCRs
    Our general methodology for determining the statewide average CCRs 
used under the LTCH PPS is similar to our established methodology for 
determining the LTCH total CCR ceiling because it is based on ``total'' 
IPPS CCR data. (For additional information on our methodology for 
determining statewide average CCRs under the LTCH PPS, we refer readers 
to the FY 2007 IPPS final rule (71 FR 48119 through 48120).) Under the 
LTCH PPS HCO policy at Sec.  412.525(a)(4)(iv)(C), the SSO policy at 
Sec.  412.529(f)(4)(iii), and the site neutral payment rate at Sec.  
412.522(c)(1)(ii), the MAC may use a statewide average CCR, which is 
established annually by CMS, if it is unable to determine an accurate 
CCR for an LTCH in one of the following circumstances: (1) New LTCHs 
that have not yet submitted their first Medicare cost report (a new 
LTCH is defined as an entity that has not accepted assignment of an 
existing hospital's provider agreement in accordance with Sec.  
489.18); (2) LTCHs whose calculated CCR is in excess of the LTCH total 
CCR ceiling; and (3) other LTCHs for whom data with which to calculate 
a CCR are not available (for example, missing or faulty data). (Other 
sources of data that the MAC may consider in determining an LTCH's CCR 
include data from a different cost reporting period for the LTCH, data 
from the cost reporting period preceding the period in which the 
hospital began to be paid as an LTCH (that is, the period of at least 6 
months that it was paid as a short-term, acute care hospital), or data 
from other comparable LTCHs, such as LTCHs in the same chain or in the 
same region.)
    Ordinarily, for this final rule, we would use IPPS total CCR data 
from the March 2021 update of the PSF for the purposes of determining 
the LTCH statewide average CCRs for FY 2022. However, for many IPPS 
hospitals, these IPPS total CCR data were derived from cost reports 
that ended during the COVID-19 PHE. As discussed in section VIII.A.4 of 
the preamble of this final rule, we believe the utilization patterns 
reflected in these cost reports were significantly impacted by the 
COVID-19 PHE. Since the IPPS total CCR data from the March 2020 update 
of the PSF was derived from cost reports ending prior to the COVID-19 
PHE, for the reasons discussed in section VIII.A.4. of the preamble of 
this final rule, we believe that these are the best available data at 
this time for the purposes of determining the LTCH statewide average 
CCRs for FY 2022. Therefore, in this final rule, using our established 
methodology for determining the LTCH statewide average CCRs, but based 
on IPPS ``total CCR'' data from the March 2020 update of the PSF, we 
are establishing LTCH PPS statewide average total CCRs for urban and 
rural hospitals that will be effective for discharges occurring on or 
after October 1, 2021, through September 30, 2022, in Table 8C listed 
in section VI. of the Addendum to this final rule (and available via 
the internet on the CMS website).
    Under the current LTCH PPS labor market areas, all areas in 
Delaware, the District of Columbia, New Jersey, and Rhode Island are 
classified as urban. Therefore, there are no rural statewide average 
total CCRs listed for those jurisdictions in Table 8C. This policy is 
consistent with the policy that we established when we revised our 
methodology for determining the applicable LTCH statewide average CCRs 
in the FY 2007 IPPS final rule (71 FR 48119 through 48121) and is the 
same as the policy applied under the IPPS. In addition, although 
Connecticut has areas that are designated as rural, in our calculation 
of the LTCH statewide average CCRs, there were no short-term, acute 
care IPPS hospitals classified as rural or LTCHs located in these rural 
areas as of March 2020. Therefore, consistent with our existing 
methodology, we used the national average total CCR for rural IPPS 
hospitals for rural Connecticut in Table 8C. While Massachusetts also 
has rural areas, the statewide average CCR for

[[Page 45562]]

rural areas in Massachusetts is based on one IPPS provider whose CCR is 
an atypical 0.949. Because this is much higher than the statewide urban 
average (0.459) and furthermore implies costs are nearly equal to 
charges, as with Connecticut, we used the national average total CCR 
for rural IPPS hospitals for rural Massachusetts in Table 8C. 
Furthermore, consistent with our existing methodology, in determining 
the urban and rural statewide average total CCRs for Maryland LTCHs 
paid under the LTCH PPS, as we proposed, we are continuing to use, as a 
proxy, the national average total CCR for urban IPPS hospitals and the 
national average total CCR for rural IPPS hospitals, respectively. We 
are using this proxy because we believe that the CCR data in the PSF 
for Maryland hospitals may not be entirely accurate (as discussed in 
greater detail in the FY 2007 IPPS final rule (71 FR 48120)).
    We did not receive any public comments on our proposals. Therefore, 
we are finalizing our proposals as described above, without 
modification.
d. Reconciliation of HCO Payments
    Under the HCO policy for cases paid under either payment rate at 
Sec.  412.525(a)(4)(iv)(D), the payments for HCO cases are subject to 
reconciliation. Specifically, any such payments are reconciled at 
settlement based on the CCR that was calculated based on the cost 
report coinciding with the discharge. For additional information on the 
reconciliation policy, we refer readers to sections 150.26 through 
150.28 of the Medicare Claims Processing Manual (Pub. 100-4), as added 
by Change Request 7192 (Transmittal 2111; December 3, 2010), and the RY 
2009 LTCH PPS final rule (73 FR 26820 through 26821).
3. High-Cost Outlier Payments for LTCH PPS Standard Federal Payment 
Rate Cases
a. High-Cost Outlier Payments for LTCH PPS Standard Federal Payment 
Rate Cases
    Under the regulations at Sec.  412.525(a)(2)(ii) and as required by 
section 1886(m)(7) of the Act, the fixed-loss amount for HCO payments 
is set each year so that the estimated aggregate HCO payments for LTCH 
PPS standard Federal payment rate cases are 99.6875 percent of 8 
percent (that is, 7.975 percent) of estimated aggregate LTCH PPS 
payments for LTCH PPS standard Federal payment rate cases. (For more 
details on the requirements for high-cost outlier payments in FY 2018 
and subsequent years under section 1886(m)(7) of the Act and additional 
information regarding high-cost outlier payments prior to FY 2018, we 
refer readers to the FY 2018 IPPS/LTCH PPS final rule (82 FR 38542 
through 38544).)
b. Fixed-Loss Amount for LTCH PPS Standard Federal Payment Rate Cases 
for FY 2022
    When we implemented the LTCH PPS, we established a fixed-loss 
amount so that total estimated outlier payments are projected to equal 
8 percent of total estimated payments (that is, the target percentage) 
under the LTCH PPS (67 FR 56022 through 56026). When we implemented the 
dual rate LTCH PPS payment structure beginning in FY 2016, we 
established that, in general, the historical LTCH PPS HCO policy would 
continue to apply to LTCH PPS standard Federal payment rate cases. That 
is, the fixed-loss amount for LTCH PPS standard Federal payment rate 
cases would be determined using the LTCH PPS HCO policy adopted when 
the LTCH PPS was first implemented, but we limited the data used under 
that policy to LTCH cases that would have been LTCH PPS standard 
Federal payment rate cases if the statutory changes had been in effect 
at the time of those discharges.
    To determine the applicable fixed-loss amount for LTCH PPS standard 
Federal payment rate cases, we estimate outlier payments and total LTCH 
PPS payments for each LTCH PPS standard Federal payment rate case (or 
for each case that would have been a LTCH PPS standard Federal payment 
rate case if the statutory changes had been in effect at the time of 
the discharge) using claims data from the MedPAR files. In accordance 
with Sec.  412.525(a)(2)(ii), the applicable fixed-loss amount for LTCH 
PPS standard Federal payment rate cases results in estimated total 
outlier payments being projected to be equal to 7.975 percent of 
projected total LTCH PPS payments for LTCH PPS standard Federal payment 
rate cases.
    In the FY 2022 IPPS/LTCH PPS proposed rule (86 FR 25735 through 
25737), we proposed to adjust our methodology for calculating the 
applicable fixed-loss amount for FY 2022 for LTCH PPS standard Federal 
payment rate cases, while maintaining estimated HCO payments at the 
projected 7.975 percent of total estimated LTCH PPS payments for LTCH 
PPS standard Federal payment rate cases. We specifically proposed to 
make a technical change to the methodology for determining the charge 
inflation factor that we apply to the charges on the MedPAR claims when 
calculating the fixed-loss amount for FY 2022. We also proposed to make 
a technical change to the methodology for determining the CCRs to use 
when calculating the fixed-loss amount for FY 2022. Furthermore, we 
proposed that these technical changes to the methodology for 
determining the charge inflation factor and the CCRs we use when 
calculating the fixed-loss amount would become a permanent part of our 
methodology for subsequent years as well. These technical changes that 
we proposed are described in greater detail in sections V.D.3.b.(1). 
and V.D.3.b.(2). of the Addendum to this final rule.
(1) Charge Inflation Factor for Use in Determining the Fixed-Loss 
Amount for LTCH PPS Standard Federal Payment Rate Cases for FY 2022
    Under the LTCH PPS, the cost of each claim is estimated by 
multiplying the charges on the claim by the provider's CCR. Due to the 
lag time in the availability of claims data, when estimating costs for 
the upcoming payment year we typically inflate the charges from the 
claims data by a uniform factor. Historically, as explained in in the 
FY 2021 IPPS/LTCH PPS final rule (85 FR 59056), when determining the 
fixed-loss amount, charges were inflated with a growth factor 
calculated from quarterly market basket update values (determined by 
the Office of the Actuary). However, an analysis of the annual increase 
in actual charges (or charge inflation) calculated from the historical 
MedPAR claims compared with previous estimates using the quarterly 
market basket update values showed the actual charge inflation has been 
generally higher than the estimate. For example, when we set rates for 
FY 2019, we used a 2-year charge inflation factor of 5.7 percent based 
on the quarterly market basket update values. This factor was applied 
to charges from the FY 2017 MedPAR claims in order to inflate them to 
projected FY 2019 levels. However, our analysis of the actual FY 2019 
MedPAR claims data shows that the actual growth in charges that 
occurred from FY 2017 to FY 2019 for standard Federal payment rate 
cases was 15.2 percent.
    For greater accuracy in calculating the fixed-loss amount, we 
proposed to make a technical change to our methodology for determining 
the charge inflation factor. Similar to the method used under the IPPS 
hospital payment methodology (as discussed in section II.A.4.h.(2) of 
the Addendum to this final rule), we proposed to determine the LTCH 
charge inflation factor based on the historical growth in charges for 
LTCH PPS standard Federal payment rate cases, calculated using 
historical MedPAR

[[Page 45563]]

claims data, instead of using estimates calculated from quarterly 
market basket update values. In this section we describe the general 
methodology we proposed to use to calculate the charge inflation factor 
for FY 2022 and subsequent years. We discuss in greater detail later in 
this section our specific application of this proposal for FY 2022, 
including the specific data we proposed to use for FY 2022 after 
considering the impact the COVID-19 PHE had on the utilization patterns 
reflected in the FY 2020 LTCH data.
Step 1--Identify LTCH PPS Standard Federal Payment Rate Cases
    The first step in our proposed methodology is to identify LTCH PPS 
standard Federal payment rate cases from the MedPAR claim files for the 
two most recently available Federal fiscal year time periods. For both 
fiscal years, consistent with our historical methodology for 
determining payment rates for the LTCH PPS, we remove any claims 
submitted by LTCHs that were all-inclusive rate providers as well as 
any Medicare Advantage claims. For both fiscal years, we also remove 
claims from providers that only had claims in one of the fiscal years.
Step 2--Remove Statistical Outliers
    The next step in our proposed methodology is to remove all claims 
from providers whose growth in average charges was a statistical 
outlier. We remove these statistical outliers prior to calculating the 
charge inflation factor because we believe they may represent 
aberrations in the data that would distort the measure of average 
charge growth. To perform this statistical trim, we first calculate 
each provider's average charge in both fiscal years. Then, we calculate 
a charge growth factor for each provider by dividing its average charge 
in the most recent fiscal year by its average charge in the prior 
fiscal year. We then remove all claims for providers whose calculated 
charge growth factor was outside 3 standard deviations from the mean 
provider charge growth factor.
Step 3--Calculate the Charge Inflation Factor
    The final step in our proposed methodology is to use the remaining 
claims to calculate a national charge inflation factor. We first 
calculate the average charge for those remaining claims in both fiscal 
years. We then calculate the national charge inflation factor by 
dividing the average charge in the more recent fiscal year by the 
average charge in the prior fiscal year.
    As discussed in section VIII.A.4. of the preamble of the proposed 
rule, we proposed to use the FY 2019 data for the FY 2022 LTCH PPS 
ratesetting in situations where the utilization patterns reflected in 
the FY 2020 data were significantly impacted by the COVID-19 PHE. For 
the purposes of calculating the proposed charge inflation factor for FY 
2022, we proposed to use the March 2020 update of the FY 2019 MedPAR 
file and the March 2019 update of the FY 2018 MedPAR as the basis of 
the LTCH PPS standard Federal payment rate cases for the two most 
recently available Federal fiscal year time periods, as described 
previously in our proposed methodology.
    Therefore, for the proposed rule, we trimmed the March 2020 update 
of the FY 2019 MedPAR file and the March 2019 update of the FY 2018 
MedPAR file using our proposed methodology. To compute the 1-year 
average annual rate-of-change in charges per case for FY 2022, we 
compared the average covered charge per case of $195,362 
($13,926,931,065/71,288 cases) from FY 2018 to the average covered 
charge per case of $207,224 ($14,172,496,534/68,392 cases) from FY 
2019. This rate-of-change was 6.0723 percent and resulted in a proposed 
1-year charge inflation factor of 1.060723, a proposed 2-year charge 
inflation factor of 1.125133 (calculated by squaring the proposed 1-
year factor), and a proposed 3-year charge inflation factor of 1.193455 
(calculated by cubing the proposed 1-year factor). We proposed to 
inflate the billed charges obtained from the FY 2019 MedPAR file by 
this 3-year charge inflation factor of 1.193455 when we determined the 
proposed fixed-loss amount for LTCH PPS standard Federal payment rate 
cases for FY 2022.
(2) CCRs for Use in Determining the Fixed-Loss Amount for LTCH PPS 
Standard Federal Payment Rate Cases for FY 2022
    Historically, as explained in the FY 2021 IPPS/LTCH PPS final rule 
(85 FR 59055 through 59056), when determining the fixed-loss amount, we 
used CCRs from the most recently available PSF file without any 
adjustment. By not making any adjustment, we assumed that CCRs in the 
current year would, on average, stay at the same level in the upcoming 
year. However, after examining actual changes to LTCH CCRs over time, 
we no longer believe this to be an appropriate assumption to make, as 
in general LTCH CCRs have not stayed at the same level year-to-year. 
For example, when we set rates for FY 2019, we assumed that CCRs would 
stay at the same level as the CCRs obtained from the March 2018 PSF. 
However, our calculations show that on average, CCRs declined 3.8 
percent from March 2018 to March 2019.
    For greater accuracy in calculating the fixed-loss amount, we 
proposed to adjust the methodology for determining the CCRs used to 
calculate the fixed-loss amount. Similar to the methodology used for 
IPPS hospitals (as discussed in section II.A.4.h.(2). of the Addendum 
to this final rule), we proposed to adjust CCRs obtained from the best 
available PSF data by an adjustment factor that is calculated based on 
historical changes in the average case weighted CCR for LTCHs. We 
believe these adjusted CCRs will more accurately reflect CCR levels in 
the upcoming payment year because they account for historical changes 
in the relationship between costs and charges for LTCHs. In this 
section, we describe the general methodology we proposed to use to 
calculate the CCR adjustment factor for FY 2022 and subsequent years. 
We discuss in greater detail later in this section our specific 
application of this proposal for FY 2022, including the specific data 
we proposed to use after considering the impact the COVID-19 PHE had on 
the utilization patterns reflected in the FY 2020 LTCH data.
Step 1--Assign Providers Their Historical CCRs
    The first step in our proposed methodology is to identify providers 
with LTCH PPS standard Federal payment rate cases in the most recent 
MedPAR claims file (excluding all-inclusive rate providers and 
providers with only Medicare Advantage claims). For each of these 
providers, we then identify the CCR from the most recently available 
PSF. For each of these providers we also identify the CCR from the PSF 
that was made available 1 year prior to the most recently available 
PSF.
Step 2--Trim Providers With Insufficient CCR Data
    The next step in our proposed methodology is to remove from the CCR 
adjustment factor calculation any providers for which we cannot 
accurately measure changes to their CCR using the PSF data. We first 
remove any provider whose CCR was missing in the most recent PSF or 
prior year PSF. We next remove any provider assigned the statewide 
average CCR for their State in either the most recent PSF or prior year 
PSF. We lastly remove any provider whose CCR was not updated between 
the most recent PSF and prior year PSF (determined by comparing the 
effective date of the records).

[[Page 45564]]

Step 3--Remove Statistical Outliers
    The next step in our proposed methodology is to remove providers 
whose change in their CCR is a statistical outlier. To perform this 
statistical trim, for those providers remaining after application of 
Step 2, we calculate a provider-level CCR growth factor by dividing the 
provider's CCR from the most recent PSF by its CCR in the prior year's 
PSF. We then remove any provider whose CCR growth factor was outside 3 
standard deviations from the mean provider CCR growth factor. These 
statistical outliers are removed prior to calculating the CCR 
adjustment factor because we believe that they may represent 
aberrations in the data that would distort the measure of average 
annual CCR change.
Step 4--Calculate the CCR Adjustment Factor
    The final step in our proposed methodology is to calculate, across 
all remaining providers after application of Step 3, the average case-
weighted CCR from both the most recent PSF and prior year PSF. The 
provider case counts that we use to calculate the case-weighted average 
are determined from claims for LTCH standard Federal rate cases from 
the most recent MedPAR claims file. We note when determining these case 
counts, consistent with our historical methodology for determining the 
MS-LTC-DRG relative weights, we do not count short-stay-outlier claims 
as full cases but instead as a fraction of a case based on the ratio of 
covered days to the geometric mean length of stay for the MS-LTC-DRG 
grouped to the case. We calculate the national CCR adjustment factor by 
dividing the case-weighted CCR from the most recent PSF by the case-
weighted CCR from the prior year PSF.
    In the proposed rule, we proposed to use the FY 2019 data for the 
FY 2022 LTCH PPS ratesetting in situations where the utilization 
patterns reflected in the FY 2020 data were significantly impacted by 
the COVID-19 PHE, for the reasons discussed in section VIII.A.4. of the 
preamble of the proposed rule. For the purposes of determining the CCRs 
used for calculating the proposed fixed-loss amount for FY 2022, we 
proposed to use the March 2020 PSF as the most recently available PSF 
and the March 2019 PSF as the PSF that was made available 1 year prior 
to the most recently available PSF, as described in our proposed 
methodology. In addition, we also proposed to use claims from the March 
2020 update of the FY 2019 MedPAR file in our calculation of average 
case-weighted CCRs described in Step 4 of our proposed methodology.
    Specifically, to calculate the CCRs we proposed to use in the 
proposed rule, we followed the proposed methodology described 
previously and, for providers with LTCH PPS standard Federal payment 
rate cases in the March 2020 update of the FY 2019 MedPAR file, we 
identified their CCRs from both the March 2019 PSF and March 2020 PSF. 
After performing the trims outlined in our proposed methodology, we 
used the LTCH PPS standard Federal payment rate case counts from the FY 
2019 MedPAR file (classified using proposed Version 39 of the GROUPER) 
to calculate the case-weighted average CCRs. For the proposed rule, we 
calculated a proposed March 2019 national average case-weighted CCR of 
0.256374 and a proposed March 2020 national average case-weighted CCR 
of 0.246517. We then calculated the proposed national CCR adjustment 
factor by dividing the March 2020 national average case-weighted CCR by 
the March 2019 national average case-weighted CCR. This resulted in a 
proposed 1-year national CCR adjustment factor of 0.961555 and a 
proposed 2-year national CCR adjustment factor of 0.924588 (calculated 
by squaring the proposed 1-year factor). When calculating the proposed 
fixed-loss amount for FY 2022, we assigned the statewide average CCR 
for the upcoming fiscal year to all providers who were assigned the 
statewide average in the March 2020 PSF or whose CCR was missing in the 
March 2020 PSF. For all other providers, we multiplied their CCR from 
the March 2020 PSF by the proposed 2-year national CCR adjustment 
factor.
(3) Fixed-Loss Amount for LTCH PPS Standard Federal Payment Rate Cases 
for FY 2022
    In the proposed rule, we proposed no other changes to our 
methodology for calculating the proposed applicable fixed-loss amount 
for LTCH PPS standard Federal payment rate cases. Therefore, for FY 
2022, using the best available data, we calculated a proposed fixed-
loss amount that would maintain estimated HCO payments at the projected 
7.975 percent of total estimated LTCH PPS payments for LTCH PPS 
standard Federal payment rate cases (based on the payment rates and 
policies for these cases presented in the proposed rule). As described 
earlier in this section and discussed in more detail in section 
VIII.A.4. of the preamble of the proposed rule, we believe the FY 2020 
MedPAR claims were significantly impacted by COVID-19 PHE. As a result, 
we proposed to use LTCH claims data from the March 2020 update of the 
FY 2019 MedPAR file to calculate a proposed fixed-loss amount for FY 
2022. Therefore, based on LTCH claims data from the March 2020 update 
of the FY 2019 MedPAR file adjusted for charge inflation and adjusted 
CCRs from the March 2020 update of the PSF, we proposed a fixed-loss 
amount for LTCH PPS standard Federal payment rate cases for FY 2022 of 
$32,680 that would result in estimated outlier payments projected to be 
equal to 7.975 percent of estimated FY 2022 payments for such cases.
    Comment: We received multiple comments on the technical changes we 
proposed to make to the methodology for calculating the applicable 
fixed-loss amount for FY 2022 for LTCH PPS standard Federal payment 
rate cases. A commenter was supportive of the technical changes we 
proposed.
    Another commenter objected to the technical changes we proposed 
stating that these changes resulted in a significant increase to the 
proposed FY 2022 fixed-loss amount for LTCH PPS standard Federal 
payment rate cases. The commenter stated that this increase will lead 
to a reduction in high-cost outlier payments and can be avoided if CMS 
does not adopt the proposed methodology changes. The commenter stated 
that it was unclear why CMS would propose these technical changes that 
more closely align with the IPPS fixed-loss threshold methodology when 
CMS has historically always used a different methodology for the LTCH 
PPS. The commenter also explained that they attempted to replicate CMS' 
methodology and calculate the proposed fixed loss amount, but were 
unable to approximate the proposed fixed-loss amount. The commenter 
believes that CMS may have made an additional change to the methodology 
that was not disclosed in the proposed rule. Specifically, the 
commenter believes that CMS may be applying a wage index adjustment 
when determining LTCH PPS fixed-loss threshold, similar to the 
adjustment that CMS applies when determining the IPPS fixed-loss 
threshold.
    Another commenter opposed the proposed increase in the fixed-loss 
amount from FY 2021. The commenter stated that the increase will result 
in a significant reduction in the number of cases that qualify as high-
cost outliers and that to the extent that increases in the fixed-loss 
amount are necessary, they should be limited to no more than the market 
basket percent increase in any given year.

[[Page 45565]]

    Response: In response to the comments that expressed concern over 
the magnitude of the proposed increase in the fixed-loss amount, we 
remind the reader that in accordance with Sec.  412.525(a)(2)(ii), 
which implements section 1886(m)(7)(b) of the Act, our proposed 
methodology projected that the proposed fixed-loss amount for LTCH PPS 
standard Federal payment rate cases would result in total outlier 
payments for FY 2022 being equal to 7.975 percent of projected total 
LTCH PPS payments for LTCH PPS standard Federal payment rate cases. An 
analysis we conducted on the historical MedPAR claims showed that high 
cost outlier payments as a percentage of total LTCH PPS standard 
Federal payment rate payments exceeded the 7.975 percent target in 
every fiscal year since FY 2016. We currently project that in FY 2021 
high cost outlier payments as a percentage of total LTCH PPS standard 
Federal payment rate payments will be approximately 8.8 percent. We 
believe our proposed changes improve the accuracy of our model, for the 
reasons explained in the proposed rule, and will result in fixed-loss 
amounts that lead to actual outlier payments being closer to the 
statutory 7.975 percent target than would occur if we did not 
incorporate our proposed changes.
    In response to the commenter that believes we may have made an 
additional change to our methodology that was not disclosed in the 
proposed rule, we confirm that no other changes to methodology were 
made when determining the proposed fixed-loss amount for FY 2022. We 
are unable to determine with the information provided any reason the 
commenter was unable to approximate the proposed fixed-loss amount.
    After considering the comments received, we are finalizing, without 
modification, the changes we proposed to our methodology for 
calculating the applicable fixed-loss amount for LTCH PPS standard 
Federal payment rate cases. Therefore, in this final rule, we followed 
the methodology explained in section V.D.3.b.(1). of the Addendum to 
this final rule to determine the charge inflation factor that we apply 
to the charges on the MedPAR claims when calculating the fixed-loss 
amount for FY 2022. As discussed in section VIII.A.4. of the preamble 
of this final rule, we are proposing to use the FY 2019 data for the FY 
2022 LTCH PPS ratesetting in situations where the utilization patterns 
reflected in the FY 2020 data were significantly impacted by the COVID-
19 PHE. For the purposes of calculating the charge inflation factor for 
FY 2022, we used the March 2020 update of the FY 2019 MedPAR file and 
the March 2019 update of the FY 2018 MedPAR as the basis of the LTCH 
PPS standard Federal payment rate cases for the two most recently 
available Federal fiscal year time periods, as described previously in 
our methodology. As discussed in greater detail in section VIII.A.4. of 
the preamble of this final rule, due to the significant impact that the 
COVID-19 PHE had on the utilization patterns reflected in the FY 2020 
MedPAR claims, we believe these are the best available data at this 
time for the purposes of calculating the charge inflation factor for FY 
2022.
    Therefore, for this final rule, we trimmed the March 2020 update of 
the FY 2019 MedPAR file and the March 2019 update of the FY 2018 MedPAR 
file using our finalized methodology. To compute the 1-year average 
annual rate-of-change in charges per case for FY 2022, we compared the 
average covered charge per case of $195,362 ($13,926,931,065/71,288 
cases) from FY 2018 to the average covered charge per case of $207,224 
($14,172,496,534/68,392 cases) from FY 2019. This rate-of-change was 
6.0723 percent and results in a 1-year charge inflation factor of 
1.060723, a 2-year charge inflation factor of 1.125133 (calculated by 
squaring the 1-year factor), and a 3-year charge inflation factor of 
1.193455 (calculated by cubing the 1-year factor). We inflated the 
billed charges obtained from the FY 2019 MedPAR file by this 3-year 
charge inflation factor of 1.193455 when determining the fixed-loss 
amount for LTCH PPS standard Federal payment rate cases for FY 2022.
    In this final rule, we followed the methodology explained in 
section V.D.3.b.(2). of the Addendum to this final rule to determine 
the CCRs to use when calculating the fixed-loss amount for FY 2022. In 
this final rule, we are using the FY 2019 data for the FY 2022 LTCH PPS 
ratesetting in situations where the utilization patterns reflected in 
the FY 2020 data were significantly impacted by the COVID-19 PHE, for 
the reasons discussed in section VIII.A.4. of the preamble of this 
final rule. Ordinarily, for this FY 2022 final rule, we would use CCR 
data from the March 2021 update of the PSF when determining the CCRs 
used for calculating the fixed-loss amount for FY 2022. However, for 
many LTCHs, these CCR data were derived from cost reports that ended 
during the COVID-19 PHE. Therefore, as we proposed, for the purposes of 
determining the CCRs used for calculating the fixed-loss amount for FY 
2022, we are using the March 2020 PSF as the most recently available 
PSF and the March 2019 PSF as the PSF that was made available 1 year 
prior to the most recently available PSF, as described in our 
methodology. Since the CCR data from the March 2020 update of the PSF 
was derived from cost reports ending prior to the COVID-19 PHE, as 
discussed in section VIII.A.4. of the preamble of this final rule, we 
believe these are the best available data at this time for the purposes 
of determining the CCRs used to calculate the fixed-loss amount for FY 
2022. In addition, as we proposed, we also are using claims from the 
March 2020 update of the FY 2019 MedPAR file in our calculation of 
average case-weighted CCRs described in Step 4 of our methodology. As 
discussed in greater detail in section VIII.A.4. of the preamble of 
this final rule, due to the significant impact that the COVID-19 PHE 
had on the utilization patterns reflected in the FY 2020 MedPAR claims, 
we believe these are the best available data at this time for the 
purposes of calculating the average case-weighted CCRs.
    Specifically, to calculate the CCRs to use in this final rule, we 
followed our finalized methodology described previously and, for 
providers with LTCH PPS standard Federal payment rate cases in the 
March 2020 update of the FY 2019 MedPAR file, we identified their CCRs 
from both the March 2019 PSF and March 2020 PSF. After performing the 
trims outlined in our methodology, we used the LTCH PPS standard 
Federal payment rate case counts from the FY 2019 MedPAR file 
(classified using finalized Version 39 of the GROUPER) to calculate the 
case-weighted average CCRs. For this final rule, we calculated a March 
2019 national average case-weighted CCR of 0.256374 and a March 2020 
national average case-weighted CCR of 0.246517. We then calculated the 
national CCR adjustment factor by dividing the March 2020 national 
average case-weighted CCR by the March 2019 national average case-
weighted CCR. This results in a 1-year national CCR adjustment factor 
of 0.961554 and a 2-year national CCR adjustment factor of 0.924586 
(calculated by squaring the 1-year factor). When calculating the fixed-
loss amount for FY 2022, we assigned the statewide average CCR for the 
upcoming fiscal year to all providers who were assigned the statewide 
average in the March 2020 PSF or whose CCR was missing in the March 
2020 PSF. For all other providers, we multiplied their CCR from the 
March 2020 PSF by the 2-year national CCR adjustment factor.
    For FY 2022, using the best available data, we calculated a fixed-
loss amount that would maintain estimated HCO payments at the projected 
7.975 percent

[[Page 45566]]

of total estimated LTCH PPS payments for LTCH PPS standard Federal 
payment rate cases (based on the payment rates and policies for these 
cases presented in the final rule). As described earlier in this 
section and discussed in more detail in section VIII.A.4. of the 
preamble of this final rule, we believe the FY 2020 MedPAR claims were 
significantly impacted by COVID-19 PHE. As a result, we are using LTCH 
claims data from the March 2020 update of the FY 2019 MedPAR file to 
calculate a fixed-loss amount for FY 2022. Therefore, based on LTCH 
claims data from the March 2020 update of the FY 2019 MedPAR file 
adjusted for charge inflation and adjusted CCRs from the March 2020 
update of the PSF, under the broad authority of section 123(a)(1) of 
the BBRA and section 307(b)(1) of the BIPA, we are finalizing a fixed-
loss amount for LTCH PPS standard Federal payment rate cases for FY 
2022 of $33,015 that will result in estimated outlier payments 
projected to be equal to 7.975 percent of estimated FY 2022 payments 
for such cases.
    We also are continuing to make an additional HCO payment for the 
cost of an LTCH PPS standard Federal payment rate case that exceeds the 
HCO threshold amount that is equal to 80 percent of the difference 
between the estimated cost of the case and the outlier threshold (the 
sum of the adjusted LTCH PPS standard Federal payment rate payment and 
the fixed-loss amount for LTCH PPS standard Federal payment rate cases 
of $33,015).
4. High-Cost Outlier Payments for Site Neutral Payment Rate Cases
    When we implemented the application of the site neutral payment 
rate in FY 2016, in examining the appropriate fixed-loss amount for 
site neutral payment rate cases issue, we considered how LTCH 
discharges based on historical claims data would have been classified 
under the dual rate LTCH PPS payment structure and the CMS' Office of 
the Actuary projections regarding how LTCHs will likely respond to our 
implementation of policies resulting from the statutory payment 
changes. We again relied on these considerations and actuarial 
projections in FY 2017 and FY 2018 because the historical claims data 
available in each of these years were not all subject to the LTCH PPS 
dual rate payment system. Similarly, for FYs 2019 through 2021, we 
continued to rely on these considerations and actuarial projections 
because, due to the transitional blended payment policy for site 
neutral payment rate cases, FY 2018 and FY 2019 claims for these cases 
were not subject to the full effect of the site neutral payment rate.
    For FYs 2016 through 2021, at that time our actuaries projected 
that the proportion of cases that would qualify as LTCH PPS standard 
Federal payment rate cases versus site neutral payment rate cases under 
the statutory provisions would remain consistent with what is reflected 
in the historical LTCH PPS claims data. Although our actuaries did not 
project an immediate change in the proportions found in the historical 
data, they did project cost and resource changes to account for the 
lower payment rates. Our actuaries also projected that the costs and 
resource use for cases paid at the site neutral payment rate would 
likely be lower, on average, than the costs and resource use for cases 
paid at the LTCH PPS standard Federal payment rate and would likely 
mirror the costs and resource use for IPPS cases assigned to the same 
MS-DRG, regardless of whether the proportion of site neutral payment 
rate cases in the future remains similar to what is found based on the 
historical data. As discussed in the FY 2016 IPPS/LTCH PPS final rule 
(80 FR 49619), this actuarial assumption is based on our expectation 
that site neutral payment rate cases would generally be paid based on 
an IPPS comparable per diem amount under the statutory LTCH PPS payment 
changes that began in FY 2016, which, in the majority of cases, is much 
lower than the payment that would have been paid if these statutory 
changes were not enacted. In light of these projections and 
expectations, we discussed that we believed that the use of a single 
fixed-loss amount and HCO target for all LTCH PPS cases would be 
problematic. In addition, we discussed that we did not believe that it 
would be appropriate for comparable LTCH PPS site neutral payment rate 
cases to receive dramatically different HCO payments from those cases 
that would be paid under the IPPS (80 FR 49617 through 49619 and 81 FR 
57305 through 57307). For those reasons, we stated that we believed 
that the most appropriate fixed-loss amount for site neutral payment 
rate cases for FYs 2016 through 2021 would be equal to the IPPS fixed-
loss amount for that particular fiscal year. Therefore, we established 
the fixed-loss amount for site neutral payment rate cases as the 
corresponding IPPS fixed-loss amounts for FYs 2016 through 2021. In 
particular, in FY 2021, we established the fixed-loss amount for site 
neutral payment rate cases as the FY 2021 IPPS fixed-loss amount of 
$29,064 (as corrected at 85 FR 78756).
    As noted earlier, because not all claims in the data used for this 
FY 2022 IPPS/LTCH PPS final rule were subject to the unblended site 
neutral payment rate, we continue to rely on the same considerations 
and actuarial projections used in FYs 2016 through 2021 when developing 
a fixed-loss amount for site neutral payment rate cases for FY 2022. 
Our actuaries continue to project that site neutral payment rate cases 
in FY 2022 will continue to mirror an IPPS case paid under the same MS-
DRG. That is, our actuaries continue to project that the costs and 
resource use for FY 2022 cases paid at the site neutral payment rate 
would likely be lower, on average, than the costs and resource use for 
cases paid at the LTCH PPS standard Federal payment rate and will 
likely mirror the costs and resource use for IPPS cases assigned to the 
same MS-DRG, regardless of whether the proportion of site neutral 
payment rate cases in the future remains similar to what was found 
based on the historical data. (Based on the FY 2019 LTCH claims data 
used in the development of this FY 2022 IPPS/LTCH PPS final rule, 
approximately 75 percent of LTCH cases were paid the LTCH PPS standard 
Federal payment rate and approximately 25 percent of LTCH cases were 
paid the site neutral payment rate for discharges occurring in FY 
2019.)
    For these reasons, we continue to believe that the most appropriate 
fixed-loss amount for site neutral payment rate cases for FY 2022 is 
the IPPS fixed-loss amount for FY 2022. Therefore, consistent with past 
practice, in the FY 2022 IPPS/LTCH PPS proposed rule (86 FR 25738), we 
proposed that the applicable HCO threshold for site neutral payment 
rate cases is the sum of the site neutral payment rate for the case and 
the IPPS fixed-loss amount. That is, we proposed a fixed-loss amount 
for site neutral payment rate cases of $30,967, which is the same FY 
2022 IPPS fixed-loss amount discussed in section II.A.4.j.(1). of the 
Addendum to the proposed rule. Accordingly, for FY 2022, we proposed to 
calculate a HCO payment for site neutral payment rate cases with costs 
that exceed the HCO threshold amount that is equal to 80 percent of the 
difference between the estimated cost of the case and the outlier 
threshold (the sum of the site neutral payment rate payment and the 
proposed fixed-loss amount for site neutral payment rate cases of 
$30,967).
    Comment: Some commenters opposed the proposed fixed-loss amount for 
site neutral payment rate cases. A commenter stated that increases in 
the fixed-loss threshold for site neutral payment rate cases should be 
limited to no more than the market basket percent increase. Another 
commenter stated that

[[Page 45567]]

site neutral patients have greater resource use and costs, on average, 
than IPPS hospital patients assigned to the same DRGs. Therefore the 
``significant increase'' in the proposed fixed-loss amount for site 
neutral payment rate cases will be magnified for LTCHs treating high-
cost Medicare patients. The commenter also stated that compared to IPPS 
hospitals, LTCHs have a greater concentration of discharges in only a 
few MS-LTC-DRGs and therefore even small changes to the IPPS fixed-loss 
threshold can have significant impact on LTCH PPS payments for site-
neutral cases.
    Response: As already stated, our actuaries continue to project that 
site neutral payment rate cases in FY 2022 will continue to mirror an 
IPPS case paid under the same MS-DRG. That is, our actuaries continue 
to project that the costs and resource use for FY 2022 cases paid at 
the site neutral payment rate would likely be lower, on average, than 
the costs and resource use for cases paid at the LTCH PPS standard 
Federal payment rate and will likely mirror the costs and resource use 
for IPPS cases assigned to the same MS DRG, on average, regardless of 
whether the proportion of site neutral payment rate cases in the future 
remains similar to what was found based on the historical data. For 
these reasons, we continue to believe that the most appropriate fixed-
loss amount for site neutral payment rate cases for FY 2022 is the IPPS 
fixed-loss amount for FY 2022.
    Therefore, after considering public comments on our proposals, we 
are finalizing our proposals as described above, without modification. 
Therefore, for FY 2022, as we proposed, we are establishing that the 
applicable HCO threshold for site neutral payment rate cases is the sum 
of the site neutral payment rate for the case and the IPPS fixed loss 
amount. That is, we are establishing a fixed-loss amount for site 
neutral payment rate cases of $30,988, which is the same FY 2022 IPPS 
fixed-loss amount discussed in section II.A.4.j.(1). of the Addendum to 
this final rule. Accordingly, under this policy, for FY 2022, we will 
calculate a HCO payment for site neutral payment rate cases with costs 
that exceed the HCO threshold amount, which is equal to 80 percent of 
the difference between the estimated cost of the case and the outlier 
threshold (the sum of site neutral payment rate payment and the fixed-
loss amount for site neutral payment rate cases of $30,988).
    In establishing a HCO policy for site neutral payment rate cases, 
we established a budget neutrality adjustment under Sec.  
412.522(c)(2)(i). We established this requirement because we believed, 
and continue to believe, that the HCO policy for site neutral payment 
rate cases should be budget neutral, just as the HCO policy for LTCH 
PPS standard Federal payment rate cases is budget neutral, meaning that 
estimated site neutral payment rate HCO payments should not result in 
any change in estimated aggregate LTCH PPS payments.
    To ensure that estimated HCO payments payable to site neutral 
payment rate cases in FY 2022 would not result in any increase in 
estimated aggregate FY 2022 LTCH PPS payments, under the budget 
neutrality requirement at Sec.  412.522(c)(2)(i), it is necessary to 
reduce site neutral payment rate payments by 5.1 percent to account for 
the estimated additional HCO payments payable to those cases in FY 
2022, in general, we proposed to continue this policy.
    As explained in the proposed rule, consistent with the IPPS HCO 
payment threshold, we estimate the proposed fixed-loss threshold would 
result in FY 2022 HCO payments for site neutral payment rate cases to 
equal 5.1 percent of the site neutral payment rate payments that are 
based on the IPPS comparable per diem amount. As such, to ensure 
estimated HCO payments payable for site neutral payment rate cases in 
FY 2022 would not result in any increase in estimated aggregate FY 2022 
LTCH PPS payments, under the budget neutrality requirement at Sec.  
412.522(c)(2)(i), as we explained in the proposed rule, it is necessary 
to reduce the site neutral payment rate amount paid under Sec.  
412.522(c)(1)(i) by 5.1 percent to account for the estimated additional 
HCO payments payable for site neutral payment rate cases in FY 2022. In 
order to achieve this, for FY 2022, we proposed to apply a budget 
neutrality factor of 0.949 (that is, the decimal equivalent of a 5.1 
percent reduction, determined as 1.0-5.1/100 = 0.949) to the site 
neutral payment rate for those site neutral payment rate cases paid 
under Sec.  412.522(c)(1)(i). We note that, consistent with our current 
policy, this HCO budget neutrality adjustment would not be applied to 
the HCO portion of the site neutral payment rate amount (81 FR 57309).
    Comment: Some commenters, as they have done since the inception of 
the dual rate payment system that created the site neutral payment 
rate, objected to the proposed site neutral payment rate HCO budget 
neutrality adjustment. The commenters' primary objection continued to 
be based on their belief that, because the IPPS base rates used in the 
IPPS comparable per diem amount calculation of the site neutral payment 
rate include a budget neutrality adjustment for IPPS HCO payments (for 
example, a 5.1 percent adjustment on the operating IPPS standardized 
amount), a ``second'' budget neutrality factor is not necessary and is, 
in fact, redundant and results in a systematic reduction of LTCH site-
neutral payments.
    Response: We continue to disagree with the commenters that a budget 
neutrality adjustment for site neutral payment rate HCO payments is 
unnecessary or duplicative. We have stated such disagreement during 
each previous rulemaking cycle. We refer readers to 84 FR 42648 through 
42649, 83 FR 41737 through 41738, 82 FR 38545 through 38546, 81 FR 
57308 through 57309, and 80 FR 49621 through 49622 for more information 
on our responses to these comments.
    After consideration of public comments, for the reasons discussed 
above, we are adopting our proposed site neutral payment rate HCO 
budget neutrality adjustment as final without modification. 
Specifically, for FY 2022, as we proposed, we are applying a budget 
neutrality factor of 0.949 (that is, the decimal equivalent of a 5.1 
percent reduction, determined as 1.0-5.1/100 = 0.949) to the site 
neutral payment rate for those site neutral payment rate cases paid 
under Sec.  412.522(c)(1)(i). We note that, consistent with our current 
policy, this HCO budget neutrality adjustment will not apply to the HCO 
portion of the site neutral payment rate amount.

E. Update to the IPPS Comparable Amount To Reflect the Statutory 
Changes to the IPPS DSH Payment Adjustment Methodology

    In the FY 2014 IPPS/LTCH PPS final rule (78 FR 50766), we 
established a policy to reflect the changes to the Medicare IPPS DSH 
payment adjustment methodology made by section 3133 of the Affordable 
Care Act in the calculation of the ``IPPS comparable amount'' under the 
SSO policy at Sec.  412.529 and the ``IPPS equivalent amount'' under 
the site neutral payment rate at Sec.  412.522. Historically, the 
determination of both the ``IPPS comparable amount'' and the ``IPPS 
equivalent amount'' includes an amount for inpatient operating costs 
``for the costs of serving a disproportionate share of low-income 
patients.'' Under the statutory changes to the Medicare DSH payment 
adjustment methodology that began in FY 2014, in general, eligible IPPS 
hospitals receive an empirically justified Medicare DSH payment equal 
to 25 percent of the amount they

[[Page 45568]]

otherwise would have received under the statutory formula for Medicare 
DSH payments prior to the amendments made by the Affordable Care Act. 
The remaining amount, equal to an estimate of 75 percent of the amount 
that otherwise would have been paid as Medicare DSH payments, reduced 
to reflect changes in the percentage of individuals who are uninsured 
and any additional statutory adjustment, is made available to make 
additional payments to each hospital that qualifies for Medicare DSH 
payments and that has uncompensated care. The additional uncompensated 
care payments are based on the hospital's amount of uncompensated care 
for a given time period relative to the total amount of uncompensated 
care for that same time period reported by all IPPS hospitals that 
receive Medicare DSH payments.
    To reflect the statutory changes to the Medicare DSH payment 
adjustment methodology in the calculation of the ``IPPS comparable 
amount'' and the ``IPPS equivalent amount'' under the LTCH PPS, we 
stated that we will include a reduced Medicare DSH payment amount that 
reflects the projected percentage of the payment amount calculated 
based on the statutory Medicare DSH payment formula prior to the 
amendments made by the Affordable Care Act that will be paid to 
eligible IPPS hospitals as empirically justified Medicare DSH payments 
and uncompensated care payments in that year (that is, a percentage of 
the operating Medicare DSH payment amount that has historically been 
reflected in the LTCH PPS payments that are based on IPPS rates). We 
also stated that the projected percentage will be updated annually, 
consistent with the annual determination of the amount of uncompensated 
care payments that will be made to eligible IPPS hospitals. We believe 
that this approach results in appropriate payments under the LTCH PPS 
and is consistent with our intention that the ``IPPS comparable 
amount'' and the ``IPPS equivalent amount'' under the LTCH PPS closely 
resemble what an IPPS payment would have been for the same episode of 
care, while recognizing that some features of the IPPS cannot be 
translated directly into the LTCH PPS (79 FR 50766 through 50767).
    As discussed in the FY 2022 IPPS/LTCH PPS proposed rule (86 FR 
25739), based on the data available at that time, we proposed to 
establish that the calculation of the ``IPPS comparable amount'' under 
Sec.  412.529 would include an applicable operating Medicare DSH 
payment amount that is equal to 79.11 percent of the operating Medicare 
DSH payment amount that would have been paid based on the statutory 
Medicare DSH payment formula absent the amendments made by the 
Affordable Care Act. Furthermore, consistent with our historical 
practice, we proposed that, if more recent data became available, we 
would use that data to determine this factor in the final rule.
    We did not receive any public comments in response to our proposal, 
and we are adopting it as final. However, as we proposed, we are 
determining the factor in this final rule using more recent data. For 
FY 2022, as discussed in greater detail in section V.E.4.b. of the 
preamble of this final rule, based on the most recent data available, 
our estimate of 75 percent of the amount that would otherwise have been 
paid as Medicare DSH payments (under the methodology outlined in 
section 1886(r)(2) of the Act) is adjusted to 68.57 percent of that 
amount to reflect the change in the percentage of individuals who are 
uninsured. The resulting amount is then used to determine the amount 
available to make uncompensated care payments to eligible IPPS 
hospitals in FY 2022. In other words, the amount of the Medicare DSH 
payments that would have been made prior to the amendments made by the 
Affordable Care Act is adjusted to 51.43 percent (the product of 75 
percent and 68.57 percent) and the resulting amount is used to 
calculate the uncompensated care payments to eligible hospitals. As a 
result, for FY 2022, we project that the reduction in the amount of 
Medicare DSH payments under section 1886(r)(1) of the Act, along with 
the payments for uncompensated care under section 1886(r)(2) of the 
Act, will result in overall Medicare DSH payments of 76.43 percent of 
the amount of Medicare DSH payments that would otherwise have been made 
in the absence of the amendments made by the Affordable Care Act (that 
is, 25 percent + 51.43 percent = 76.43 percent).
    Therefore, for FY 2022, consistent with our proposal, we are 
establishing that the calculation of the ``IPPS comparable amount'' 
under Sec.  412.529 will include an applicable operating Medicare DSH 
payment amount that is equal to 76.43 percent of the operating Medicare 
DSH payment amount that would have been paid based on the statutory 
Medicare DSH payment formula absent the amendments made by the 
Affordable Care Act.

F. Computing the Adjusted LTCH PPS Federal Prospective Payments for FY 
2022

    Section 412.525 sets forth the adjustments to the LTCH PPS standard 
Federal payment rate. Under the dual rate LTCH PPS payment structure, 
only LTCH PPS cases that meet the statutory criteria to be excluded 
from the site neutral payment rate are paid based on the LTCH PPS 
standard Federal payment rate. Under Sec.  412.525(c), the LTCH PPS 
standard Federal payment rate is adjusted to account for differences in 
area wages by multiplying the labor-related share of the LTCH PPS 
standard Federal payment rate for a case by the applicable LTCH PPS 
wage index (the FY 2022 values are shown in Tables 12A through 12B 
listed in section VI. of the Addendum to this final rule and are 
available via the internet on the CMS website). The LTCH PPS standard 
Federal payment rate is also adjusted to account for the higher costs 
of LTCHs located in Alaska and Hawaii by the applicable COLA factors 
(the final FY 2022 factors are shown in the chart in section V.C. of 
this Addendum) in accordance with Sec.  412.525(b). In this final rule, 
we are establishing an LTCH PPS standard Federal payment rate for FY 
2022 of $44,713.67, as discussed in section V.A. of the Addendum to 
this final rule. We illustrate the methodology to adjust the LTCH PPS 
standard Federal payment rate for FY 2022 in the following example:
    Example:
    During FY 2022, a Medicare discharge that meets the criteria to be 
excluded from the site neutral payment rate, that is, an LTCH PPS 
standard Federal payment rate case, is from an LTCH that is located in 
CBSA 16984, which has a FY 2022 LTCH PPS wage index value of 1.0372 
(obtained from Table 12A listed in section VI. of the Addendum to this 
final rule and available via the internet on the CMS website). The 
Medicare patient case is classified into MS-LTC-DRG 189 (Pulmonary 
Edema & Respiratory Failure), which has a relative weight for FY 2022 
of 0.9448 (obtained from Table 11 listed in section VI. of the Addendum 
to this final rule and available via the internet on the CMS website). 
The LTCH submitted quality reporting data for FY 2022 in accordance 
with the LTCH QRP under section 1886(m)(5) of the Act.
    To calculate the LTCH's total adjusted Federal prospective payment 
for this Medicare patient case in FY 2022, we computed the wage-
adjusted Federal prospective payment amount by multiplying the 
unadjusted FY 2022 LTCH PPS standard Federal payment

[[Page 45569]]

rate ($44,713.67) by the labor-related share (0.679 percent) and the 
wage index value (1.0372). This wage-adjusted amount was then added to 
the nonlabor-related portion of the unadjusted LTCH PPS standard 
Federal payment rate (0.321 percent; adjusted for cost of living, if 
applicable) to determine the adjusted LTCH PPS standard Federal payment 
rate, which is then multiplied by the MS-LTC-DRG relative weight 
(0.9448) to calculate the total adjusted LTCH PPS standard Federal 
prospective payment for FY 2022 ($43,312.54). The table illustrates the 
components of the calculations in this example.
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VI. Tables Referenced in This Final Rule Generally Available Through 
the Internet on the CMS Website

    This section lists the tables referred to throughout the preamble 
of this final rule and in the Addendum. In the past, a majority of 
these tables were published in the Federal Register as part of the 
annual proposed and final rules. However, similar to FYs 2012 through 
2021, for the FY 2022 rulemaking cycle, the IPPS and LTCH PPS tables 
will not be published in the Federal Register in the annual IPPS/LTCH 
PPS proposed and final rules and will be available through the 
internet. Specifically, all IPPS tables listed in the final rule, with 
the exception of IPPS Tables 1A, 1B, 1C, and 1D, and LTCH PPS Table 1E, 
will generally be available through the internet. IPPS Tables 1A, 1B, 
1C, and 1D, and LTCH PPS Table 1E are displayed at the end of this 
section and will continue to be published in the Federal Register as 
part of the annual proposed and final rules. For additional discussion 
of the information included in the IPPS and LTCH PPS tables associated 
with the IPPS/LTCH PPS proposed and final rules, as well as prior 
changes to the information included in these tables, we refer readers 
to the FY 2021 IPPS/LTCH PPS final rule (85 FR 59059 through 59060).
    In addition, under the HAC Reduction Program, established by 
section 3008 of the Affordable Care Act, a hospital's total payment may 
be reduced by 1 percent if it is in the lowest HAC performance 
quartile. The hospital-level data for the FY 2022 HAC Reduction Program 
will be made publicly available once it has undergone the review and 
corrections process.
    As was the case for the FY 2021 IPPS/LTCH PPS proposed and final 
rules, we are no longer including Table 15, which had typically 
included the fiscal year readmissions payment adjustment factors 
because hospitals have not yet had the opportunity to review and 
correct the data before the data are made public under our policy 
regarding the reporting of hospital-specific data. After hospitals have 
been given an opportunity to review and correct their calculations for 
FY 2022, we will post Table 15 (which will be available via the 
internet on the CMS website) to display the final FY 2022 readmissions 
payment adjustment factors that will be applicable to discharges 
occurring on or after October 1, 2021. We expect Table 15 will be 
posted on the CMS website in the fall of 2021.
    Readers who experience any problems accessing any of the tables 
that are posted on the CMS websites identified in this final rule 
should contact Michael Treitel at (410) 786-4552.
    The following IPPS tables for this final rule are generally 
available through the internet on the CMS website at: http://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/AcuteInpatientPPS/index.html. Click on the link on the left side of the 
screen titled, ``FY 2022 IPPS Final rule Home Page'' or ``Acute 
Inpatient -Files- for Download.''

Table 2--Case-Mix Index and Wage Index Table by CCN--FY 2022 Final Rule
Table 3--Wage Index Table by CBSA--FY 2022 Final Rule
Table 4A--List of Counties Eligible for the Out-Migration Adjustment 
under Section 1886(d)(13) of the Act--FY 2022 Final Rule
Table 4B--Counties Redesignated under Section 1886(d)(8)(B) of the Act 
(LUGAR Counties)--FY 2022 Final Rule
Table 5-- List of Medicare Severity Diagnosis-Related Groups (MS-DRGs), 
Relative Weighting Factors, and Geometric and Arithmetic Mean Length of 
Stay--FY 2022
Table 6A--New Diagnosis Codes--FY 2022
Table 6B--New Procedure Codes--FY 2022
Table 6C--Invalid Diagnosis Codes--FY 2022
Table 6D--Invalid Procedure Codes--FY 2022
Table 6E--Revised Diagnosis Code Titles--FY 2022
Table 6F--Revised Procedure Code Titles--FY 2022
Table 6G.1--Secondary Diagnosis Order Additions to the CC Exclusions 
List--FY 2022
Table 6G.2--Principal Diagnosis Order Additions to the CC Exclusions 
List--FY 2022
Table 6H.1--Secondary Diagnosis Order Deletions to the CC Exclusions 
List--FY 2022
Table 6H.2--Principal Diagnosis Order Deletions to the CC Exclusions 
List--FY 2022
Table 6I--Complete MCC List--FY 2022
Table 6I.1--Additions to the MCC List--FY 2022
Table 6I.2--Deletions to the MCC List--FY 2022
Table 6J--Complete CC List--FY 2022
Table 6J.1--Additions to the CC List--FY 2022
Table 6J.2--Deletions to the CC List--FY 2022
Table 6K-- Complete List of CC Exclusions--FY 2022
Table 6P-- ICD-10-CM and ICD-10-PCS Codes for MS-DRG Changes--FY 2022 
(Table 6P contains multiple tables, 6P.1a. through 6P.3a that

[[Page 45570]]

include the ICD-10-CM and ICD-10-PCS code lists relating to specific 
MS-DRG changes. These tables are referred to throughout section II.D. 
of the preamble of this final rule.)
Table 7A--Medicare Prospective Payment System Selected Percentile 
Lengths of Stay: FY 2019 MedPAR Update March 2020--GROUPER Version 38 
MS-DRGs
Table 7B--Medicare Prospective Payment System Selected Percentile 
Lengths of Stay: FY 2019 MedPAR Update March 2020--GROUPER Version 39 
MS-DRGs
Table 8A--Final FY 2022 Statewide Average Operating Cost-to-Charge 
Ratios (CCRs) for Acute Care Hospitals (Urban and Rural)
Table 8B--Final FY 2022 Statewide Average Capital Cost-to-Charge Ratios 
(CCRs) for Acute Care Hospitals
Table 18--Final FY 2022 Medicare DSH Uncompensated Care Payment Factor 
3

    The following LTCH PPS tables for this FY 2022 final rule are 
available through the internet on the CMS website at: http://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/LongTermCareHospitalPPS/index.html under the list item for Regulation 
Number CMS-1752-F:

Table 8C--FY 2022 Statewide Average Total Cost-to-Charge Ratios (CCRs) 
for LTCHs (Urban and Rural)
Table 11--MS-LTC-DRGs, Relative Weights, Geometric Average Length of 
Stay, and Short-Stay Outlier (SSO) Threshold for LTCH PPS Discharges 
Occurring from October 1, 2021 through September 30, 2022
Table 12A--LTCH PPS Wage Index for Urban Areas for Discharges Occurring 
from October 1, 2021 through September 30, 2022
Table 12B--LTCH PPS Wage Index for Rural Areas for Discharges Occurring 
from October 1, 2021 through September 30, 2022
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BILLING CODE 4120-01-C

Appendix A: Economic Analyses

I. Regulatory Impact Analysis

A. Statement of Need

    This final rule is necessary in order to make payment and policy 
changes under the IPPS for Medicare acute care hospital inpatient 
services for operating and capital-related costs as well as for 
certain hospitals and hospital units excluded from the IPPS. This 
final rule also is necessary to make payment and policy changes for 
Medicare hospitals under the LTCH PPS. Also, as we note later in 
this Appendix, the primary objective of the IPPS and the LTCH PPS is 
to create incentives for hospitals to operate efficiently and 
minimize unnecessary costs, while at the same time ensuring that 
payments are sufficient to adequately compensate hospitals for their 
legitimate costs in delivering necessary care to Medicare 
beneficiaries. In addition, we share national goals of preserving 
the Medicare Hospital Insurance Trust Fund.
    In this final rule, we are repealing the requirement that a 
hospital report on the Medicare cost report the median payer-
specific negotiated charge that the hospital has negotiated with all 
of its MA organization payers, by MS-DRG, for cost reporting periods 
ending on or after January 1, 2021. We are also repealing the 
market-based MS-DRG relative weight methodology that was adopted 
effective for FY 2024, and to continue using the existing cost-based 
MS-DRG relative weight methodology to set Medicare payment rates for 
inpatient stays for FY 2024 and subsequent fiscal years. As 
discussed in section V.L. of the preamble of this final rule, we 
believe we need to further consider the questions raised regarding 
the ability for this data to represent market-based pricing given 
the relationship between Medicare FFS and MA organization rates, and 
therefore the usefulness and appropriateness of this data for 
Medicare FFS ratesetting purposes. In addition, this final rule 
finalizes the Medicare wage index provisions adopted in our May 10, 
2021 interim final rule with comment period (CMS-1762-IFC), which 
amended current regulations to allow hospitals with a rural 
redesignation to reclassify through the Medicare Geographic 
Classification Review Board using the rural reclassified area as the 
geographic area in which the hospital is located. These regulatory 
changes align our policy with the decision in Bates County Memorial 
Hospital v. Azar, 464 F. Supp. 3d (D.D.C. 2020).
    Section 1886(b)(3)(B)(viii) of the Act requires subsection (d) 
hospitals to report data in accordance with the requirements of the 
Hospital IQR Program for purposes of measuring and making publicly 
available information on health care quality, and links the quality 
data submission to the annual applicable percentage increase. 
Sections 1886(b)(3)(B)(ix), 1886(n), and 1814(l) of the Act require 
eligible hospitals and CAHs to

[[Page 45572]]

demonstrate they are meaningful users of certified EHR technology 
for purposes of electronic exchange of health information to improve 
the quality of health care, and links the submission of information 
demonstrating meaningful use to the annual applicable percentage 
increase for eligible hospitals and the applicable percent for CAHs. 
Section 1886(m)(5) of the Act requires each LTCH to submit quality 
measure data in accordance with the requirements of the LTCH QRP for 
purposes of measuring and making publicly available information on 
health care quality, and in order to avoid a 2-percentage point 
reduction. Section 1886(o) of the Act requires value-based incentive 
payments for subsection (d) hospitals that meet the performance 
standards established under the Hospital VBP Program on an announced 
set of quality and efficiency measures for the purpose of measuring, 
linking measure performance to payment, and making publicly 
available information on health care quality. Section 1886(p) of the 
Act requires a reduction in payment for subsection (d) hospitals 
that rank in the worst-performing 25 percent with respect to 
measures of hospital-acquired conditions under the HAC Reduction 
Program for the purpose of measuring, linking measure performance to 
payment, and making publicly available information on health care 
quality. Section 1886(q) of the Act requires a reduction in payment 
for subsection (d) hospitals for excess readmissions based on 
measures for applicable conditions under the hospital Readmissions 
Reduction Program for the purpose of measuring, linking measure 
performance to payment, and making publicly available information on 
health care quality. Section 1866(k) of the Act applies to hospitals 
described in section 1886(d)(1)(B)(v) of the Act (referred to as 
``PPS-Exempt Cancer Hospitals'' or ``PCHs'') and requires PCHs to 
report data in accordance with the requirements of the PCHQR Program 
for purposes of measuring and making publicly available information 
on health care quality, however, there is no link to PCHs' payments. 
In this final rule, we are adopting new measures, including a 
Maternal Morbidity Structural Measure for the Hospital IQR Program 
and the COVID-19 Vaccination Coverage Among Health Care Personnel 
measure for the Hospital IQR Program, PCHQR Program, and the LTCH 
QRP, removing certain existing measures, and updating other 
administrative requirements. For the reasons described throughout 
this final rule for each change, we believe that the changes in this 
final rule, including the updates to the IPPS and LTCH PPS rates, 
the repeal of the requirement that a hospital report on the Medicare 
cost report the median payer-specific negotiated charge by MS-DRG, 
the repeal the market-based MS-DRG relative weight methodology, and 
the policies and discussions relating to applications for new 
technology add-on payments, are needed to further each of these 
goals while maintaining the financial viability of the hospital 
industry and ensuring access to high quality health care for 
Medicare beneficiaries.
    We expect that these changes will ensure that the outcomes of 
the prospective payment systems are reasonable and provide equitable 
payments, while avoiding or minimizing unintended adverse 
consequences.

B. Overall Impact

    We have examined the impacts of this final rule as required by 
Executive Order 12866 on Regulatory Planning and Review (September 
30, 1993), Executive Order 13563 on Improving Regulation and 
Regulatory Review (January 18, 2011), the Regulatory Flexibility Act 
(RFA) (September 19, 1980, Pub. L. 96-354), section 1102(b) of the 
Act, section 202 of the Unfunded Mandates Reform Act of 1995 (March 
22, 1995; Pub. L. 104-4), Executive Order 13132 on Federalism 
(August 4, 1999), and the Congressional Review Act (5 U.S.C. 804(2).
    Executive Orders 12866 and 13563 direct agencies to assess all 
costs and benefits of available regulatory alternatives and, if 
regulation is necessary, to select regulatory approaches that 
maximize net benefits (including potential economic, environmental, 
public health and safety effects, distributive impacts, and equity). 
Section 3(f) of Executive Order 12866 defines a ``significant 
regulatory action'' as an action that is likely to result in a rule: 
(1) Having an annual effect on the economy of $100 million or more 
in any 1 year, or adversely and materially affecting a sector of the 
economy, productivity, competition, jobs, the environment, public 
health or safety, or State, local or tribal governments or 
communities (also referred to as ``economically significant''); (2) 
creating a serious inconsistency or otherwise interfering with an 
action taken or planned by another agency; (3) materially altering 
the budgetary impacts of entitlement grants, user fees, or loan 
programs or the rights and obligations of recipients thereof; or (4) 
raising novel legal or policy issues arising out of legal mandates, 
the President's priorities, or the principles set forth in the 
Executive Order.
    A regulatory impact analysis (RIA) must be prepared for major 
rules with significant regulatory action(s) and/or with economically 
significant effects ($100 million or more in any 1 year). Based on 
our estimates, OMB's Office of Information and Regulatory Affairs 
has determined this rulemaking is ``economically significant'' as 
measured by the $100 million threshold, and hence also a major rule 
under Subtitle E of the Small Business Regulatory Enforcement 
Fairness Act of 1996 (also known as the Congressional Review Act)''. 
Accordingly, we have prepared a Regulatory Impact Analysis that to 
the best of our ability presents the costs and benefits of the 
rulemaking. We estimate that the changes for FY 2022 acute care 
hospital operating and capital payments will redistribute amounts in 
excess of $100 million to acute care hospitals. The applicable 
percentage increase to the IPPS rates required by the statute, in 
conjunction with other payment changes in this final rule, will 
result in an estimated $2.3 billion increase in FY 2022 payments, 
primarily driven by: (a) A combined $1.6 billion increase in FY 2022 
operating payments, including uncompensated care payments and the 
recently enacted statutory provision that provides for an imputed 
floor adjustment for all-urban States in a non-budget neutral manner 
beginning in FY 2022 and discussed in section III.G.2. of this rule, 
and (b) a combined increase of $0.7 billion resulting from estimated 
changes in new technology add-on payments, and FY 2022 capital 
payments. These changes are relative to payments made in FY 2021. 
The impact analysis of the capital payments can be found in section 
I.I. of this Appendix. In addition, as described in section I.J. of 
this Appendix, LTCHs are expected to experience an increase in 
payments by approximately $42 million in FY 2022 relative to FY 
2021.
    Our operating impact estimate includes the 0.5 percentage point 
adjustment required under section 414 of the MACRA applied to the 
IPPS standardized amount, as discussed in section II.D. of the 
preamble of this final rule. In addition, our operating payment 
impact estimate includes the 2.0 percent hospital update to the 
standardized amount (which includes the estimated 2.7 percent market 
basket update reduced by 0.7 percentage point for the productivity 
adjustment). The estimates of IPPS operating payments to acute care 
hospitals do not reflect any changes in hospital admissions or real 
case-mix intensity, which will also affect overall payment changes.
    The analysis in this Appendix, in conjunction with the remainder 
of this document, demonstrates that this final rule is consistent 
with the regulatory philosophy and principles identified in 
Executive Orders 12866 and 13563, the RFA, and section 1102(b) of 
the Act. This final rule would affect payments to a substantial 
number of small rural hospitals, as well as other classes of 
hospitals, and the effects on some hospitals may be significant. 
Finally, in accordance with the provisions of Executive Order 12866, 
the Executive Office of Management and Budget has reviewed this 
final rule.

C. Objectives of the IPPS and the LTCH PPS

    The primary objective of the IPPS and the LTCH PPS is to create 
incentives for hospitals to operate efficiently and minimize 
unnecessary costs, while at the same time ensuring that payments are 
sufficient to adequately compensate hospitals for their costs in 
delivering necessary care to Medicare beneficiaries. In addition, we 
share national goals of preserving the Medicare Hospital Insurance 
Trust Fund.
    We believe that the changes in this final rule will further each 
of these goals while maintaining the financial viability of the 
hospital industry and ensuring access to high quality health care 
for Medicare beneficiaries. We expect that these changes will ensure 
that the outcomes of the prospective payment systems are reasonable 
and equitable, while avoiding or minimizing unintended adverse 
consequences.
    Because this final rule contains a range of policies, we refer 
readers to the section of the final rule where each policy is 
discussed. These sections include the rationale for our decisions, 
including the need for the policy.

D. Limitations of Our Analysis

    The following quantitative analysis presents the projected 
effects of our policy

[[Page 45573]]

changes, as well as statutory changes effective for FY 2022, on 
various hospital groups. We estimate the effects of individual 
policy changes by estimating payments per case, while holding all 
other payment policies constant. We use the best data available, 
but, generally unless specifically indicated, we do not attempt to 
make adjustments for future changes in variables such as admissions, 
lengths of stay, case mix, changes to the Medicare population, or 
incentives. In addition, we discuss limitations of our analysis for 
specific policies in the discussion of those policies as needed.

E. Hospitals Included In and Excluded From the IPPS

    The prospective payment systems for hospital inpatient operating 
and capital related- costs of acute care hospitals encompass most 
general short-term, acute care hospitals that participate in the 
Medicare program. There were 27 Indian Health Service hospitals in 
our database, which we excluded from the analysis due to the special 
characteristics of the prospective payment methodology for these 
hospitals. Among other short term, acute care hospitals, hospitals 
in Maryland are paid in accordance with the Maryland Total Cost of 
Care Model, and hospitals located outside the 50 States, the 
District of Columbia, and Puerto Rico (that is, 6 short-term acute 
care hospitals located in the U.S. Virgin Islands, Guam, the 
Northern Mariana Islands, and American Samoa) receive payment for 
inpatient hospital services they furnish on the basis of reasonable 
costs, subject to a rate-of-increase ceiling.
    As discussed in section II.A.4 of the Addendum to this final 
rule, consistent with our use of the Provider Specific File (PSF), 
we included 3,195 IPPS acute care hospitals in our analysis. This 
represents approximately 53 percent of all Medicare-participating 
hospitals. The majority of this impact analysis focuses on this set 
of hospitals. There also are approximately 1,420 CAHs. These small, 
limited service hospitals are paid on the basis of reasonable costs, 
rather than under the IPPS. IPPS-excluded hospitals and units, which 
are paid under separate payment systems, include IPFs, IRFs, LTCHs, 
RNHCIs, children's hospitals, cancer hospitals, extended neoplastic 
disease care hospital, and short-term acute care hospitals located 
in the Virgin Islands, Guam, the Northern Mariana Islands, and 
American Samoa. Changes in the prospective payment systems for IPFs 
and IRFs are made through separate rulemaking. Payment impacts of 
changes to the prospective payment systems for these IPPS-excluded 
hospitals and units are not included in this final rule. The impact 
of the update and policy changes to the LTCH PPS for FY 2022 is 
discussed in section I.J. of this Appendix.

F. Effects on Hospitals and Hospital Units Excluded From the IPPS

    As discussed in section II.A.4. of the Addendum to this final 
rule, consistent with our use of the PSF, there were 94 children's 
hospitals, 11 cancer hospitals, 6 short term- acute care hospitals 
located in the Virgin Islands, Guam, the Northern Mariana Islands 
and American Samoa, 1 extended neoplastic disease care hospital, and 
15 RNHCIs being paid on a reasonable cost basis subject to the rate-
of-increase ceiling under Sec.  413.40. (In accordance with Sec.  
403.752(a) of the regulation, RNHCIs are paid under Sec.  413.40.) 
Among the remaining providers, the rehabilitation hospitals and 
units, and the LTCHs, are paid the Federal prospective per discharge 
rate under the IRF PPS and the LTCH PPS, respectively, and the 
psychiatric hospitals and units are paid the Federal per diem amount 
under the IPF PPS. As stated previously, IRFs and IPFs are not 
affected by the rate updates discussed in this final rule. The 
impacts of the changes on LTCHs are discussed in section I.J. of 
this Appendix.
    For the children's hospitals, cancer hospitals, short-term acute 
care hospitals located in the Virgin Islands, Guam, the Northern 
Mariana Islands, and American Samoa, the extended neoplastic disease 
care hospital, and RNHCIs, the update of the rate-of-increase limit 
(or target amount) is the estimated FY 2022 percentage increase in 
the 2018-based IPPS operating market basket, consistent with section 
1886(b)(3)(B)(ii) of the Act, and Sec. Sec.  403.752(a) and 413.40 
of the regulations. Consistent with current law, based on IGI's 2021 
second quarter forecast of the 2018-based IPPS market basket 
increase, we are estimating the FY 2022 update to be 2.7 percent 
(that is, the estimate of the market basket rate-of-increase), as 
discussed in section IV.A. of the preamble of this final rule. We 
used the more recent data available for this final rule to calculate 
the IPPS operating market basket update for FY 2022. However, the 
Affordable Care Act requires a productivity adjustment (0.7 
percentage point reduction for FY 2022), resulting in a 2.0 percent 
applicable percentage increase for IPPS hospitals that submit 
quality data and are meaningful EHR users, as discussed in section 
IV.A. of the preamble of this final rule. Children's hospitals, 
cancer hospitals, short term acute care hospitals located in the 
Virgin Islands, Guam, the Northern Mariana Islands, and American 
Samoa, the extended neoplastic disease care hospital, and RNHCIs 
that continue to be paid based on reasonable costs subject to rate-
of-increase limits under Sec.  413.40 of the regulations are not 
subject to the reductions in the applicable percentage increase 
required under the Affordable Care Act. Therefore, for those 
hospitals paid under Sec.  413.40 of the regulations, the update is 
the percentage increase in the 2018-based IPPS operating market 
basket for FY 2022, estimated at 2.7 percent.
    The impact of the update in the rate-of-increase limit on those 
excluded hospitals depends on the cumulative cost increases 
experienced by each excluded hospital since its applicable base 
period. For excluded hospitals that have maintained their cost 
increases at a level below the rate-of-increase limits since their 
base period, the major effect is on the level of incentive payments 
these excluded hospitals receive. Conversely, for excluded hospitals 
with cost increases above the cumulative update in their rate-of-
increase limits, the major effect is the amount of excess costs that 
would not be paid.
    We note that, under Sec.  413.40(d)(3), an excluded hospital 
that continues to be paid under the TEFRA system and whose costs 
exceed 110 percent of its rate-of-increase limit receives its rate-
of-increase limit plus the lesser of: (1) 50 Percent of its 
reasonable costs in excess of 110 percent of the limit; or (2) 10 
percent of its limit. In addition, under the various provisions set 
forth in Sec.  413.40, hospitals can obtain payment adjustments for 
justifiable increases in operating costs that exceed the limit.

G. Quantitative Effects of the Policy Changes Under the IPPS for 
Operating Costs

1. Basis and Methodology of Estimates

    In this final rule, we are announcing policy changes and payment 
rate updates for the IPPS for FY 2022 for operating costs of acute 
care hospitals. The FY 2022 updates to the capital payments to acute 
care hospitals are discussed in section I.I. of this Appendix.
    Based on the overall percentage change in payments per case 
estimated using our payment simulation model, we estimate that total 
FY 2022 operating payments will increase by 2.6 percent, compared to 
FY 2021. In addition to the applicable percentage increase, this 
amount reflects the 0.5 percentage point permanent adjustment to the 
standardized amount required under section 414 of MACRA. The impacts 
do not reflect changes in the number of hospital admissions or real 
case-mix intensity, which will also affect overall payment changes.
    We have prepared separate impact analyses of the changes to each 
system. This section deals with the changes to the operating 
inpatient prospective payment system for acute care hospitals. Our 
payment simulation model relies on the best available claims data to 
enable us to estimate the impacts on payments per case of certain 
changes in this final rule. As discussed in section I.A of this 
final rule, we believe that the FY 2019 claims data is the best 
available data for purposes of the FY 2022 ratesetting and this 
impact analysis reflects the use of that data. However, there are 
other changes for which we do not have data available that would 
allow us to estimate the payment impacts using this model. For those 
changes, we have attempted to predict the payment impacts based upon 
our experience and other more limited data.
    The data used in developing the quantitative analyses of changes 
in payments per case presented in this section are taken from the FY 
2019 MedPAR file and are consistent with our use of Provider-
Specific File (PSF) data, as discussed previously in this final 
rule. Although the analyses of the changes to the operating PPS do 
not incorporate cost data, data from the best available hospital 
cost reports were used to categorize hospitals, specifically, cost 
report data from the FY 2018 HCRIS, as also discussed previously in 
this final rule. Our analysis has several qualifications. First, in 
this analysis, we do not make adjustments for future changes in such 
variables as admissions, lengths of stay, or underlying growth in 
real case-mix. Second, due to the interdependent nature of the IPPS 
payment components, it is very difficult to precisely quantify the 
impact associated with each

[[Page 45574]]

change. Third, we use various data sources to categorize hospitals 
in the tables. In some cases, particularly the number of beds, there 
is a fair degree of variation in the data from the different 
sources. We have attempted to construct these variables with the 
best available source overall. However, for individual hospitals, 
some miscategorizations are possible.
    Using cases from the FY 2019 MedPAR file, we simulate payments 
under the operating IPPS given various combinations of payment 
parameters. As described previously, Indian Health Service hospitals 
and hospitals in Maryland were excluded from the simulations. The 
impact of payments under the capital IPPS, and the impact of 
payments for costs other than inpatient operating costs, are not 
analyzed in this section. Estimated payment impacts of the capital 
IPPS for FY 2022 are discussed in section I.I. of this Appendix.
    We discussed the following changes:
     The effects of the application of the applicable 
percentage increase of 2.0 percent (that is, a 2.7 percent market 
basket update with a reduction of 0.7 percentage point for the 
productivity adjustment), and a 0.5 percentage point adjustment 
required under section 414 of the MACRA to the IPPS standardized 
amount, and the applicable percentage increase (including the market 
basket update and the productivity adjustment) to the hospital-
specific rates.
     The effects of the changes to the relative weights and 
MS-DRG GROUPER.
     The effects of the changes in hospitals' wage index 
values reflecting updated wage data from hospitals' cost reporting 
periods beginning during FY 2018, compared to the FY 2017 wage data, 
to calculate the FY 2022 wage index.
     The effects of the geographic reclassifications by the 
MGCRB (as of publication of this final rule) that will be effective 
for FY 2022.
     The effects of the rural floor with the application of 
the national budget neutrality factor to the wage index.
     The effects of the imputed floor wage index adjustment. 
This provision is not budget neutral.
     The effects of the frontier State wage index adjustment 
under the statutory provision that requires hospitals located in 
States that qualify as frontier States to not have a wage index less 
than 1.0. This provision is not budget neutral.
     The effects of the implementation of section 
1886(d)(13) of the Act, as added by section 505 of Public Law 108-
173, which provides for an increase in a hospital's wage index if a 
threshold percentage of residents of the county where the hospital 
is located commute to work at hospitals in counties with higher wage 
indexes for FY 2022. This provision is not budget neutral.
     The total estimated change in payments based on the FY 
2022 policies relative to payments based on FY 2021 policies.
    To illustrate the impact of the FY 2022 changes, our analysis 
begins with a FY 2021 baseline simulation model using: The FY 2021 
applicable percentage increase of 2.4 percent; the 0.5 percentage 
point adjustment required under section 414 of the MACRA applied to 
the IPPS standardized amount; the FY 2021 MS-DRG GROUPER (Version 
38); the FY 2021 CBSA designations for hospitals based on the OMB 
definitions from the 2010 Census; the FY 2021 wage index; and no 
MGCRB reclassifications. Outlier payments are set at 5.1 percent of 
total operating MS-DRG and outlier payments for modeling purposes.
    Section 1886(b)(3)(B)(viii) of the Act, as added by section 
5001(a) of Public Law 109-171, as amended by section 4102(b)(1)(A) 
of the ARRA (Pub. L. 111-5) and by section 3401(a)(2) of the 
Affordable Care Act (Pub. L. 111-148), provides that, for FY 2007 
and each subsequent year through FY 2014, the update factor will 
include a reduction of 2.0 percentage points for any subsection (d) 
hospital that does not submit data on measures in a form and manner, 
and at a time specified by the Secretary. Beginning in FY 2015, the 
reduction is one-quarter of such applicable percentage increase 
determined without regard to section 1886(b)(3)(B)(ix), (xi), or 
(xii) of the Act, or one-quarter of the market basket update. 
Therefore, hospitals that do not submit quality information under 
rules established by the Secretary and that are meaningful EHR users 
under section 1886(b)(3)(B)(ix) of the Act will receive an 
applicable percentage increase of 1.325 percent. At the time this 
impact was prepared, 68 hospitals are estimated to not receive the 
full market basket rate-of-increase for FY 2022 because they failed 
the quality data submission process or did not choose to 
participate, but are meaningful EHR users. For purposes of the 
simulations shown later in this section, we modeled the payment 
changes for FY 2022 using a reduced update for these hospitals.
    For FY 2022, in accordance with section 1886(b)(3)(B)(ix) of the 
Act, a hospital that has been identified as not a meaningful EHR 
user will be subject to a reduction of three-quarters of such 
applicable percentage increase determined without regard to section 
1886(b)(3)(B)(ix), (xi), or (xii) of the Act. Therefore, hospitals 
that are identified as not meaningful EHR users and do submit 
quality information under section 1886(b)(3)(B)(viii) of the Act 
will receive an applicable percentage increase of -0.025 percent. At 
the time this impact analysis was prepared, 97 hospitals are 
estimated to not receive the full market basket rate-of-increase for 
FY 2022 because they are identified as not meaningful EHR users that 
do submit quality information under section 1886(b)(3)(B)(viii) of 
the Act. For purposes of the simulations shown in this section, we 
modeled the payment changes for FY 2022 using a reduced update for 
these hospitals.
    Hospitals that are identified as not meaningful EHR users under 
section 1886(b)(3)(B)(ix) of the Act and also do not submit quality 
data under section 1886(b)(3)(B)(viii) of the Act will receive an 
applicable percentage increase of -0.7 percent, which reflects a 
one-quarter reduction of the market basket update for failure to 
submit quality data and a three-quarter reduction of the market 
basket update for being identified as not a meaningful EHR user. At 
the time this impact was prepared, 24 hospitals are estimated to not 
receive the full market basket rate-of-increase for FY 2022 because 
they are identified as not meaningful EHR users that do not submit 
quality data under section 1886(b)(3)(B)(viii) of the Act.
    Each policy change, statutory or otherwise, is then added 
incrementally to this baseline, finally arriving at an FY 2022 model 
incorporating all of the changes. This simulation allows us to 
isolate the effects of each change.
    Our comparison illustrates the percent change in payments per 
case from FY 2021 to FY 2022. Two factors not discussed separately 
have significant impacts here. The first factor is the update to the 
standardized amount. In accordance with section 1886(b)(3)(B)(i) of 
the Act, we are updating the standardized amounts for FY 2022 using 
a applicable percentage increase of 2.0 percent. This includes our 
forecasted IPPS operating hospital market basket increase of 2.7 
percent with a 0.7 percentage point reduction for the productivity 
adjustment. Hospitals that fail to comply with the quality data 
submission requirements and are meaningful EHR users will receive an 
update of 1.325 percent. This update includes a reduction of one-
quarter of the market basket update for failure to submit these 
data. Hospitals that do comply with the quality data submission 
requirements but are not meaningful EHR users would receive a update 
of -0.025 percent, which includes a reduction of three-quarters of 
the market basket update. Furthermore, hospitals that do not comply 
with the quality data submission requirements and also are not 
meaningful EHR users would receive an update of -0.7 percent. Under 
section 1886(b)(3)(B)(iv) of the Act, the update to the hospital-
specific amounts for SCHs and MDHs is also equal to the applicable 
percentage increase, or 2.0 percent, if the hospital submits quality 
data and is a meaningful EHR user.
    A second significant factor that affects the changes in 
hospitals' payments per case from FY 2021 to FY 2022 is the change 
in hospitals' geographic reclassification status from one year to 
the next. That is, payments may be reduced for hospitals 
reclassified in FY 2021 that are no longer reclassified in FY 2022. 
Conversely, payments may increase for hospitals not reclassified in 
FY 2021 that are reclassified in FY 2022.

2. Analysis of Table I

    Table I displays the results of our analysis of the changes for 
FY 2022. The table categorizes hospitals by various geographic and 
special payment consideration groups to illustrate the varying 
impacts on different types of hospitals. The top row of the table 
shows the overall impact on the 3,195 acute care hospitals included 
in the analysis.
    The next two rows of Table I contain hospitals categorized 
according to their geographic location: Urban and rural. There are 
2,459 hospitals located in urban areas and 736 hospitals in rural 
areas included in our analysis. The next two groupings are by bed-
size categories, shown separately for urban and rural hospitals. The 
last groupings by geographic location are by census divisions, also 
shown separately for urban and rural hospitals.

[[Page 45575]]

    The second part of Table I shows hospital groups based on 
hospitals' FY 2022 payment classifications, including any 
reclassifications under section 1886(d)(10) of the Act. For example, 
the rows labeled urban and rural show that the numbers of hospitals 
paid based on these categorizations after consideration of 
geographic reclassifications (including reclassifications under 
sections 1886(d)(8)(B) and 1886(d)(8)(E) of the Act that have 
implications for capital payments) are 1,983, and 1,212, 
respectively.
    The next three groupings examine the impacts of the changes on 
hospitals grouped by whether or not they have GME residency programs 
(teaching hospitals that receive an IME adjustment) or receive 
Medicare DSH payments, or some combination of these two adjustments. 
There are 2,031 nonteaching hospitals in our analysis, 907 teaching 
hospitals with fewer than 100 residents, and 257 teaching hospitals 
with 100 or more residents.
    In the DSH categories, hospitals are grouped according to their 
DSH payment status, and whether they are considered urban or rural 
for DSH purposes. The next category groups together hospitals 
considered urban or rural, in terms of whether they receive the IME 
adjustment, the DSH adjustment, both, or neither.
    The next three rows examine the impacts of the changes on rural 
hospitals by special payment groups (SCHs, MDHs and RRCs). There 
were 523 RRCs, 305 SCHs, 153 MDHs, 154 hospitals that are both SCHs 
and RRCs, and 27 hospitals that are both MDHs and RRCs.
    The next series of groupings are based on the type of ownership 
and the hospital's Medicare utilization expressed as a percent of 
total inpatient days. These data were taken from the FY 2018 or FY 
2017 Medicare cost reports.
    The next grouping concerns the geographic reclassification 
status of hospitals. The first subgrouping is based on whether a 
hospital is reclassified or not. The second and third subgroupings 
are based on whether urban and rural hospitals were reclassified by 
the MGCRB for FY 2022 or not, respectively. The fourth subgrouping 
displays hospitals that reclassified from urban to rural in 
accordance with section 1886(d)(8)(E) of the Act. The fifth 
subgrouping displays hospitals deemed urban in accordance with 
section 1886(d)(8)(B) of the Act.
BILLING CODE 4120-01-P

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BILLING CODE 4120-01-C

a. Effects of the Hospital Update and Other Adjustments (Column 1)

    As discussed in section V.A. of the preamble of this final rule, 
this column includes the hospital update, including the 2.7 percent 
market basket update reduced by the 0.7 percentage point for the 
productivity adjustment. In addition, as discussed in section II.D. 
of the preamble of this final rule, this column includes the FY 2022 
+0.5 percentage point adjustment required under section 414 of the 
MACRA. As a result, we make a 2.5 percent update to the national 
standardized amount. This column also includes the update to the 
hospital-specific rates which includes the 2.7 percent market basket 
update reduced by the 0.7 percentage point for the productivity 
adjustment. As a result, we are making a 2.0 percent update to the 
hospital-specific rates.
    Overall, hospitals will experience a 2.5 percent increase in 
payments primarily due to the combined effects of the hospital 
update to the national standardized amount and the hospital update 
to the hospital-specific rate. Hospitals that are paid under the 
hospital-specific rate would experience a 2.0 percent increase in 
payments; therefore, hospital categories containing hospitals paid 
under the hospital-specific rate would experience a lower than 
average increase in payments.

b. Effects of the Changes to the MS-DRG Reclassifications and Relative 
Cost-Based Weights With Recalibration Budget Neutrality (Column 2)

    Column 2 shows the effects of the changes to the MS-DRGs and 
relative weights with the application of the recalibration budget 
neutrality factor to the standardized amounts. Section 
1886(d)(4)(C)(i) of the Act requires us annually to make appropriate 
classification changes in order to reflect changes in treatment 
patterns, technology, and any other factors that may change the 
relative use of hospital resources. Consistent with section 
1886(d)(4)(C)(iii) of the Act, we calculated a recalibration budget 
neutrality factor to account for the changes in MS-DRGs and relative 
weights to ensure that the overall payment impact is budget neutral.
    As discussed in section II.E. of the preamble of this final 
rule, the FY 2022 MS-DRG relative weights will be 100 percent cost-
based and 100 percent MS-DRGs. For FY 2022, we are calculating the 
MS-DRGs using the FY 2019 MedPAR data grouped to the Version 39 (FY 
2022) MS-DRGs. The methodology to calculate the relative weights and 
the reclassification changes to the GROUPER are described in more 
detail in section II.G. of the preamble of this final rule.
    The ``All Hospitals'' line in Column 2 indicates that changes 
due to the MS-DRGs and relative weights will result in a 0.0 percent 
change in payments with the application of the recalibration budget 
neutrality factor of 1.000107 to the standardized amount.

c. Effects of the Wage Index Changes (Column 3)

    Column 3 shows the impact of the updated wage data using FY 2018 
cost report data, with the application of the wage budget neutrality 
factor. The wage index is calculated and assigned to hospitals on 
the basis of the labor market area in which the hospital is located. 
Under section 1886(d)(3)(E) of the Act, beginning with FY 2005, we 
delineate hospital labor market areas based on the Core Based 
Statistical Areas (CBSAs) established by OMB. The current 
statistical standards used in FY 2022 are based on OMB standards 
published on February 28, 2013 (75 FR 37246 and 37252), and 2010 
Decennial Census data (OMB Bulletin No. 13-01), as updated in OMB 
Bulletin Nos. 15-01, 17-01, and 18-04. (We refer readers to the FY 
2015 IPPS/LTCH PPS final rule (79 FR 49951 through 49963) for a full 
discussion on our adoption of the OMB labor market area 
delineations, based on the 2010 Decennial Census data, effective 
beginning with the FY 2015 IPPS wage index, to the FY 2017 IPPS/LTCH 
PPS final rule (81 FR 56913) for a discussion of our adoption of the 
CBSA updates in OMB Bulletin No. 15-01, which were effective 
beginning with the FY 2017 wage index, to the FY 2020 IPPS/LTCH PPS 
final rule (83 FR 41362) for a discussion of our adoption of the 
CBSA update in OMB Bulletin No. 17-01 for the FY 2020 wage index, 
and to the FY 2021 IPPS/LTCH PPS final rule (85 FR 58743 through 
58755) for a discussion of our adoption of the CBSA update in OMB 
Bulletin No. 18-04 for the FY 2021 wage index.
    Section 1886(d)(3)(E) of the Act requires that, beginning 
October 1, 1993, we annually update the wage data used to calculate 
the wage index. In accordance with this requirement, the wage index 
for acute care hospitals for FY 2022 is based on data submitted for 
hospital cost reporting periods, beginning on or after October 1, 
2017 and before October 1, 2018. The estimated impact of the updated 
wage data using the FY 2018 cost report data and the OMB labor 
market area delineations on hospital payments is isolated in Column 
3 by holding the other payment parameters constant in this 
simulation. That is, Column 3 shows the percentage change in 
payments when going from a model using the FY 2021 wage index, based 
on FY 2017 wage data, the labor-related share of 68.3 percent, under 
the OMB delineations and having a 100-percent occupational mix 
adjustment applied, to a model using the FY 2022 pre-
reclassification wage index based on FY 2018 wage data with the 
labor-related share of 67.6 percent, under the OMB delineations, 
also having a 100-percent occupational mix adjustment applied, while 
holding other payment parameters, such as use of the Version 39 MS-
DRG GROUPER constant. The FY 2022 occupational mix adjustment is 
based on the CY 2019 occupational mix survey.
    In addition, the column shows the impact of the application of 
the wage budget neutrality to the national standardized amount. In 
FY 2010, we began calculating separate wage budget neutrality and 
recalibration budget neutrality factors, in accordance with section 
1886(d)(3)(E) of the Act, which specifies that budget neutrality to 
account for wage index changes or updates made under that 
subparagraph must be made without regard to the 62 percent labor-
related share guaranteed under section 1886(d)(3)(E)(ii) of the Act. 
Therefore, for FY 2022, we are calculating the wage budget 
neutrality factor to ensure that payments under updated wage data 
and the labor-related share of 67.6 percent are budget neutral, 
without regard to the lower labor-related share of 62 percent 
applied to hospitals with a wage index less than or equal to 1.0. In 
other words, the wage budget neutrality is calculated under the 
assumption that all hospitals receive the higher labor-related share 
of the standardized amount. The FY 2022 wage budget neutrality 
factor is 1.000712 and the overall payment change is 0 percent.
    Column 3 shows the impacts of updating the wage data using FY 
2018 cost reports. Overall, the new wage data and the labor-related 
share, combined with the wage budget neutrality adjustment, will 
lead to no change for all hospitals, as shown in Column 3.
    In looking at the wage data itself, the national average hourly 
wage would increase 3.0 percent compared to FY 2021. Therefore, the 
only manner in which to maintain or exceed the previous year's wage 
index was to match or exceed the 3.0 percent increase in the 
national average hourly wage. Of the 3,163 hospitals with wage data 
for both FYs 2021 and 2022, 1,578 or 50 percent would experience an 
average hourly wage increase of 3.0 percent or more.
    The following chart compares the shifts in wage index values for 
hospitals due to changes in the average hourly wage data for FY 2022 
relative to FY 2021. These figures reflect changes in the ``pre-
reclassified, occupational mix-adjusted wage index,'' that is, the 
wage index before the application of geographic reclassification, 
the rural floor, the out-migration adjustment, and other wage index 
exceptions and adjustments. We note that the ``post-reclassified 
wage index'' or ``payment wage index,'' which is the wage index that 
includes all such exceptions and adjustments (as reflected in Tables 
2 and 3 associated with this final rule, which are available via the 
internet on the CMS website) is used to adjust the labor-related 
share of a hospital's standardized amount, either 67.6 percent (as 
proposed and finalized) or 62 percent, depending upon whether a 
hospital's wage index is greater than 1.0 or less than or equal to 
1.0. Therefore, the pre-reclassified wage index figures in the 
following chart may illustrate a somewhat larger or smaller change 
than would occur in a hospital's payment wage index and total 
payment.
    The following chart shows the projected impact of changes in the 
area wage index values for urban and rural hospitals.

[[Page 45580]]

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d. Effects of MGCRB Reclassifications (Column 4)

    Our impact analysis to this point has assumed acute care 
hospitals are paid on the basis of their actual geographic location 
(with the exception of ongoing policies that provide that certain 
hospitals receive payments on bases other than where they are 
geographically located). The changes in Column 4 reflect the per 
case payment impact of moving from this baseline to a simulation 
incorporating the MGCRB decisions for FY 2022.
    By spring of each year, the MGCRB makes reclassification 
determinations that will be effective for the next fiscal year, 
which begins on October 1. The MGCRB may approve a hospital's 
reclassification request for the purpose of using another area's 
wage index value. Hospitals may appeal denials by the MGCRB of 
reclassification requests to the CMS Administrator. Further, 
hospitals have 45 days from the date the IPPS proposed rule is 
issued in the Federal Register to decide whether to withdraw or 
terminate an approved geographic reclassification for the following 
year (we refer readers to the discussion of our clarification of 
this policy in section III.I.2. of the preamble to this final rule.)
    The overall effect of geographic reclassification is required by 
section 1886(d)(8)(D) of the Act to be budget neutral. Therefore, 
for purposes of this impact analysis, we are applying an adjustment 
of 0.986737 to ensure that the effects of the reclassifications 
under sections 1886(d)(8)(B) and (C) and 1886(d)(10) of the Act are 
budget neutral (section II.A. of the Addendum to this final rule).
    As discussed elsewhere in this final rule, after a review of the 
public comments received on the interim final rule with comment 
period titled ``Medicare Program; Modification of Limitations on 
Redesignation by the Medicare Geographic Classification Review Board 
(MGCRB)'' (CMS-1762-IFC), we are finalizing those policies. Because 
these are MGCRB policies, the redistributional impacts of these 
policies in FY 2022 are included in Column 4 and they are taken into 
account in the calculation of the budget neutrality adjustment to 
ensure that the effects of the reclassifications under sections 
1886(d)(8)(B) and (C) and 1886(d)(10) of the Act are budget neutral.
    Geographic reclassification generally benefits hospitals in 
rural areas. We estimate that the geographic reclassification would 
increase payments to rural hospitals by an average of 1.3 percent. 
By region, most rural hospital categories would experience increases 
in payments due to MGCRB reclassifications.
    Table 2 listed in section VI. of the Addendum to this final rule 
and available via the internet on the CMS website reflects the 
reclassifications for FY 2022.

e. Effects of the Rural Floor, Including Application of National Budget 
Neutrality (Column 5)

    As discussed in section III.B. of the preamble of the FY 2009 
IPPS final rule, the FY 2010 IPPS/RY 2010 LTCH PPS final rule, the 
FYs 2011 through 2021 IPPS/LTCH PPS final rules, and this FY 2022 
IPPS/LTCH PPS final rule, section 4410 of Public Law 105-33 
established the rural floor by requiring that the wage index for a 
hospital in any urban area cannot be less than the wage index 
applicable to hospitals located in rural areas in the same State. We 
apply a uniform budget neutrality adjustment to the wage index. 
Column 5 shows the effects of the rural floor.
    The Affordable Care Act requires that we apply one rural floor 
budget neutrality factor to the wage index nationally. We have 
calculated a FY 2022 rural floor budget neutrality factor to be 
applied to the wage index of 0.992868, which would reduce wage 
indexes by approximately 0.7 percent.
    Column 5 shows the projected impact of the rural floor with the 
national rural floor budget neutrality factor applied to the wage 
index based on the OMB labor market area delineations. The column 
compares the post-reclassification FY 2022 wage index of providers 
before the rural floor adjustment and the post-reclassification FY 
2022 wage index of providers with the rural floor adjustment based 
on the OMB labor market area delineations. Only urban hospitals can 
benefit from the rural floor. Because the provision is budget 
neutral, all other hospitals that do not receive an increase to 
their wage index from the rural floor adjustment (that is, all rural 
hospitals and those urban hospitals to which the adjustment is not 
made) would experience a decrease in payments due to the budget 
neutrality adjustment that is applied to the wage index nationally. 
(As finalized in the FY 2020 IPPS/LTCH PPS final rule, we calculate 
the rural floor without including the wage data of hospitals that 
have reclassified as rural under Sec.  412.103.)
    We estimate that 269 hospitals would receive the rural floor in 
FY 2022. All IPPS hospitals in our model would have their wage 
indexes reduced by the rural floor budget neutrality adjustment of 
0.992868. We project that, in aggregate, rural hospitals would 
experience a 0.2 percent decrease in payments as a result of the 
application of the rural floor budget neutrality because the rural 
hospitals do not benefit from the rural floor, but have their wage 
indexes downwardly adjusted to ensure that the application of the 
rural floor is budget neutral overall. We project that, in the 
aggregate, hospitals located in urban areas would experience no 
change in payments because increases in payments to hospitals 
benefitting from the rural floor offset decreases in payments to 
nonrural floor urban hospitals whose wage index is downwardly 
adjusted by the rural floor budget neutrality factor. Urban 
hospitals in the New England region would experience a 3.7 percent 
increase in payments primarily due to the application of the rural 
floor in Massachusetts.

f. Effects of the Imputed Floor

    As discussed in section III.X. of this rule, section 9831 of 
Public Law 117-2 established a minimum area wage index for hospitals 
in all-urban States for discharges occurring on or after October 1, 
2021. Specifically, section 1886(d)(3)(E)(iv)(I) and (II) of the Act 
provides that for discharges occurring on or after October 1, 2021, 
the area wage index applicable to any hospital in an all-urban State 
may not be less than the minimum area wage index for the fiscal year 
for hospitals in that State established using the methodology 
described in Sec.  412.64(h)(4)(vi) as in effect for FY 2018. Thus, 
effective beginning October 1, 2021 (FY 2022), section 
1886(d)(3)(E)(iv) of the Act reinstates the imputed floor wage index 
policy for all-urban States, with no expiration date.
    Unlike the imputed floor that was in effect from FYs 2005 
through 2018, section 1886(d)(3)(E)(iv)(III) of the Act provides 
that the imputed floor wage index is not applied in a budget neutral 
manner. Therefore, for FY 2022, the imputed floor adjustment is not 
budget neutral and would increase payments overall by approximately 
0.2 percent compared to the provision not being in effect.
    Column 6 shows the projected impact of the imputed floor 
adjustment applied to the wage index based on the OMB labor market 
area delineations. The column compares the post-reclassification FY 
2022 wage index of providers after the rural floor adjustment and 
the post reclassification FY 2022 wage index of providers with the 
imputed floor adjustment.
    There are an estimated 69 providers that will receive the 
imputed floor wage index

[[Page 45581]]

adjustment in FY 2022. This adjustment is not budget neutral, and we 
estimate the impact of the application of the imputed floor will be 
approximately $195 million.

g. Effects of the Application of the Frontier State Wage Index and Out-
Migration Adjustment (Column 7)

    This column shows the combined effects of the application of 
section 10324(a) of the Affordable Care Act, which requires that we 
establish a minimum post-reclassified wage index of 1.00 for all 
hospitals located in ``frontier States,'' and the effects of section 
1886(d)(13) of the Act, as added by section 505 of Public Law 108-
173, which provides for an increase in the wage index for hospitals 
located in certain counties that have a relatively high percentage 
of hospital employees who reside in the county, but work in a 
different area with a higher wage index. These two wage index 
provisions are not budget neutral and would increase payments 
overall by 0.1 percent compared to the provisions not being in 
effect.
    The term ``frontier States'' is defined in the statute as States 
in which at least 50 percent of counties have a population density 
less than 6 persons per square mile. Based on these criteria, 5 
States (Montana, Nevada, North Dakota, South Dakota, and Wyoming) 
are considered frontier States and an estimated 44 hospitals located 
in those States would receive a frontier wage index of 1.0000. 
Overall, this provision is not budget neutral and is estimated to 
increase IPPS operating payments by approximately $64 million.
    In addition, section 1886(d)(13) of the Act, as added by section 
505 of Public Law 108-173, provides for an increase in the wage 
index for hospitals located in certain counties that have a 
relatively high percentage of hospital employees who reside in the 
county, but work in a different area with a higher wage index. 
Hospitals located in counties that qualify for the payment 
adjustment would receive an increase in the wage index that is equal 
to a weighted average of the difference between the wage index of 
the resident county, post-reclassification and the higher wage index 
work area(s), weighted by the overall percentage of workers who are 
employed in an area with a higher wage index. There are an estimated 
245 providers that will receive the out-migration wage adjustment in 
FY 2022. This out-migration wage adjustment is not budget neutral, 
and we estimate the impact of these providers receiving the out-
migration increase will be approximately $55 million.

h. Effects of All FY 2022 Changes (Column 8)

    Column 7 shows our estimate of the changes in payments per 
discharge from FY 2021 and FY 2022, resulting from all changes 
reflected in this final rule for FY 2022. It includes combined 
effects of the year-to-year change of the previous columns in the 
table.
    The average increase in payments under the IPPS for all 
hospitals is approximately 2.6 percent for FY 2022 relative to FY 
2021 and for this row is primarily driven by the changes reflected 
in Column 1. Column 7 includes the annual hospital update of 2.5 
percent to the national standardized amount. This annual hospital 
update includes the 2.7 percent market basket update reduced by the 
0.7 percentage point productivity adjustment. As discussed in 
section II.D. of the preamble of this final rule, this column also 
includes the +0.5 percentage point adjustment required under section 
414 of the MACRA. Hospitals paid under the hospital-specific rate 
would receive a 2.0 percent hospital update. As described in Column 
1, the annual hospital update with the +0.5 percent adjustment for 
hospitals paid under the national standardized amount, combined with 
the annual hospital update for hospitals paid under the hospital-
specific rates, will result in a 2.6 percent increase in payments in 
FY 2022 relative to FY 2021. Column 8 also includes the effects of 
the continued policy to increase the wage index for hospitals with a 
wage index value below the 25th percentile wage index (that is, the 
lowest quartile wage index adjustment), the extended transition 
policy to place a 5-percent cap on any decrease in a hospital's wage 
index from its final wage index in FY 2021 (that is, the 5-percent 
cap), and the associated budget neutrality factors as discussed in 
section III.K.3. of the preamble of this final rule. There are 
interactive effects among the various factors comprising the payment 
system that we are not able to isolate, which contribute to our 
estimate of the changes in payments per discharge from FY 2021 and 
FY 2022 in Column 8.
    Overall payments to hospitals paid under the IPPS due to the 
applicable percentage increase and changes to policies related to 
MS-DRGs, geographic adjustments, and outliers are estimated to 
increase by 2.6 percent for FY 2022. Hospitals in urban areas will 
experience a 2.6 percent increase in payments per discharge in FY 
2022 compared to FY 2021. Hospital payments per discharge in rural 
areas are estimated to increase by 2.8 percent in FY 2022.

3. Impact Analysis of Table II

    Table II presents the projected impact of the changes for FY 
2022 for urban and rural hospitals and for the different categories 
of hospitals shown in Table I. It compares the estimated average 
payments per discharge for FY 2021 with the estimated average 
payments per discharge for FY 2022, as calculated under our models. 
Therefore, this table presents, in terms of the average dollar 
amounts paid per discharge, the combined effects of the changes 
presented in Table I. The estimated percentage changes shown in the 
last column of Table II equal the estimated percentage changes in 
average payments per discharge from Column 7 of Table I.
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H. Effects of Other Policy Changes

    In addition to those policy changes discussed previously that we 
are able to model using our IPPS payment simulation model, we are 
making various other changes in this final rule. As noted in section 
I.G. of this Appendix A, our payment simulation model uses the most 
recent available claims data to estimate the impacts on payments per 
case of certain changes in this final rule. Generally, we have 
limited or no specific data available with which to estimate the 
impacts of these changes using that payment simulation model. For 
those changes, we have attempted to predict the payment impacts 
based upon our experience and other more limited data. Our estimates 
of the likely impacts associated with these other changes are 
discussed in this section.

1. Effects of Policies Relating to New Medical Service and Technology 
Add-On Payments and New COVID-19 Treatments Add-on Payment (NCTAP)

a. FY 2022 Status of Technologies Approved for FY 2021 New Technology 
Add-On Payments

    In section II.F.4. of the preamble of this final rule, as 
proposed we are continuing to make new technology add-on payments 
for AZEDRA[supreg], BAROSTIM NEO System, BALVERSA\TM\, 
Jakafi[supreg], FETROJA[supreg], Optimizer[supreg] System, 
RECARBRIO\TM\, Soliris[supreg], XENLETA\TM\, and ZERBAXA[supreg] in 
FY 2022 because these technologies would still be considered new for 
purposes of new technology add-on payments. We are also finalizing a 
1-year extension for FY 2022 of the new technology add-on payments 
for the following technologies, for which new technology add-on 
payments would otherwise be discontinued beginning with FY 2022: 
AndexXa\TM\, Cablivi[supreg], ContaCT, Eluvia Drug-Eluting Vascular 
Stent System, ELZONRIS[supreg], Esketamine (SPRAVATO[supreg]), 
Hemospray, IMFINZI/TECENTRIQ, NUZYRA, Spinejack, T2 Bacteria Test 
Panel, XOSPATA[supreg], and ZEMDRITM. We refer

[[Page 45584]]

readers to section II.F. of the preamble of this final rule with 
regard to our finalization of this 1-year extension of new 
technology add-on payments for these technologies in FY 2022.
    Under Sec.  412.88(a)(2), the new technology add-on payment for 
each case would be limited to the lesser of: (1) 65 percent of the 
costs of the new technology (or 75 percent of the costs for 
technologies designated as Qualified Infectious Disease Products 
(QIDPs) or approved under the Limited Population Pathway for 
Antibacterial and Antifungal Drugs (LPAD) pathway); or (2) 65 
percent of the amount by which the costs of the case exceed the 
standard MS-DRG payment for the case (or 75 percent of the amount 
for technologies designated as QIDPs or approved under the LPAD 
pathway). Because it is difficult to predict the actual new 
technology add-on payment for each case, our estimates in this final 
rule are based on applicant's estimate at the time they submitted 
their original application and the increase in new technology add-on 
payments for FY 2022 as if every claim that would qualify for a new 
technology add-on payment would receive the maximum add-on payment. 
In the following table are estimates for the 23 technologies for 
which we are continuing to make new technology add-on payments in FY 
2022:
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b. FY 2022 Applications for New Technology Add-On Payments

    In sections II.F.5. and 6. of the preamble to this final rule, 
we discussed 43 technologies for which we received applications for 
add-on payments for new medical services and technologies for FY 
2022. We note that 5 applicants withdrew their application prior to 
the issuance of the proposed rule. We further note that 7 applicants 
withdrew their application prior to the issuance of the final rule, 
and 3 applicants did not meet the July 1, 2021 deadline for FDA 
marketing authorization. As explained in the preamble to this final 
rule, add-on payments for new medical services and technologies 
under section 1886(d)(5)(K) of the Act are not required to be budget 
neutral. As discussed in section II.F.6. of the preamble of this 
final rule, under the alternative pathway for new technology add-on 
payments, new technologies that are medical products with a QIDP 
designation, approved through the FDA LPAD pathway, or are part of 
the Breakthrough Device program will be considered new and not 
substantially similar to an existing technology and will not need to 
demonstrate that the technology represents a substantial clinical 
improvement. These technologies must still meet the cost criterion.
    As also discussed in section II.F.6. of the preamble of this 
final rule, we are approving or conditionally approving 10 
alternative pathway applications for FY 2022 new technology add-on 
payments. Based on information from the applicants at the time of 
rulemaking, we estimate that total payments for the 10 technologies 
that we are approving or conditionally approving under the 
alternative pathway would be approximately $151 million for FY 2022. 
Total estimated FY 2022 payments for new technologies that are 
designated as a QIDP would be approximately $50 million, and total 
estimated FY 2022 payments for new technologies that are part of the 
Breakthrough Device program will be approximately $101 million. In 
the following table are estimates for the 10 technologies for which 
we are approving new technology add-on payments under the 
alternative pathway in FY 2022:

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    As discussed in section II.F.5. of the preamble of this final 
rule, we are approving 7 technologies under the traditional pathway 
for new technology add-on payments for FY 2022. Based on information 
from the applicants at the time of rulemaking, we estimate that 
total payments for the 7 technologies that we are approving under 
the traditional pathway would be approximately $498 million for FY 
2022. In the following table are estimates for the 7 technologies 
for which we are approving new technology add-on payments under the 
traditional pathway in FY 2022:
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c. Changes to FY 2022 New COVID-19 Treatments Add-On Payment (NCTAP)

    As discussed in section II.F. of the preamble of this final 
rule, in response to the COVID-19 PHE, we established the NCTAP 
under the IPPS for COVID-19 cases that meet certain criteria (85 FR 
71157 and 71158). In this final rule, we are finalizing to extend 
the NCTAP through the end of the fiscal year in which the PHE ends 
for all eligible products, including those approved for new 
technology add-on payments for FY 2022.
    Given that it is unknown what the cost and utilization of 
inpatient stays using these new treatments will be, the net overall 
cost of the extension of the NCTAP is not estimable. On one extreme, 
if all of the new COVID-19 treatments decrease the net cost of 
hospitalizations (for example, due to shortened lengths of stay), 
including the cost of the new treatment, below the Medicare payment 
for discharges after the end of the PHE and through the end of the 
fiscal year in which the PHE ends, then there would be no NCTAP made 
and no additional cost to the Medicare program as a result of this 
extension. On the other extreme, if all of the new COVID-19 
treatments result in the net cost of hospitalizations that exceed 
the outlier threshold (for example, due to the cost of the new 
treatment) for discharges after the end of the PHE and through the 
end of the fiscal year in which the PHE ends, the cost to the 
Medicare program would be the sum over all such NCTAP cases of 0.65 
times the outlier threshold for each case.

2. Effects of the Changes to Medicare DSH and Uncompensated Care 
Payments for FY 2022

    As discussed in section V.E. of the preamble of this final rule, 
under section 3133 of the Affordable Care Act, hospitals that are 
eligible to receive Medicare DSH payments will receive 25 percent of 
the amount they previously would have received under the statutory 
formula for Medicare DSH payments under section 1886(d)(5)(F) of the 
Act. The remainder, equal to an estimate of 75 percent of what 
formerly would have been paid as Medicare DSH payments (Factor 1), 
reduced to reflect changes in the percentage of uninsured 
individuals and any additional statutory adjustment (Factor 2), is 
available to make additional payments to each hospital that 
qualifies for Medicare DSH payments and that has uncompensated care. 
Each hospital eligible for Medicare DSH payments will receive an 
additional payment based on its estimated share of the total amount 
of uncompensated care for all hospitals eligible for Medicare DSH 
payments. The uncompensated care payment methodology has 
redistributive effects based on the proportion of a hospital's 
amount of uncompensated care relative to the aggregate amount of 
uncompensated care of all hospitals eligible for Medicare DSH 
payments (Factor 3). The change to Medicare DSH payments under 
section 3133 of the Affordable Care Act is not budget neutral.
    In this final rule, as we proposed, we are establishing the 
amount to be distributed as uncompensated care payments to DSH 
eligible hospitals for FY 2022. The final estimate of the amount 
available to make uncompensated care payments is $7,192,008,709.70. 
This figure represents 75 percent of the amount that otherwise would 
have been paid for Medicare DSH payment adjustments adjusted by a 
Factor 2 of 68.57 percent. For FY 2021, the amount available to be 
distributed for uncompensated care was $8,290,014,520.96 or 75 
percent of the amount that otherwise would have been paid for 
Medicare DSH payment adjustments adjusted by a Factor 2 of 72.86 
percent. Consistent with the policy adopted in the FY 2021 IPPS/LTCH 
PPS final rule for FY 2022 and subsequent fiscal years, we are using 
a single year of data on uncompensated care costs from Worksheet S-
10 of the FY 2018 cost reports to calculate Factor 3 in the FY 2022 
methodology for all eligible hospitals with the exception of Indian 
Health Service (IHS) and Tribal hospitals and Puerto Rico Hospitals. 
To calculate Factor 3 for Puerto Rico hospitals and Indian Health 
Service and Tribal hospitals, we are using data regarding Medicaid 
utilization from 2013 cost reports from the most recent HCRIS 
database extract and the most recent available SSI days (or, for 
Puerto Rico hospitals, a proxy for Medicare SSI utilization data). 
For a complete discussion of the methodology for

[[Page 45586]]

calculating Factor 3, we refer readers to section V.E.4. of the 
preamble of this final rule.
    To estimate the impact of the combined effect of the changes in 
Factors 1 and 2, as well as the changes to the data used in 
determining Factor 3, on the calculation of Medicare uncompensated 
care payments, we compared total uncompensated care payments 
estimated in the FY 2021 IPPS/LTCH PPS final rule to total 
uncompensated care payments estimated in this FY 2022 IPPS/LTCH PPS 
final rule. For FY 2021, we calculated 75 percent of the estimated 
amount that would be paid as Medicare DSH payments absent section 
3133 of the Affordable Care Act, adjusted by a Factor 2 of 72.86 
percent and multiplied by a Factor 3 calculated using the 
methodology described in the FY 2021 IPPS/LTCH PPS final rule. For 
FY 2022, we calculated 75 percent of the estimated amount that would 
be paid as Medicare DSH payments during FY 2022 absent section 3133 
of the Affordable Care Act, adjusted by a Factor 2 of 68.57 percent 
and multiplied by a Factor 3 calculated using the methodology 
described previously.
    Our analysis included 2,366 hospitals that are projected to be 
eligible for DSH in FY 2022. It did not include hospitals that had 
terminated their participation in the Medicare program as of June 
28, 2021, Maryland hospitals, new hospitals, MDHs, and SCHs that are 
expected to be paid based on their hospital-specific rates. The 26 
hospitals participating in the Rural Community Hospital 
Demonstration Program were excluded from this analysis, as 
participating hospitals are not eligible to receive empirically 
justified Medicare DSH payments and uncompensated care payments. In 
addition, the data from merged or acquired hospitals were combined 
under the surviving hospital's CMS certification number (CCN), and 
the non surviving CCN was excluded from the analysis. The estimated 
impact of the changes in Factors 1, 2, and 3 on uncompensated care 
payments across all hospitals projected to be eligible for DSH 
payments in FY 2022, by hospital characteristic, is presented in the 
following table.
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BILLING CODE 4120-01-C
    The changes in projected FY 2022 uncompensated care payments 
from payments in FY 2021 are driven by a decrease in Factor 1 and a 
decrease in Factor 2, as well as by a decrease in the number of 
hospitals projected to be eligible to receive DSH in FY 2022 
relative to FY 2021. Factor 1 has decreased from the FY 2021 final 
rule's Factor 1 of $11.378 billion to this FY 2022 final rule's 
Factor 1 of $10.489 billion, while the percent change in the percent 
of individuals who are uninsured (Factor 2) has decreased from 72.86 
percent to 68.57 percent. Based on the changes in these two factors, 
the impact analysis found that, across all projected DSH eligible 
hospitals, FY 2022 uncompensated care payments are estimated at 
approximately $7.192 billion, or a decrease of approximately 13.24 
percent from FY 2021 uncompensated care payments (approximately 
$8.290 billion). While these changes will result in a net decrease 
in the amount available to be distributed in uncompensated care 
payments, the projected payment decreases vary by hospital type. 
This redistribution of uncompensated care payments is caused by 
changes in Factor 3. As seen in the previous table, a percent change 
of less than negative 13.24 percent indicates that hospitals within 
the specified category are projected to experience a larger decrease 
in uncompensated care payments, on average, compared to the universe 
of projected FY 2022 DSH hospitals. Conversely, a percent change 
greater than negative 13.24 percent indicates that a hospital type 
is projected to have a smaller decrease than the overall average. 
The variation in the distribution of payments by hospital 
characteristic is largely dependent on a given hospital's 
uncompensated care costs as reported in the Worksheet S-10, or 
number of Medicaid days and SSI days for Puerto Rico hospitals and 
Indian Health Service and Tribal hospitals, used in the Factor 3 
computation.
    Rural hospitals, in general, are projected to experience larger 
decreases in uncompensated care payments than their urban 
counterparts. Overall, rural hospitals are projected to receive a 
17.22 percent decrease in uncompensated care payments, which is a 
greater decrease than the overall hospital average, while urban 
hospitals are projected to receive a 13.00 percent decrease in 
uncompensated care payments, similar to the overall hospital 
average.
    By bed size, smaller rural hospitals are projected to receive 
the largest decreases in uncompensated care payments. Rural 
hospitals with 0-99 beds are projected to receive an 18.91 percent 
payment decrease, and rural hospitals with 100-249 beds are 
projected to receive a 15.46 percent decrease. In contrast, larger 
rural hospitals with 250+ beds are projected to receive a 14.09 
percent payment decrease. Among urban hospitals, the smallest urban 
hospitals, those with 0-99 and 100-249 beds, are projected to 
receive a decrease in uncompensated care payments that is greater 
than the overall hospital average, at 15.43 and 15.54 percent, 
respectively. In contrast, the largest urban hospitals with 250+ 
beds are projected to receive a 12.01 percent decrease in 
uncompensated care payments, which is a smaller decrease than the 
overall hospital average.
    By region, rural hospitals are expected to receive larger than 
average decreases in uncompensated care payments in all Regions, 
except for rural hospitals in New England, which are projected to 
receive a decrease of 1.19 percent in uncompensated care payments, 
and rural hospitals in the East South Central Region, which are 
projected to receive a smaller than average decrease of 12.94 
percent. Regionally, urban hospitals are projected to receive a more 
varied range of payment changes. Urban hospitals in the New England, 
Middle Atlantic, East South Central, and Pacific Regions are 
projected to receive larger than average decreases in uncompensated 
care payments. Urban hospitals in the South Atlantic, East North 
Central, West North Central, West South Central, and Mountain 
Regions, as well as hospitals in Puerto Rico are projected to 
receive smaller than average decreases in uncompensated care 
payments.
    By payment classification, although hospitals in urban areas 
overall are expected to receive a 12.72 percent decrease in 
uncompensated care payments, hospitals in large urban areas are 
expected to see a decrease in uncompensated care payments of 13.54 
percent, while hospitals in other urban areas are expected to 
receive a decrease in uncompensated care payments of 11.12 percent. 
Rural hospitals are projected to receive the largest decrease of 
14.27 percent.
    Nonteaching hospitals are projected to receive a payment 
decrease of 13.34 percent, teaching hospitals with fewer than 100 
residents are projected to receive a payment decrease of 13.02 
percent, and teaching hospitals with 100+ residents have a projected 
payment decrease of 13.39 percent. All of these decreases closely 
approximate the overall hospital average. Proprietary and voluntary 
hospitals are projected to receive smaller than average decreases of 
11.50 and 12.62 percent respectively, while government hospitals are 
expected to receive a larger payment decrease of 15.22 percent. All

[[Page 45589]]

hospitals with less than 50 percent Medicare utilization are 
projected to receive decreases in uncompensated care payments 
consistent with the overall hospital average percent change, while 
hospitals with 50-65 percent and greater than 65 percent Medicare 
utilization are projected to receive larger decreases of 20.79 and 
32.81 percent, respectively.

3. Effects of Reductions Under the Hospital Readmissions Reduction 
Program for FY 2022

    In section V.G. of the preamble of this final rule, we discuss 
our policies for the FY 2022 Hospital Readmissions Reduction 
Program. This program requires a reduction to a hospital's base 
operating DRG payment to account for excess readmissions of selected 
applicable conditions and procedures. The table and analysis in this 
final rule illustrate the estimated financial impact of the Hospital 
Readmissions Reduction Program payment adjustment methodology by 
hospital characteristic. In the FY 2022 IPPS/LTCH PPS proposed rule 
(86 FR 25758 through 25760), for the purpose of modeling the FY 2022 
payment adjustment factors, we used the payment adjustment factors 
from the FY 2021 Hospital Readmissions Reduction Program and the FY 
2021 Hospital IPPS final rule Impact File to analyze results by 
hospital characteristics. In this final rule, we are updating the 
estimated financial impact using the estimated payment adjustment 
factors from the FY 2022 Hospital Readmissions Reduction Program and 
the FY 2022 Hospital IPPS proposed rule Impact File to analyze 
results by hospital characteristics. Hospitals are stratified into 
quintiles based on the proportion of dual-eligible stays among 
Medicare fee-for-service (FFS) and managed care stays between July 
1, 2017 and December 1, 2019 (that is, the data period used for the 
FY 2022 Hospital Readmissions Reduction Program). Hospitals' excess 
readmission ratios (ERRs) are assessed relative to their peer group 
median and a neutrality modifier is applied in the payment 
adjustment factor calculation to maintain budget neutrality. In this 
FY 2022 IPPS/LTCH PPS final rule, we provide an updated estimate of 
the financial impact using the proportion of dually-eligible 
beneficiaries, excess readmission ratios, and aggregate payments for 
each condition/procedure and all discharges for applicable hospitals 
from the FY 2022 Hospital Readmissions Reduction Program applicable 
period. We note that for the FY 2022 applicable period, we will only 
be assessing data from July 1, 2017 through December 1, 2019 due to 
the COVID-19 public health emergency (PHE) nationwide Extraordinary 
Circumstance Exception (ECE) which excluded data from January 1, 
2020 through June 30, 2020 from the Hospital Readmissions Reduction 
Program calculations.\1391\
---------------------------------------------------------------------------

    \1391\ Although the FY 2022 applicable period is July 1, 2017 
through June 30, 2020, we note that first and second quarter data 
from CY 2020 is excluded from consideration for calculations 
purposes due to the nationwide ECE that was granted in response to 
the COVID-19 PHE. Taking into consideration the 30-day window to 
identify readmissions, the period for identifying index stays will 
be adjusted to July 1, 2017 through December 1, 2019. Further 
information will be found in the FY 2022 Hospital Specific Report 
(HSR) User Guide located on QualityNet website at: https://qualitynet.cms.gov/inpatient/hrrp/reports that is anticipated to 
become available in August 2021.
---------------------------------------------------------------------------

    The results in the table include 2,938 non-Maryland hospitals 
eligible to receive a penalty during the performance period. 
Hospitals are eligible to receive a penalty if they have 25 or more 
eligible discharges for at least one measure between July 1, 2017 
and December 1, 2019. The second column in the table indicates the 
total number of non-Maryland hospitals with available data for each 
characteristic that have an estimated payment adjustment factor less 
than 1 (that is, penalized hospitals).
    The third column in the table indicates the percentage of 
penalized hospitals among those eligible to receive a penalty by 
hospital characteristic. For example, 82.16 percent of eligible 
hospitals characterized as non-teaching hospitals are expected to be 
penalized. Among teaching hospitals, 88.94 percent of eligible 
hospitals with fewer than 100 residents and 93.33 percent of 
eligible hospitals with 100 or more residents are expected to be 
penalized.
    The fourth column in the table estimates the financial impact on 
hospitals by hospital characteristic. The table shows the share of 
penalties as a percentage of all base operating DRG payments for 
hospitals with each characteristic. This is calculated as the sum of 
penalties for all hospitals with that characteristic over the sum of 
all base operating DRG payments for those hospitals between January 
1, 2019 and December 31, 2019 (CY 2019). For example, the penalty as 
a share of payments for urban hospitals is 0.63 percent. This means 
that total penalties for all urban hospitals are 0.63 percent of 
total payments for urban hospitals. Measuring the financial impact 
on hospitals as a percentage of total base operating DRG payments 
accounts for differences in the amount of base operating DRG 
payments for hospitals with the characteristic when comparing the 
financial impact of the program on different groups of hospitals.
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    We did not receive any public comments regarding the impact of 
our proposals.

4. Effects of Changes Under the FY 2022 Hospital Value-Based Purchasing 
(VBP) Program

    In section V.H. of the preamble of this final rule, we discuss 
the Hospital VBP Program under which the Secretary makes value-based 
incentive payments to hospitals based on their performance on 
measures during the performance period with respect to a fiscal 
year. We are finalizing our proposals to suppress the Hospital 
Consumer Assessment of Healthcare Providers and Systems (HCAHPS) 
survey, Medicare Spending Per Beneficiary (MSPB) and five 
healthcare-associated infection (HAI) measures, as well as changing 
the scoring and payment methodologies for the FY 2022 program year, 
such that all participating hospitals will receive a value-based 
incentive payment percentage that results in a value-based incentive 
payment amount that is equal to the applicable percentage (2 
percent). Specifically, we will calculate the measure rates for all 
of the measures we have selected for the FY 2022 program year, but 
we will not generate achievement or improvement points for any of 
the measures we are suppressing. Additionally, we will not award 
domain scores for the Person and Community Engagement, Efficiency 
and Cost Reduction, and Safety domains. Therefore, we will not award 
hospitals a TPS, and will instead award hospitals a payment 
incentive multiplier that results in a value-based incentive payment 
amount that is equal to the amount withheld for the fiscal year (2 
percent). That is, each hospital will receive a 2 percent reduction 
to its base operating DRG payment amount for each FY 2022 discharge 
and will then receive a value-based incentive payment percentage 
that will result in a value-based incentive payment amount that is 
equal to the 2 percent withheld. Under these finalized policies, the 
impact for every hospital under the Hospital VBP Program will be a 
net percentage payment adjustment of zero.
    In the FY 2022 IPPS/LTCH PPS proposed rule (86 FR 25760 through 
25761), we also provided the estimated impact of the FY 2022 program 
because those impacts would apply if the proposals discussed 
previously were not finalized. However, because we are finalizing 
the policies as proposed, all adjustment factors for all hospitals 
will reflect a net-neutral payment adjustment for hospitals in 
accordance with the finalized FY 2022 special scoring policy at 
Sec.  412.168.
    We are also finalizing our proposal to suppress the MORT-30-PN 
measure for the FY 2023 program year. Under this finalized policy, 
we will calculate the measure rate for the MORT-30-PN program year. 
However, we will not generate achievement or improvement points for 
that measure. In the FY 2022 IPPS/LTCH PPS proposed rule (86 FR 
25469 through 25496), we did not propose to suppress any other 
measures for the FY 2023 program year. We also did not propose any 
changes to the scoring methodology for the FY 2023 program in the 
proposed rule. Hospitals will still receive achievement and 
improvement points on the remaining measures for which they report 
the minimum number of cases, and they will receive scores on domains 
for which they report the minimum number of measures for the FY 2023 
program year. The domain scores, weighted at 25 percent each, will 
be used to calculate TPSs for the FY 2023 program year. As discussed 
in section VI.H.3.c. of this final rule, we are also finalizing our 
proposal to remove the CMS PSI 90 measure beginning with the FY 2023 
program year. However, because we are removing this measure before 
it would be used in calculating a hospital's TPS under the Hospital 
VBP Program, we do not expect this provision will have impacts for 
the FY 2023 program year.
    We did not receive any public comments regarding the impact of 
our proposals.

5. Effects Under the HAC Reduction Program for FY 2022

    We are presenting the estimated impact of the FY 2022 Hospital-
Acquired Condition (HAC) Reduction Program on hospitals by hospital 
characteristic in the following table, Estimated Proportion of 
Hospitals in the Worst-Performing Quartile (>75th percentile) of the 
Total HAC Scores for the FY 2022 HAC

[[Page 45592]]

Reduction Program (by Hospital Characteristic). These estimated 
results were calculated using the Equal Measure Weights approach 
finalized in the FY 2019 IPPS/LTCH PPS final rule (83 FR 41486 
through 41489). Each hospital's Total HAC Score was calculated as 
the equally weighted average of the hospital's measure scores. The 
table in this section presents the estimated proportion of hospitals 
in the worst-performing quartile of Total HAC Scores by hospital 
characteristic using the 1-year performance period for the HAI 
measures pursuant to the measure suppression policy discussed in 
section IX.I.3.d. of the preamble of this final rule and its 
adoption for the FY 2022 program year.
    The table calculates hospitals' CMS Patient Safety and Adverse 
Events Composite (CMS PSI 90) measure results based on Medicare fee-
for-service (FFS) discharges from July 1, 2018 through December 31, 
2019 \1392\ and version 11.0 of the PSI software. Hospitals' measure 
results for the Centers for Disease Control and Prevention (CDC) 
Central Line-Associated Bloodstream Infection (CLABSI), Catheter-
Associated Urinary Tract Infection (CAUTI), Colon and Abdominal 
Hysterectomy Surgical Site Infection (SSI), Methicillin-resistant 
Staphylococcus aureus (MRSA) bacteremia, and Clostridium difficile 
Infection (CDI) measures are derived from standardized infection 
ratios (SIRs) calculated with hospital surveillance data reported to 
the National Healthcare Safety Network (NHSN) for infections 
occurring between January 1, 2019 and December 31, 2019.\1393\
---------------------------------------------------------------------------

    \1392\ As explained in section V.I.7., in memorandum released in 
March 2020, through application of our ECE policy, we excluded first 
and second quarter CY 2020 CMS PSI 90 data from FY 2022 Total HAC 
Scores. The resulting applicable period for the CMS PSI 90 measure 
in the FY 2022 HAC Reduction Program is the 18-month period from 
July 1, 2018 through December 31, 2019.
    \1393\ As explained in section V.I.7., in an interim final rule 
with comment period (IFC) published on September 2, 2020, through 
application of our ECE policy, we excluded first and second quarter 
CY 2020 CDC NHSN HAI data from FY 2022 Total HAC Scores. In section 
V.I.3.d. of the preamble of this final rule, we finalized the 
suppression of third and fourth quarter CY 2020 CDC NHSN HAI data 
from FY 2022 Total HAC Scores. The resulting applicable period for 
the CDC NHSN HAI measures in the FY 2022 HAC Reduction Program is 
the 12-month period from January 1, 2019 through December 31, 2019.
---------------------------------------------------------------------------

    The table includes 3,067 non-Maryland hospitals with a FY 2022 
Total HAC Score. Maryland hospitals and hospitals without a Total 
HAC Score are excluded from the table. The first column presents a 
breakdown of each characteristic and the second column indicates the 
number of hospitals for the respective characteristic.
    The third column in the table indicates the number of hospitals 
for each characteristic that would be in the worst-performing 
quartile of Total HAC Scores. These hospitals would receive a 
payment reduction under the FY 2022 HAC Reduction Program. For 
example, regarding teaching status, 426 hospitals out of 1,929 
hospitals characterized as non-teaching hospitals would be subject 
to a payment reduction. Among teaching hospitals, 221 out of 875 
hospitals with fewer than 100 residents and 117 out of 257 hospitals 
with 100 or more residents would be subject to a payment reduction.
    The fourth column in the table indicates the proportion of 
hospitals for each characteristic that would be in the worst 
performing quartile of Total HAC Scores and thus receive a payment 
reduction under the FY 2022 HAC Reduction Program. For example, 22.1 
percent of the 1,929 hospitals characterized as non-teaching 
hospitals, 25.3 percent of the 875 teaching hospitals with fewer 
than 100 residents, and 45.5 percent of the 257 teaching hospitals 
with 100 or more residents would be subject to a payment reduction.
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BILLING CODE 4120-01-C
    We did not receive any public comments regarding the impact of 
our proposals.

6. Effects of Implementation of the Rural Community Hospital 
Demonstration Program in FY 2022

    In section V.J. of the preamble of this final rule for FY 2022, 
we discussed our implementation and budget neutrality methodology 
for section 410A of Public Law 108-173, as amended by sections 3123 
and 10313 of Public Law 111-148, by section 15003 of Public Law 114-
255, and most recently, by section 128 of Public Law 116-260, which 
requires the Secretary to conduct a demonstration that would modify 
payments for inpatient services for up to 30 rural hospitals.
    Section 128 of Public Law 116-255 requires the Secretary to 
conduct the Rural Community Hospital Demonstration for a 15-year 
extension period (that is, for an additional 5 years beyond the 
current extension period). In addition, the statute provides for 
continued participation for all hospitals participating in the 
demonstration program as of December 30, 2019. We, therefore, 
interpret the statute as providing for an additional 5-year period 
under the reasonable cost-based reimbursement methodology for the 
demonstration for the hospitals that were participating as of this 
date.
    Section 410A(c)(2) of Public Law 108-173 requires that in 
conducting the demonstration program under this section, the 
Secretary shall ensure that the aggregate payments made by the 
Secretary do not exceed the amount which the Secretary would have 
paid if the demonstration program under this section was not 
implemented (budget neutrality). We are adopting the general 
methodology used in previous years, whereby we estimate the 
additional payments made by the program for each of the 
participating hospitals as a result of the demonstration, and then 
adjust the national IPPS rates by an amount sufficient to account 
for the added costs of this demonstration. In other words, we apply 
budget neutrality across the payment system as a whole rather than 
across the participants of this demonstration. The language of the 
statutory budget neutrality requirement permits the agency to 
implement the budget neutrality provision in this manner. The 
statutory language requires that aggregate payments made by the 
Secretary do not exceed the amount which the Secretary would have 
paid if the demonstration was not implemented, but does not identify 
the range across which aggregate payments must be held equal.
    For this final rule, the resulting amount applicable to FY 2022 
is $65,779,803, which we are proposing to include in the budget 
neutrality offset adjustment for FY 2022. This estimated amount is 
based on the specific assumptions regarding the data sources used, 
that is, recently available ``as submitted'' cost reports and 
historical and currently finalized update factors for cost and 
payment.
    In previous years, we have incorporated a second component into 
the budget neutrality offset amounts identified in the final IPPS 
rules. As finalized cost reports became available, we determined the 
amount by which the actual costs of the demonstration for an 
earlier, given year differed from the estimated costs for the 
demonstration set forth in the final IPPS rule for the corresponding 
fiscal year, and we incorporated that amount into the budget 
neutrality offset amount for the upcoming fiscal year. We have 
calculated this difference for FYs 2005 through 2015 between the 
actual costs of the demonstration as determined from finalized cost 
reports once available, and estimated costs of the demonstration as 
identified in the applicable IPPS final rules for these years.
    With the extension of the demonstration for another 5-year 
period, as authorized by section 128 of Public Law 116-260, we will 
continue this general procedure. All finalized cost reports are now 
available for the 18 hospitals that completed a cost reporting 
period beginning in FY 2016 according to the demonstration cost-
based payment methodology. For this fiscal year, the actual costs of 
the demonstration as indicated by the finalized cost reports 
exceeded the estimated amount identified in the final rule for that 
year by $3,797,994. Keeping with previous practice, we are adding 
this difference to the estimated about for the upcoming year in 
arriving at the total budget neutrality offset amount for FY 2022. 
This amount is $69,577,797, which we will subtract from the national 
IPPS payment rates.

7. Effects of the Repeal of the Market-Based MS-DRG Policy

    In section V.L. of the preamble of this final rule, we discuss 
the final policy to repeal the requirement that a hospital report on 
the Medicare cost report the median payer-specific negotiated charge 
that the hospital has negotiated with all of its MA organization 
payers, by MS-DRG, for cost reporting periods ending on or after 
January 1, 2021, as finalized in the FY 2021 IPPS/LTCH PPS final 
rule. In the FY 2021 IPPS/LTCH PPS final rule, we estimated the 
total annual burden hours for this data collection requirement as 
follows: 20 hours per hospital times 3,189 total hospitals equals 
63,780 annual burden hours and $4,315,993 annually for all hospitals 
nationally. We refer readers to 85 FR 59015 for further analysis of 
this assessment.
    The market-based MS-DRG relative weight methodology, as 
finalized in the FY 2021 IPPS/LTCH PPS final rule, was adopted 
effective beginning with the relative weights calculated for FY 
2024. As discussed in section V.L of the preamble of this final 
rule, we are finalizing our proposal to repeal the market-based MS-
DRG relative weight methodology effective in FY 2024. As such, we 
will continue calculating the MS-DRG relative weights using the 
current cost-based MS-DRG relative weight methodology for FY 2024 
and subsequent fiscal years.
    Repealing the market-based data collection requirement and 
market-based MS-DRG relative weight methodology does not result in a 
payment impact to hospitals or increase hospital burden.

8. Effects of Continued Implementation of the Frontier Community Health 
Integration Project (FCHIP) Demonstration

    In section VII.B.2. of the preamble of this final rule, we 
discuss the implementation of the FCHIP demonstration, which allows

[[Page 45595]]

eligible entities to develop and test new models for the delivery of 
health care services in eligible counties in order to improve access 
to and better integrate the delivery of acute care, extended care, 
and other health care services to Medicare beneficiaries in no more 
than four States. Budget neutrality estimates for the demonstration 
described in the preamble of this rule are based on the time period 
from August 1, 2016 through July 31, 2019 (referred to in this 
section as the ``initial period'' of the demonstration). Section 129 
of the Consolidated Appropriations Act (Pub. L. 116-159) extends the 
FCHIP Demonstration by 5 years (referred to in this section as the 
``extension period'' of the demonstration). The FCHIP Demonstration 
will resume on January 1, 2022, and CAHs participating in the 
demonstration project during the extension period shall begin such 
participation in the cost reporting year that begins on or after 
January 1. The initial period of the demonstration included three 
intervention prongs, under which specific waivers of Medicare 
payment rules allowed for enhanced payment: Telehealth, skilled 
nursing facility/nursing facility services, and ambulance services. 
These waivers were implemented with the goal of increasing access to 
care with no net increase in costs. (We also discussed this policy 
in the FY 2018 IPPS/LTCH PPS final rule (82 FR 38294 through 38296), 
the FY 2019 IPPS/LTCH PPS final rule (83 FR 41516 through 41517), 
the FY 2020 IPPS/LTCH PPS final rule (84 FR 42427 and 42428) and the 
FY 2021 IPPS/LTCH PPS final rule (85 FR 588894 through 58896), but 
did not make any changes to the policy that was adopted in FY 2017.)
    We specified the payment enhancements for the demonstration 
initial period and selected CAHs for participation with the goal of 
maintaining the budget neutrality of the demonstration on its own 
terms (that is, the demonstration would produce savings from reduced 
transfers and admissions to other health care providers, thus 
offsetting any increase in payments resulting from the 
demonstration). However, because of the small size of this 
demonstration program and uncertainty associated with projected 
Medicare utilization and costs, in the FY 2017 IPPS/LTCH PPS final 
rule we adopted a contingency plan (81 FR 57064 through 57065) to 
ensure that the budget neutrality requirement in section 123 of 
Public Law 110-275 would be met. Accordingly, if analysis of claims 
data for the Medicare beneficiaries receiving services at each of 
the participating CAHs, as well as of other data sources, including 
cost reports, shows that increases in Medicare payments under the 
demonstration during the 3-year initial period are not sufficiently 
offset by reductions elsewhere, we will recoup the additional 
expenditures attributable to the demonstration through a reduction 
in payments to all CAHs nationwide. The demonstration was projected 
to impact payments to participating CAHs under both Medicare Part A 
and Part B. Thus, in the event that we determine that aggregate 
payments under the demonstration exceed the payments that would 
otherwise have been made, we will recoup payments through reductions 
of Medicare payments to all CAHs under both Medicare Part A and Part 
B. Because of the small scale of the demonstration, it would not be 
feasible to implement budget neutrality by reducing payments only to 
the participating CAHs. Therefore, our policy was to make the 
reduction to payments to all CAHs, not just those participating in 
the demonstration, because the FCHIP demonstration is specifically 
designed to test innovations that affect delivery of services by 
this provider category. As we explained in the FY 2017 IPPS/LTCH PPS 
final rule (81 FR 57064 through 57065), we believe that the language 
of the statutory budget neutrality requirement at section 
123(g)(1)(B) of the Act permits the agency to implement the budget 
neutrality provision in this manner. The statutory language merely 
refers to ensuring that aggregate payments made by the Secretary do 
not exceed the amount which the Secretary estimates would have been 
paid if the demonstration project was not implemented, and does not 
identify the range across which aggregate payments must be held 
equal.
    Under the policy finalized in the FY 2017 IPPS/LTCH PPS final 
rule, in the event the demonstration is found not to have been 
budget neutral, any excess costs will be recouped over a period of 3 
cost reporting years, beginning in CY 2020. In the FY 2021 IPPS/LTCH 
PPS final rule (85 FR 58895), we stated that based on the currently 
available data, the determination of budget neutrality results was 
preliminary and the amount of any reduction to CAH payments that 
would be needed in order to recoup excess costs under the 
demonstration remained uncertain. Therefore, we revised the policy 
originally adopted in the FY 2017 IPPS/LTCH PPS final rule, to delay 
the implementation of any budget neutrality adjustment and stated 
that we would revisit this policy in rulemaking for FY 2022, when we 
expected to have complete data for the inital demonstration period. 
Based on the data and actuarial analysis described previously, we 
have concluded the initial period of the FCHIP demonstration 
(covering the time period August 1, 2016, to July 31, 2019) has 
satisfied the budget neutrality requirement described in section 
123(g)(1)(B) of Public Law 110-275. Therefore, we are not applying a 
budget neutrality payment offset to payments to CAHs in FY 2022. 
This policy will have no impact for any national payment system for 
FY 2022.

9. Effects of the Policy Regarding Medicaid Enrollment of Medicare 
Providers and Suppliers for Purposes of Processing Claims for Cost 
Sharing for Services Furnished to Dually Eligible Beneficiaries

    In section X.A. of the preamble of this final rule, we discuss 
our provision regarding Medicaid enrollment of Medicare providers 
and suppliers for purposes of processing claims for cost-sharing for 
services furnished to dually eligible beneficiaries.
    Under section 1902(a)(10)(E) of the Act, States are liable for 
Medicare cost-sharing amounts for certain beneficiaries dually 
eligible for Medicare and Medicaid, including those in the Qualified 
Medicare Beneficiary (QMB) program. Per section 1905(p)(3) of the 
Act, this cost-sharing liability includes costs incurred with 
respect to a QMB regardless of whether the costs incurred were for 
items and services covered under the Medicaid State plan. 
Nevertheless, some States in the past have hindered some Medicare 
providers from enrolling in Medicaid. As a result, these non-
Medicaid-enrolled providers may not be able to submit a claim for 
payment of Medicare cost-sharing.
    Because some States at times have not met their obligation at 
section 1905(p)(3) of the Act to determine Medicare cost-sharing 
liability, we are finalizing the addition of a new paragraph (d) to 
42 CFR 455.410 to specify, in part, how States must meet this 
obligation. Specifically, we propose that by January 1, 2023, for 
purposes of determining Medicare cost-sharing liability, state 
Medicaid programs must accept enrollment from all Medicare-enrolled 
providers and suppliers (even if a provider or supplier is of a type 
that the State would not otherwise enroll in the state Medicaid 
program), if the provider otherwise meets all other Federal Medicaid 
enrollment requirements, including, but not limited to, all 
applicable provisions of 42 CFR part 455, subparts B and E.
    We solicited comment on the cost and savings resulting from this 
policy. We received comments from close to 50 stakeholders on the 
new regulation as detailed in section X.A, however no comments on 
the impact analysis. However, we have further considered and revised 
this estimated impact since the proposed rule.
    There are three areas where this policy would have impact; 
listed here and discussed in further detail later in this section.
     Updating state Medicaid systems with other provider 
types and cost-sharing logic.
     New providers and suppliers enrolling in state Medicaid 
systems.
     Reducing Medicare bad debt appeals.
    We are unable to estimate the change in Medicaid program costs 
or on Medicare bad debt payments in this analysis because States 
have flexibility to choose their cost-sharing payment methodology 
for different provider types in their Medicaid State plan, and we do 
not have a clear basis for assumptions about their future choices. 
States can choose to pay Medicare cost-sharing at the Medicare rate, 
which means the State pays the amount that Medicare establishes as 
the cost-sharing amount. States can also choose to pay Medicare 
cost-sharing using the Medicaid State plan rate, which means the 
State takes into consideration the amount that Medicare paid when 
determining the amount (if any) that the State will pay to bring the 
provider's total payment up to the Medicaid State plan rate. 
Usually, the Medicaid State plan rate is lower than the Medicare 
rate (Medicare paid amount), resulting in no additional Medicare 
cost-sharing payment to the provider from the State. However, if the 
Medicaid State plan rate is higher than the Medicare rate (Medicare 
paid amount), the State would then pay the difference between the 
Medicare paid amount and the Medicaid State plan rate. States can 
also choose to apply a lesser-of policy, in which States pay the 
lesser of the cost-sharing based on the Medicare rate or the 
Medicaid State plan rate. Lastly, States can pay at a negotiated 
rate.

[[Page 45596]]

    Historically, most States elect a lesser-of policy for state 
payment of cost-sharing for hospital claims, meaning that they pay 
very little, if any, Medicare cost-sharing. For example, 43 States 
used the lesser-of policy for cost-sharing for Medicare inpatient 
hospital claims in 2018. Therefore, it seems plausible that these 
States would choose to elect lesser-of payment policies for any 
newly enrolled providers, generally limiting new cost-sharing 
liability to zero. However, because States have the flexibly to set 
their cost-sharing methodology for newly enrolled provider types, we 
have not estimated costs based on those future elections. However, 
by properly processing claims for Medicare cost-sharing it ensures 
Medicare is not inappropriately paying bad debt on any cost-sharing 
liability the State should have paid through its Medicaid State plan 
elections.

a. Updating State Medicaid Systems With Other Provider Types and Cost-
Sharing Logic

    While some States in the past have inhibited enrollment of 
certain types of providers or suppliers that are not explicitly 
included in their Medicaid State plan, we have no sound basis upon 
which to estimate how many States will need to make systems changes 
to implement the policy. We estimate a one-time burden for any state 
or territory Medicaid program that needs to make systems changes to 
comply with the provider enrollment requirement as indicated in 
section X.A of the preamble of this final rule. We estimate that it 
would take a maximum of 6 months of work (approximately 960 hours) 
by a computer programmer working at a Bureau of Labor Statistics 
(BLS) mean hourly rate of $44.53 per hour to make the necessary 
systems changes. We project a cost per State of approximately 
$42,749 (960 * $44.53 = $42,749). States are likely eligible for 90/
10 Federal medical assistance percentage (FMAP) for the State 
Medicaid Management Information System (MMIS) as set forth in 
1903(a)(3)(A) of the Act.
    We estimate a 6-month implementation period for these system 
updates. In this final rule, there will be 17 months between when we 
publish the final rule in August 2021, and the January 1, 2023 
applicability date. The purpose of the 17-month window is to give 
organizations flexibility to find a 6-month period to perform 
updates as indicated in section X.A. of the preamble of this final 
rule. States have the ability to choose, in consultation with CMS, 
when in the 17-month implementation period they want to make this 
change. Therefore, as noted previously, the total cost impact per 
State of $42,749 will occur over 6 months within this 17-month 
period.

b. New Providers and Suppliers Enrolling in State Medicaid Systems

    We are uncertain how many providers and suppliers will seek to 
newly enroll in Medicaid as a result of this policy. We estimate 
enrollment will take an average of three hours for a provider office 
manager, at a BLS mean hourly rate of $28.91 per hour, to complete 
and would cost $86.73 for each provider (3 hours * $28.91/hr). 
Therefore, for every 100 providers and suppliers that apply to 
enroll in Medicaid, we estimate a cost of $8,673. We assume that it 
will take States a similar amount of time to review and process 
these enrollment applications. Therefore, for every 100 providers 
and suppliers for which a State will need to process enrollment 
applications, we estimate the total cost per State is $8,673.

c. Reducing Medicare Bad Debt Appeals

    This final rule will not affect existing bad debt appeals. 
However, we believe the final rule may reduce the number of future 
bad debt appeals by ensuring certain Medicare-enrolled providers and 
suppliers can enroll with state Medicaid programs, receive Medicaid 
Remittance Advice (RA), and claim Medicare bad debt. In eliminating 
these appeals, the provision will eliminate the cost for providers 
and suppliers to pursue such appeals and subsequent litigation, as 
well as the costs for CMS to defend them. Therefore, we estimate 
provider and Medicare cost savings from avoiding future Medicare bad 
debt appeals. As noted previously, we did not estimate a reduction 
in Medicare bad debt payments that would result from an increase in 
State payment of Medicare cost-sharing because States have 
flexibility to choose their cost-sharing payment methodology for 
different provider types in their Medicaid State plan, and we do not 
have a clear basis for assumptions about their future choices.
    While we cannot predict the outcome of future appeals and 
litigation, the February 2021 decision in the Select Specialty 
Hospital--Denver v. Azar case, which included claims from 77 
providers in 26 states from 2005 to 2010, helps us better understand 
the potential costs avoided by finalizing this provision.
    Medicare Hospital Insurance Trust Fund Payments. After an 
adverse decision for CMS in that case, the Federal government 
ultimately paid the plaintiffs a total of $23,649,492, which 
included the principal amount of $18,656,588 for the payment of bad 
debt claims that had been denied, plus associated interest of 
$4,992,904. This provision helps ensure that the amount paid for bad 
debt accurately reflects State liability; it would also eliminate 
costs associated with interest, should future cases be decided 
similarly to Select Specialty Hospital--Denver v. Azar.
    Litigation costs. In the case, the plaintiffs sought $1,174,000 
in total costs of attorneys' fees and costs incurred to litigate 
denied Medicare bad debt claims dating from 2005 to 2010 through the 
Medicare Provider Reimbursement Review Board (PRRB) and in Federal 
District Court. The court denied this request, so these costs were 
borne by the providers. Their true litigation costs might have been 
higher since there were subsequent proceedings in the case not 
reflected in the fee request.
    The Federal government also bears significant costs to process 
and defend these appeals and subsequent litigation: The Medicare 
Administrative Contractor (MAC) and the Federal Specialized Service 
prepare the documentation to present at the PRRB; the PRRB holds a 
hearing and issues a decision; the CMS Attorney Advisor disseminates 
the PRRB decision to the appropriate parties, such as the Federal 
Specialized Service and CMS payment policy staff, for input on the 
PRRB decision and then issues a final Administrator's decision on 
the case, if appropriate; the Office of General Council defends the 
case in court, prepares and files briefs and motions, which may also 
involve components of the U.S. Department of Justice; if necessary, 
the Office of General Council advises CMS regarding any appropriate 
settlements or implementation of any adverse decisions, which the 
MAC then implements.
    Currently, there are at least 20 open cases before the PRRB for 
the same issue presented in the Select Specialty Hospital--Denver 
case, involving claims with dates of service from 2007 to 2020. We 
estimate the provider bad debt reimbursement in controversy across 
these 20 open cases to be $17,248,242. Of these 20 open cases, nine 
cases are under remand from the Federal District Court with a 
calculated potential interest amount of $2,740,794.
    Because we are finalizing this proposal, it is likely that 
appeals on this issue, and their associated costs for Medicare 
providers and for the Federal government described previously, will 
not continue into the future.
    In sum, we note that the estimated costs saved by providers, 
CMS, and other Federal agencies in avoiding ongoing Medicare bad 
debt appeals likely offset the aggregate spending for providers and 
suppliers to enroll with state Medicaid programs, and for States to 
process those applications, as well as the aggregate spending for 
States to update the state Medicaid systems, which will likely be 
eligible for 90/10 FMAP, as described previously.

10. Effects of the Policy Changes to the Medicare Shared Savings 
Program

    In section X.B. of the preamble of this final rule, we describe 
the changes to the Medicare Shared Savings Program (Shared Savings 
Program) established under section 1899 of the Act that we are 
adopting in this final rule. As previously communicated in the 
regulatory impact analysis for the preceding proposed rule, the 
changes are estimated to reduce program spending relative to a 
status quo baseline by extending the flexibility for certain ACOs to 
elect to ``freeze'' their participation level along the BASIC 
track's glide path for PY 2022. Such special flexibility--having 
proven popular among ACOs that chose to ``freeze'' their level of 
participation for PY 2021 in light of the uncertainties caused by 
the COVID-19 PHE, is expected to again help retain ACO participation 
in the program, particularly among ACOs leery of taking on downside 
risk, or increasing levels of downside risk, in the midst of 
pandemic-related uncertainty. In modeling the impacts of the 
changes, we used ACO performance data from the 6-month performance 
year from July 1, 2019, through December 31, 2019, based on CY 2019, 
along with preliminary data from performance year 2020 to identify 
ACOs that would be likely to opt for this flexibility and to 
estimate the potential impact on program spending. We also 
considered the benchmark and performance information ACOs would have 
available when making participation decisions for PY 2022 in the 
context of

[[Page 45597]]

participation decisions made by ACOs in similar positions entering 
PY 2021.
    We estimate that the flexibility would prevent between 20 to 30 
ACOs that would otherwise be required to transition to performance-
based risk in PY 2022 from dropping out of the Shared Savings 
Program. Additionally, we estimate that between 60 to 80 ACOs that 
would otherwise attempt the transition to performance-based risk 
would, out of caution, opt to stay in a one-sided model in PY 2022 
(that is BASIC track Level A or B) despite the opportunity to 
graduate to a higher level of potential reward (under BASIC track 
Levels A and B, ACOs share at most 40 percent of savings, whereas 
BASIC track Levels C, D, and E allow for greater upside potential 
with a maximum sharing rate of 50 percent). The net effect of 
offering this flexibility is estimated to be a $90 million reduction 
in Federal spending, with the reduction ranging from $50 to $140 
million. The estimated impact is roughly evenly split between net 
savings generated by ACOs that would otherwise have terminated their 
participation in the program absent the flexibility and reduced 
shared savings payouts to ACOs that elect to remain at the lower 
sharing rates in Levels A or B of the BASIC track despite the fact 
they would have ultimately earned--as a group--more shared savings 
had they transitioned to a risk arrangement in Level C, D, or E of 
the BASIC track. Although we have estimated the impact of this 
policy over the single performance year for which it would expand 
certain ACOs' participation options, it is possible there could be 
secondary impacts over a longer time period. However, we do not 
believe the longer run potential effects are readily quantifiable. 
On one hand, the final policy could allow certain ACOs to delay 
making more aggressive care delivery changes if they expect CMS is 
likely to continue to offer risk-free participation in the program 
in future rulemaking, as has been the case for two successive rules 
(the May 8, 2020 COVID-19 interim final rule with comment period and 
this FY 2022 IPPS/LTCH PPS final rule). On the other hand, the final 
policy could give other ACOs additional time to grow in confidence 
in their ability to manage the transition to risk, while at the same 
time finding stability in their operations after the disruption from 
the COVID-19 PHE. ACOs in the latter category may then find longer-
term success (including driving lower net spending for the program) 
that might have otherwise been curtailed had the ACO been forced to 
transition to performance-based risk for PY 2022. These two 
scenarios illustrate potential countervailing longer run impacts 
from the ``freeze'' for PY 2022, and while we have not attempted to 
estimate a net impact across the mix of such possible scenarios for 
ACOs impacted by this policy, we assert that offering ACOs in the 
BASIC track the opportunity to ``freeze'' their level of 
participation for PY 2022 increases the chance that the program 
could sustain a larger mix of participants and this outcome 
outweighs the risk that certain ACOs might be marginally slower to 
make efficiency-related changes in care delivery.
    We did not receive any comments regarding the discussion of the 
impacts of this policy in the proposed rule. As discussed in section 
X.B. of the preamble of this final rule, we are finalizing the 
proposed policy without modification. Furthermore, our projection of 
the impact of this change has not changed from what was previously 
communicated in the proposed rule.

I. Effects of Changes in the Capital IPPS

1. General Considerations

    As discussed, in section III.A of the Addendum to this final 
rule, we used claims from the March 2020 update of the FY 2019 
MedPAR file and provider data from the March 2020 update of the 
Provider Specific File (PSF) for purposes of determining the capital 
Federal rate for FY 2022. Consistent with these policies, for the 
impact analysis presented in this section, we used data from the 
March 2020 update of the FY 2019 MedPAR file and the March 2020 
update of the PSF that was used for payment purposes. Although the 
analyses of the changes to the capital prospective payment system do 
not incorporate cost data, we used the March 2021 update of the 
hospital cost report data (FYs 2017 and 2018) to categorize 
hospitals. Our analysis has several qualifications and uses the best 
data available, as described later in this section.
    Due to the interdependent nature of the IPPS, it is very 
difficult to precisely quantify the impact associated with each 
change. In addition, we drew upon various sources for the data used 
to categorize hospitals in the tables. In some cases (for instance, 
the number of beds), there is a fair degree of variation in the data 
from different sources. We have attempted to construct these 
variables with the best available sources overall. However, it is 
possible that some individual hospitals are placed in the wrong 
category.
    Using cases from the March 2020 update of the FY 2019 MedPAR 
file, we simulated payments under the capital IPPS for FY 2021 and 
the payments for FY 2022 for a comparison of total payments per 
case. Short-term, acute care hospitals not paid under the general 
IPPS (for example, hospitals in Maryland) are excluded from the 
simulations.
    The methodology for determining a capital IPPS payment is set 
forth at Sec.  412.312. The basic methodology for calculating the 
capital IPPS payments in FY 2022 is as follows:
    (Standard Federal rate) x (DRG weight) x (GAF) x (COLA for 
hospitals located in Alaska and Hawaii) x (1 + DSH adjustment factor 
+ IME adjustment factor, if applicable).
    In addition to the other adjustments, hospitals may receive 
outlier payments for those cases that qualify under the threshold 
established for each fiscal year. We modeled payments for each 
hospital by multiplying the capital Federal rate by the GAF and the 
hospital's case-mix. Then we added estimated payments for indirect 
medical education, disproportionate share, and outliers, if 
applicable. For purposes of this impact analysis, the model includes 
the following assumptions:
     The capital Federal rate was updated, beginning in FY 
1996, by an analytical framework that considers changes in the 
prices associated with capital-related costs and adjustments to 
account for forecast error, changes in the case-mix index, allowable 
changes in intensity, and other factors. As discussed in section 
III.A.1. of the Addendum to this final rule, the update to the 
capital Federal rate is 0.80 percent for FY 2022.
     In addition to the FY 2022 update factor, the FY 2022 
capital Federal rate was calculated based on a GAF/DRG budget 
neutrality adjustment factor of 1.0004, a budget neutrality factor 
for the lowest quartile hospital wage index adjustment and the 5 
percent cap on wage index decreases policy of 0.9974, and an outlier 
adjustment factor of 0.9471.

2. Results

    We used the payment simulation model previously described in 
section I.I. of Appendix A of this final rule to estimate the 
potential impact of the changes for FY 2022 on total capital 
payments per case, using a universe of 3,195 hospitals. As 
previously described, the individual hospital payment parameters are 
taken from the best available data, including the March 2020 update 
of the FY 2019 MedPAR file, the March 2020 update to the PSF, and 
the cost report data for FYs 2017 and 2018 from the March 2021 
update of HCRIS. In Table III, we present a comparison of estimated 
total payments per case for FY 2021 and estimated total payments per 
case for FY 2022 based on the FY 2022 payment policies. Column 2 
shows estimates of payments per case under our model for FY 2021. 
Column 3 shows estimates of payments per case under our model for FY 
2022. Column 4 shows the total percentage change in payments from FY 
2021 to FY 2022. The change represented in Column 4 includes the 
0.80 percent update to the capital Federal rate and other changes in 
the adjustments to the capital Federal rate. The comparisons are 
provided by: (1) Geographic location; (2) region; and (3) payment 
classification.
    The simulation results show that, on average, capital payments 
per case in FY 2022 are expected to increase as compared to capital 
payments per case in FY 2021. This expected increase overall is 
primarily due to the 0.80 percent update to the capital Federal rate 
for FY 2022 and the reinstatement of the imputed floor in a non-
budget neutral manner. The increase in capital payments due to these 
changes was partially offset by an estimated decrease in capital DSH 
payments due to the estimated increase in the number of hospitals 
that reclassify from urban to rural under Sec.  412.103. We 
approximate that there are 82 hospitals classified as urban (for 
payment purposes) and receiving capital DSH payments in FY 2021, 
that will be classified as rural (for payment purposes) and will not 
receive capital DSH payments in FY 2022. Under Sec.  412.320, in 
order to receive capital DSH payments a hospital must be located in 
an urban area for payment purposes and have 100 or more beds, and 
paragraph (a)(1)(iii) specifies that the geographic classification 
of an urban hospital that is reclassified as rural as set forth in 
Sec.  412.103 is rural. In general, regional variations in estimated 
capital payments per case in FY 2022 as compared to capital payments 
per case in FY 2021 are

[[Page 45598]]

primarily due to the changes in GAFs, and are generally consistent 
with the projected changes in payments due to changes in the wage 
index (and policies affecting the wage index), as shown in Table I 
in section I.G. of this Appendix A.
    The net impact of these changes is an estimated 0.9 percent 
increase in capital payments per case from FY 2021 to FY 2022 for 
all hospitals (as shown in Table III).
    The geographic comparison shows that, on average, hospitals in 
both urban and rural classifications would experience an increase in 
capital IPPS payments per case in FY 2022 as compared to FY 2021. 
Capital IPPS payments per case will increase by an estimated 0.9 
percent for hospitals in urban areas while payments to hospitals in 
rural areas will increase by 1.5 percent in FY 2021 to FY 2022.
    The comparisons by region show that the estimated increases in 
capital payments per case from FY 2021 to FY 2022 for all urban 
areas ranging from a 0.2 percent increase for the West South Central 
region to a 1.5 percent increase for the New England and South 
Atlantic regions. We also estimate that all rural regions are 
expected to experience an increase in capital payments per case from 
FY 2021 to FY 2022, ranging from 0.8 percent for the Pacific rural 
region to 2.3 percent for the West South Central rural region. These 
regional differences are primarily due to the changes in the GAFs 
and estimated changes in outlier and DSH payments.
    All Hospital types of ownerships (Voluntary, Proprietary, and 
Government) are expected to experience an increase in capital 
payments per case from FY 2021 to FY 2022. Government hospitals are 
expected to experience an increase in capital IPPS payments of 0.4 
percent, and the projected increase in capital payments for 
proprietary and voluntary hospitals is estimated to be 1.0 percent 
and 0.9 percent, respectively.
    Section 1886(d)(10) of the Act established the MGCRB. Hospitals 
may apply for reclassification for purposes of the wage index for FY 
2022. Reclassification for wage index purposes also affects the GAFs 
because that factor is constructed from the hospital wage index. To 
present the effects of the hospitals being reclassified as of the 
publication of this final rule for FY 2022, we show the average 
capital payments per case for reclassified hospitals for FY 2022. 
Urban reclassified hospitals are expected to experience an increase 
in capital payments of 0.3 percent; urban nonreclassified hospitals 
are expected to experience an increase in capital payments of 1.3 
percent. The lower expected increase in payments for urban 
reclassified hospitals compared to urban nonreclassified hospitals 
is primarily due to estimated decreases in capital DSH payments to 
urban reclassified hospitals caused by the increase in the number of 
hospitals that reclassify from urban to rural under Sec.  412.103. 
Section 401 Reclassified Hospitals (that is, hospitals that 
reclassify from urban to rural under Sec.  412.103) are expected to 
experience a decrease in capital payments of 0.1 percent. The 
estimated percentage increase for both rural reclassified and 
nonreclassified hospitals is 1.4 percent.
BILLING CODE 4120-01-P

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[GRAPHIC] [TIFF OMITTED] TR13AU21.352


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[GRAPHIC] [TIFF OMITTED] TR13AU21.353

BILLING CODE 4120-01-C

J. Effects of Payment Rate Changes and Policy Changes Under the 
LTCH PPS

1. Introduction and General Considerations

    In section VIII. of the preamble of this final rule and section 
V. of the Addendum to this final rule, we set forth the annual 
update to the payment rates for the LTCH PPS for FY 2022. In the 
preamble of this final rule, we specify the statutory authority for 
the provisions that are presented, identify the policies for FY 
2022, and present rationales for our provisions as well as 
alternatives that were considered. In this section of Appendix A to 
this final rule, we discuss the impact of the changes to the payment 
rate, factors, and other payment rate policies related to the LTCH 
PPS that are presented in the preamble of this final rule in terms 
of their estimated

[[Page 45601]]

fiscal impact on the Medicare budget and on LTCHs.
    There are 363 LTCHs included in this impact analysis. We note 
that, although there were 373 LTCHs with cases in the FY 2019 MedPAR 
files, for purposes of this impact analysis, we excluded the data of 
all-inclusive rate providers consistent with the development of the 
FY 2022 MS-LTC-DRG relative weights (discussed in section 
VIII.B.3.c. of the preamble of this final rule. Moreover, in the 
claims data used for this final rule, 3 of these 363 LTCHs only have 
claims for site neutral payment rate cases and, therefore, do not 
affect our impact analysis for LTCH PPS standard Federal payment 
rate cases.)
    In the impact analysis, we used the payment rate, factors, and 
policies presented in this final rule, the 1.9 percent annual update 
to the LTCH PPS standard Federal payment rate, the update to the MS-
LTC-DRG classifications and relative weights, the update to the wage 
index values and labor-related share, and the best available claims 
and CCR data to estimate the change in payments for FY 2022.
    Under the dual rate LTCH PPS payment structure, payment for LTCH 
discharges that meet the criteria for exclusion from the site 
neutral payment rate (that is, LTCH PPS standard Federal payment 
rate cases) is based on the LTCH PPS standard Federal payment rate. 
Consistent with the statute, the site neutral payment rate is the 
lower of the IPPS comparable per diem amount as determined under 
Sec.  412.529(d)(4), including any applicable outlier payments as 
specified in Sec.  412.525(a), reduced by 4.6 percent for FYs 2018 
through 2026; or 100 percent of the estimated cost of the case as 
determined under Sec.  412.529(d)(2). In addition, there are two 
separate high cost outlier targets--one for LTCH PPS standard 
Federal payment rate cases and one for site neutral payment rate 
cases. The statute also establishes a transitional payment method 
for cases that are paid the site neutral payment rate for LTCH 
discharges occurring in cost reporting periods beginning during FY 
2016 through FY 2019. For FY 2021 and FY 2022, we expected no site 
neutral payment rate cases would still be eligible for the 
transitional payment method since it only applies to those site 
neutral payment rate cases whose discharges occur during a LTCH's 
cost reporting period that begins before October 1, 2019. Site 
neutral payment rate cases whose discharges from an LTCH occur 
during the LTCH's cost reporting period that begins on or after 
October 1, 2019 are paid the site neutral payment rate amount 
determined under Sec.  412.522(c)(1). Therefore, for purposes of 
this impact analysis, to estimate total LTCH PPS payments for site 
neutral payment rate cases in FYs 2021 and 2022 the site neutral 
payment rate amount was applied in full.
    Based on the best available data for the 363 LTCHs in our 
database that were considered in the analyses used for this final 
rule, we estimate that overall LTCH PPS payments in FY 2022 will 
increase by approximately 1.1 percent (or approximately $42 million) 
based on the rates and factors presented in section VIII. of the 
preamble and section V. of the Addendum to this final rule.
    Based on the FY 2019 LTCH cases that were used for the analysis 
in this final rule, approximately 25 percent of those cases were 
classified as site neutral payment rate cases (that is, 25 percent 
of LTCH cases did not meet the statutory patient-level criteria for 
exclusion from the site neutral payment rate). Our Office of the 
Actuary currently estimates that the percent of LTCH PPS cases that 
will be paid at the site neutral payment rate in FY 2022 will not 
change significantly from the most recent historical data. Taking 
into account updates to the IPPS rates and other changes that will 
apply to the site neutral payment rate cases in FY 2022, we estimate 
that aggregate LTCH PPS payments for these site neutral payment rate 
cases will increase by approximately 3 percent (or approximately $11 
million). This projected increase in payments to LTCH PPS site 
neutral payment rate cases is primarily due to the updates to the 
IPPS rates used in calculating the IPPS comparable per diem amount, 
as well as an estimated increase in costs for these cases determined 
using the charge and CCR adjustment factors described in section 
V.D.3.b. of the Addendum to this final rule. We note, we estimate 
payments to site neutral payment rate cases in FY 2022 represent 
approximately 10 percent of estimated aggregate FY 2022 LTCH PPS 
payments.
    Based on the FY 2019 LTCH cases that were used for the analysis 
in this final rule, approximately 75 percent of LTCH cases will meet 
the patient-level criteria for exclusion from the site neutral 
payment rate in FY 2022, and will be paid based on the LTCH PPS 
standard Federal payment rate for the full year. We estimate that 
total LTCH PPS payments for these LTCH PPS standard Federal payment 
rate cases in FY 2022 will increase approximately 0.9 percent (or 
approximately $31 million). This estimated increase in LTCH PPS 
payments for LTCH PPS standard Federal payment rate cases in FY 2022 
is primarily due to the 1.9 percent annual update to the LTCH PPS 
standard Federal payment rate for FY 2022 and the projected 0.8 
percent decrease in high cost outlier payments as a percentage of 
total LTCH PPS standard Federal payment rate payments, which is 
discussed later in this section.
    Based on the 363 LTCHs that were represented in the FY 2019 LTCH 
cases that were used for the analyses in this final rule presented 
in this Appendix, we estimate that aggregate FY 2021 LTCH PPS 
payments will be approximately $3.771 billion, as compared to 
estimated aggregate FY 2022 LTCH PPS payments of approximately 
$3.813 billion, resulting in an estimated overall increase in LTCH 
PPS payments of approximately $42 million. We note that the 
estimated $42 million increase in LTCH PPS payments in FY 2022 does 
not reflect changes in LTCH admissions or case-mix intensity, which 
will also affect the overall payment effects of the policies in this 
final rule.
    The LTCH PPS standard Federal payment rate for FY 2021 is 
$43,755.34. For FY 2022, we are establishing an LTCH PPS standard 
Federal payment rate of $ 44,713.67 which reflects the 1.9 percent 
annual update to the LTCH PPS standard Federal payment rate and the 
budget neutrality factor for the updates to the area wage level 
adjustment of 1.002848 (discussed in section V.B.6. of the Addendum 
to this final rule). For LTCHs that fail to submit data for the LTCH 
QRP, in accordance with section 1886(m)(5)(C) of the Act, we are 
establishing an LTCH PPS standard Federal payment rate of 
$43,836.08. This LTCH PPS standard Federal payment rate reflects the 
updates and factors previously described, as well as the required 
2.0 percentage point reduction to the annual update for failure to 
submit data under the LTCH QRP.
    Table IV shows the estimated impact for LTCH PPS standard 
Federal payment rate cases. The estimated change attributable solely 
to the annual update of 1.9 percent to the LTCH PPS standard Federal 
payment rate is projected to result in an increase of 1.8 percent in 
payments per discharge for LTCH PPS standard Federal payment rate 
cases from FY 2021 to FY 2022, on average, for all LTCHs (Column 6). 
The estimated increase of 1.8 percent shown in Column 6 of Table IV 
also includes estimated payments for short-stay outlier (SSO) cases, 
a portion of which are not affected by the annual update to the LTCH 
PPS standard Federal payment rate, as well as the reduction that is 
applied to the annual update for LTCHs that do not submit the 
required LTCH QRP data. For most hospital categories, the projected 
increase in payments based on the LTCH PPS standard Federal payment 
rate to LTCH PPS standard Federal payment rate cases also rounds to 
approximately 1.8 percent.
    For FY 2022, we are updating the wage index values based on the 
most recent available data (data from cost reporting periods 
beginning during FY 2018 which is the same data used for the FY 2022 
IPPS wage index). In addition, we are establishing a labor-related 
share of 67.9 percent for FY 2022, based on the most recent 
available data (IGI's second quarter 2021 forecast) on the relative 
importance of the labor-related share of operating and capital costs 
of the 2017-based LTCH market basket. We also applying an area wage 
level budget neutrality factor of 1.002848 to ensure that the 
changes to the area wage level adjustment will not result in any 
change in estimated aggregate LTCH PPS payments to LTCH PPS standard 
Federal payment rate cases.
    For LTCH PPS standard Federal payment rate cases, we currently 
estimate high cost outlier payments as a percentage of total LTCH 
PPS standard Federal payment rate payments will decrease from FY 
2021 to FY 2022. Based on the FY 2019 LTCH cases that were used for 
the analyses in this final rule, we estimate that the FY 2021 high 
cost outlier threshold of $27,195 (as established in the FY 2021 
IPPS/LTCH PPS final rule) will result in estimated high cost outlier 
payments for LTCH PPS standard Federal payment rate cases in FY 2021 
that are projected to exceed the 7.975 percent target. Specifically, 
we currently estimate that high cost outlier payments for LTCH PPS 
standard Federal payment rate cases will be approximately 8.8 
percent of the estimated total LTCH PPS standard Federal payment 
rate payments in FY 2021. Combined with our estimate that FY 2022 
high cost outlier

[[Page 45602]]

payments for LTCH PPS standard Federal payment rate cases will be 
7.975 percent of estimated total LTCH PPS standard Federal payment 
rate payments in FY 2022, this will result in an estimated decrease 
in high cost outlier payments as a percentage of total LTCH PPS 
standard Federal payment rate payments of approximately 0.83 percent 
between FY 2021 and FY 2022. We note that, in calculating these 
estimated high cost outlier payments, we inflated charges reported 
on the FY 2019 claims by the charge inflation factor in section 
V.D.3.b. of the Addendum to this final rule. We also note that, in 
calculating these estimated high cost outlier payments, we estimated 
the cost of each case by multiplying the inflated charges by the 
adjusted CCRs that we determined using our methodology described in 
section V.D.3.b. of the Addendum to this final rule.
    Table IV shows the estimated impact of the payment rate and 
policy changes on LTCH PPS payments for LTCH PPS standard Federal 
payment rate cases for FY 2022 by comparing estimated FY 2021 LTCH 
PPS payments to estimated FY 2022 LTCH PPS payments. (As noted 
earlier, our analysis does not reflect changes in LTCH admissions or 
case-mix intensity.) We note that these impacts do not include LTCH 
PPS site neutral payment rate cases for the reasons discussed in 
section I.J.3. of this Appendix.
    As we discuss in detail throughout this final rule, based on the 
best available data, we believe that the provisions of this final 
rule relating to the LTCH PPS, which are projected to result in an 
overall increase in estimated aggregate LTCH PPS payments, and the 
resulting LTCH PPS payment amounts will result in appropriate 
Medicare payments that are consistent with the statute.
    Comment: Multiple commenters expressed concerns about the 
application of the site neutral payment rate once the PHE waivers 
are ended. Several of these commenters stated their belief that 
cases paid at the site neutral payment rate will continue to be 
underpaid as those cases, according to commenters, have on average 
higher levels of clinical complexity and costs that significantly 
exceed IPPS-level payment and that the lower payment of site neutral 
cases relative to the LTCH PPS standard Federal payment rate has 
negatively impacted LTCHs as a provider type. Some of these 
commenters acknowledged that CMS is unable to change this policy but 
request that CMS take into consideration the costs of site neutral 
payment rate cases when proposing any future changes to the LTCH 
PPS.
    A commenter expressed concern that our impact analysis is done 
based on LTCHs as a class of providers and not on a hospital-by-
hospital basis.
    Response: We acknowledge commenters' concerns about the costs of 
treating site neutral cases, however, as noted by some commenters 
and discussed previously, the site neutral payment rate is a 
statutory requirement. We will consider the costs of site neutral 
payment rate cases as appropriate in future rulemaking. For readers 
interested in the provider-level data used for this impact analysis, 
we refer them to the FY 2022 LTCH PPS Final Rule Impact File which 
can be found on our website at: https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/LongTermCareHospitalPPS/LTCHPPS-Historical-Impact-Files.

2. Impact on Rural Hospitals

    For purposes of section 1102(b) of the Act, we define a small 
rural hospital as a hospital that is located outside of an urban 
area and has fewer than 100 beds. As shown in Table IV, we are 
projecting a 1.2 percent increase in estimated payments for LTCH PPS 
standard Federal payment rate cases for LTCHs located in a rural 
area. This estimated impact is based on the FY 2019 data for the 19 
rural LTCHs (out of 360 LTCHs) that were used for the impact 
analyses shown in Table IV.

3. Anticipated Effects of LTCH PPS Payment Rate Changes and Policy 
Changes

a. Budgetary Impact

    Section 123(a)(1) of the BBRA requires that the PPS developed 
for LTCHs ``maintain budget neutrality.'' We believe that the 
statute's mandate for budget neutrality applies only to the first 
year of the implementation of the LTCH PPS (that is, FY 2003). 
Therefore, in calculating the FY 2003 standard Federal payment rate 
under Sec.  412.523(d)(2), we set total estimated payments for FY 
2003 under the LTCH PPS so that estimated aggregate payments under 
the LTCH PPS were estimated to equal the amount that would have been 
paid if the LTCH PPS had not been implemented.
    Section 1886(m)(6)(A) of the Act establishes a dual rate LTCH 
PPS payment structure with two distinct payment rates for LTCH 
discharges beginning in FY 2016. Under this statutory change, LTCH 
discharges that meet the patient-level criteria for exclusion from 
the site neutral payment rate (that is, LTCH PPS standard Federal 
payment rate cases) are paid based on the LTCH PPS standard Federal 
payment rate. LTCH discharges paid at the site neutral payment rate 
are generally paid the lower of the IPPS comparable per diem amount, 
reduced by 4.6 percent for FYs 2018 through 2026, including any 
applicable high cost outlier (HCO) payments, or 100 percent of the 
estimated cost of the case, reduced by 4.6 percent.
    As discussed in section I.J.2. of this Appendix, we project an 
increase in aggregate LTCH PPS payments in FY 2022 of approximately 
$42 million. This estimated increase in payments reflects the 
projected increase in payments to LTCH PPS standard Federal payment 
rate cases of approximately $31 million and the projected increase 
in payments to site neutral payment rate cases of approximately $11 
million under the dual rate LTCH PPS payment rate structure required 
by the statute beginning in FY 2016.
    As discussed in section V.D. of the Addendum to this final rule, 
our actuaries project cost and resource changes for site neutral 
payment rate cases due to the site neutral payment rates required 
under the statute. Specifically, our actuaries project that the 
costs and resource use for cases paid at the site neutral payment 
rate will likely be lower, on average, than the costs and resource 
use for cases paid at the LTCH PPS standard Federal payment rate, 
and will likely mirror the costs and resource use for IPPS cases 
assigned to the same MS-DRG. While we are able to incorporate this 
projection at an aggregate level into our payment modeling, because 
the historical claims data that we are using in this final rule to 
project estimated FY 2022 LTCH PPS payments (that is, FY 2019 LTCH 
claims data) do not reflect this actuarial projection, we are unable 
to model the impact of the change in LTCH PPS payments for site 
neutral payment rate cases at the same level of detail with which we 
are able to model the impacts of the changes to LTCH PPS payments 
for LTCH PPS standard Federal payment rate cases. Therefore, Table 
IV only reflects changes in LTCH PPS payments for LTCH PPS standard 
Federal payment rate cases and, unless otherwise noted, the 
remaining discussion in section I.J.3. of this Appendix refers only 
to the impact on LTCH PPS payments for LTCH PPS standard Federal 
payment rate cases. In the following section, we present our 
provider impact analysis for the changes that affect LTCH PPS 
payments for LTCH PPS standard Federal payment rate cases.

b. Impact on Providers

    The basic methodology for determining a per discharge payment 
for LTCH PPS standard Federal payment rate cases is currently set 
forth under Sec. Sec.  412.515 through 412.533 and 412.535. In 
addition to adjusting the LTCH PPS standard Federal payment rate by 
the MS-LTC-DRG relative weight, we make adjustments to account for 
area wage levels and SSOs. LTCHs located in Alaska and Hawaii also 
have their payments adjusted by a COLA. Under our application of the 
dual rate LTCH PPS payment structure, the LTCH PPS standard Federal 
payment rate is generally only used to determine payments for LTCH 
PPS standard Federal payment rate cases (that is, those LTCH PPS 
cases that meet the statutory criteria to be excluded from the site 
neutral payment rate). LTCH discharges that do not meet the patient-
level criteria for exclusion are paid the site neutral payment rate, 
which we are calculating as the lower of the IPPS comparable per 
diem amount as determined under Sec.  412.529(d)(4), reduced by 4.6 
percent for FYs 2018 through 2026, including any applicable outlier 
payments, or 100 percent of the estimated cost of the case as 
determined under existing Sec.  412.529(d)(2). In addition, when 
certain thresholds are met, LTCHs also receive HCO payments for both 
LTCH PPS standard Federal payment rate cases and site neutral 
payment rate cases that are paid at the IPPS comparable per diem 
amount.
    To understand the impact of the changes to the LTCH PPS payments 
for LTCH PPS standard Federal payment rate cases presented in this 
final rule on different categories of LTCHs for FY 2022, it is 
necessary to estimate payments per discharge for FY 2021 using the 
rates, factors, and the policies established in the FY 2021 IPPS/
LTCH PPS final rule and estimate payments per discharge for FY 2022 
using the rates, factors, and the policies in this FY 2022 IPPS/LTCH 
PPS final rule (as discussed in section VIII. of the preamble of 
this final rule and section V. of the Addendum to this final

[[Page 45603]]

rule). As discussed elsewhere in this final rule, these estimates 
are based on the best available LTCH claims data and other factors, 
such as the application of inflation factors to estimate costs for 
HCO cases in each year. The resulting analyses can then be used to 
compare how our policies applicable to LTCH PPS standard Federal 
payment rate cases affect different groups of LTCHs.
    For the following analysis, we group hospitals based on 
characteristics provided in the OSCAR data, cost report data in 
HCRIS, and PSF data. Hospital groups included the following:
     Location: large urban/other urban/rural.
     Participation date.
     Ownership control.
     Census region.
     Bed size.

c. Calculation of LTCH PPS Payments for LTCH PPS Standard Federal 
Payment Rate Cases

    For purposes of this impact analysis, to estimate the per 
discharge payment effects of our policies on payments for LTCH PPS 
standard Federal payment rate cases, we simulated FY 2021 and final 
FY 2022 payments on a case-by-case basis using historical LTCH 
claims from the FY 2019 MedPAR files that met or would have met the 
criteria to be paid at the LTCH PPS standard Federal payment rate if 
the statutory patient-level criteria had been in effect at the time 
of discharge for all cases in the FY 2019 MedPAR files. For modeling 
FY 2021 LTCH PPS payments, we used the FY 2021 standard Federal 
payment rate of $43,755.34 (or $42,899.90 for LTCHs that failed to 
submit quality data as required under the requirements of the LTCH 
QRP). Similarly, for modeling payments based on the FY 2022 LTCH PPS 
standard Federal payment rate, we used the final FY 2022 standard 
Federal payment rate of $44,713.67 (or $43,836.08 for LTCHs that 
failed to submit quality data as required under the requirements of 
the LTCH QRP). In each case, we applied the applicable adjustments 
for area wage levels and the COLA for LTCHs located in Alaska and 
Hawaii. Specifically, for modeling FY 2021 LTCH PPS payments, we 
used the current FY 2021 labor-related share (68.1 percent), the 
wage index values established in the Tables 12A and 12B listed in 
the Addendum to the FY 2021 IPPS/LTCH PPS final rule (which are 
available via the internet on the CMS website), the FY 2021 HCO 
fixed-loss amount for LTCH PPS standard Federal payment rate cases 
of $27,195 (as reflected in the FY 2021 IPPS/LTCH PPS final rule), 
and the FY 2021 COLA factors (shown in the table in section V.C. of 
the Addendum to that final rule) to adjust the FY 2021 nonlabor-
related share (31.9 percent) for LTCHs located in Alaska and Hawaii. 
Similarly, for modeling FY 2022 LTCH PPS payments, we used the FY 
2022 LTCH PPS labor-related share (67.9 percent), the FY 2022 wage 
index values from Tables 12A and 12B listed in section VI. of the 
Addendum to this final rule (which are available via the internet on 
the CMS website), the FY 2022 HCO fixed-loss amount for LTCH PPS 
standard Federal payment rate cases of $33,015 (as discussed in 
section V.D.3. of the Addendum to this final rule), and the FY 2022 
COLA factors (shown in the table in section V.C. of the Addendum to 
this final rule) to adjust the FY 2022 nonlabor-related share (32.1 
percent) for LTCHs located in Alaska and Hawaii. We note that in 
modeling payments for HCO cases for LTCH PPS standard Federal 
payment rate cases, we inflated charges reported on the FY 2019 
claims by the charge inflation factors in section V.D.3.b. of the 
Addendum to this final rule. We also note that in modeling payments 
for HCO cases for LTCH PPS standard Federal payment rate cases, we 
estimated the cost of each case by multiplying the inflated charges 
by the adjusted CCRs that we determined using our methodology 
described in section V.D.3.b. of the Addendum to this final rule.
    The impacts that follow reflect the estimated ``losses'' or 
``gains'' among the various classifications of LTCHs from FY 2021 to 
FY 2022 based on the payment rates and policy changes applicable to 
LTCH PPS standard Federal payment rate cases presented in this final 
rule. Table IV illustrates the estimated aggregate impact of the 
change in LTCH PPS payments for LTCH PPS standard Federal payment 
rate cases among various classifications of LTCHs. (As discussed 
previously, these impacts do not include LTCH PPS site neutral 
payment rate cases.)
     The first column, LTCH Classification, identifies the 
type of LTCH.
     The second column lists the number of LTCHs of each 
classification type.
     The third column identifies the number of LTCH cases 
expected to meet the LTCH PPS standard Federal payment rate 
criteria.
     The fourth column shows the estimated FY 2021 payment 
per discharge for LTCH cases expected to meet the LTCH PPS standard 
Federal payment rate criteria (as described previously).
     The fifth column shows the estimated FY 2022 payment 
per discharge for LTCH cases expected to meet the LTCH PPS standard 
Federal payment rate criteria (as described previously).
     The sixth column shows the percentage change in 
estimated payments per discharge for LTCH cases expected to meet the 
LTCH PPS standard Federal payment rate criteria from FY 2021 to FY 
2022 due to the annual update to the standard Federal rate (as 
discussed in section V.A.2. of the Addendum to this final rule).
     The seventh column shows the percentage change in 
estimated payments per discharge for LTCH PPS standard Federal 
payment rate cases from FY 2021 to FY 2022 for changes to the area 
wage level adjustment (that is, the updated hospital wage data and 
labor-related share) and the application of the corresponding budget 
neutrality factor (as discussed in section V.B.6. of the Addendum to 
this final rule).
     The eighth column shows the percentage change in 
estimated payments per discharge for LTCH PPS standard Federal 
payment rate cases from FY 2021 (Column 4) to FY 2022 (Column 5) for 
all changes.
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d. Results

    Based on the FY 2019 LTCH cases (from 363 LTCHs) that were used 
for the analyses in this final rule, we have prepared the following 
summary of the impact (as shown in Table IV) of the LTCH PPS payment 
rate and policy changes for LTCH PPS standard Federal payment rate 
cases presented in this final rule. The impact analysis in Table IV 
shows that estimated payments per discharge for LTCH PPS standard 
Federal payment rate

[[Page 45606]]

cases are projected to increase 0.9 percent, on average, for all 
LTCHs from FY 2021 to FY 2022 as a result of the payment rate and 
policy changes applicable to LTCH PPS standard Federal payment rate 
cases presented in this final rule. This estimated 0.9 percent 
increase in LTCH PPS payments per discharge was determined by 
comparing estimated FY 2022 LTCH PPS payments (using the payment 
rates and factors discussed in this final rule) to estimated FY 2021 
LTCH PPS payments for LTCH discharges which will be LTCH PPS 
standard Federal payment rate cases if the dual rate LTCH PPS 
payment structure was or had been in effect at the time of the 
discharge (as described in section I.J.3. of this Appendix).
    As stated previously, we are updating the LTCH PPS standard 
Federal payment rate for FY 2022 by 1.9 percent. For LTCHs that fail 
to submit quality data under the requirements of the LTCH QRP, as 
required by section 1886(m)(5)(C) of the Act, a 2.0 percentage point 
reduction is applied to the annual update to the LTCH PPS standard 
Federal payment rate. Consistent with Sec.  412.523(d)(4), we also 
are applying a budget neutrality factor for changes to the area wage 
level adjustment of 1.002848 (discussed in section V.B.6. of the 
Addendum to this final rule), based on the best available data at 
this time, to ensure that any changes to the area wage level 
adjustment will not result in any change (increase or decrease) in 
estimated aggregate LTCH PPS standard Federal payment rate payments. 
As we also explained earlier in this section, for most categories of 
LTCHs (as shown in Table IV, Column 6), the estimated payment 
increase due to the 1.9 percent annual update to the LTCH PPS 
standard Federal payment rate is projected to result in 
approximately a 1.8 percent increase in estimated payments per 
discharge for LTCH PPS standard Federal payment rate cases for all 
LTCHs from FY 2021 to FY 2022. We note our estimate of the changes 
in payments due to the update to the LTCH PPS standard Federal 
payment rate also includes estimated payments for short-stay outlier 
(SSO) cases, a portion of which are not affected by the annual 
update to the LTCH PPS standard Federal payment rate, as well as the 
reduction that is applied to the annual update for LTCHs that do not 
submit the required LTCH QRP.

(1) Location

    Based on the most recent available data, the vast majority of 
LTCHs are located in urban areas. Only approximately 5 percent of 
the LTCHs are identified as being located in a rural area, and 
approximately 4 percent of all LTCH PPS standard Federal payment 
rate cases are expected to be treated in these rural hospitals. The 
impact analysis presented in Table IV shows that the overall average 
percent increase in estimated payments per discharge for LTCH PPS 
standard Federal payment rate cases from FY 2021 to FY 2022 for all 
hospitals is 0.9 percent. The projected increase for urban hospitals 
is 0.9 percent for urban hospitals, while the projected increase for 
rural hospitals is 1.2 percent.

(2) Participation Date

    LTCHs are grouped by participation date into four categories: 
(1) Before October 1983; (2) between October 1983 and September 
1993; (3) between October 1993 and September 2002; and (4) October 
2002 and after. Based on the best available data, the categories of 
LTCHs with the largest expected percentage of LTCH PPS standard 
Federal payment rate cases (approximately 41 percent and 43 percent, 
respectively) are in LTCHs that began participating in the Medicare 
program between October 1993 and September 2002 and after October 
2002. These LTCHs are expected to both experience an increase in 
estimated payments per discharge for LTCH PPS standard Federal 
payment rate cases from FY 2021 to FY 2022 of 0.9 percent. LTCHs 
that began participating in the Medicare program between October 
1983 and September 1993 are also projected to experience an increase 
in estimated payments per discharge for LTCH PPS standard Federal 
payment rate cases from FY 2021 to FY 2022 of 0.9 percent, as shown 
in Table IV. Approximately 3 percent of LTCHs began participating in 
the Medicare program before October 1983, and these LTCHs are 
projected to experience an average percent increase of 0.5 percent 
in estimated payments per discharge for LTCH PPS standard Federal 
payment rate cases from FY 2021 to FY 2022.

(3) Ownership Control

    LTCHs are grouped into three categories based on ownership 
control type: Voluntary, proprietary, and government. Based on the 
best available data, approximately 17 percent of LTCHs are 
identified as voluntary (Table IV). The majority (approximately 81 
percent) of LTCHs are identified as proprietary, while government 
owned and operated LTCHs represent approximately 3 percent of LTCHs. 
Based on ownership type, voluntary and proprietary LTCHs are each 
expected to experience an increase of 0.6 percent and 1.0 percent in 
payments to LTCH PPS standard Federal payment rate cases, 
respectively. Government owned and operated LTCHs, meanwhile, are 
expected to experience a 1.1 percent increase in payments to LTCH 
PPS standard Federal payment rate cases from FY 2021 to FY 2022.

(4) Census Region

    Estimated payments per discharge for LTCH PPS standard Federal 
payment rate cases for FY 2022 are projected to increase across all 
census regions. LTCHs located in the Mountain region are projected 
to experience the largest increase at 1.5 percent. The remaining 
regions are projected to experience an increase in payments in the 
range of 0.4 to 1.2 percent. These regional variations are primarily 
due to the changes to the area wage adjustment.

(5) Bed Size

    LTCHs are grouped into six categories based on bed size: 0-24 
beds; 25-49 beds; 50-74 beds; 75-124 beds; 125-199 beds; and greater 
than 200 beds. We project that LTCHs with 0-24 beds and 125-199 beds 
will experience the lowest increase in payments for LTCH PPS 
standard Federal payment rate cases, 0.6 percent. LTCHs with 25-49 
beds and 75-124 beds are projected to experience the largest 
increase in payments of 1.0 percent. LTCHs with 50-74 beds and 
greater than 200 beds are projected to experience an increase in 
payments of 0.9 percent and 0.8 percent, respectively.

4. Effect on the Medicare Program

    As stated previously, we project that the provisions of this 
final rule will result in an increase in estimated aggregate LTCH 
PPS payments to LTCH PPS standard Federal payment rate cases in FY 
2022 relative to FY 2021 of approximately $31 million (or 
approximately 0.9 percent) for the 363 LTCHs in our database. 
Although, as stated previously, the hospital-level impacts do not 
include LTCH PPS site neutral payment rate cases, we estimate that 
the provisions of this final rule will result in an increase in 
estimated aggregate LTCH PPS payments to site neutral payment rate 
cases in FY 2022 relative to FY 2021 of approximately $11 million 
(or approximately 3 percent) for the 363 LTCHs in our database. (As 
noted previously, we estimate payments to site neutral payment rate 
cases in FY 2022 represent approximately 10 percent of total 
estimated FY 2022 LTCH PPS payments.) Therefore, we project that the 
provisions of this final rule will result in an increase in 
estimated aggregate LTCH PPS payments for all LTCH cases in FY 2022 
relative to FY 2021 of approximately $42 million (or approximately 
1.1 percent) for the 363 LTCHs in our database.

5. Effect on Medicare Beneficiaries

    Under the LTCH PPS, hospitals receive payment based on the 
average resources consumed by patients for each diagnosis. We do not 
expect any changes in the quality of care or access to services for 
Medicare beneficiaries as a result of this final rule, but we 
continue to expect that paying prospectively for LTCH services will 
enhance the efficiency of the Medicare program. As discussed 
previously, we do not expect the continued implementation of the 
site neutral payment system to have a negative impact on access to 
or quality of care, as demonstrated in areas where there is little 
or no LTCH presence, general short-term acute care hospitals are 
effectively providing treatment for the same types of patients that 
are treated in LTCHs.

K. Effects of Requirements for the Hospital Inpatient Quality 
Reporting (IQR) Program

    In section IX.C. of the preamble of this final rule, we discuss 
our current requirements and finalized proposals for hospitals to 
report quality data under the Hospital IQR Program in order to 
receive the full annual percentage increase for the FY 2023 payment 
determination and subsequent years.
    In this final rule, we are finalizing: (1) Adopting the Maternal 
Morbidity structural measure beginning with a shortened reporting 
period from October 1 through December 31, 2021 (affecting the FY 
2023 payment determination), followed by annual reporting periods 
(affecting the FY 2024 payment determination and subsequent years); 
(2) adopting the Hybrid HWM measure beginning with a 1-year 
voluntary reporting period beginning July 1, 2022 through June 30, 
2023, before requiring mandatory reporting of the measure for the

[[Page 45607]]

reporting period that would run from July 1, 2023 through June 30, 
2024, affecting the FY 2026 payment determination and for subsequent 
years; (3) adopting the COVID-19 Vaccination Coverage among HCP 
measure beginning with a shortened reporting period from October 1, 
2021 through December 31, 2021 affecting the FY 2023 payment 
determination followed by quarterly reporting deadlines affecting 
the FY 2024 payment determination and subsequent years; (4) adopting 
two medication-related adverse event eCQMs (Hospital Harm-Severe 
Hypoglycemia eCQM and Hospital Harm-Severe Hyperglycemia eCQM) 
beginning with the CY 2023 reporting period/FY 2025 payment 
determination; (5) removing the Discharged on Statin Medication eCQM 
(STK-06) beginning with the FY 2026 payment determination; (6) 
removing the Exclusive Breast Milk Feeding (PC-05) measure beginning 
with the FY 2026 payment determination; (7) removing the Admit 
Decision Time to ED Departure Time for Admitted Patients (ED-2) 
measure beginning with the FY 2026 payment determination; (8) 
revising regulations at 42 CFR 412.140(a)(2) by replacing the term 
``QualityNet Administrator'' with the term ``QualityNet security 
official'' and 42 CFR 412.140(e)(2)(iii) by replacing the term 
``QualityNet system administrator'' with the term ``QualityNet 
security official''; (9) revising regulations at 42 CFR 
412.140(a)(1) and 42 CFR 412.140(c)(2)(i) to remove references to 
``QualityNet.org'' and replace with ``QualityNet website''; (10) 
requiring the 2015 Edition Cures Update of CEHRT for eCQMs and 
hybrid measures beginning with the FY 2025 payment determination; 
and (11) extending the effects of educational reviews for fourth 
quarter data such that if an error is identified during the 
education review process for fourth quarter data, we will use the 
corrected quarterly score to compute the final confidence interval 
used for payment determination beginning with validations affecting 
the FY 2024 payment determination. We are not finalizing our 
proposal to remove the Anticoagulation Therapy for Atrial 
Fibrillation/Flutter eCQM (STK-03) or the Death Among Surgical 
Inpatients with Serious Treatable Complications (CMS PSI-04) 
measure.
    As shown in summary table in section XII.B.7.k. of the preamble 
of this final rule, we estimate a total information collection 
burden increase for 3,300 IPPS hospitals of 2,475 hours at a cost of 
$101,475 annually associated with our finalized policies and updated 
burden estimates across a 4-year period from the CY 2022 reporting 
period/FY 2024 payment determination through the CY 2025 reporting 
period/FY 2027 payment determination, compared to our currently 
approved information collection burden estimates. Note that for the 
CY 2022 reporting period/FY 2024 payment determination, the total 
burden increase is only 1,375 hours at a cost of $56,375 due to 
reporting of the Hybrid HWR measure being only for two quarters 
versus four quarters for the CY 2023 reporting period/FY 2025 
payment determination and subsequent years. We refer readers to 
section XII.B.7. of the preamble of this final rule (information 
collection requirements) for a detailed discussion of the 
calculations estimating the changes to the information collection 
burden for submitting data to the Hospital IQR Program.
    As described in sections IX.C.9.e. and IX.C.9.f. of the preamble 
of this final rule, as proposed, we are finalizing an update to 
certification requirements requiring the use of the 2015 Edition 
Cures Update for eCQMs and hybrid measures beginning with the FY 
2025 payment determination. We expect this policy to have no impact 
on information collection burden for the Hospital IQR Program 
because this policy does not require hospitals to submit new data to 
CMS. With respect to any costs unrelated to data submission, 
although this finalized policy will require some investment in 
systems updates, the Medicare Promoting Interoperability Program 
(previously known as the Medicare and Medicaid EHR Incentive 
Programs) previously finalized a requirement that hospitals use the 
2015 Edition Cures Update for eCQMs (85 FR 84818 through 84825). 
Because all hospitals participating in the Hospital IQR Program are 
subsection (d) hospitals that also participate in the Medicare 
Promoting Interoperability Program (previously known as the Medicare 
and Medicaid EHR Incentive Programs), we do not anticipate any 
additional costs as a result of this finalized policy. This is 
because the burden and costs involved in updating to the 2015 
Edition Cures Update is the same regardless of whether the 
technology is used for eCQMs or hybrid measures. Hybrid measure data 
are derived from both claims and clinical EHR data, via submission 
of QRDA I files, and we already collect and utilize claims data and 
QRDA I file data for other measures in the Hospital IQR Program 
measure set. In other words, what hospitals need to do is not 
measure-dependent. Therefore, we believe that the Medicare Promoting 
Interoperability Program has already addressed the additional costs 
unrelated to data submission through their previously finalized 
requirements.
    We also note that in sections IX.C.5. and IX.C.6 of the preamble 
of this final rule, we are finalizing our proposals to adopt two new 
eCQMs and remove three eCQMs. We are not finalizing our proposal to 
remove Anticoagulation Therapy for Atrial Fibrillation/Flutter eCQM 
(STK-03); however, this retention will not change impacts to 
hospitals. Similar to the FY 2019 IPPS/LTCH PPS final rule regarding 
removal of eCQM measures, while there is no change in information 
collection burden related to those finalized provisions, we believe 
that costs are multifaceted and include not only the burden 
associated with reporting but also the costs associated with 
implementing and maintaining Program measures in hospitals' EHR 
systems for all of the eCQMs available for use in the Hospital IQR 
Program (83 FR 41771).
    In section IX.C.5.c. of the preamble of this final rule, as 
proposed, we are finalizing our proposal to adopt a COVID-19 
Vaccination Coverage among HCP measure beginning with a reporting 
period from October 1 to December 31, 2021 affecting the CY 2021 
reporting period/FY 2023 payment determination followed by quarterly 
reporting beginning with the FY 2024 payment determination and 
subsequent years.\1394\ Regarding public reporting of this measure, 
based on public comment, we are finalizing a modification to our 
proposal. Under this modification, we will not finalize our plan to 
add one additional quarter of data during each advancing refresh, 
until the point that four full quarters of data is reached and then 
publicly report the measure using four rolling quarters of data. 
Instead, we will only publicly report the most recent quarter of 
data. However, this will not change the impacts to hospitals as we 
are finalizing the data submission requirements as proposed. 
Hospitals would submit data through the Centers for Disease Control 
and Prevention (CDC) National Healthcare Safety Network (NHSN). The 
NHSN is a secure, internet-based system maintained by the CDC and 
provided free. Currently the CDC does not estimate burden for COVID-
19 vaccination reporting under the CDC PRA package approved under 
OMB control number 0920-1317 because the agency has been granted a 
waiver under section 321 of the National Childhood Vaccine Injury 
Act (NCVIA).\1395\
---------------------------------------------------------------------------

    \1394\ We note that the proposed rule incorrectly read ``annual 
reporting periods'' however the section of the proposed rule on data 
submission (IX.C.5.c.) correctly described the data submission 
process and timelines.
    \1395\ Section 321 of the National Childhood Vaccine Injury Act 
(NCVIA) provides the PRA waiver for activities that come under the 
NCVIA, including those in the NCVIA at section 2102 of the Public 
Health Service Act (42 U.S.C. 300aa-2). Section 321 is not codified 
in the U.S. Code, but can be found in a note at 42 U.S.C. 300aa-1.
---------------------------------------------------------------------------

    Although the burden associated with the COVID-19 Vaccination 
Coverage among HCP measure is not accounted for under the CDC PRA 
0920-1317 or 0920-0666, the cost and burden information are included 
in this section. We estimate that it will take each IPPS subsection 
(d) hospital, on average, 1 hour per month to collect data for the 
COVID-19 Vaccination Coverage among HCP measure and enter it into 
NHSN. We have estimated the time to complete this entire activity, 
since it could vary based on provider systems and staff 
availability. This burden is comprised of administrative hours and 
wages. We believe an Administrative Assistant\1396\ would spend 
between 45 minutes and 1 hour and 15 minutes to enter this data into 
NHSN. For the shortened CY 2021 reporting period, 3 months are 
required. For the CY 2021 reporting period/FY 2023 payment 
determination, IPPS subsection (d) hospitals would incur an 
additional burden between 2.25 hours (0.75 hours x 3 months) and 
3.75 hours (1.25 hours x 3 months) per hospital. For all 3,300 
hospitals, the total burden would range from 7,425 hours (2.25 hours 
x 3,300 IPPS hospitals) and 12,375 hours (3.75 hours x 3,300 IPPS 
hospitals). Each hospital would incur an estimated cost of between 
$27.47 (0.75 hours x $36.62) and $45.78 (1.25 hours x $36.62) 
monthly and

[[Page 45608]]

between $82.40 (2.25 hours x $36.62) and $137.33 (3.75 hours x 
$36.62) in total over the shortened period to complete this task. 
Thereafter, 12 months of data are required annually (12 months x 1 
hour per month) with quarterly data submission deadlines. IPPS 
subsection (d) hospitals would incur an additional annual burden 
between 9 hours (0.75 hours x 12 months) and 15 hours (1.25 hours x 
12 months) per hospital and between 29,700 hours (9 hours x 3,300 
IPPS hospitals) and 49,500 hours (15 hours x 3,300 IPPS hospitals) 
for all hospitals. Each hospital would incur an estimated cost of 
between $329.58 (9 hours x $36.62) and $549.30 annually (15 hours x 
$36.62). The estimated cost across all 3,300 IPPS hospitals would be 
between $271,920 ($82.40 x 3,300 IPPS hospitals) and $453,189 
($137.33 x 3,300 IPPS hospitals) for the shortened CY 2021 reporting 
period. The estimated cost across all 3,300 IPPS hospitals would be 
between $1,087,614 ($329.58 x 3,300 IPPS hospitals) and $1,812,690 
($549.30 x 3,300 IPPS hospitals) annually thereafter. We recognize 
that many healthcare facilities are also reporting other COVID-19 
data to HHS. We believe the benefits of reporting data on the COVID-
19 Vaccination Coverage among HCP measure to monitor, track, and 
provide transparency for the public on this important tool to combat 
COVID-19 outweigh the costs of reporting. We welcomed comments on 
the estimated time to collect data and enter it into NHSN.
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    \1396\ https://www.bls.gov/oes/current/oes436013.htm (accessed 
on March 30, 2021). The adjusted hourly wage rate of $36.62/hour 
includes an adjustment of 100 percent of the median hourly wage to 
account for the cost of overhead, including fringe benefits.
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    Historically, 100 hospitals, on average, that participate in the 
Hospital IQR Program do not receive the full annual percentage 
increase in any fiscal year due to the failure to meet all 
requirements of this Program. We anticipate that the number of 
hospitals not receiving the full annual percentage increase will be 
approximately the same as in past years.
    We did not receive any public comments regarding the estimated 
time to collect data and enter it into the NHSN.

L. Effects of Requirements for the PPS-Exempt Cancer Hospital 
Quality Reporting (PCHQR) Program

    In section IX.D. of the preamble of this final rule, we discuss 
our proposed and finalized policies for the quality data reporting 
program for PPS-exempt cancer hospitals (PCHs), which we refer to as 
the PPS-Exempt Cancer Hospital Quality Reporting (PCHQR) Program. 
The PCHQR Program is authorized under section 1866(k) of the Act, 
which was added by section 3005 of the Affordable Care Act. There is 
no financial impact to PCH Medicare reimbursement if a PCH does not 
submit data.
    In section IX.D.4. of the preamble of this final rule, we are 
finalizing the removal of the Oncology: Plan of Care for Pain--
Medical Oncology and Radiation Oncology (NQF #0383/PCH-15) measure 
beginning with the FY 2024 program year, adopting the COVID-19 
Vaccination Coverage among Healthcare Personnel (HCP) measure 
beginning with the FY 2023 program year, with reporting for the FY 
2023 program year from October 1 through December 31, 2021, followed 
by quarterly reporting periods \1397\ beginning with the FY 2024 
program year, and codifying existing program policies. As stated in 
section XII.B.7. of the preamble of this final rule, we estimated 
the total burden reduction associated with the removal of PCH-15 
beginning with the FY 2024 program year to be 2.75 hours (0.25 hours 
x 11 PCHs) with a total cost reduction of $113 (2.75 hours x $41.00/
hour).
---------------------------------------------------------------------------

    \1397\ We note that the proposed rule incorrectly read ``annual 
reporting periods'' however the section of the proposed rule on data 
submission (IX.D.5.c.) correctly described the data submission 
process and timelines.
---------------------------------------------------------------------------

    In section IX.D.5. of the preamble of this final rule, we are 
finalizing our proposal to adopt a COVID-19 Vaccination Coverage 
among HCP measure beginning with a shortened reporting period from 
October 1 to December 31, 2021, affecting the FY 2023 program year 
followed by quarterly reporting \1398\ beginning with the FY 2024 
program year and subsequent years. PCHs will submit data through the 
CDC NHSN. The NHSN is a secure, internet-based system maintained by 
the CDC and provided free. Currently, the CDC does not estimate 
burden for COVID-19 vaccination reporting under the CDC PRA package 
approved under OMB control number 0920-1317 because the agency has 
been granted a waiver under section 321 of the National Childhood 
Vaccine Injury Act (NCVIA).\1399\
---------------------------------------------------------------------------

    \1398\ We note that the proposed rule incorrectly read ``annual 
reporting periods'' however the section of the proposed rule on data 
submission (IX.D.5.c.) correctly described the data submission 
process and timelines.
    \1399\ Section 321 of the National Childhood Vaccine Injury Act 
(NCVIA) provides the PRA waiver for activities that come under the 
NCVIA, including those in the NCVIA at section 2102 of the Public 
Health Service Act (42 U.S.C. 300aa-2). Section 321 is not codified 
in the U.S. Code, but can be found in a note at 42 U.S.C. 300aa-1.
---------------------------------------------------------------------------

    Although the burden associated with the COVID-19 Vaccination 
Coverage among HCP measure is not accounted for under the CDC PRA 
0920-1317 or 0920-0666, the cost and burden information are included 
in this section. We estimate that it would take each PCH, on 
average, approximately 1 hour per month to collect data for the 
COVID-19 Vaccination Coverage among HCP measure and enter it into 
NHSN. We have estimated the time to complete this entire activity, 
since it could vary based on provider systems and staff 
availability. This burden is comprised of administrative hours and 
wages. We believe it would take an Administrative Assistant \1400\ 
between 45 minutes and 1 hour and 15 minutes to enter this data into 
NHSN. For the shortened CY 2021 reporting period (consisting of 
October 1, 2021 through December 31, 2021), 3 months would be 
required. For the CY 2021 reporting period/FY 2023 program year, 
PCHs would incur an additional burden of between 2.25 hours (0.75 
hours x 3 months) and 3.75 hours (1.25 hours x 3 months) per PCH. 
For all 11 PCHs, the total burden would range from 24.75 hours (2.25 
hours x 11 hospitals) and 41.25 hours (3.75 hours x 11 hospitals). 
Each PCH would incur an estimated cost of between $27.47 (0.75 hour 
x $36.62/hr) and $45.78 (1.25 hours x 36.62/hour) monthly and 
between $82.40 (2.25 hours x $36.62/hr) and $137.33 (3.75 hours x 
$36.62/hour) in total over the shortened period to complete this 
task. Thereafter, 12 months of data would be required annually. 
Therefore, PCHs would incur an additional annual burden between 9 
hours (0.75 hours/month x 12 months) and 15 hours (1.25 hours/month 
x 12 months) per PCH and between 99 hours (9 hours/hospital x 11 
hospitals) and 165 hours (15 hours/hospital x 11 hospitals) for all 
PCHs. Each PCH would incur an estimated cost of between $329.58 (9 
hours x $36.62/hour) and $549.30 annually (15 hours x $36.62/hour). 
The estimated cost across all 11 PCHs would be between $906.40 
($82.40/hospital x 11 hospitals) and $1,510.63 ($137.33/hospital x 
11 hospitals) for the shortened CY 2021 reporting period. The 
estimated cost across all 11 PCHs would be between $3,625.38 
($329.58/hospital x 11 hospitals) and $6,042.30 ($549.30/hospital x 
11 hospitals) annually thereafter. We recognize that many healthcare 
facilities are also reporting other COVID-19 data to HHS. We believe 
the benefits of reporting data on the COVID-19 Vaccination Coverage 
among HCP measure to monitor, track, and provide transparency for 
the public on this important tool to combat COVID-19 outweigh the 
costs of reporting. We welcomed comments on the estimated time to 
collect data and enter it into the NHSN.
---------------------------------------------------------------------------

    \1400\ https://www.bls.gov/oes/current/oes436013.htm (accessed 
on March 30, 2021). The hourly rate of $36.62 includes an adjustment 
of 100 percent of the mean hourly wage to account for the cost of 
overhead, including fringe benefits.
---------------------------------------------------------------------------

    We did not receive any public comments regarding the estimated 
time to collect data and enter it into the NHSN.

M. Effects of Requirements for the Long-Term Care Hospital Quality 
Reporting Program (LTCH QRP)

    In section IX.E.4. of the preamble of this final rule,, we are 
finalizing our proposal to adopt one measure under the Long-Term 
Care Hospital (LTCH) Quality Reporting Program (QRP), the COVID-19 
Vaccination Coverage among Healthcare Personnel (HCP) measure 
beginning with the FY 2023 LTCH QRP. We are finalizing our proposal 
to update a measure adopted in the FY 2020 IPPS/LTCH final rule (84 
FR 42044), the Transfer of Health (TOH) Information to the Patient--
Post-Acute Care (PAC) measure beginning with the FY 2023 LTCH QRP. 
We are also finalizing our proposals to begin publicly displaying 
data for the quality measures Compliance with Spontaneous Breathing 
Trial (SBT) by Day 2 of the LTCH Stay and the Ventilator Liberation 
Rate for the Post-Acute Care (PAC) Long-Term Care Hospital (LTCH) 
Quality Reporting Program (QRP) on Care Compare and PDC, and to 
publicly report the COVID-19 Vaccination Coverage among HCP measure 
on Care Compare. In addition, we are finalizing our proposal to 
publicly report LTCH QRP measures using fewer quarters of data than 
previously finalized due to an exemption we granted the LTCHs under 
our regulations at 42 CFR 412.560(c)(4). Finally, we sought 
information on two issues: CMS' future plans

[[Page 45609]]

to define digital quality measures (dQMs) for the LTCH QRP; the 
potential use of Fast Healthcare Interoperability Resources (FHIR) 
for dQMs within the LTCH QRP; and input on CMS continued efforts to 
close the health equity gap.
    The CDC will account for the burden associated with the COVID-19 
Vaccination Coverage among HCP measure collection under OMB control 
number 0920-1317 (expiration January 31, 2024). However, the CDC 
currently has a PRA waiver for the collection and reporting of 
vaccination data under section 321 of the National Childhood Vaccine 
Injury Act of 1986 (Pub. L. 99-660, enacted on November 14, 1986) 
(NCVIA).\1401\ We refer readers to section XII.B.8. of this final 
rule, where CMS has provided an estimate of the burden and cost to 
LTCHs, and note that the CDC will include it in a revised 
information collection request for 0920-1317.
---------------------------------------------------------------------------

    \1401\ Section 321 of the NCVIA provides the PRA waiver for 
activities that come under the NCVIA, including those in the NCVIA 
at section 2102 of the Public Health Service Act (42 U.S.C. 300aa-
2). Section 321 is not codified in the U.S. Code, but can be found 
in a note at 42 U.S.C. 300aa-1.
---------------------------------------------------------------------------

N. Effects of Requirements Regarding the Medicare Promoting 
Interoperability Program

    In section IX.F.3.b. of the preamble of this final rule, we are 
finalizing the following proposed changes for CY 2022 with eligible 
hospitals and CAHs that attest to CMS under the Medicare Promoting 
Interoperability Program: (1) To maintain the Electronic Prescribing 
Objective's Query of PDMP measure as optional while increasing its 
available bonus from five points to 10 points for the EHR reporting 
period in CY 2022; (2) to add a new Health Information Exchange 
(HIE) Bi-Directional Exchange measure as a yes/no attestation to the 
HIE objective as an optional alternative to the two existing 
measures, beginning with the EHR reporting period in CY 2022; (3) to 
require reporting on four of the existing Public Health and Clinical 
Data Exchange Objective measures (Syndromic Surveillance Reporting, 
Immunization Registry Reporting, Electronic Case Reporting, and 
Electronic Reportable Laboratory Result Reporting); (4) to add a new 
measure to the Protect Patient Health Information objective that 
requires eligible hospitals and CAHs to attest to having completed 
an annual assessment of the SAFER Guides, beginning with the EHR 
reporting period in CY 2022; (5) to remove attestation statements 2 
and 3 from the Promoting Interoperability Program's prevention of 
information blocking requirement; and (6) to increase the minimum 
required score for the objectives and measures from 50 points to 60 
points (out of 100 points) in order to be considered a meaningful 
EHR user. We are amending our regulation text as necessary to 
incorporate these changes.
    In section IX.F.3.b. of the preamble of this final rule, we are 
finalizing the following proposed changes for CY 2024 with eligible 
hospitals and CAHs that attest to CMS under the Medicare Promoting 
Interoperability Program: (1) An EHR reporting period of a minimum 
of any continuous 180-day period in CY 2024 for new and returning 
participants (eligible hospitals and CAHs); and (2) to remove three 
eCQMs from the Medicare Promoting Interoperability Program's eCQM 
measure set beginning with the reporting period in CY 2024, which is 
in alignment with the proposals being finalized under the Hospital 
IQR Program. We are not finalizing our proposal to remove 
Anticoagulation Therapy for Atrial Fibrillation/Flutter eCQM (STK-
03) in alignment with the Hospital IQR Program; however, this 
retention will not change impacts to hospitals. Similar to the FY 
2019 IPPS/LTCH PPS final rule regarding removal of eCQM measures, 
while there is no change in information collection burden related to 
those finalized provisions, we believe that costs are multifaceted 
and include not only the burden associated with reporting but also 
the costs associated with implementing and maintaining program 
measures in hospitals' EHR systems for all of the eCQMs available 
for use in the Medicare Promoting Interoperability and Hospital IQR 
Programs (83 FR 41771). We are amending our regulation text as 
necessary to incorporate these changes.
    As described in section IX.F.11.4. of the preamble of this final 
rule, as proposed, we are finalizing an update to certification 
requirements requiring the use of the 2015 Edition Cures Update for 
eCQMs in alignment with the finalized proposal for the Hospital IQR 
Program, beginning with the FY 2025 payment determination. We expect 
this policy to have no impact on information collection burden for 
the Medicare Promoting Interoperability Program because this policy 
does not require hospitals to submit new data to CMS. Because the 
Medicare Promoting Interoperability Program previously finalized a 
requirement that hospitals use the 2015 Edition Cures Update (85 FR 
84818 through 84825), we do not anticipate any additional costs as a 
result of this finalized policy.
    For the EHR reporting period in CY 2022, the provisions 
summarized here are mainly extensions from or continuations of 
existing policies from the FY 2021 IPPS/LTCH PPS final rule (85 FR 
58966 through 58977) and finalized proposals included in the CY 2021 
PFS final rule (85 FR 84825 through 84828). However, due to an 
update of the hospital staff professional who most likely conducts 
the reporting for the Medicare Promoting Interoperability Program, 
we have updated the Bureau of Labor Statistics wage rate. Such 
changes will result in an estimated total burden cost of $879,450 
for CY 2022 (a net decrease of $607,893 from CY 2021). While in this 
final rule, we are finalizing proposals that influence programmatic 
policies in CY 2023 and CY 2024, we do not believe they would 
attribute to a rise in burden hours, meaning that both prospective 
years would maintain the same estimated total burden cost of 
$879,450. We refer readers to section XII.B. of the preamble of this 
final rule (information collection requirements) for a detailed 
discussion of the calculations estimating the changes to the 
information collection burden for submitting data to the Medicare 
Promoting Interoperability Program.
    We received no comments on these effects.

O. Alternatives Considered

    This final rule contains a range of policies. It also provides 
descriptions of the statutory provisions that are addressed, 
identifies the finalized policies, and presents rationales for our 
decisions and, where relevant, alternatives that were considered.

1. Use of FY 2020 or FY 2019 Data in the FY 2022 IPPS and LTCH PPS 
Ratesetting

    In the FY 2022 IPPS and LTCH PPS proposed rule (86 FR 25086 
through 25090) we explained that for the IPPS and LTCH PPS 
ratesetting, our longstanding goal is to use the best available 
data. We discussed our analysis of the best available data for use 
in the development of the FY 2022 IPPS/LTCH PPS proposed rule given 
the potential impact of the PHE for COVID-19. We proposed to use FY 
2019 data, such as the FY 2019 MedPAR file, for the FY 2022 
ratesetting for circumstances where the FY 2020 data is 
significantly impacted by the COVID-19 PHE, primarily in that the 
utilization of inpatient services reflect generally markedly 
different utilization for certain types of services in FY 2020 than 
would have been expected in the absence of the PHE.
    Alternatively, we considered whether we should use the FY 2020 
data instead of the FY 2019 data for FY 2022 ratesetting purposes. 
The FY 2020 data is what CMS would ordinarily use for purposes of FY 
2022 ratesetting. Public comments were largely supportive of CMS use 
of FY 2019 data. Most commenters agreed that, to the extent 
possible, CMS should use the best available data and that the PHE 
for COVID-19 impacted FY 2020 claims data in a way that may make it 
less accurate and appropriate for FY 2022 ratesetting purposes. As 
discussed in section II.F. of the preamble of this final rule, and 
following our review of public comments, we are finalizing use of 
the FY 2019 data for the FY 2022 IPPS and LTCH PPS ratesetting for 
circumstances where the FY 2020 data is significantly impacted by 
the COVID-19 PHE. For example, we are finalizing our proposal to use 
the FY 2019 MedPAR claims data for purposes where we ordinarily 
would have used the FY 2020 MedPAR claims data, such as in our 
analysis of changes to MS-DRG classifications (as discussed in 
greater detail in section II.D. of the preamble of this final rule). 
Similarly, we are finalizing the use of cost report data from the FY 
2018 HCRIS file for purposes where we ordinarily would have used the 
FY 2019 HCRIS file, such as in determining the final FY 2022 IPPS 
MS-DRG (as discussed in greater detail in section II.D. of the 
preamble of this final rule) and finalized FY 2022 MS-LTC-DRG 
relative weights (as discussed in greater detail section VI.B. of 
the preamble of this final rule).

2. Market-Based MS-DRG Relative Weight Policy

    In the FY 2021 IPPS/LTCH PPS final rule, we finalized a 
requirement for a hospital to report on the Medicare cost report the 
median payer-specific negotiated charge that the hospital has 
negotiated with all of its MA organization payers, by MS-DRG, for 
cost reporting periods ending on or after January 1, 2021 (85 FR 
58873 through 58892); this data collection requirement was specified 
in

[[Page 45610]]

42 CFR 413.20(d)(3). We also finalized the use of this data in a new 
market-based methodology for calculating the IPPS MS-DRG relative 
weights to reflect relative market-based pricing, beginning in FY 
2024. Specifically, we finalized that we would begin using the 
reported median payer-specific negotiated charge by MS-DRG for MA 
organizations in the market-based MS-DRG relative weight methodology 
beginning with the relative weights calculated for FY 2024.
    In the FY 2022 IPPS and LTCH PPS proposed rule, we proposed to 
repeal the requirement that a hospital report on the Medicare cost 
report the median payer-specific negotiated charge that the hospital 
has negotiated with all of its MA organization payers, by MS-DRG, 
for cost reporting periods ending on or after January 1, 2021. We 
also proposed to repeal the market-based MS-DRG relative weight 
methodology adopted for calculating the MS-DRG relative weights 
effective in FY 2024, and to continue using the existing cost-based 
methodology for calculating the MS-DRG relative weights for FY 2024 
and subsequent fiscal years.
    In the FY 2022 IPPS/LTCH PPS proposed rule, we considered an 
alternative to our proposal to maintain the requirement that 
hospitals report the median payer-specific negotiated charge for MA 
organizations on the Medicare cost report, but delay the 
implementation of the market-based MS-DRG relative weight 
methodology from FY 2024 to a later date. Under the alternative to 
delay the implementation of the market-based MS-DRG relative weight 
methodology, we would maintain the market-based MS-DRG relative 
weight data collection policy, as finalized in the FY 2021 IPPS/LTCH 
PPS final rule, and would require that hospitals follow the steps 
outlined in the frequently asked questions document published on 
January 15, 2021 that provides examples for how hospitals would 
calculate the median payer specific negotiated charge so that the 
market-based data is comparable and consistent across different 
negotiation tactics used by hospitals and MA organizations.
    After consideration of the public comments, as discussed in 
section V.L. of the preamble of this final rule, we are finalizing 
our proposal to repeal the requirement that hospitals report on the 
Medicare cost report the median payer-specific negotiated charge 
that the hospital has negotiated with all of its MA organization 
payers, by MS-DRG, for cost reporting periods ending on or after 
January 1, 2021, as finalized in the FY 2021 IPPS/LTCH PPS final 
rule. We are also finalizing our proposal to repeal the market-based 
MS-DRG relative weight methodology adopted effective for FY 2024, as 
finalized in the FY 2021 IPPS/LTCH PPS final rule.

P. Overall Conclusion

1. Acute Care Hospitals

    Acute care hospitals are estimated to experience an increase of 
approximately $2.293 billion in FY 2022, including operating, 
capital, and new technology changes, as estimated for this final 
rule. The estimated change in operating payments is approximately 
$1.6 billion (discussed in section I.G. and I.H. of this Appendix). 
The estimated change in capital payments is approximately $0.076 
billion (discussed in section I.I. of this Appendix). The estimated 
change in new technology add-on payments is approximately $0.65 
billion as discussed in section I.H. of this Appendix. The change in 
new technology add-on payments reflects the net impact of new and 
continuing new technology add-on payments. Total may differ from the 
sum of the components due to rounding.
    Table I. of section I.G. of this Appendix also demonstrates the 
estimated redistributional impacts of the IPPS budget neutrality 
requirements for the final MS-DRG and wage index changes, and for 
the wage index reclassifications under the MGCRB.
    We estimate that hospitals would experience a 0.9 percent 
increase in capital payments per case, as shown in Table III. of 
section I.I. of this Appendix. We project that there will be a $76 
million increase in capital payments in FY 2022 compared to FY 2021.
    The discussions presented in the previous pages, in combination 
with the remainder of this final rule, constitute a regulatory 
impact analysis.

2. LTCHs

    Overall, LTCHs are projected to experience an increase in 
estimated payments in FY 2022. In the impact analysis, we are using 
the final rates, factors, and policies presented in this final rule 
based on the best available claims and CCR data to estimate the 
change in payments under the LTCH PPS for FY 2022. Accordingly, 
based on the best available data for the 363 LTCHs in our database, 
we estimate that overall FY 2022 LTCH PPS payments will increase 
approximately $42 million relative to FY 2021 primarily due to the 
annual update to the LTCH PPS standard Federal rate.

Q. Regulatory Review Costs

    If regulations impose administrative costs on private entities, 
such as the time needed to read and interpret a rule, we should 
estimate the cost associated with regulatory review. Due to the 
uncertainty involved with accurately quantifying the number of 
entities that would review the proposed rule, we assumed that the 
total number of timely pieces of correspondence on last year's 
proposed rule would be the number of reviewers of the proposed rule. 
We acknowledge that this assumption may understate or overstate the 
costs of reviewing the rule. It is possible that not all commenters 
reviewed last year's rule in detail, and it is also possible that 
some reviewers chose not to comment on the proposed rule. For those 
reasons, and consistent with our approach in previous rulemakings 
(83 FR 41777, 84 FR 42697, and 85 FR 32460), we believe that the 
number of past commenters would be a fair estimate of the number of 
reviewers of the proposed rule. We welcomed any public comments on 
the approach in estimating the number of entities that reviewed the 
proposed rule.
    We also recognize that different types of entities are in many 
cases affected by mutually exclusive sections of the rule. 
Therefore, for the purposes of our estimate, and consistent with our 
approach in previous rulemakings (83 FR 41777, 84 FR 42697, and 85 
FR 32460), we assume that each reviewer read approximately 50 
percent of the proposed rule. We welcomed public comments on this 
assumption.
    We have used the number of timely pieces of correspondence on 
the FY 2021 IPPS/LTCH proposed rule as our estimate for the number 
of reviewers of the proposed rule. We continue to acknowledge the 
uncertainty involved with using this number, but we believe it is a 
fair estimate due to the variety of entities affected and the 
likelihood that some of them choose to rely (in full or in part) on 
press releases, newsletters, fact sheets, or other sources rather 
than the comprehensive review of preamble and regulatory text. Using 
the wage information from the BLS for medical and health service 
managers (Code 11-9111), we estimate that the cost of reviewing the 
final rule is $114.24 per hour, including overhead and fringe 
benefits (https://www.bls.gov/oes/current/oes_nat.htm). Assuming an 
average reading speed, we estimate that it would take approximately 
31.96 hours for the staff to review half of this final rule. For 
each IPPS hospital or LTCH that reviews this final rule, the 
estimated cost is $3,651.40 (31.96 hours x $114.24). Therefore, we 
estimate that the total cost of reviewing this final rule is 
$102,450,869 ($3,651.40 x 28,058 reviewers).

II. Accounting Statements and Tables

A. Acute Care Hospitals

    As required by OMB Circular A-4 (available at https://obamawhitehouse.archives.gov/omb/circulars_a-004_a-4/ and https://georgewbush-whitehouse.archives.gov/omb/circulars/a004/a-4.html), in 
Table V. of this Appendix, we have prepared an accounting statement 
showing the classification of the expenditures associated with the 
provisions of this final rule as they relate to acute care 
hospitals. This table provides our best estimate of the change in 
Medicare payments to providers as a result of the changes to the 
IPPS presented in this final rule. All expenditures are classified 
as transfers to Medicare providers.
    As shown in Table V. of this Appendix, the net costs to the 
Federal Government associated with the policies finalized in this 
final rule are estimated at $2.293 billion.

[[Page 45611]]

[GRAPHIC] [TIFF OMITTED] TR13AU21.356

B. LTCHs

    As discussed in section I.J. of this Appendix, the impact 
analysis of the payment rates and factors presented in this final 
rule under the LTCH PPS is projected to result in an increase in 
estimated aggregate LTCH PPS payments in FY 2022 relative to FY 2021 
of approximately $42 million based on the data for 363 LTCHs in our 
database that are subject to payment under the LTCH PPS. Therefore, 
as required by OMB Circular A-4 (available at: https://obamawhitehouse.archives.gov/omb/circulars_a004_a-4/ and https://georgewbush-whitehouse.archives.gov/omb/circulars/a004/a-4.html), in 
Table VI. of this Appendix, we have prepared an accounting statement 
showing the classification of the expenditures associated with the 
provisions of this final rule as they relate to the changes to the 
LTCH PPS. Table VI. of this Appendix provides our best estimate of 
the estimated change in Medicare payments under the LTCH PPS as a 
result of the final payment rates and factors and other provisions 
presented in this final rule based on the data for the 363 LTCHs in 
our database. All expenditures are classified as transfers to 
Medicare providers (that is, LTCHs).
    As shown in Table VI. of this Appendix, the net cost to the 
Federal Government associated with the final policies for LTCHs in 
this final rule are estimated at $42 million.
[GRAPHIC] [TIFF OMITTED] TR13AU21.357

III. Regulatory Flexibility Act (RFA) Analysis

    The RFA requires agencies to analyze options for regulatory 
relief of small entities. For purposes of the RFA, small entities 
include small businesses, nonprofit organizations, and small 
government jurisdictions. We estimate that most hospitals and most 
other providers and suppliers are small entities as that term is 
used in the RFA. The great majority of hospitals and most other 
health care providers and suppliers are small entities, either by 
being nonprofit organizations or by meeting the SBA definition of a 
small business. Table VII. details the size standards for those 
industries that may be affected by this rule, though we expect that 
General Medical and Surgical Hospitals would be most affected.
[GRAPHIC] [TIFF OMITTED] TR13AU21.358

    For purposes of the RFA, all hospitals and other providers and 
suppliers are considered to be small entities. Because all hospitals 
are considered to be small entities for purposes of the RFA, the 
hospital impacts described in this final rule are impacts on small 
entities. Individuals and States are not included in the definition 
of a small entity. MACs are not considered to be small entities 
because they do not meet the SBA definition of a small business.
    HHS's practice in interpreting the RFA's reference to a 
``significant economic impact on a substantial number of small 
entities'' is to consider effects economically ``significant'' if 
greater than 5 percent of small providers reach a threshold of 3 to 
5 percent or more of total revenue or total costs. We believe that 
the provisions of this final rule relating to IPPS hospitals will 
have an economically significant impact on small entities as 
explained in this Appendix. Therefore, this RFA analysis serves as 
the Final Regulatory Flexibility Analysis. In ``Table I.--Impact 
Analysis of Changes to the IPPS for Operating Costs for FY 2022'', 
we display the expected impact on the 3,198 IPPS hospitals. Column 8 
indicates the total expected impact of all changes to the IPPS for 
various classifications of hospitals. For instance, we detail the 
expected impact by bed size for urban and rural hospitals. Under our 
final policies, we estimate that the 634 urban hospitals with a bed 
size of 0 to 99 would have an impact of a 2.7 percent increase in 
their IPPS payments, while the 311 rural hospitals with a bed size 
of 0 to 49 would have an impact of a 4.3 percent increase in their 
IPPS payments. Overall, the impact on hospitals by bed size ranges 
from 2.4 percent to 4.3 percent, primarily due to the hospital rate 
update, as discussed in section I.G. of this Appendix. We note that 
for some hospitals, these figures may represent the total expected 
impact on their inpatient hospital revenue; for other hospitals, 
this represents only a portion of the total expected impact, as much 
of their revenue comes from non-Medicare cases.
    In ``Table IV. Impact of Payment Rate and Policy Changes to LTCH 
PPS Payments and Policy Changes to LTCH PPS Payments for LTCH PPS 
Standard Payment Rate Cases for FY 2022 (Estimated FY 2022 Payments 
Compared to Estimated FY 2021 Payments)'' we display the expected 
impact on the 363 LTCH PPS hospitals. Column 8 indicates the total 
expected impact of all changes to the LTCH PPS for various 
classifications of LTCH PPS hospitals. Under our final policies, we 
estimate that hospitals with a bed size of 0 to 24 would have an 
impact of 0.6 percent, while hospitals with a bed size of 25 to 49 
would have an impact of 1.0 percent. Overall, the impact on 
hospitals by bed size ranges from 0.6 to 1.0 percent, primarily due 
to the

[[Page 45612]]

1.9 percent annual update to the LTCH PPS standard Federal payment 
rate for FY 2022 and the projected 0.8 percent decrease in high cost 
outlier payments as a percentage of total LTCH PPS standard Federal 
payment rate payments, as discussed in section I.J. of this 
Appendix.
    This final rule contains a range of policies as summarized in 
section A. It provides descriptions of the statutory provisions that 
are addressed, identifies the policies, and presents rationales for 
our decisions and, where relevant, alternatives that were 
considered. We note that section 1886(b)(3)(B) of the Act sets the 
requirements for the FY 2022 applicable percentage increase. 
Therefore, consistent with the statute, the applicable percentage 
increase for FY 2022 is 2.0 percent, provided the hospital submits 
quality data and is a meaningful EHR user consistent with these 
statutory requirements.
    Under section 1886(m) of the Act, the annual update to the LTCH 
PPS is equal to the estimated LTCH market basket increase reduced by 
the productivity adjustment. Therefore, consistent with the statute, 
the applicable percentage increase for FY 2022 is 1.9 percent (that 
is, the most recent estimate of the LTCH PPS market basket increase 
of 2.6 percent less the productivity adjustment of 0.7 percentage 
point), provided the hospital submits quality reporting data under 
the LTCH Quality Reporting Program. The majority of the LTCH PPS 
hospitals included in the impact analysis shown in ``Table IV. 
Impact of Payment Rate and Policy Changes to LTCH PPS Payments and 
Policy Changes to LTCH PPS Payments for LTCH PPS Standard Payment 
Rate Cases for FY 2022 (Estimated FY 2022 Payments Compared to 
Estimated FY 2021 Payments)'' on average are expected to see 
increases in the range of 0.9 percent, primarily due to the 1.9 
percent annual update to the LTCH PPS standard Federal payment rate 
for FY 2022 and the projected 0.8 percent decrease in high cost 
outlier payments as a percentage of total LTCH PPS standard Federal 
payment rate payments, as discussed in section I.J. of this 
Appendix.
    This final rule contains a range of policies. It provides 
descriptions of the statutory provisions that are addressed, 
identifies the policies, and presents rationales for our decisions 
and, where relevant, alternatives that were considered. The analyses 
discussed in this Appendix and throughout the preamble of this final 
rule constitutes our regulatory flexibility analysis. We solicited 
public comments on our estimates and analysis of the impact of our 
policies on small entities. We received on no public comments on 
those estimates and analysis.

IV. Impact on Small Rural Hospitals

    Section 1102(b) of the Act requires us to prepare a regulatory 
impact analysis for any proposed or final rule that may have a 
significant impact on the operations of a substantial number of 
small rural hospitals. This analysis must conform to the provisions 
of section 604 of the RFA. With the exception of hospitals located 
in certain New England counties, for purposes of section 1102(b) of 
the Act, we define a small rural hospital as a hospital that is 
located outside of an urban area and has fewer than 100 beds. 
Section 601(g) of the Social Security Amendments of 1983 (Pub. L. 
98-21) designated hospitals in certain New England counties as 
belonging to the adjacent urban area. Thus, for purposes of the IPPS 
and the LTCH PPS, we continue to classify these hospitals as urban 
hospitals.
    As shown in Table I. in section I.G. of this Appendix, rural 
IPPS hospitals with 0-49 beds (311 hospitals) and 50-99 beds (253 
hospitals) are expected to experience an increase in payments from 
FY 2021 to FY 2022 of 4.3 percent and 2.4 percent, respectively, 
primarily driven by the hospital rate update, as discussed in 
section I.G of this Appendix. We refer readers to Table I. in 
section I.G. of this Appendix for additional information on the 
quantitative effects of the policy changes under the IPPS for 
operating costs.
    All rural LTCHs (19 hospitals) shown in Table IV. in section 
I.J. of this Appendix have less than 100 beds. These hospitals are 
expected to experience an increase in payments from FY 2021 to FY 
2022 of 1.2 percent, primarily due to the 1.9 percent annual update 
to the LTCH PPS standard Federal payment rate for FY 2022 and the 
projected 0.8 percent decrease in high cost outlier payments as a 
percentage of total LTCH PPS standard Federal payment rate payments, 
as discussed in section I.J. of this Appendix.

V. Unfunded Mandates Reform Act Analysis

    Section 202 of the Unfunded Mandates Reform Act of 1995 (Pub. L. 
104-4) also requires that agencies assess anticipated costs and 
benefits before issuing any rule whose mandates require spending in 
any 1 year of $100 million in 1995 dollars, updated annually for 
inflation. In 2021, that threshold level is approximately $158 
million. This final rule would not mandate any requirements that 
meet the threshold for State, local, or tribal governments, nor 
would it affect private sector costs.

VI. Executive Order 13175

    Executive Order 13175 directs agencies to consult with Tribal 
officials prior to the formal promulgation of regulations having 
tribal implications. Section 1880(a) of the Act states that a 
hospital of the Indian Health Service, whether operated by such 
Service or by an Indian tribe or tribal organization, is eligible 
for Medicare payments so long as it meets all of the conditions and 
requirements for such payments which are applicable generally to 
hospitals. Consistent with section 1880(a) of the Act, this final 
rule contains general provisions also applicable to hospitals and 
facilities operated by the Indian Health Service or Tribes or Tribal 
organizations under the Indian Self-Determination and Education 
Assistance Act.
    As discussed in section V.E.4. of the preamble of this final 
rule, we remain committed to working with stakeholders to determine 
the methodology for determining uncompensated care payments to IHS 
and Tribal hospitals. Consistent with Executive Order 13175, we also 
continue to engage in consultation with Tribal officials on this 
issue. We intend to use input received from these consultations with 
Tribal officials, as well as the comments on the proposed rule, to 
inform future rulemaking.

VII. Executive Order 12866

    In accordance with the provisions of Executive Order 12866, the 
Office of Management and Budget reviewed this final rule.

Appendix B: Recommendation of Update Factors for Operating Cost Rates 
of Payment for Inpatient Hospital Services

I. Background

    Section 1886(e)(4)(A) of the Act requires that the Secretary, 
taking into consideration the recommendations of MedPAC, recommend 
update factors for inpatient hospital services for each fiscal year 
that take into account the amounts necessary for the efficient and 
effective delivery of medically appropriate and necessary care of 
high quality. Under section 1886(e)(5) of the Act, we are required 
to publish update factors recommended by the Secretary in the 
proposed and final IPPS rules. Accordingly, this Appendix provides 
the recommendations for the update factors for the IPPS national 
standardized amount, the hospital-specific rate for SCHs and MDHs, 
and the rate-of-increase limits for certain hospitals excluded from 
the IPPS, as well as LTCHs. In prior years, we made a recommendation 
in the IPPS proposed rule and final rule for the update factors for 
the payment rates for IRFs and IPFs. However, for FY 2022, 
consistent with our approach for FY 2021, we are including the 
Secretary's recommendation for the update factors for IRFs and IPFs 
in separate Federal Register documents at the time that we announce 
the annual updates for IRFs and IPFs. We also discuss our response 
to MedPAC's recommended update factors for inpatient hospital 
services.

II. Inpatient Hospital Update for FY 2022

A. FY 2022 Inpatient Hospital Update

    As discussed in section V.A. of the preamble to this final rule, 
for FY 2022, consistent with section 1886(b)(3)(B) of the Act, as 
amended by sections 3401(a) and 10319(a) of the Affordable Care Act, 
we are setting the applicable percentage increase by applying the 
following adjustments in the following sequence. Specifically, the 
applicable percentage increase under the IPPS is equal to the rate-
of-increase in the hospital market basket for IPPS hospitals in all 
areas, subject to a reduction of one-quarter of the applicable 
percentage increase (prior to the application of other statutory 
adjustments; also referred to as the market basket update or rate-
of-increase (with no adjustments)) for hospitals that fail to submit 
quality information under rules established by the Secretary in 
accordance with section 1886(b)(3)(B)(viii) of the Act and a 
reduction of three-quarters of the applicable percentage increase 
(prior to the application of other statutory adjustments; also 
referred to as the market basket update or rate-of-increase (with no 
adjustments)) for hospitals not considered to be meaningful 
electronic

[[Page 45613]]

health record (EHR) users in accordance with section 
1886(b)(3)(B)(ix) of the Act, and then subject to an adjustment 
based on changes in economy-wide productivity (the productivity 
adjustment). Section 1886(b)(3)(B)(xi) of the Act, as added by 
section 3401(a) of the Affordable Care Act, states that application 
of the productivity adjustment may result in the applicable 
percentage increase being less than zero. (We note that section 
1886(b)(3)(B)(xii) of the Act required an additional reduction each 
year only for FYs 2010 through 2019.)
    We note that, in compliance with section 404 of the MMA, in the 
FY 2018 IPPS/LTCH PPS final rule (82 FR 38158 through 38175), we 
replaced the FY 2010-based IPPS operating and capital market baskets 
with the rebased and revised 2014-based IPPS operating and capital 
market baskets effective beginning in FY 2018. In this final rule, 
we are replacing the 2014-based IPPS operating and capital market 
baskets with the rebased and revised 2018-based IPPS operating and 
capital market baskets beginning in FY 2022.
    In the FY 2022 IPPS/LTCH PPS proposed rule, in accordance with 
section 1886(b)(3)(B) of the Act, we proposed to base the proposed 
FY 2022 market basket update used to determine the applicable 
percentage increase for the IPPS on IGI's fourth quarter 2020 
forecast of the proposed 2018-based IPPS market basket rate-of-
increase with historical data through third quarter 2020, which was 
estimated to be 2.5 percent. In accordance with section 
1886(b)(3)(B) of the Act, as amended by section 3401(a) of the 
Affordable Care Act, in section IV.B. of the preamble of the FY 2022 
IPPS/LTCH PPS proposed rule, based on IGI's fourth quarter 2020 
forecast, we proposed a productivity adjustment of 0.2 percentage 
point for FY 2022. We also proposed that if more recent data 
subsequently became available, we would use such data, if 
appropriate, to determine the FY 2022 market basket update and 
productivity adjustment for the final rule.
    In the FY 2022 IPPS/LTCH PPS proposed rule, based on IGI's 
fourth quarter 2020 forecast of the 2018-based IPPS market basket 
and the productivity adjustment, depending on whether a hospital 
submits quality data under the rules established in accordance with 
section 1886(b)(3)(B)(viii) of the Act (hereafter referred to as a 
hospital that submits quality data) and is a meaningful EHR user 
under section 1886(b)(3)(B)(ix) of the Act (hereafter referred to as 
a hospital that is a meaningful EHR user), we presented 4 possible 
applicable percentage increases that could be applied to the 
standardized amount.
    In accordance with section 1886(b)(3)(B) of the Act, as amended 
by section 3401(a) of the Affordable Care Act, we are establishing 
the applicable percentages increase for the FY 2022 updates based on 
IGI's second quarter 2021 forecast of the 2018-based IPPS market 
basket of 2.7 percent and the productivity adjustment of 0.7 
percentage point, as discussed in section V.A. of the preamble of 
this final rule, depending on whether a hospital submits quality 
data under the rules established in accordance with section 
1886(b)(3)(B)(viii) of the Act and is a meaningful EHR user under 
section 1886(b)(3)(B)(ix) of the Act, as shown in the table in this 
section.
[GRAPHIC] [TIFF OMITTED] TR13AU21.359

B. Update for SCHs and MDHs for FY 2022

    Section 1886(b)(3)(B)(iv) of the Act provides that the FY 2022 
applicable percentage increase in the hospital-specific rate for 
SCHs and MDHs equals the applicable percentage increase set forth in 
section 1886(b)(3)(B)(i) of the Act (that is, the same update factor 
as for all other hospitals subject to the IPPS). Under current law, 
the MDH program is effective for discharges through September 30, 
2022, as discussed in the FY 2019 IPPS/LTCH PPS final rule (83 FR 
41429 through 41430).
    As previously stated, the update to the hospital specific rate 
for SCHs and MDHs is subject to section 1886(b)(3)(B)(i) of the Act, 
as amended by sections 3401(a) and 10319(a) of the Affordable Care 
Act. Accordingly, depending on whether a hospital submits quality 
data and is a meaningful EHR user, we are establishing the same four 
possible applicable percentage increases in the previous table for 
the hospital-specific rate applicable to SCHs and MDHs.

C. FY 2022 Puerto Rico Hospital Update

    Because Puerto Rico hospitals are no longer paid with a Puerto 
Rico-specific standardized amount under the amendments to section 
1886(d)(9)(E) of the Act, there is no longer a need for us to make 
an update to the Puerto Rico standardized amount. Hospitals in 
Puerto Rico are now paid 100 percent of the national standardized 
amount and, therefore, are subject to the same update to the 
national standardized amount discussed under section V.A.1. of the 
preamble of this final rule.
    In addition, as discussed in section V.A.2. of the preamble of 
this final rule, section 602 of Public Law 114-113 amended section 
1886(n)(6)(B) of the Act to specify that subsection (d) Puerto Rico 
hospitals are eligible for incentive payments for the meaningful use 
of certified EHR technology, effective beginning FY 2016. In 
addition, section 1886(n)(6)(B) of the Act was amended to specify 
that the adjustments to the applicable percentage increase under 
section 1886(b)(3)(B)(ix) of the Act apply to subsection (d) Puerto 
Rico hospitals that are not meaningful EHR users, effective 
beginning FY 2022.
    Accordingly, for FY 2022, section 1886(b)(3)(B)(ix) of the Act 
in conjunction with section 602(d) of Public Law 114-113 requires 
that any subsection (d) Puerto Rico hospital that is not a 
meaningful EHR user as defined in section 1886(n)(3) of the Act and 
not subject to an exception under section 1886(b)(3)(B)(ix) of the 
Act will have ``three-quarters'' of the applicable percentage 
increase (prior to the application of other statutory adjustments), 
or three-quarters of the applicable market basket rate-of-increase, 
reduced by 33\1/3\ percent. The reduction to three-quarters of the 
applicable percentage increase for subsection (d) Puerto Rico

[[Page 45614]]

hospitals that are not meaningful EHR users increases to 66\2/3\ 
percent for FY 2023, and, for FY 2024 and subsequent fiscal years, 
to 100 percent. In the FY 2019 IPPS/LTCH PPS final rule, we 
finalized the payment reductions (83 FR 41674).
    Based on IGI's fourth quarter 2020 forecast of the proposed 
2018-based IPPS market basket update with historical data through 
third quarter 2020, in the FY 2022 IPPS/LTCH PPS proposed rule, in 
accordance with section 1886(b)(3)(B) of the Act, as previously 
discussed, for Puerto Rico hospitals, we proposed a market basket 
update of 2.5 percent and a productivity adjustment of 0.2 percent. 
Therefore, for FY 2022, depending on whether a Puerto Rico hospital 
is a meaningful EHR user, we stated that there are two possible 
applicable percentage increases that can be applied to the 
standardized amount. Based on these data, we determined the 
following proposed applicable percentage increases to the 
standardized amount for FY 2022 for Puerto Rico hospitals:
     For a Puerto Rico hospital that is a meaningful EHR 
user, we proposed an applicable percentage increase to the FY 2022 
operating standardized amount of 2.3 percent (that is, the FY 2022 
estimate of the proposed market basket rate-of-increase of 2.5 
percent less an adjustment of 0.2 percentage point for the 
productivity adjustment).
     For a Puerto Rico hospital that is not a meaningful EHR 
user, we proposed an applicable percentage increase to the operating 
standardized amount of 1.675 percent (that is, the FY 2022 estimate 
of the proposed market basket rate-of-increase of 2.5 percent, less 
an adjustment of 0.625 percentage point (the proposed market basket 
rate-of-increase of 2.5 percent x 0.75)/3) for failure to be a 
meaningful EHR user, less an adjustment of 0.2 percentage point for 
the productivity adjustment.
    As noted previously, we proposed that if more recent data 
subsequently become available, we would use such data, if 
appropriate, to determine the FY 2022 market basket update and the 
productivity adjustment for the FY 2022 IPPS/LTCH PPS final rule.
    As discussed in section V.A.1. of the preamble of this final 
rule, based on more recent data available for this FY 2022 IPPS/LTCH 
PPS final rule (that is, IGI's second quarter 2021 forecast of the 
2018-based IPPS market basket rate-of-increase with historical data 
through the first quarter of 2021), we estimate that the FY 2022 
market basket update used to determine the applicable percentage 
increase for the IPPS is 2.7 percent and a productivity adjustment 
of 0.7 percent. Therefore, in accordance with section 1886(b)(3)(B) 
of the Act, for this final rule, for Puerto Rico hospitals the more 
recent update of the market basket update is 2.7 percent and a 
productivity adjustment of 0.7 percent. For FY 2022, depending on 
whether a Puerto Rico hospital is a meaningful EHR user, there are 
two possible applicable percentage increases that can be applied to 
the standardized amount. Based on these data, we determined the 
following applicable percentage increases to the standardized amount 
for FY 2022 for Puerto Rico hospitals:
     For a Puerto Rico hospital that is a meaningful EHR 
user, an applicable percentage increase to the FY 2022 operating 
standardized amount of 2.0 percent (that is, the FY 2022 estimate of 
the market basket rate-of-increase of 2.7 percent less an adjustment 
of 0.7 percentage point for the productivity adjustment)).
     For a Puerto Rico hospital that is not a meaningful EHR 
user, an applicable percentage increase to the operating 
standardized amount of 1.325 percent (that is, the FY 2022 estimate 
of the market basket rate-of-increase of 2.7 percent, less an 
adjustment of 0.675 percentage point (the market basket rate of-
increase of 2.7 percent x 0.75)/3) for failure to be a meaningful 
EHR user, less an adjustment of 0.7 percentage point for the 
productivity adjustment.

D. Update for Hospitals Excluded From the IPPS for FY 2022

    Section 1886(b)(3)(B)(ii) of the Act is used for purposes of 
determining the percentage increase in the rate-of-increase limits 
for children's hospitals, cancer hospitals, and hospitals located 
outside the 50 States, the District of Columbia, and Puerto Rico 
(that is, short-term acute care hospitals located in the U.S. Virgin 
Islands, Guam, the Northern Mariana Islands, and America Samoa). 
Section 1886(b)(3)(B)(ii) of the Act sets the percentage increase in 
the rate-of-increase limits equal to the market basket percentage 
increase. In accordance with Sec.  403.752(a) of the regulations, 
RNHCIs are paid under the provisions of Sec.  413.40, which also use 
section 1886(b)(3)(B)(ii) of the Act to update the percentage 
increase in the rate-of-increase limits.
    Currently, children's hospitals, PPS-excluded cancer hospitals, 
RNHCIs, and short-term acute care hospitals located in the U.S. 
Virgin Islands, Guam, the Northern Mariana Islands, and American 
Samoa are among the remaining types of hospitals still paid under 
the reasonable cost methodology, subject to the rate-of-increase 
limits. In addition, in accordance with Sec.  412.526(c)(3) of the 
regulations, extended neoplastic disease care hospitals (described 
in Sec.  412.22(i) of the regulations) also are subject to the rate-
of-increase limits. As discussed in section VI. of the preamble of 
this final rule, we are finalizing to use the percentage increase in 
the 2018-based IPPS operating market basket to update the target 
amounts for children's hospitals, PPS-excluded cancer hospitals, 
RNHCIs, short-term acute care hospitals located in the U.S. Virgin 
Islands, Guam, the Northern Mariana Islands, and American Samoa, and 
extended neoplastic disease care hospitals for FY 2022 and 
subsequent fiscal years. Accordingly, for FY 2022, the rate-of-
increase percentage to be applied to the target amount for these 
children's hospitals, cancer hospitals, RNHCIs, extended neoplastic 
disease care hospitals, and short-term acute care hospitals located 
in the U.S. Virgin Islands, Guam, the Northern Mariana Islands, and 
American Samoa is the FY 2022 percentage increase in the 2018-based 
IPPS operating market basket. For this final rule, the current 
estimate of the IPPS operating market basket percentage increase for 
FY 2022 is 2.7 percent.

E. Update for LTCHs for FY 2022

    Section 123 of Public Law 106-113, as amended by section 307(b) 
of Public Law 106-554 (and codified at section 1886(m)(1) of the 
Act), provides the statutory authority for updating payment rates 
under the LTCH PPS.
    As discussed in section V.A. of the Addendum to this final rule, 
we are establishing an update to the LTCH PPS standard Federal 
payment rate for FY 2022 of 1.9 percent, consistent with section 
1886(m)(3) of the Act which provides that any annual update be 
reduced by the productivity adjustment described in section 
1886(b)(3)(B)(xi)(II) of the Act. Furthermore, in accordance with 
the LTCHQR Program under section 1886(m)(5) of the Act, we are 
reducing the annual update to the LTCH PPS standard Federal rate by 
2.0 percentage points for failure of a LTCH to submit the required 
quality data. Accordingly, we are establishing an update factor of 
1.019 in determining the LTCH PPS standard Federal rate for FY 2022. 
For LTCHs that fail to submit quality data for FY 2022, we are 
establishing an annual update to the LTCH PPS standard Federal rate 
of -0.1 percent (that is, the annual update for FY 2022 of 1.9 
percent less 2.0 percentage points for failure to submit the 
required quality data in accordance with section 1886(m)(5)(C) of 
the Act and our rules) by applying a update factor of 0.999 in 
determining the LTCH PPS standard Federal rate for FY 2022. (We note 
that, as discussed in section VIII.C. of the preamble of this final 
rule, the update to the LTCH PPS standard Federal payment rate of 
1.9 percent for FY 2022 does not reflect any budget neutrality 
factors).

III. Secretary's Recommendations

    MedPAC is recommending an inpatient hospital update of 2.0 
percent. MedPAC's rationale for this update recommendation is 
described in more detail in this section. As previously stated, 
section 1886(e)(4)(A) of the Act requires that the Secretary, taking 
into consideration the recommendations of MedPAC, recommend update 
factors for inpatient hospital services for each fiscal year that 
take into account the amounts necessary for the efficient and 
effective delivery of medically appropriate and necessary care of 
high quality. Consistent with current law, depending on whether a 
hospital submits quality data and is a meaningful EHR user, we are 
recommending the four applicable percentage increases to the 
standardized amount listed in the table under section II. of this 
Appendix B. We are recommending that the same applicable percentage 
increases apply to SCHs and MDHs.
    In addition to making a recommendation for IPPS hospitals, in 
accordance with section 1886(e)(4)(A) of the Act, we are 
recommending update factors for certain other types of hospitals 
excluded from the IPPS. Consistent with our policies for these 
facilities, we are recommending an update to the target amounts for 
children's hospitals, cancer hospitals, RNHCIs, short-term acute 
care hospitals located in the U.S. Virgin Islands, Guam, the 
Northern Mariana Islands, and American Samoa and extended neoplastic 
disease care hospitals of 2.7 percent.

[[Page 45615]]

    For FY 2022, consistent with policy set forth in section VIII. 
of the preamble of this final rule, for LTCHs that submit quality 
data, we are recommending an update of 1.9 percent to the LTCH PPS 
standard Federal rate. For LTCHs that fail to submit quality data 
for FY 2022, we are recommending an annual update to the LTCH PPS 
standard Federal rate of -0.1 percent.

IV. MedPAC Recommendation for Assessing Payment Adequacy and Updating 
Payments in Traditional Medicare

    In its March 2021 Report to Congress, MedPAC assessed the 
adequacy of current payments and costs, and the relationship between 
payments and an appropriate cost base. MedPAC recommended an update 
to the hospital inpatient rates by 2.0 percent with the difference 
between this and the update amount specified in current law to be 
used to increase payments under MedPAC's Medicare quality program, 
the ``Hospital Value Incentive Program (HVIP).'' MedPAC initially 
recommended in March 2019 a redesign of the current hospital quality 
payment programs. MedPAC stated that together, these 
recommendations, paired with the recommendation to eliminate the 
current hospital quality program incentives, would increase hospital 
payments by increasing the base payment rate and by increasing the 
average rewards hospitals receive under MedPAC's Medicare HVIP. We 
refer readers to the March 2021 MedPAC report, which is available 
for download at www.medpac.gov, for a complete discussion on these 
recommendations.
    Response: With regard to MedPAC's recommendation of an update to 
the hospital inpatient rates equal to 2.0 percent, with the 
remainder of the applicable percentage increase specified in current 
law to be used to fund its recommended Medicare HVIP, section 
1886(b)(3)(B) of the Act sets the requirements for the FY 2022 
applicable percentage increase. Therefore, consistent with the 
statute, we are establishing an applicable percentage increase for 
FY 2022 of 2.0 percent, provided the hospital submits quality data 
and is a meaningful EHR user consistent with these statutory 
requirements. Furthermore, we continue to appreciate MedPAC's 
recommendation concerning a new HVIP. We agree that continual 
improvement motivated by quality programs is an important incentive 
of the IPPS.
    We note that, because the operating and capital payments in the 
IPPS remain separate, we are continuing to use separate updates for 
operating and capital payments in the IPPS. The update to the 
capital rate is discussed in section III. of the Addendum to this 
final rule.

[FR Doc. 2021-16519 Filed 8-2-21; 4:15 pm]
 BILLING CODE 4120-01-P